COVID-19 Can Infect and Harm Digestive Organs

Authors: E.J. Mundell

 The coronavirus isn’t just attacking the lungs: New research shows it’s causing harm to the gastrointestinal tract, especially in more advanced cases of COVID-19.

A variety of imaging scans performed on hospitalized COVID-19 patients showed bowel abnormalities, according to a study published online May 11 in Radiology. Many of the effects were severe and linked with clots and impairment of blood flow.

“Some findings were typical of bowel ischemia, or dying bowel, and in those who had surgery we saw small vessel clots beside areas of dead bowel,” said study lead author Dr. Rajesh Bhayana, who works in the department of radiology at Massachusetts General Hospital in Boston.

“Patients in the ICU can have bowel ischemia for other reasons, but we know COVID-19 can lead to clotting and small vessel injury, so bowel might also be affected by this,” Bhayana explained in a journal news release.

One expert unconnected to the new study said the findings aren’t surprising.

“Our emerging understanding of COVID-19 has found the disease to have multisystem involvement including the nervous, cardiac, vascular [excess clotting] and finally the digestive systems, among others,” said Dr. Sherif Andrawes. He directs endoscopy in the division of gastroenterology and hematology at Staten Island University in New York City.

“It seems that this disease is intricate, in the sense that it can involve multiorgan systems, rather than being a disease of the respiratory system solely,” Andrawes said.

In fact, a study published online May 13 in the journal Science Immunology has found evidence that SARS-CoV-2, the virus behind COVID-19, can infect the human digestive system.

Researchers led by Siyuan Ding of Washington University School of Medicine in St. Louis, said their findings “highlight the intestine as a potential site of SARS-CoV-2 replication, which may contribute to local and systemic illness and overall disease progression.”

That seems to be borne out by the Boston study.

That research included 412 COVID-19 patients who were hospitalized between March 27 and April 10. They averaged 57 years of age, and 134 of them underwent abdominal imaging, including 137 radiographs, 44 ultrasounds, 42 CT scans, and one MRI.

Intestinal Damage in COVID-19: SARS-CoV-2 Infection and Intestinal Thrombosis

Authors: Xiaoming Wu1Haijiao Jing1Chengyue Wang1Yufeng Wang1Nan Zuo1Tao Jiang2*Valerie A. Novakovic3 and Jialan Shi1,3,4* Front. Microbiol., 22 March 2022 | https://doi.org/10.3389/fmicb.2022.860931

The intestinal tract, with high expression of angiotensin-converting enzyme 2 (ACE2), is a major site of extrapulmonary infection in COVID-19. During pulmonary infection, the virus enters the bloodstream forming viremia, which infects and damages extrapulmonary organs. Uncontrolled viral infection induces cytokine storm and promotes a hypercoagulable state, leading to systemic microthrombi. Both viral infection and microthrombi can damage the gut–blood barrier, resulting in malabsorption, malnutrition, and intestinal flora entering the blood, ultimately increasing disease severity and mortality. Early prophylactic antithrombotic therapy can prevent these damages, thereby reducing mortality. In this review, we discuss the effects of SARS-CoV-2 infection and intestinal thrombosis on intestinal injury and disease severity, as well as corresponding treatment strategies.

Introduction

COVID-19 has become a worldwide pandemic causing widespread illness and mortality. SARS-CoV-2 mainly infects the respiratory tract through attachment to angiotensin-converting enzyme 2 (ACE2) receptors (Lan et al., 2020). ACE2 is also highly expressed on intestinal epithelial cells, allowing SARS-CoV-2 to infect the intestinal tract (Xiao et al., 2020a). Recent meta-analyses show that 48%–54% of fecal samples from COVID-19 patients have tested positive for viral RNA, and 15%–17% of patients have gastrointestinal (GI) symptoms (Cheung et al., 2020Mao et al., 2020Sultan et al., 2020). Additionally, live virus can be isolated from fecal samples of COVID-19 patients (Wang et al., 2020). Some studies have proposed fecal–oral transmission as the cause of intestinal infection (Guo et al., 2021). However, direct evidence for fecal–oral transmission is still lacking. Meanwhile, the virus has been detected in the blood of both symptomatic and asymptomatic patients (Chang et al., 2020), and disseminated virus could infect extrapulmonary organs (Jacobs and Mellors, 2020). Thus, the potential that intestinal infection occurs via blood transmission should be carefully considered.

Pulmonary infection triggers cytokine storm and induces a prothrombotic state (McFadyen et al., 2020Moore and June, 2020). Venous and arterial thrombosis are common in COVID-19 (Moore and June, 2020). Systematic reviews estimate that 14%–31% of in-hospital patients develop a clinically apparent thrombotic event (Suh et al., 2021Tan et al., 2021), while autopsy reports show a high prevalence of microthrombi in multiple organs, including lung, heart, liver, kidney, and gastrointestinal tract (Bradley et al., 2020Polak et al., 2020). A cohort study showed that COVID-19 patients with intestinal ischemia had markedly elevated D-dimer levels and poor outcomes (Norsa et al., 2020). Additionally, recent studies have shown that mesenteric thrombosis often results in intestinal resection and significantly increases mortality (Bhayana et al., 2020El Moheb et al., 2020). Therefore, it is essential to outline the mechanisms of intestinal thrombosis and its contribution to intestinal damage and disease progression.

In this review, we discuss blood transmission as a potential route for intestinal infection. We then summarize the characteristics and mechanism of intestinal thrombosis formation in COVID-19. Next, we focus on the effects of intestinal infection and thrombosis on intestinal damage and disease severity. Finally, we discuss therapeutic strategies to prevent intestinal damage.

Gastrointestinal Symptoms and SARS-CoV-2 Infection

Multiple studies have reported GI symptoms in COVID-19 patients, including diarrhea, nausea, vomiting, anorexia, and abdominal pain (Cheung et al., 2020Mao et al., 2020Sultan et al., 2020). According to a meta-analysis comprising 10,890 COVID-19 patients, the pooled prevalence estimates of GI symptoms were: diarrhea (7.7%), nausea or vomiting (7.8%), and abdominal pain (2.7%; Sultan et al., 2020) with 10% of these patients reporting GI symptoms as being their initial symptoms (Cheung et al., 2020). These data indicate potential gastrointestinal infection by SARS-CoV-2, which is reported to infect and replicate in epithelial cells of human small intestinal organoids (Zang et al., 2020). Both viral nucleocapsid proteins and viral particles have been detected in infected patient intestinal biopsies (Livanos et al., 2021). Additionally, SARS-CoV-2 RNA and live virus can be found in the stool of patients (Wang et al., 2020). More importantly, SARS-CoV-2 subgenomic mRNA is transcribed in actively replicating cells and has been detected in fecal samples (Wölfel et al., 2020). Further, rectal viral shedding persists for longer than that of the respiratory system (Zhao et al., 2020). All these data demonstrate that SARS-CoV-2 directly infects and replicates in intestinal epithelial cells of patients.

Intestinal Infection and Transmission Routes

With the deepening understanding of COVID-19, GI symptoms have been recognized as early signs of the disease. The high expression of ACE2 in the GI tract, isolation of live virus from fecal samples, and a subset of patients presenting with only GI symptoms seem to suggest fecal–oral transmission. However, problems with the feasibility of this mode of transmission remain. First, studies have shown that SARS-CoV-2 loses infectivity in simulated gastric acid within 10 min (Chan et al., 2020Zang et al., 2020Zhong et al., 2020). Secondly, SARS-CoV-2, as an enveloped virus, is largely unable to withstand the detergent effect of bile salts and the activity of digestive enzymes in the duodenum (Figure 1). Although some studies have suggested that highly viscous mucus in the gastrointestinal tract protects SARS-CoV-2, allowing the virus to retain its infectivity (Guo et al., 2021Zhang H. et al., 2021), there is still a lack of direct evidence. Bushman et al. (2019) had previously investigated the links between the structures of viruses and routes of transmission and found a strong association between fecal–oral transmission and the absence of a lipid envelope. Lastly, although some studies have isolated intact viruses from feces (Wang et al., 2020Zhang Y. et al., 2020Zhou et al., 2020Xiao et al., 2020b), most of them have not further confirmed the infectivity of these viruses (Wang et al., 2020Zhang Y. et al., 2020Xiao et al., 2020b). Zhou et al. (2020) confirmed viral propagation by RT-PCR, but only in a single fecal sample. Previous research has shown that SARS-CoV-2 is completely inactivated in simulated human colonic fluid over the course of 24 h, which may explain the sporadic detection of infection-active SARS-CoV-2 from feces samples.FIGURE 1

Figure 1. Intestinal infection and transmission routes. ① Direct evidence for fecal–oral transmission is still lacking. SARS-CoV-2 may be unable to enter the small intestine from the stomach due to gastric acid, bile and digestive enzymes. ② SARS-CoV-2 released from type II alveolar cells infects alveolar capillary endothelial cells (ECs). The virus replicates in ECs and is released into the blood to form viremia. ③ SARS-CoV-2 is released from infected ciliary cells of the nasal cavity and breaks through the basement membrane, infecting the vascular ECs and eventually entering circulation. ④ Blood transmission after alveolar or nasal infection is a potential route of intestinal infection. Eventually, SARS-CoV-2 is released into the gut and infects surrounding intestinal epithelial cells along the intestinal tract. ⑤ SARS-CoV-2 in the gut can also enter the capillaries and cause viremia, leading to recurrence of disease.

Several lines of evidence suggest that SARS-CoV-2 may infect the intestinal tract via the bloodstream. Deng et al. (2020) detected SARS-CoV-2 RNA in anal swabs from intratracheally but not intragastrically infected rhesus macaques, suggesting blood transmission. Indeed, SARS-CoV-2 RNA has been detected in blood and urine samples of patients (Wang et al., 2020). The virus can also be detected in multiple organs (including heart, brain, and kidney) and is associated with organ injury, indicating that the virus can reach and infect extrapulmonary organs (Puelles et al., 2020). Another study showed that SARS-CoV-2 viremia was associated with intestinal damage, independent of disease severity (Li Y. et al., 2021). Thus, blood transmission could be the cause of intestinal infection. Specifically, SARS-CoV-2 replicating in alveolar epithelial cells and capillary ECs is released into the bloodstream and infects new vascular ECs. The capillary network is then the main route by which the virus enters and infects extrapulmonary organs. The extensive surface area of intestinal capillaries makes intestinal epithelial cells more susceptible to infection than other extrapulmonary organs. Following infection of intestinal capillaries, SARS-CoV-2 is released into the gut and infects surrounding intestinal epithelial cells along the intestinal tract (Figure 1). Once established in the gut, SARS-CoV-2 can also reenter the capillaries, potentially leading to recurrence of disease. Consistent with this, in patients who experienced recurrence, the phylogenetic analysis of infection samples has shown that recurrent virus evolves from the original parent virus (Hu et al., 2020).

Additionally, SARS-CoV-2 RNA can also be detected in the blood and urine of asymptomatic patients, suggesting a second pathway to viremia through the nasal cavity (Chang et al., 2020Hasanoglu et al., 2021). The abundant blood vessels, thin mucous membrane, and higher levels of ACE2 (Huang et al., 2021) make it possible for the virus to initiate viremia from the nasal cavity. Specifically, SARS-CoV-2 is released from infected ciliary cells of the nasal cavity and breaks through the basement membrane, infecting the vascular ECs and eventually entering circulation (Figure 1). Blood transmission after nasal infection is therefore another potential route of intestinal infection.

Intestinal Damage, Malnutrition, and Poor Outcomes

A recent study has shown that a fecal sample positive for SARS-CoV-2 RNA at any time during hospitalization was associated with higher mortality [HR: 3.4 (1.2–9.9); Das Adhikari et al., 2021]. Similarly, another study showed that small-bowel thickening on CT was strongly associated with ICU admission (Wölfel et al., 2020). This relationship did not hold for colon or rectal thickening. These data indicates that small-bowel damage contributes to poor outcomes. As the main organ for nutrient absorption, damage to the small intestine will result in malabsorption and malnutrition, both of which commonly occur in COVID-19 patients (Di Filippo et al., 2021Lv et al., 2021) and are associated with disease severity (Luo et al., 2020Zhang P. et al., 2021). A fecal metabolome study showed that feces of COVID-19 patients were enriched with important nutrients that should be metabolized or absorbed, consistent with malabsorption (Lv et al., 2021). A prospective study showed that 29% of COVID-19 patients (31% of hospitalization patients and 21% of patients quarantined at home) had lost >5% of body weight [median weight loss, 6.5 (5.0–9.0) kg or 8.1 (6.1–10.9) %; Di Filippo et al., 2021]. Those patients with weight loss had greater systemic inflammation, impaired renal function and longer disease duration. A large, multicenter study (including 3,229 patients with GI symptoms) showed that 23% of patients had malnutrition, of whom 56.4% were unable to gain weight after 6 months follow-up (Rizvi et al., 2021). Studies also showed that malnutrition was associated with higher incidences of acute respiratory distress syndrome, acute myocardial injury, secondary infection, shock, and 28-day ICU mortality (Luo et al., 2020Zhang P. et al., 2021). Overall, malabsorption and malnutrition due to damaged small intestine increased disease severity and mortality.

Nutrient absorption in the small intestine is mainly through ATP-dependent active transport. Intestinal infection, hypoxemia, and intestinal ischemia contribute to malabsorption. SARS-CoV-2 adhesion depletes ACE2 levels on intestinal epithelial cells, which alters the expression of the neutral amino acid transporter B0AT1, reducing the intake of tryptophan and the production of nicotinamide (D’Amico et al., 2020). Meanwhile, uncontrolled viral replication consumes large amounts of ATP and nutrients, resulting in decreased nutrients entering the bloodstream. More importantly, anaerobic glycolysis caused by hypoxemia and intestinal ischemia significantly decreases ATP and active transport, leading to malabsorption. Additionally, hypoxemia and intestinal ischemia can also cause anorexia, nausea, vomiting, and enteral nutrition intolerance, reducing food intake. A prospective multicenter study showed that reduced food intake was associated with higher ICU admission and mortality (Caccialanza et al., 2021).

Intestinal Ischemia and Thrombosis

Intestinal ischemia is a common manifestation in COVID-19 patients. Autopsy results have shown that 31.6% of deceased patients had focal ischemic intestinal changes (Chiu et al., 2020). In a separate imaging study, bowel wall thickening and pneumatosis intestinalis, which indicate intestinal ischemia, were found on 38.1% (16 of 42) of abdominal CT images (Bhayana et al., 2020). Of these, 4 (9.5%) patients with pneumatosis intestinalis developed severe intestinal necrosis and needed resection. In another cohort study, 55.8% (58/104) of ICU patients developed an ileus (Kaafarani et al., 2020). Although mechanical factors cannot be ruled out, insufficient intestinal motility due to intestinal ischemia was more likely to be the cause of ileus in COVID-19 patients. In these patients with ileus, 4 (3.8%) developed severe intestinal ischemia and require emergency surgery. Both studies found microthrombi in these resected intestinal samples, which were the main cause of intestinal ischemia and increased mortality.

Additional intestinal ischemia and necrosis follows the formation of mesenteric thrombosis. However, there is currently relatively little data of mesenteric thrombus in COVID-19. Therefore, we have summarized the characteristics of 40 patients in 39 case reports published on PubMed (Supplementary Table 1). The median age of these patients was 50 (20–82) years, 26 (65%) were male, 38 (95%) developed bowel ischemia or necrosis, 30 (75%) needed bowel resection, 7 (17.5%) required no surgery, at least 3 (7.5%) developed sepsis, and 13 (32.5%) died. Other abdominal thrombotic events (such as celiac aortic thrombosis) leading to mesenteric ischemia can also result in severe intestinal necrosis and require intestinal resection (Zamboni et al., 2021).

Mild intestinal ischemia can lead to reduced diet and malabsorption. Severe intestinal ischemia or necrosis leads to the dissemination of gut bacteria, endotoxins, and microbial metabolites into the blood (Figure 2 bottom), aggravating hyperinflammation and the hypercoagulability state. Such patients need emergency excision of the necrotic bowel, which significantly increases mortality.FIGURE 2

Figure 2. Intestinal thrombosis leads to intestinal mucosal necrosis and dissemination of gut bacteria, endotoxins, and microbial metabolites in blood. (Top) Mesenteric vascular endotheliitis (initiated by viremia and accelerated by cytokines), hyperactivated platelets and high levels of phosphatidylserine (PS) promote a high rate of mesenteric thrombus in COVID-19 patients (mesenteric vein is shown in Supplementary Figure 1). (Bottom) Intestinal microthrombi and hypoxemia rapidly lead to intestinal mucosal ischemia and necrosis. The damaged gut–blood barrier leads to dissemination of gut bacteria, endotoxins, and microbial metabolites in blood.

Long-Term Gastrointestinal Sequelae

Long-term GI complications are common in recovering COVID-19 patients. In one systematic review of post-acute COVID-19 manifestations, diarrhea was among the top 10 most common complaints, with a prevalence of 6%. Other long-term GI symptoms include nausea, vomiting, abdominal pain, loss of appetite, and weight loss (Aiyegbusi et al., 2021Huang et al., 2021). The exact mechanisms of the GI sequelae remain unclear. Recently, persistent endotheliopathy, higher levels of thrombin (Fogarty et al., 2021), and residual SARS-CoV-2 viral antigens in the GI tract (Cheung et al., 2022) were described in convalescent COVID-19 patients. These data suggest that prolonged intestinal infection, persistent endothelial injury (abnormal intestinal–blood barrier), and microthrombi could be causes of the persistent GI symptoms.

The Mechanisms of Intestinal Thrombosis

Damaged Endothelial Cells

Resected bowel samples from COVID-19 patients routinely exhibit thrombi and endotheliitis, indicating the important role of EC injury in mesenteric thrombosis (Bhayana et al., 2020Chiu et al., 2020Kaafarani et al., 2020). SARS-CoV-2 infection (Varga et al., 2020) and elevated inflammatory cytokines (He et al., 2016) damage mesenteric vascular ECs. In response, EC cell margins retract, extending phosphatidylserine (PS) positive filopods and releasing endothelial microparticles (MPs; Figure 3BHe et al., 2016). The PS+ filopods and MPs can be co-stained by Xa and Va and support fibrin formation (Figures 3BD). The exposed PS then activates tissue factor on ECs, triggering the extrinsic coagulation pathway (Versteeg et al., 2013). Next, higher levels of FVIII and vWF released from damaged EC contribute to the hypercoagulable state and platelet aggregation, respectively (Goshua et al., 2020). Thrombomodulin is then released from ECs in its soluble form, which has an attenuated capacity to activate Protein C due to a lack of other cofactors on ECs, such as endothelial protein C receptor (Versteeg et al., 2013). Finally, upregulation of endothelial cell adhesion molecules recruits neutrophils and platelets and further contributes to thrombosis (Tong et al., 2020Li L. et al., 2021).FIGURE 3

Figure 3. Phosphatidylserine exposure on activated/apoptotic cells and microparticles (MPs) promotes fibrin formation. (A) Phosphatidylserine is usually confined to the inner leaflet of the cell membrane. This asymmetry is maintained through ATP-dependent inward transport of PS by flippases and outward transport of non-PS by floppases (left). Upon stimulation, calcium transients will inhibit ATP-dependent transport and stimulate the nonselective lipid transporter scramblase (ATP-independent), resulting in PS exposure (right). (B–D) Human umbilical vein ECs were treated with healthy human plasma and TNF-ɑ (our previous study; He et al., 2016). (B) ECs retracts the cell margins, extends PS positive filopods and releases endothelial-MPs. (C) The PS+ filopods and MPs can be co-stained by Xa and Va. (D) ECs (green) were incubated with MPs-depleted plasma (MDP) in the presence of calcium for 30 min and stained with Alexa Fluro 647-anti-fibrin for 30 min. Considerable fibrin stands among cultured ECs along with filopodia. (E) Confocal images showed PS expression on platelets of patients stained with Alexa 488 lactadherin (our previous study; Ma et al., 2017). MPs from the activated platelet (*) had formed at the margin area located between the distinct outlines. (F) MPs from plasma were co-stained by Xa and Va (or lactadherin and annexin V; our previous study; Gao et al., 2015). (G) MPs that were incubated with recalcified MDP for 30 min and stained with Alexa Fluro 647-anti-fibrin for 30 min. Converted fibrin networks were detected around MPs. The inset bars represent 5 μm in (B–D,G) and 2 μm in (E,F).

Hyperactivated Platelets and Phosphatidylserine Storm

Although COVID-19 patients exhibit mild thrombocytopenia, the remaining platelets are hyperactivated (Manne et al., 2020Taus et al., 2020Zaid et al., 2020). Studies have shown that platelets from COVID-19 patients have increased P-selectin and αIIbβ3 expression. P-selectin on activated platelets interacts with integrin αIIb3 on monocytes to form platelet-monocyte complexes, which induce monocyte tissue factor expression (Hottz et al., 2020). The activated platelets can also induce neutrophils to release neutrophil extracellular traps (NETs; Middleton et al., 2020). Furthermore, platelets from COVID-19 patients aggregate and adhere more efficiently to collagen-coated surfaces under flow conditions (Manne et al., 2020Zaid et al., 2020). Meanwhile, activated platelets release α- and dense-granule contents including FV, FXI, fibrinogen and vWF (Zaid et al., 2020). In addition, activated platelets also produce inflammatory cytokines, fueling cytokine storm (Taus et al., 2020Zaid et al., 2020). Most importantly, activated platelets expose higher levels of PS and release higher numbers of PS+ MPs (Figures 3EGZaid et al., 2020Althaus et al., 2021).

Phosphatidylserine is the most abundant negatively charged phospholipid in mammalian cells and is usually confined to the inner leaflet of the cell membrane (Versteeg et al., 2013). This asymmetry is maintained through ATP-dependent inward transport of PS by flippases and outward transport of other phospholipids by floppases (Figure 3A left). Upon stimulation, transiently increased calcium inhibits ATP-dependent transport and stimulates the nonselective lipid transporter scramblase (ATP-independent), resulting in PS exposure on the outer membrane (Figure 3A right). During this process, microvesicles derived from the budding of cellular membranes will be released. These MPs are typically <1 μm and express PS (Burnier et al., 2009). The exposure of PS on the surface of cells and MPs provides a catalytic surface for factor Xa and thrombin formation in vivo (Versteeg et al., 2013). We have previously demonstrated that PS mediates 90% of Xa and thrombin formation and significantly increases thrombosis in vivo (Shi and Gilbert, 2003).

Cytokines and virus infection can activate blood cells and ECs, resulting in higher levels of PS+ cells and MPs. As COVID-19 progresses, the developing cytokine storm activates more blood cells, leading to PS storm. Platelets are highly sensitive to circulating cytokines, releasing large amounts of cytokines and PS exposed MPs into the plasma (Taus et al., 2020Althaus et al., 2021) and thus are a major contributor to PS storm. Previous studies found an unusual elevation of FVa in severe COVID-19 patients (248 IU/dl, higher than any previous disease; Stefely et al., 2020von Meijenfeldt et al., 2021). The degree of FVa elevation in these patients may be the result of PS storm.

Collectively, SARS-CoV-2 infection is the initiating factor for injury of the intestinal vascular ECs, which is then aggravated by systemic cytokines, leading to endotheliitis. Subsequently, the hyperactivated platelets in circulation rapidly accumulate around the damaged ECs, inducing tissue factor expression, NET release, and activating the intrinsic/extrinsic coagulation pathways. Simultaneously, the high levels of PS expression in circulating cells and MPs further promote thrombin and fibrin formation (Figure 2 top).

Early Antithrombotic Treatment

Vaccines and antithrombotic therapy are effective measures to reduce intestinal damage and fight against the COVID-19 pandemic (Baden et al., 2021Chalmers et al., 2021). Vaccines induce adaptive immunity to clear the virus, reducing intestinal infection and intestinal damage. However, the usefulness of vaccines is limited by incomplete vaccine acceptance and viral mutations (Hacisuleyman et al., 2021Wang et al., 2021). Vaccines are also ineffective for already infected patients. Therefore, more attention should be paid to antithrombotic therapy. Studies had shown that thrombotic events mainly occurred within 7 days of COVID-19 diagnosis (both inpatients and outpatients; Mouhat et al., 2020Ho et al., 2021). Meanwhile, two large randomized controlled trials (RCTs) from the same platform showed that therapeutic anticoagulation reduced mortality in moderate cases but not in severe ones, suggesting that delayed anticoagulant therapy may lead to treatment failure (REMAP-CAP Investigators et al., 2021a,b). More importantly, a recent study reported three asymptomatic COVID-19 patients who developed abdominal (or intestinal) thrombosis leading to intestinal necrosis (Zamboni et al., 2021). All these data suggest that antithrombotic therapy should be initiated once COVID-19 is diagnosed (excluding patients with contraindications). Early prophylactic antithrombotic therapy can reduce the activation of vascular ECs and blood cells, preventing intestinal thrombosis, ensuring sufficient intestinal perfusion, maintaining the normal gut–blood barrier, avoiding malabsorption, malnutrition, and intestinal flora entering the bloodstream. Further, attenuated injury and decreased microthrombi in convalescent patients may lower the risk of long-term GI sequelae. Meanwhile, unobstructed systemic circulation can also accelerate the removal of SARS-CoV-2, inflammatory cytokines and damaged blood cells by the mononuclear phagocyte system.

Anticoagulation

Table 1 summarizes the RCTs of anticoagulant therapy in COVID-19 patients. For outpatients, early anticoagulant therapy reduced hospitalization and supplemental oxygen (Gonzalez-Ochoa). While, delayed treatment had no similar effect (ACTIV-4B and Ananworanich). Thus, oral anticoagulant therapy should be initiated in outpatients once COVID-19 is diagnosed. For non-critically ill patients, therapeutic doses of low molecular weight heparin (LMWH) reduced thrombotic events and mortality, and increased organ support-free days (REMAP-CAP, ACTIV-4a, ATTACC; RAPID; HEP-COVID). However, therapeutic doses of rivaroxaban did not improve clinical outcomes and increased bleeding (ACTION). This is potentially because novel oral anticoagulants do not share the anti-inflammatory and antiviral functions of heparin. Intestinal damage might also result in abnormal absorption of oral anticoagulants. Therefore, therapeutic LMWH should be the first choice for non-critically ill patients. For critically ill patients, RCTs showed that moderate and therapeutic doses were not superior to prophylactic ones. Results from several other studies suggest that the overwhelming thrombosis leads to failure of anticoagulant therapy at therapeutic doses (Leentjens et al., 2021Poor, 2021). Faced with this dilemma, an editorial in N Engl J Med argued that profibrinolytic strategies should be considered (Ten Cate, 2021). More studies are needed to explore optimal antithrombotic therapy in critically ill patients.TABLE 1

Table 1. Randomized clinical trials of anticoagulant therapy in COVID-19 patients.

Inhibition of Platelet Activation

As COVID-19 progresses, cytokine storm activates platelets, which not only participate in primary hemostasis, but also are the major components of PS storm. Autopsy results show a high prevalence of platelet-fibrin-rich microthrombi in lung and extrapulmonary organs, including the gastrointestinal tract (Bradley et al., 2020Polak et al., 2020). Early inhibition of platelet activation can reduce platelet activity and prevent PS storm, thus decreasing thrombosis and mortality. Several observational studies have shown that aspirin decreases mechanical ventilation, ICU admission, and mortality (Chow et al., 2020Santoro et al., 2022). The RCTs testing antiplatelet agents were still preliminary. A recent RCT suggested that aspirin was associated with an increase in survival and reduction in thrombotic events (RECOVERY Collaborative Group, 2022). In addition, anti-inflammatory therapy (e.g., dexamethasone, 6 mg once daily; RECOVERY Collaborative Group et al., 2020) inhibits cytokine storm, as well as platelet activation, reducing mortality. Overall, inhibition of platelet activation is also important to reduce mortality through the prevention of thrombosis and organs damage.

Factors Influencing Antithrombotic Treatment

Thrombotic Risk Factors or Co-morbidities

Studies have shown that obesity, hyperglycemia and diabetes are associated with increased thrombotic events (including intestinal thrombosis), COVID-19 severity, and mortality (Drucker, 2021Stefan et al., 2021). Other thrombotic risk factors include previous venous thromboembolism, active cancer, known thrombophilic condition, recent trauma or surgery, age ≥70 years, respiratory/cardiac/renal failure, and inflammatory bowel disease (Susen et al., 2020). These factors or co-morbidities heighten basal inflammatory levels and endothelial damage, leading to premature cytokine and PS storms, ultimately increasing thrombosis and mortality. Thus, more active antithrombotic therapy strategies should be adopted in these patients. For patients with mild COVID-19 with these factors, the French Working Group on Perioperative Hemostasis and the French Study Group on Thrombosis and Hemostasis recommend higher (intermediate) doses of anticoagulant therapy (Susen et al., 2020). For moderately ill patients, therapeutic doses of anticoagulant therapy should be initiated as soon as possible to prevent excessive microthrombus formation. The need for extended thromboprophylaxis in discharged patients remains controversial. However, a recent RCT showed that rivaroxaban (10 mg/day, 35 days) improved clinical outcomes in discharged COVID-19 patients with higher thrombotic risk factors (Ramacciotti et al., 2022), supporting extended thromboprophylaxis in patients with these risk factors or co-morbidities.

Vaccination

Although more than half the world population has received at least one dose of the vaccines, there are relatively little data of antithrombotic therapy in vaccinated patients. Studies of viral dynamics show that the viral loads of vaccinated patients are as high as that of unvaccinated patients, but drop significantly faster (Brown et al., 2021Klompas, 2021). Thus, vaccinated patients have shorter hospital stays, and are less likely to progress to critical illness and death (Tenforde et al., 2021Thompson et al., 2021). Nevertheless, antithrombotic therapy is still beneficial for the vaccinated patients. Firstly, heparin has anti-inflammatory and antiviral functions and can interfere with the binding of SARS-CoV-2 to ACE2 and shorten the duration of virus infection (Kwon et al., 2020Pereyra et al., 2021). Secondly, antithrombotic therapy protects cells from damage, PS exposure, and microthrombi formation, maintains unobstructed blood circulation, and facilitates virus clearance (by vaccine-induced adaptive immunity). Thirdly, thrombosis remains an important factor in disease progression. Antithrombotic therapy further reduces thrombosis and mortality, especially in vaccinated patients with high risk factors or co-morbidities. Lastly, although vaccines reduce the incidence, a subset of vaccinated patients will still develop long-term sequelae or Long Covid (Ledford, 2021Antonelli et al., 2022). Persistent viral infection and microthrombi are the primary causes (Ledford, 2021Xie et al., 2022), and early antithrombotic therapy is still needed to prevent them.

Conclusion and Future Research

During COVID-19 disease progression, SARS-CoV-2 infiltrates the blood stream from the initial respiratory tract infection, causing viremia, hyperactivated platelets and PS storm. The virus settles into the vascular beds of extrapulmonary organs, ultimately causing infection of intestinal epithelial cell. Damaged ECs, combined with hyperactivated platelets and PS storm, promote intestinal thrombosis, resulting in intestinal ischemia or necrosis. The damaged gut–blood barrier leads to malabsorption, malnutrition and intestinal flora entering the bloodstream, which significantly increase disease severity and mortality. Prolonged intestinal infection, persistent endothelial injury and microthrombi contribute to the long-term GI sequelae after discharge. Early prophylactic antithrombotic therapy can prevent microthrombi, ensuring sufficient intestinal perfusion, maintaining the normal intestinal function, and reducing the risk of long-term GI sequelae. More active antithrombotic therapy should be adopted in patients with other thrombotic risk factors or co-morbidities. Even in vaccinated COVID-19 patients, antithrombotic therapy is also important to decrease (intestinal) thrombosis, mortality and the risk of long-term GI sequelae.

With the Omicron pandemic, patients requiring hospitalization and ICU treatment decline rapidly. However, people are increasingly concerned about Long Covid. In terms of long-term GI sequelae, the detailed mechanisms of prolonged intestinal infection and persistent microthrombi remain unclear. And whether anticoagulant therapy can decrease GI symptoms in patients with long-term GI sequelae deserves further study. Finally, the impact of vaccines on long-term GI sequelae remains unclear in previously infected and breakthrough infected patients.

References

Aiyegbusi, O. L., Hughes, S. E., Turner, G., Rivera, S. C., McMullan, C., Chandan, J. S., et al. (2021). Symptoms, complications and management of long COVID: a review. J. R. Soc. Med. 114, 428–442. doi: 10.1177/01410768211032850

PubMed Abstract | CrossRef Full Text | Google Scholar

Althaus, K., Marini, I., Zlamal, J., Pelzl, L., Singh, A., Häberle, H., et al. (2021). Antibody-induced procoagulant platelets in severe COVID-19 infection. Blood 137, 1061–1071. doi: 10.1182/blood.2020008762

PubMed Abstract | CrossRef Full Text | Google Scholar

Ananworanich, J., Mogg, R., Dunne, M. W., Bassyouni, M., David, C. V., Gonzalez, E., et al. (2021). Randomized study of rivaroxaban vs. placebo on disease progression and symptoms resolution in high-risk adults with mild COVID-19. Clin. Infect. Dis. doi: 10.1093/cid/ciab813 [Epub ahead of print].

PubMed Abstract | CrossRef Full Text | Google Scholar

Antonelli, M., Penfold, R. S., Merino, J., Sudre, C. H., Molteni, E., Berry, S., et al. (2022). Risk factors and disease profile of post-vaccination SARS-CoV-2 infection in UK users of the COVID symptom study app: a prospective, community-based, nested, case-control study. Lancet Infect. Dis. 22, 43–55. doi: 10.1016/S1473-3099(21)00460-6

CrossRef Full Text | Google Scholar

Baden, L. R., El Sahly, H. M., Essink, B., Kotloff, K., Frey, S., Novak, R., et al. (2021). Efficacy and safety of the mRNA-1273 SARS-CoV-2 vaccine. N. Engl. J. Med. 384, 403–416. doi: 10.1056/NEJMoa2035389

CrossRef Full Text | Google Scholar

Bhayana, R., Som, A., Li, M. D., Carey, D. E., Anderson, M. A., Blake, M. A., et al. (2020). Abdominal imaging findings in COVID-19: preliminary observations. Radiology 297, E207–E215. doi: 10.1148/radiol.2020201908

PubMed Abstract | CrossRef Full Text | Google Scholar

Bradley, B. T., Maioli, H., Johnston, R., Chaudhry, I., Fink, S. L., Xu, H., et al. (2020). Histopathology and ultrastructural findings of fatal COVID-19 infections in Washington state: a case series. Lancet 396, 320–332. doi: 10.1016/S0140-6736(20)31305-2

PubMed Abstract | CrossRef Full Text | Google Scholar

Brown, C. M., Vostok, J., Johnson, H., Burns, M., Gharpure, R., Sami, S., et al. (2021). Outbreak of SARS-CoV-2 infections, including COVID-19 vaccine breakthrough infections, associated with large public gatherings – Barnstable County, Massachusetts, July 2021. MMWR Morb. Mortal. Wkly Rep. 70, 1059–1062. doi: 10.15585/mmwr.mm7031e2

PubMed Abstract | CrossRef Full Text | Google Scholar

Burnier, L., Fontana, P., Kwak, B. R., and Angelillo-Scherrer, A. (2009). Cell-derived microparticles in haemostasis and vascular medicine. Thromb. Haemost. 101, 439–451. doi: 10.1160/TH08-08-0521

CrossRef Full Text | Google Scholar

Bushman, F. D., McCormick, K., and Sherrill-Mix, S. (2019). Virus structures constrain transmission modes. Nat. Microbiol. 4, 1778–1780. doi: 10.1038/s41564-019-0523-5

PubMed Abstract | CrossRef Full Text | Google Scholar

Caccialanza, R., Formisano, E., Klersy, C., Ferretti, V., Ferrari, A., Demontis, S., et al. (2021). Nutritional parameters associated with prognosis in non-critically ill hospitalized COVID-19 patients: the NUTRI-COVID19 study. Clin. Nutr. doi: 10.1016/j.clnu.2021.06.020 [Epub ahead of print].

CrossRef Full Text | Google Scholar

Chalmers, J. D., Crichton, M. L., Goeminne, P. C., Cao, B., Humbert, M., Shteinberg, M., et al. (2021). Management of hospitalised adults with coronavirus disease 2019 (COVID-19): a European Respiratory Society living guideline. Eur. Respir. J. 57:2100048. doi: 10.1183/13993003.00048-2021

PubMed Abstract | CrossRef Full Text | Google Scholar

Chan, K. H., Sridhar, S., Zhang, R. R., Chu, H., Fung, A. Y., Chan, G., et al. (2020). Factors affecting stability and infectivity of SARS-CoV-2. J. Hosp. Infect. 106, 226–231. doi: 10.1016/j.jhin.2020.07.009

CrossRef Full Text | Google Scholar

Chang, L., Zhao, L., Gong, H., Wang, L., and Wang, L. (2020). Severe acute respiratory syndrome coronavirus 2 RNA detected in blood donations. Emerg. Infect. Dis. 26, 1631–1633. doi: 10.3201/eid2607.200839

PubMed Abstract | CrossRef Full Text | Google Scholar

Cheung, C. C. L., Goh, D., Lim, X., Tien, T. Z., Lim, J. C. T., Lee, J. N., et al. (2022). Residual SARS-CoV-2 viral antigens detected in GI and hepatic tissues from five recovered patients with COVID-19. Gut 71, 226–229. doi: 10.1136/gutjnl-2021-324280

PubMed Abstract | CrossRef Full Text | Google Scholar

Cheung, K. S., Hung, I. F. N., Chan, P. P. Y., Lung, K. C., Tso, E., Liu, R., et al. (2020). Gastrointestinal manifestations of SARS-CoV-2 infection and virus load in faecal samples from a Hong Kong cohort: systematic review and meta-analysis. Gastroenterology 159, 81–95. doi: 10.1053/j.gastro.2020.03.065

CrossRef Full Text | Google Scholar

Chiu, C. Y., Sarwal, A., Mon, A. M., Tan, Y. E., and Shah, V. (2020). Gastrointestinal: COVID-19 related ischemic bowel disease. J. Gastroenterol. Hepatol. 36:850. doi: 10.1111/jgh.15254

PubMed Abstract | CrossRef Full Text | Google Scholar

Chow, J. H., Khanna, A. K., Kethireddy, S., Yamane, D., Levine, A., Jackson, A. M., et al. (2020). Aspirin use is associated with decreased mechanical ventilation, ICU admission, and in-hospital mortality in hospitalized patients with COVID-19. Anesth. Analg. 132, 930–941. doi: 10.1213/ANE.0000000000005292

CrossRef Full Text | Google Scholar

Connors, J. M., Brooks, M. M., Sciurba, F. C., Krishnan, J. A., Bledsoe, J. R., Kindzelski, A., et al. (2021). Effect of antithrombotic therapy on clinical outcomes in outpatients with clinically stable symptomatic COVID-19: the ACTIV-4B randomized clinical trial. JAMA 326, 1703–1712. doi: 10.1001/jama.2021.17272

PubMed Abstract | CrossRef Full Text | Google Scholar

D’Amico, F., Baumgart, D. C., Danese, S., and Peyrin-Biroulet, L. (2020). Diarrhea during COVID-19 infection: pathogenesis, epidemiology, prevention, and management. Clin. Gastroenterol. Hepatol. 18, 1663–1672. doi: 10.1016/j.cgh.2020.04.001

PubMed Abstract | CrossRef Full Text | Google Scholar

Das Adhikari, U., Eng, G., Farcasanu, M., Avena, L. E., Choudhary, M. C., Triant, V. A., et al. (2021). Faecal SARS-CoV-2 RNA is associated with decreased COVID-19 survival. Clin. Infect. Dis. doi: 10.1093/cid/ciab623 Epub ahead of print

PubMed Abstract | CrossRef Full Text | Google Scholar

Deng, W., Bao, L., Gao, H., Xiang, Z., Qu, Y., Song, Z., et al. (2020). Ocular conjunctival inoculation of SARS-CoV-2 can cause mild COVID-19 in rhesus macaques. Nat. Commun. 11:4400. doi: 10.1038/s41467-020-18149-6

CrossRef Full Text | Google Scholar

Di Filippo, L., De Lorenzo, R., D’Amico, M., Sofia, V., Roveri, L., Mele, R., et al. (2021). COVID-19 is associated with clinically significant weight loss and risk of malnutrition, independent of hospitalisation: a post-hoc analysis of a prospective cohort study. Clin. Nutr. 40, 2420–2426. doi: 10.1016/j.clnu.2020.10.043

PubMed Abstract | CrossRef Full Text | Google Scholar

Drucker, D. J. (2021). Diabetes, obesity, metabolism, and SARS-CoV-2 infection: the end of the beginning. Cell Metab. 33, 479–498. doi: 10.1016/j.cmet.2021.01.016

CrossRef Full Text | Google Scholar

El Moheb, M., Naar, L., Christensen, M. A., Kapoen, C., Maurer, L. R., Farhat, M., et al. (2020). Gastrointestinal complications in critically ill patients with and without COVID-19. JAMA 324, 1899–1901. doi: 10.1001/jama.2020.19400

PubMed Abstract | CrossRef Full Text | Google Scholar

Fogarty, H., Townsend, L., Morrin, H., Ahmad, A., Comerford, C., Karampini, E., et al. (2021). Persistent endotheliopathy in the pathogenesis of long COVID syndrome. J. Thromb. Haemost. 19, 2546–2555. doi: 10.1111/jth.15490

CrossRef Full Text | Google Scholar

Gao, C., Xie, R., Yu, C., Ma, R., Dong, W., Meng, H., et al. (2015). Thrombotic role of blood and endothelial cells in uremia through phosphatidylserine exposure and microparticle release. PLoS One 10:e0142835. doi: 10.1371/journal.pone.0142835

PubMed Abstract | CrossRef Full Text | Google Scholar

Gonzalez-Ochoa, A. J., Raffetto, J. D., Hernández, A. G., Zavala, N., Gutiérrez, O., Vargas, A., et al. (2021). Sulodexide in the treatment of patients with early stages of COVID-19: a randomized controlled trial. Thromb. Haemost. 121, 944–954. doi: 10.1055/a-1414-5216

CrossRef Full Text | Google Scholar

Goshua, G., Pine, A. B., Meizlish, M. L., Chang, C. H., Zhang, H., Bahel, P., et al. (2020). Endotheliopathy in COVID-19-associated coagulopathy: evidence from a single-Centre, cross-sectional study. Lancet Haematol. 7, e575–e582. doi: 10.1016/S2352-3026(20)30216-7

CrossRef Full Text | Google Scholar

Guo, M., Tao, W., Flavell, R. A., and Zhu, S. (2021). Potential intestinal infection and faecal-oral transmission of SARS-CoV-2. Nat. Rev. Gastroenterol. Hepatol. 18, 269–283. doi: 10.1038/s41575-021-00416-6

CrossRef Full Text | Google Scholar

Hacisuleyman, E., Hale, C., Saito, Y., Blachere, N. E., Bergh, M., Conlon, E. G., et al. (2021). Vaccine breakthrough infections with SARS-CoV-2 variants. N. Engl. J. Med. 384, 2212–2218. doi: 10.1056/NEJMoa2105000

CrossRef Full Text | Google Scholar

Hasanoglu, I., Korukluoglu, G., Asilturk, D., Cosgun, Y., Kalem, A. K., Altas, A. B., et al. (2021). Higher viral loads in asymptomatic COVID-19 patients might be the invisible part of the iceberg. Infection 49, 117–126. doi: 10.1007/s15010-020-01548-8

PubMed Abstract | CrossRef Full Text | Google Scholar

He, Z., Si, Y., Jiang, T., Ma, R., Zhang, Y., Cao, M., et al. (2016). Phosphotidylserine exposure and neutrophil extracellular traps enhance procoagulant activity in patients with inflammatory bowel disease. Thromb. Haemost. 115, 738–751. doi: 10.1160/TH15-09-0710

CrossRef Full Text | Google Scholar

Ho, F. K., Man, K. K. C., Toshner, M., Church, C., Celis-Morales, C., Wong, I. C. K., et al. (2021). Thromboembolic risk in hospitalized and nonhospitalized COVID-19 patients: a self-controlled case series analysis of a nationwide cohort. Mayo Clin. Proc. 96, 2587–2597. doi: 10.1016/j.mayocp.2021.07.002

PubMed Abstract | CrossRef Full Text | Google Scholar

Hottz, E. D., Azevedo-Quintanilha, I. G., Palhinha, L., Teixeira, L., Barreto, E. A., Pão, C. R. R., et al. (2020). Platelet activation and platelet-monocyte aggregates formation trigger tissue factor expression in severe COVID-19 patients. Blood 136, 1330–1341. doi: 10.1182/blood.2020007252

PubMed Abstract | CrossRef Full Text | Google Scholar

Hu, F., Chen, F., Ou, Z., Fan, Q., Tan, X., Wang, Y., et al. (2020). A compromised specific Humoral immune response against the SARS-CoV-2 receptor-binding domain is related to viral persistence and periodic shedding in the gastrointestinal tract. Cell. Mol. Immunol. 17, 1119–1125. doi: 10.1038/s41423-020-00550-2

CrossRef Full Text | Google Scholar

Huang, N., Pérez, P., Kato, T., Mikami, Y., Okuda, K., Gilmore, R. C., et al. (2021). SARS-CoV-2 infection of the oral cavity and saliva. Nat. Med. 27, 892–903. doi: 10.1038/s41591-021-01296-8

PubMed Abstract | CrossRef Full Text | Google Scholar

INSPIRATION Investigators Sadeghipour, P., Talasaz, A. H., Rashidi, F., Sharif-Kashani, B., Beigmohammadi, M. T., et al. (2021). Effect of intermediate-dose vs. standard-dose prophylactic anticoagulation on thrombotic events, extracorporeal membrane oxygenation treatment, or mortality among patients with COVID-19 admitted to the intensive care unit: the INSPIRATION randomized clinical trial. JAMA 325, 1620–1630. doi: 10.1001/jama.2021.4152

PubMed Abstract | CrossRef Full Text | Google Scholar

Jacobs, J. L., and Mellors, J. W. (2020). Detection of SARS-CoV-2 RNA in blood of patients with COVID-19: what does it mean? Clin. Infect. Dis. doi: 10.1093/cid/ciaa1316 [Epub ahead of print].

CrossRef Full Text | Google Scholar

Kaafarani, H. M. A., El Moheb, M., Hwabejire, J. O., Naar, L., Christensen, M. A., Breen, K., et al. (2020). Gastrointestinal complications in critically ill patients with COVID-19. Ann. Surg. 272, e61–e62. doi: 10.1097/SLA.0000000000004004

CrossRef Full Text | Google Scholar

Klompas, M. (2021). Understanding breakthrough infections following mRNA SARS-CoV-2 vaccination. JAMA 326, 2018–2020. doi: 10.1001/jama.2021.19063

PubMed Abstract | CrossRef Full Text | Google Scholar

Kwon, P. S., Oh, H., Kwon, S. J., Jin, W., Zhang, F., Fraser, K., et al. (2020). Sulfated polysaccharides effectively inhibit SARS-CoV-2 in vitro. Cell Discov. 6:50. doi: 10.1038/s41421-020-00192-8

PubMed Abstract | CrossRef Full Text | Google Scholar

Lan, J., Ge, J., Yu, J., Shan, S., Zhou, H., Fan, S., et al. (2020). Structure of the SARS-CoV-2 spike receptor-binding domain bound to the ACE2 receptor. Nature 581, 215–220. doi: 10.1038/s41586-020-2180-5

CrossRef Full Text | Google Scholar

Ledford, H. (2021). Do vaccines protect against long COVID? What the data say. Nature 599, 546–548. doi: 10.1038/d41586-021-03495-2

CrossRef Full Text | Google Scholar

Leentjens, J., van Haaps, T. F., Wessels, P. F., Schutgens, R. E. G., and Middeldorp, S. (2021). COVID-19-associated coagulopathy and antithrombotic agents-lessons after 1 year. Lancet Haematol. 8, e524–e533. doi: 10.1016/S2352-3026(21)00105-8

PubMed Abstract | CrossRef Full Text | Google Scholar

Lemos, A. C. B., do Espírito Santo, D. A., Salvetti, M. C., Gilio, R. N., Agra, L. B., Pazin-Filho, A., et al. (2020). Therapeutic versus prophylactic anticoagulation for severe COVID-19: a randomized phase II clinical trial (HESACOVID). Thromb. Res. 196, 359–366. doi: 10.1016/j.thromres.2020.09.026

PubMed Abstract | CrossRef Full Text | Google Scholar

Li, L., Huang, M., Shen, J., Wang, Y., Wang, R., Yuan, C., et al. (2021). Serum levels of soluble platelet endothelial cell adhesion molecule 1 in COVID-19 patients are associated with disease severity. J. Infect. Dis. 223, 178–179. doi: 10.1093/infdis/jiaa642

PubMed Abstract | CrossRef Full Text | Google Scholar

Li, Y., Schneider, A. M., Mehta, A., Sade-Feldman, M., Kays, K. R., Gentili, M., et al. (2021). SARS-CoV-2 viremia is associated with distinct proteomic pathways and predicts COVID-19 outcomes. J. Clin. Invest. 131:e148635. doi: 10.1172/JCI148635

CrossRef Full Text | Google Scholar

Livanos, A. E., Jha, D., Cossarini, F., Gonzalez-Reiche, A. S., Tokuyama, M., Aydillo, T., et al. (2021). Intestinal host response to SARS-CoV-2 infection and COVID-19 outcomes in patients with gastrointestinal symptoms. Gastroenterology 16, 2435.e34–2450.e34. doi: 10.1053/j.gastro.2021.02.056

CrossRef Full Text | Google Scholar

Lopes, R. D., de Barros, E., Silva, P. G. M., Furtado, R. H. M., Macedo, A. V. S., Bronhara, B., et al. (2021). Therapeutic versus prophylactic anticoagulation for patients admitted to hospital with COVID-19 and elevated D-dimer concentration (ACTION): an open-label, multicentre, randomised, controlled trial. Lancet 397, 2253–2263. doi: 10.1016/S0140-6736(21)01203-4

CrossRef Full Text | Google Scholar

Luo, Y., Xue, Y., Mao, L., Yuan, X., Lin, Q., Tang, G., et al. (2020). Prealbumin as a predictor of prognosis in patients with coronavirus disease 2019. Front. Med. 7:374. doi: 10.3389/fmed.2020.00374

PubMed Abstract | CrossRef Full Text | Google Scholar

Lv, L., Jiang, H., Chen, Y., Gu, S., Xia, J., Zhang, H., et al. (2021). The faecal metabolome in COVID-19 patients is altered and associated with clinical features and gut microbes. Anal. Chim. Acta 1152:338267. doi: 10.1016/j.aca.2021.338267

PubMed Abstract | CrossRef Full Text | Google Scholar

Ma, R., Xie, R., Yu, C., Si, Y., Wu, X., Zhao, L., et al. (2017). Phosphatidylserine-mediated platelet clearance by endothelium decreases platelet aggregates and procoagulant activity in sepsis. Sci. Rep. 7:4978. doi: 10.1038/s41598-018-24187-4

PubMed Abstract | CrossRef Full Text | Google Scholar

Manne, B. K., Denorme, F., Middleton, E. A., Portier, I., Rowley, J. W., Stubben, C., et al. (2020). Platelet gene expression and function in patients with COVID-19. Blood 136, 1317–1329. doi: 10.1182/blood.2020007214

PubMed Abstract | CrossRef Full Text | Google Scholar

Mao, R., Qiu, Y., He, J. S., Tan, J. Y., Li, X. H., Liang, J., et al. (2020). Manifestations and prognosis of gastrointestinal and liver involvement in patients with COVID-19: a systematic review and meta-analysis. Lancet Gastroenterol. Hepatol. 5, 667–678. doi: 10.1016/S2468-1253(20)30126-6

PubMed Abstract | CrossRef Full Text | Google Scholar

Marcos-Jubilar, M., Carmona-Torre, F., Vidal Laso, R., Ruiz-Artacho, P., Filella, D., Carbonell, C., et al. (2022). Therapeutic versus prophylactic bemiparin in hospitalized patients with non-severe COVID-19 pneumonia (BEMICOP): an open-label, multicenter, randomized trial. Thromb. Haemost. 122, 295–299. doi: 10.1055/a-1667-7534

PubMed Abstract | CrossRef Full Text | Google Scholar

McFadyen, D. J., Stevens, H., and Karlheinz, P. (2020). The emerging threat of (micro)thrombosis in COVID-19 and its therapeutic implications. Circ. Res. 127, 571–587. doi: 10.1161/CIRCRESAHA.120.317447

CrossRef Full Text | Google Scholar

Middleton, E. A., He, X. Y., Denorme, F., Campbell, R. A., Ng, D., Salvatore, S. P., et al. (2020). Neutrophil extracellular traps contribute to immunothrombosis in COVID-19 acute respiratory distress syndrome. Blood 136, 1169–1179. doi: 10.1182/blood.2020007008

CrossRef Full Text | Google Scholar

Moore, J. B., and June, C. H. (2020). Cytokine release syndrome in severe COVID-19. Science 368, 473–474. doi: 10.1126/science.abb8925

CrossRef Full Text | Google Scholar

Mouhat, B., Besutti, M., Bouiller, K., Grillet, F., Monnin, C., Ecarnot, F., et al. (2020). Elevated D-dimers and lack of anticoagulation predict PE in severe COVID-19 patients. Eur. Respir. J. 56:2001811. doi: 10.1183/13993003.01811-2020

PubMed Abstract | CrossRef Full Text | Google Scholar

Norsa, L., Bonaffini, P. A., Indriolo, A., Valle, C., Sonzogni, A., and Sironi, S. (2020). Poor outcome of intestinal ischemic manifestations of COVID-19. Gastroenterology 159, 1595.e1–1597.e1. doi: 10.1053/j.gastro.2020.06.041

PubMed Abstract | CrossRef Full Text | Google Scholar

Perepu, U. S., Chambers, I., Wahab, A., Ten Eyck, P., Wu, C., Dayal, S., et al. (2021). Standard prophylactic versus intermediate dose enoxaparin in adults with severe COVID-19: a multi-center, open-label, randomized controlled trial. J. Thromb. Haemost. 19, 2225–2234. doi: 10.1111/jth.15450

PubMed Abstract | CrossRef Full Text | Google Scholar

Pereyra, D., Heber, S., Schrottmaier, W. C., Santol, J., Pirabe, A., Schmuckenschlager, A., et al. (2021). Low molecular weight heparin use in COVID-19 is associated with curtailed viral persistence: a retrospective multicenter observational study. Cardiovasc. Res. 117, 2807–2820. doi: 10.1093/cvr/cvab308

PubMed Abstract | CrossRef Full Text | Google Scholar

Polak, S. B., Van Gool, I. C., Cohen, D., von der Thüsen, J. H., and van Paassen, J. (2020). A systematic review of pathological findings in COVID-19: a pathophysiological timeline and possible mechanisms of disease progression. Mod. Pathol. 33, 2128–2138. doi: 10.1038/s41379-020-0603-3

CrossRef Full Text | Google Scholar

Poor, H. D. (2021). Pulmonary thrombosis and thromboembolism in COVID-19. Chest 160, 1471–1480. doi: 10.1016/j.chest.2021.06.016

CrossRef Full Text | Google Scholar

Puelles, V. G., Lütgehetmann, M., Lindenmeyer, M. T., Sperhake, J. P., Wong, M. N., Allweiss, L., et al. (2020). Multiorgan and renal tropism of SARS-CoV-2. N. Engl. J. Med. 383, 590–592. doi: 10.1056/NEJMc2011400

PubMed Abstract | CrossRef Full Text | Google Scholar

Ramacciotti, E., Barile Agati, L., Calderaro, D., Aguiar, V. C. R., Spyropoulos, A. C., de Oliveira, C. C. C., et al. (2022). Rivaroxaban versus no anticoagulation for post-discharge thromboprophylaxis after hospitalisation for COVID-19 (MICHELLE): an open-label, multicentre, randomised, controlled trial. Lancet 399, 50–59. doi: 10.1016/S0140-6736(21)02392-8

PubMed Abstract | CrossRef Full Text | Google Scholar

RECOVERY Collaborative Group (2022). Aspirin in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial. Lancet 399, 143–151. doi: 10.1016/S0140-6736(21)01825-0

CrossRef Full Text | Google Scholar

RECOVERY Collaborative Group Horby, P., Lim, W. S., Emberson, J. R., Mafham, M., Bell, J. L., et al. (2020). Dexamethasone in hospitalized patients with Covid-19. N. Engl. J. Med. 384, 693–704. doi: 10.1056/NEJMoa2021436

PubMed Abstract | CrossRef Full Text | Google Scholar

REMAP-CAP Investigators ACTIV-4a Investigators ATTACC Investigators Goligher, E. C., Bradbury, C. A., McVerry, B. J., et al. (2021a). Therapeutic anticoagulation with heparin in critically ill patients with Covid-19. N. Engl. J. Med. 385, 777–789. doi: 10.1056/NEJMoa2103417

PubMed Abstract | CrossRef Full Text | Google Scholar

REMAP-CAP Investigators ACTIV-4a Investigators ATTACC Investigators Lawler, P. R., Goligher, E. C., Berger, J. S., et al. (2021b). Therapeutic anticoagulation with heparin in noncritically ill patients with Covid-19. N. Engl. J. Med. 385, 790–802. doi: 10.1056/NEJMoa2105911

PubMed Abstract | CrossRef Full Text | Google Scholar

Rizvi, A., Patel, Z., Liu, Y., Satapathy, S. K., Sultan, K., and Trindade, A. J. (2021). Gastrointestinal sequelae 3 and 6 months after hospitalization for coronavirus disease 2019. Clin. Gastroenterol. Hepatol. 19, 2438.e1–2440.e1. doi: 10.1016/j.cgh.2021.06.046

CrossRef Full Text | Google Scholar

Santoro, F., Nuñez-Gil, I. J., Vitale, E., Viana-Llamas, M. C., Reche-Martinez, B., Romero-Pareja, R., et al. (2022). Antiplatelet therapy and outcome in COVID-19: the health outcome predictive evaluation registry. Heart 108, 130–136. doi: 10.1136/thoraxjnl-2021-217561

PubMed Abstract | CrossRef Full Text | Google Scholar

Shi, J., and Gilbert, G. E. (2003). Lactadherin inhibits enzyme complexes of blood coagulation by completing for phospholipid binding sites. Blood 101, 2628–2636. doi: 10.1182/blood-2002-07-1951

PubMed Abstract | CrossRef Full Text | Google Scholar

Sholzberg, M., Tang, G. H., Rahhal, H., AlHamzah, M., Kreuziger, L. B., Áinle, F. N., et al. (2021). Effectiveness of therapeutic heparin versus prophylactic heparin on death, mechanical ventilation, or intensive care unit admission in moderately ill patients with covid-19 admitted to hospital: RAPID randomised clinical trial. BMJ 375:n2400. doi: 10.1136/bmj.n2400

CrossRef Full Text | Google Scholar

Spyropoulos, A. C., Goldin, M., Giannis, D., Diab, W., Wang, J., Khanijo, S., et al. (2021). Efficacy and safety of therapeutic-dose heparin vs. standard prophylactic or intermediate-dose heparins for thromboprophylaxis in high-risk hospitalized patients with COVID-19: the HEP-COVID randomized clinical trial. JAMA Intern. Med. 181, 1612–1620. doi: 10.1001/jamainternmed.2021.6203

PubMed Abstract | CrossRef Full Text | Google Scholar

Stefan, N., Birkenfeld, A. L., and Schulze, M. B. (2021). Global pandemics interconnected – obesity, impaired metabolic health and COVID-19. Nat. Rev. Endocrinol. 17, 135–149. doi: 10.1038/s41574-020-00462-1

CrossRef Full Text | Google Scholar

Stefely, J. A., Christensen, B. B., Gogakos, T., Cone Sullivan, J. K., Montgomery, G. G., Barranco, J. P., et al. (2020). Marked factor V activity elevation in severe COVID-19 is associated with venous thromboembolism. Am. J. Hematol. 95, 1522–1530. doi: 10.1002/ajh.25979

PubMed Abstract | CrossRef Full Text | Google Scholar

Suh, Y. J., Hong, H., Ohana, M., Bompard, F., Revel, M. P., Valle, C., et al. (2021). Pulmonary embolism and deep vein thrombosis in COVID-19: a systematic review and meta-analysis. Radiology 298, E70–E80. doi: 10.1148/radiol.2020203557

CrossRef Full Text | Google Scholar

Sultan, S., Altayar, O., Siddique, S. M., Davitkov, P., Feuerstein, J. D., Lim, J. K., et al. (2020). AGA institute rapid review of the gastrointestinal and liver manifestations of COVID-19, meta-analysis of international data, and recommendations for the consultative management of patients with COVID-19. Gastroenterology 159, 320.e27–334.e27. doi: 10.1053/j.gastro.2020.05.001

PubMed Abstract | CrossRef Full Text | Google Scholar

Susen, S., Tacquard, C. A., Godon, A., Mansour, A., Garrigue, D., Nguyen, P., et al. (2020). Prevention of thrombotic risk in hospitalized patients with COVID-19 and hemostasis monitoring. Crit. Care 24:364. doi: 10.1186/s13054-020-03000-7

CrossRef Full Text | Google Scholar

Tan, B. K., Mainbourg, S., Friggeri, A., Bertoletti, L., Douplat, M., Dargaud, Y., et al. (2021). Arterial and venous thromboembolism in COVID-19: a study-level meta-analysis. Thorax 76, 970–979. doi: 10.1136/thoraxjnl-2020-215383

PubMed Abstract | CrossRef Full Text | Google Scholar

Taus, F., Salvagno, G., Canè, S., Fava, C., Mazzaferri, F., Carrara, E., et al. (2020). Platelets promote thromboinflammation in SARS-CoV-2 pneumonia. Arterioscler. Thromb. Vasc. Biol. 40, 2975–2989. doi: 10.1161/ATVBAHA.120.315175

PubMed Abstract | CrossRef Full Text | Google Scholar

Ten Cate, H. (2021). Surviving Covid-19 with heparin? N. Engl. J. Med. 385, 845–846. doi: 10.1056/NEJMe2111151

PubMed Abstract | CrossRef Full Text | Google Scholar

Tenforde, M. W., Self, W. H., Adams, K., Gaglani, M., Ginde, A. A., McNeal, T., et al. (2021). Association between mRNA vaccination and COVID-19 hospitalization and disease severity. JAMA 326, 2043–2054. doi: 10.1001/jama.2021.19499

CrossRef Full Text | Google Scholar

Thompson, M. G., Burgess, J. L., Naleway, A. L., Tyner, H., Yoon, S. K., Meece, J., et al. (2021). Prevention and attenuation of Covid-19 with the BNT162b2 and mRNA-1273 vaccines. N. Engl. J. Med. 385, 320–329. doi: 10.1056/NEJMoa2107058

PubMed Abstract | CrossRef Full Text | Google Scholar

Tong, M., Jiang, Y., Xia, D., Xiong, Y., Zheng, Q., Chen, F., et al. (2020). Elevated expression of serum endothelial cell adhesion molecules in COVID-19 patients. J. Infect. Dis. 222, 894–898. doi: 10.1093/infdis/jiaa349

CrossRef Full Text | Google Scholar

Varga, Z., Flammer, A. J., Steiger, P., Haberecker, M., Andermatt, R., Zinkernagel, A. S., et al. (2020). Endothelial cell infection and endotheliitis in COVID-19. Lancet 395, 1417–1418. doi: 10.1016/S0140-6736(20)30937-5

PubMed Abstract | CrossRef Full Text | Google Scholar

Versteeg, H. H., Heemskerk, J. W., Levi, M., and Reitsma, P. H. (2013). New fundamentals in hemostasis. Physiol. Rev. 93, 327–358. doi: 10.1152/physrev.00016.2011

PubMed Abstract | CrossRef Full Text | Google Scholar

von Meijenfeldt, F. A., Havervall, S., Adelmeijer, J., Lundström, A., Magnusson, M., Mackman, N., et al. (2021). Elevated factor V activity and antigen levels in patients with Covid-19 are related to disease severity and 30-day mortality. Am. J. Hematol. 96, E98–E100. doi: 10.1002/ajh.26085

PubMed Abstract | CrossRef Full Text | Google Scholar

Wang, P., Nair, M. S., Liu, L., Iketani, S., Luo, Y., Guo, Y., et al. (2021). Antibody resistance of SARS-CoV-2 variants B.1.351 and B.1.1.7. Nature 593, 130–135. doi: 10.1038/s41586-021-03398-2

CrossRef Full Text | Google Scholar

Wang, W., Xu, Y., Gao, R., Han, K., Wu, G., and Tan, W. (2020). Detection of SARS-CoV-2 in different types of clinical specimens. JAMA 323, 1843–1844. doi: 10.1001/jama.2020.3786

PubMed Abstract | CrossRef Full Text | Google Scholar

Wölfel, R., Corman, V. M., Guggemos, W., Seilmaier, M., Zange, S., Müller, M. A., et al. (2020). Virological assessment of hospitalized patients with COVID-2019. Nature 581, 465–469. doi: 10.1038/s41586-020-2196-x

CrossRef Full Text | Google Scholar

Xiao, F., Sun, J., Xu, Y., Li, F., Huang, X., Li, H., et al. (2020a). Infectious SARS-CoV-2 in feces of patient with severe COVID-19. Emerg. Infect. Dis. 26, 1920–1922. doi: 10.3201/eid2608.200681

PubMed Abstract | CrossRef Full Text | Google Scholar

Xiao, F., Tang, M., Zheng, X., Liu, Y., Li, X., and Shan, H. (2020b). Evidence for gastrointestinal infection of SARS-CoV-2. Gastroenterology 158, 1831.e3–1833.e3. doi: 10.1053/j.gastro.2020.02.055

PubMed Abstract | CrossRef Full Text | Google Scholar

Xie, Y., Xu, E., Bowe, B., and Al-Aly, Z. (2022). Long-term cardiovascular outcomes of COVID-19. Nat. Med. doi: 10.1038/s41591-022-01689-3 [Epub ahead of print].

CrossRef Full Text | Google Scholar

Zaid, Y., Puhm, F., Allaeys, I., Naya, A., Oudghiri, M., Khalki, L., et al. (2020). Platelets can associate with SARS-CoV-2 RNA and are hyperactivated in COVID-19. Circ. Res. 127, 1404–1418. doi: 10.1161/CIRCRESAHA.120.317703

CrossRef Full Text | Google Scholar

Zamboni, P., Bortolotti, D., Occhionorelli, S., Traina, L., Neri, L. M., Rizzo, R., et al. (2021). Bowel ischemia as onset of COVID-19 in otherwise asymptomatic patients with persistently negative swab. J. Intern. Med. 291, 224–231. doi: 10.1111/joim.13385

CrossRef Full Text | Google Scholar

Zang, R., Gomez Castro, M. F., McCune, B. T., Zeng, Q., Rothlauf, P. W., Sonnek, N. M., et al. (2020). TMPRSS2 and TMPRSS4 promote SARS-CoV-2 infection of human small intestinal enterocytes. Sci. Immunol. 5:eabc3582. doi: 10.1126/sciimmunol.abc3582

CrossRef Full Text | Google Scholar

Zhang, Y., Chen, C., Zhu, S., Shu, C., Wang, D., Song, J., et al. (2020). Isolation of 2019-nCoV from a stool specimen of a laboratory- confirmed case of the coronavirus disease 2019 (COVID-19). China CDC Wkly 2, 123–124. doi: 10.46234/ccdcw2020.033

PubMed Abstract | CrossRef Full Text | Google Scholar

Zhang, P., He, Z., Yu, G., Peng, D., Feng, Y., Ling, J., et al. (2021). The modified NUTRIC score can be used for nutritional risk assessment as well as prognosis prediction in critically ill COVID-19 patients. Clin. Nutr. 40, 534–541. doi: 10.1016/j.clnu.2020.05.051

PubMed Abstract | CrossRef Full Text | Google Scholar

Zhang, H., Shao, B., Dang, Q., Chen, Z., Zhou, Q., Luo, H., et al. (2021). Pathogenesis and mechanism of gastrointestinal infection With COVID-19. Front. Immunol. 12:674074. doi: 10.3389/fimmu.2021.674074

CrossRef Full Text | Google Scholar

Zhao, F., Yang, Y., Wang, Z., Li, L., Liu, L., and Liu, Y. (2020). The time sequences of respiratory and rectal viral shedding in patients with coronavirus disease 2019. Gastroenterology 159, 1158.e2–1160.e2. doi: 10.1053/j.gastro.2020.05.035

CrossRef Full Text | Google Scholar

Zhong, P., Xu, J., Yang, D., Shen, Y., Wang, L., Feng, Y., et al. (2020). COVID-19-associated gastrointestinal and liver injury: clinical features and potential mechanisms. Signal Transduct. Target. Ther. 5:256. doi: 10.1038/s41392-020-00373-7

PubMed Abstract | CrossRef Full Text | Google Scholar

Zhou, J., Li, C., Liu, X., Chiu, M. C., Zhao, X., Wang, D., et al. (2020). Infection of bat and human intestinal organoids by SARS-CoV-2. Nat. Med. 26, 1077–1083. doi: 10.1038/s41591-020-0912-6

Review of Mesenteric Ischemia in COVID-19 Patients

Authors: Amit GuptaOshin SharmaKandhala SrikanthRahul MishraAmoli Tandon & Deepak Rajput  Indian Journal of Surgery (2022) Published: 

Abstract

The new coronavirus (COVID-19) infection, first detected in Wuhan, China in 2019 has become a pandemic that has spread to nearly every country in the world. Through October 11, 2021, more than 23 billion confirmed cases and 4.8 million fatalities were reported globally. The bulk of individuals afflicted in India during the first wave were elderly persons. The second wave, however, resulted in more severe diseases and mortality in even younger age groups due to mutations in the wild virus. Symptoms may range from being asymptomatic to fatal acute respiratory distress syndrome (ARDS). In addition to respiratory symptoms, patients may present with gastrointestinal symptoms such as stomach pain, vomiting, loose stools, or mesenteric vein thrombosis. The frequency of patients presenting with thromboembolic symptoms has recently increased. According to certain studies, the prevalence of venous thromboembolism among hospitalized patients ranges from 9 to 25%. It was also shown that the incidence is significantly greater among critically sick patients, with a prevalence of 21–31%. Although the exact origin of thromboembolism is unknown, it is considered to be produced by several altered pathways that manifest as pulmonary embolism, myocardial infarction, stroke, limb gangrene, and acute mesenteric ischemia. Acute mesenteric ischemia (AMI) is becoming an increasingly prevalent cause of acute surgical abdomen in both intensive care unit (ICU) and emergency room (ER) patients. Mesenteric ischemia should be evaluated in situations with unexplained stomach discomfort. In suspected situations, appropriate imaging techniques and early intervention, either non-surgical or surgical, are necessary to avert mortality. The purpose of this article is to look at the data on acute mesenteric ischemia in people infected with COVID-19.

Introduction

Aside from the respiratory system, the gastrointestinal system is the most common site of SARS-COV-2 infection. This might be because enterocyte and vascular endothelial membranes have large amounts of angiotensin-converting enzyme receptor 2, a membrane integral protein. As a result, the COVID virus induces direct enterocyte invasion as well as indirect endothelial injury-induced thrombosis/intestinal ischemia in the bowel [1]. ICU patients are more prone than non-ICU patients to suffer acute mesenteric ischemia. This might be because, in addition to the direct viral activity on vascular endothelium, ICU patients have extra persistent pro-inflammatory effects. Cases have been observed even among individuals who have recovered from infection [2]. A rising number of cases of acute mesenteric ischemia in COVID-19 patients have been reported in the literature since the outbreak of this pandemic (list of reported cases are summarized in the Table 1). AMI risk was shown to be increased with age, male sex, and comorbidities such as hypertension, obesity, and diabetes mellitus. Because of delayed clinical manifestation, AMI-related mortality is quite significant, with 60–80% [3].Table 1 Summary of the cases reported on mesenteric ischemia in COVID-19 patientsFull size table

Case summary

A 55 years old man with no known comorbidity presented to the emergency department of our institute with severe pain abdomen and multiple episodes of vomiting. He reported the recent recovery from the non-complicated COVID-related illness. He did not report any intake of anticoagulants. On clinical examination, abdomen was unremarkable. X-ray chest, x-ray erect abdomen, and ultrasound abdomen were unremarkable. Mesenteric ischemia was suspected and the patient was subjected to CT angiography abdomen, which revealed thrombus at the origin of the superior mesenteric artery and impending gangrene of the small bowel (Fig. 1). Emergency laparotomy was done and intraoperatively found the gangrenous bowel involving the distal jejunum and almost the entire ileum sparing the terminal ileum (Fig. 2). Resection of the gangrenous small bowel and end jejunostomy was done. Later, he was given ICU care, but unfortunately, the patient succumbed to multi-organ dysfunction syndrome.

figure 1
Fig. 1
figure 2
Fig. 2

Pathophysiology

Although the specific etiology of hypercoagulable state and subsequent mesenteric ischemia in COVID-19 patients is unknown, these thromboembolic events can be related to alterations in all three Virchow triad characteristics (vascular endothelial injury, hypercoagulability, and stasis). A variety of variables complicate the etiology of thrombus development, one of which is vascular endothelial injury. Capillary permeability, hemostasis, and fibrinolysis are all maintained by the vascular endothelium (Fig. 3). Direct invasion causes endothelial cells to be damaged and lysed, resulting in an imbalance between pro and anticoagulant states [4]. Furthermore, vascular endothelial cells displayed morphological changes such as cellular expansion, retraction, and intercellular connection breakage [5]. The elevated levels of pro-inflammatory markers, von Willebrand factor, tissue factor, fibrinogen, and circulating microvesicles in the COVID-19 patients explain their hypercoagulability [6]. Antiphospholipid antibodies are elevated in some situations [7]. Patients who are critically ill, on limited oxygen support, and mechanical breathing are less mobilized, which increases the risk of deep venous thrombosis [3].

figure 3
Fig. 3

These mesenteric vascular thromboses cause acute hypoxia in the intestinal wall, which stimulates the renin-angiotensin system, causing mesenteric vasospasm and an elevated risk of hypoxic injury. SARS-COV binds to ACE 2 receptors in intestinal cells, causing cell lysis [8]. As a result, both hypoxia and direct invasion can trigger intestinal cell death. The loss of this epithelial barrier function in the gut promotes increased contact with enteric bacteria/endotoxins and viral particle penetration into the circulation [5]. The hypoxia continues, resulting in transmural infarction, perforation, and peritonitis. In one example of mesenteric ischemia induced by invasive mucormycosis, the presence of fungal components in the mesenteric microcirculation was documented [2]. See the flow chart summarizing the pathophysiology of mesenteric ischemia in covid-19 infection.

Clinical Presentation

Patients with mesenteric ischemia may exhibit a range of symptoms, from nonspecific complaints to peritonitis-like symptoms. Most of the patients developed symptoms a few days after being discharged successfully with proper symptomatic inpatient care. Although the respiratory symptoms predominate mesenteric ischemia presents with nonspecific abdominal symptoms such as loose stools, abdominal pain, nausea, vomiting, abdominal distension, and bleeding per rectum may occur in addition to the usual clinical presentation with respiratory features [6]. When opposed to arterial thrombosis, venous thrombosis has a delayed onset of symptoms. At first, sudden onset pain in the abdomen may be the sole symptom, and it may develop after 5–14 days. Abdominal clinical examination is nonyielding in the majority of cases. Abdominal signs would not develop unless the bowel gangrene or bowel perforation with peritonitis occurs [9].

Investigations

Blood investigations

Despite extensive study on the subject of acute mesenteric ischemia, the associated biomarkers were shown to be neither sensitive nor selective [10]. Elevated lactic acid levels and fibrin degradation products like D-dimer have low specificity and remain elevated in severe COVID-19 without AMI. However, biomarkers associated with hypercoagulable conditions aid in the initiation of preventive treatment and, to a lesser extent, in the management of COVID-related thrombotic events. Increased biomarkers of inflammation and infection include leukopenia (due to corticosteroid usage) and other signs such as C-reactive protein, procalcitonin, and IL-6. D-dimer, ferritin, prothrombin time, and lactate dehydrogenase are additional significant markers. The severity of increased lactate dehydrogenase and ferritin levels is associated with high mortality[8].

Radiological imaging

In the emergency room, an X-ray of the abdomen and an ultrasound are helpful for early examinations. X-ray of the erect abdomen helps in initial assessment in cases presented with features of obstruction or perforation. Ultrasound in the early phase may show SMA occlusion and bowel spasm or ultrasound findings in the early stages of acute mesenteric ischemia may appear normal [11]. In the intermediate phase, USG is not useful because of the presence of a large amount of gas-filled intestinal loops. In the late phase, USG may reveal fluid-filled lumen, bowel wall thinning, evidence of extra-luminal fluid, decreased or absent peristalsis. Therefore, USG may be helpful in the diagnosis of advanced bowel obstruction, gangrene, and perforation with peritoneal collection [12]. Ultrasonography revealed some other important features with distended and sludge-filled gall bladder with bile stasis. Portal venous gas also can be detected on ultrasonography which can be better characterized with the help of computed tomography [13].

Computed tomography

The gold standard investigation is CT angiography. CT observations commonly encountered in acute mesenteric ischemia secondary to COVID-19 includes thrombus in the aorta/SMA/portal circulation, augmentation of the bowel wall, thickness of the bowel wall with distention(> 3 cm), edema, and stranding of the mesentery, pneumatosis intestinalis or portal venous gas suggesting bowel wall ischemia, and non-enhancing thick bowel wall seen in bowel infarction, bowel perforation secondary to bowel infarction may present discontinuity of bowel wall with localized air collection. One should remember that pneumatosis intestinalis may also occur due to mechanical ventilation. Pneumoperitoneum occurs when there is severe intestinal necrosis and perforation. There were additional reports of nonspecific features such as a dilated gut with a fluid-filled lumen, distended gallbladder with bile stasis, features of solid organ ischemia, and pancreatitis [14]. MRI, despite its accessibility, has drawbacks such as a longer acquisition time and lower resolution than CT angiography [12].

Management

A summary of cases of acute mesenteric ischemia has been tabulated (Table 1). Management of acute mesenteric ischemia in COVID-19 includes the following:

  • Supportive measures: Crystalloid rehydration and empirical antibacterial treatment should begin before angiography or any surgical resection. Comorbidity management, hemodynamic support in unstable patients, and electrolyte balance correction are all critical components of patient care [10].
  • Anticoagulation: There is insufficient data in 19 patients to warrant thromboprophylaxis. According to the Tang et al. study, low-dose heparin prophylaxis decreased thrombotic events and mortality in those with D-dimer levels over 3 mg/ml. Despite the increased risk of bleeding, mesenteric ischemia should be treated with intraoperative and postoperative anticoagulation [15].
  • Revascularisation: Revascularization with catheter-directed thrombolysis and thrombectomy by percutaneous/surgical intervention can be explored in instances where there is no indication of significant intestinal ischemia. Catheter-directed thrombolysis with unfractionated heparin and recombinant tissue plasminogen activators can accomplish this. Because of the increased risk of re-thrombosis, vascular clearance is not indicated in instances of superior mesenteric vein thrombus [15].
  • Resection of the gangrenous bowel: Depending on clinical suspicion, a CT angiography examination of mesenteric vasculature and bowel health can be performed, and an emergency exploration call should be placed. Intraoperatively, if the patient is normotensive, has no sepsis or peritonitis, and the remaining bowel viability is unquestionable, the gangrenous bowel is to be removed, and the remaining bowel can be considered for re-anastomosis. In unfavorable circumstances, a stoma should be created following gangrenous bowel resection [11]. The margin dissection in venous thrombosis should be broader than in arterial thrombosis. To assure the bowel’s survivability, abdominal closure should be temporary, and a relook laparotomy should be done 48 h later. Histopathological examination of the resected intestine may indicate patchy or widespread necrotic changes from mucosa to transmural thickness. In the submucosal vasculature, fibrin-containing microthrombi with perivascular neutrophilic infiltration is observed.
  • Management of short bowel syndrome: The therapy varies depending on the length of colon left after excision of infarcted bowel caused by mesenteric ischemia.
  • Medical- In severe diarrhea, fluid and electrolyte loss must be replaced. TPN for feeding and histamine-2 receptor antagonists or PPIs for stomach acid secretion reduction. Loperamide and diphenoxylate are anti-motility medicines that delay small intestine transit whereas Octreotide reduces the volume of gastrointestinal secretions.
  • Non-transplant surgical therapy- Done to improve the absorption capacity of the remaining intestine by restoring intestinal continuity. Increased nutrient and fluid absorption is the goal. Segmental reversal of the small bowel, fabrication of small intestinal valves, and electrical pacing of the small bowel are all procedures used to delay intestinal transit. Longitudinal intestinal lengthening and tailoring technique (LILT) and serial transverse arthroplasty process are two intestinal lengthening procedures (STEP).
  • Intestinal transplantation- Life-threatening problems such as liver failure, thrombosis of major central veins, frequent episodes of severe dehydration, and catheter-related sepsis are reasons for intestinal transplantation [16].

Prognosis

Acute mesenteric ischemia has a poor prognosis, and life is reliant on prompt diagnosis and treatment. If detected within 24 h, the likelihood of survival is 50%, but it declines to 30% beyond that [17].In operated cases, COVID infection acts as an independent risk factor and is responsible for higher mortality [18].

Conclusion

SARS-COV-2 infection even though initially thought to be respiratory infection; later cases detected presenting with multisystem involvement. The presentation may vary from asymptomatic or mildly symptomatic to severe respiratory distress syndrome or thromboembolic phenomenon requiring ICU care. The exact mechanism of thromboembolism is not established. However, the increasing number of acute mesenteric ischemia is quite alarming. The treating physician should be overcautious in patients presenting with abdominal symptoms either currently affected or recovered from COVID-related illness. In high-risk patients, early start of prophylactic anticoagulation may be beneficial. Earlier intervention is known acute mesenteric ischemia cases with operative or minimally invasive procedures may give higher survival benefits. It mandates more research to determine the causes of thromboembolism, as well as preventive and therapeutic anticoagulation in these individuals.

References

  1. Jin B, Singh R, Ha SE, Zogg H, Park PJ, Ro S (2021) Pathophysiological mechanisms underlying gastrointestinal symptoms in patients with COVID-19. World J Gastroenterol. Baishideng Publishing Group Co 27:2341–52CAS Article Google Scholar 
  2. Jain M, Tyagi R, Tyagi R, Jain G (2021) Post-COVID-19 gastrointestinal invasive mucormycosis. Indian J Surg 22:1–3
  3. Kerawala AA, Das B, Solangi A (2021) Mesenteric ischemia in COVID-19 patients: a review of current literature. World J Clin Cases 9(18):4700–4708Article Google Scholar 
  4. Kichloo A, Dettloff K, Aljadah M, Albosta M, Jamal S, Singh J et al (2020) COVID-19 and hypercoagulability: a review. Clin Appl Thromb 26
  5. Parry AH, Wani AH, Yaseen M (2020) Acute mesenteric ischemia in severe Coronavirus-19 (COVID-19): possible mechanisms and diagnostic pathway. Acad Radiol 27(8):1190Article Google Scholar 
  6. Cheung S, Quiwa JC, Pillai A, Onwu C, Tharayil ZJ, Gupta R (2020) Superior mesenteric artery thrombosis and acute intestinal ischemia as a consequence of COVID-19 infection. Am J Case Rep 21:1–3Google Scholar 
  7. Zhang Y, Xiao M, Zhang S, Xia P, Cao W, Jiang W et al (2020) Coagulopathy and antiphospholipid antibodies in patients with Covid-19. N Engl J Med. 382(17):e38Article Google Scholar 
  8. Al Mahruqi G, Stephen E, Abdelhedy I, Al WK (2021) Our early experience with mesenteric ischemia in COVID-19 positive patients. Ann Vasc Surg 73:129–132Article Google Scholar 
  9. Karna ST, Panda R, Maurya AP, Kumari S (2020) Superior mesenteric artery thrombosis in COVID-19 Pneumonia: an underestimated diagnosis—first case report in Asia. Indian J Surg 82(6):1235–1237Article Google Scholar 
  10. Singh B, Kaur P (2021) COVID-19 and acute mesenteric ischemia: a review of literature. Hematol Transfus Cell Ther 43(1):112–116Article Google Scholar 
  11. Janež J, Klen J (2021) Multidisciplinary diagnostic and therapeutic approach to acute mesenteric ischaemia: a case report with literature review. SAGE Open Med Case Rep 9:2050313X2110048Article Google Scholar 
  12. Mc W (2010) Acute mesenteric ischemia: diagnostic approach and surgical treatment. Semin Vasc Surg 23(1):9–20Article Google Scholar 
  13. Bhayana R, Som A, Li MD, Carey DE, Anderson MA, Blake MA et al (2020) Abdominal imaging findings in COVID-19: Preliminary observations. Radiology 297(1):E207–E215
  14. Keshavarz P, Rafiee F, Kavandi H, Goudarzi S, Heidari F, Gholamrezanezhad A (2021) Ischemic gastrointestinal complications of COVID-19: a systematic review on imaging presentation. Clin Imaging 73:86–95Article Google Scholar 
  15. Bergqvist D, Svensson PJ (2010) Treatment of mesenteric vein thrombosis. Semin Vasc Surg 23(1):65–68Article Google Scholar 
  16. Seetharam P, Rodrigues G (2011) Short bowel syndrome: a review of management options. Saudi J Gastroenterol 17(4):229–235Article Google Scholar 
  17. Krothapalli N, Jacob J (2021) A rare case of acute mesenteric ischemia in the setting of COVID-19 infection. Cureus 13(3):0–4Google Scholar 
  18. Haffner MR, Le HV, Saiz AM, Han G, Fine J, Wolinsky P et al (2021) Postoperative In-hospital morbidity and mortality of patients with COVID-19 infection compared with patients without COVID-19 infection. JAMA Netw Open 4(4):10–13Article Google Scholar 
  19. Ucpinar BA, Sahin C (2020) Superior mesenteric artery thrombosis in a patient with COVID-19: a unique presentation. J Coll Physicians Surg Pak 30(10):S112–S114Google Scholar 
  20. Khesrani LS, Chana k, Sadar FZ, Dahdouh A, Ladjadj Y, Bouguermouh D (2020) Intestinal ischemia secondary to Covid-19. J Pediatr Surg Case Rep 61:101604Article Google Scholar 
  21. Norsa L, Valle C, Morotti D, Bonaffini PA, Indriolo A, Sonzogni A (2020) Intestinal ischemia in the COVID-19 era. Dig Liver Dis 52(10):1090–1091CAS Article Google Scholar 
  22. Rodriguez-Nakamura RM, Gonzalez-Calatayud M, Martinez Martinez AR (2020) Acute mesenteric thrombosis in two patients with COVID-19. Two cases report and literature review. Int J Surg Case Rep 76:409–14Article Google Scholar 
  23. VartanogluAktokmakyan T, Tokocin M, Meric S, Celebi F (2021) Is mesenteric ischemia in COVID-19 patients a surprise? Surg Innov 28(2):236–238Article Google Scholar 
  24. Levolger S, Bokkers RPH, Wille J, Kropman RHJ, de Vries JPPM (2020) Arterial thrombotic complications in COVID-19 patients. J Vasc Surg Cases Innov Tech 6(3):454–459Article Google Scholar 
  25. Thuluva SK, Zhu H, Tan MML, Gupta S, Yeong KY, Wah STC et al (2020) A 29-year-old male construction worker from india who presented with left-sided abdominal pain due to isolated superior mesenteric vein thrombosis associated with SARS-CoV-2 infection. Am J Case Rep 21:1–5Article Google Scholar 
  26. Lari E, Lari A, AlQinai S, Abdulrasoul M, AlSafran S, Ameer A et al (2020) Severe ischemic complications in Covid-19—a case series. Int J Surg Case Rep 75(June):131–135Article Google Scholar 
  27. Singh B, Mechineni A, Kaur P, Ajdir N, Maroules M, Shamoon F et al (2020) Acute intestinal ischemia in a patient with COVID-19 infection. Korean J Gastroenterol 76(3):164–166Article Google Scholar 
  28. De Roquetaillade C, Chousterman BG, Tomasoni D, Zeitouni M, Houdart E (2020) Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID- 19. The COVID-19 resource centre is hosted on Elsevier Connect , the company ’ s public news and information. (January)
  29. Sehhat S, Talebzadeh H, Hakamifard A, Melali H, Shabib S, Rahmati A et al (2020) Acute mesenteric ischemia in a patient with COVID-19: a case report. Arch Iran Med 23(9):639–643Article Google Scholar 
  30. Beccara LA, Pacioni C, Ponton S, Francavilla S, Cuzzoli A (2020) Arterial mesenteric thrombosis as a complication of SARS-CoV-2 infection. Eur J Case Rep Intern Med 7(5).
  31. Ignat M, Philouze G, Aussenac-belle L (2020) Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID- 19 . The COVID-19 resource centre is hosted on Elsevier Connect , the company ’ s public news and information. (Jan)
  32. Farina D, Rondi P, Botturi E, Renzulli M, Borghesi A, Guelfi D et al (2021) Gastrointestinal: bowel ischemia in a suspected coronavirus disease (COVID-19) patient. J Gastroenterol Hepatol 36(1):41CAS Article Google Scholar 
  33. Azouz E, Yang S, Monnier-Cholley L, Arrivé L (2020) Systemic arterial thrombosis and acute mesenteric ischemia in a patient with COVID-19. Intensive Care Med 46(7):1464–1465CAS Article Google Scholar 
  34. Vulliamy P, Jacob S, Davenport RA (2020) Acute aorto-iliac and mesenteric arterial thromboses as presenting features of COVID-19. Br J Haematol 189(6):1053–1054CAS Article Google Scholar 
  35. Bianco F, Ranieri AJ, Paterniti G, Pata F, Gallo G (2020) Acute intestinal ischemia in a patient with COVID-19. Tech Coloproctol 24(11):1217–1218CAS Article Google Scholar 
  36. Filho A do C, Cunha B da S (2020) Case report – inferior mesenteric vein thrombosis and COVID-19. 2020060282
  37. Mitchell JM, Rakheja D, Gopal P (2021) SARS-CoV-2-related hypercoagulable state leading to ischemic enteritis secondary to superior mesenteric artery thrombosis. Clin Gastroenterol Hepatol 19(11):e111CAS Article Google Scholar 
  38. English W, Banerjee S (2020) Coagulopathy and mesenteric ischaemia in severe SARS-CoV-2 infection. ANZ J Surg 90(9):1826Article Google Scholar 
  39. de Barry O, Mekki A, Diffre C, Seror M, El Hajjam M, Carlier RY (2020) Arterial and venous abdominal thrombosis in a 79-year-old woman with COVID-19 pneumonia. Radiol Case Rep 15(7):1054–1057Article Google Scholar 
  40. Kraft M, Pellino G, Jofra M, Sorribas M, Solís-Peña A, Biondo S, Espín-Basany E (2021) Incidence, features, outcome and impact on health system of de-novo abdominal surgical diseases in patients admitted with COVID-19. Surg J R Coll Surg Edinb Irel 19:e53–e58Google Scholar 
  41. Besutti G, Bonacini R, Iotti V, Marini G, Riva N, Dolci G et al (2020) Abdominal visceral infarction in 3 patients with COVID-19. Emerg Infect Dis 26(8):1926–1928CAS Article Google Scholar 
  42. Kielty J, Duggan WP, O’Dwyer M (2020) Extensive pneumatosis intestinalis and portal venous gas mimicking mesenteric ischaemia in a patient with SARS-CoV-2. Ann R Coll Surg Engl 102(6):E145–E147CAS Article Google Scholar 
  43. Pang JHQ, Tang JH, Eugene-Fan B (2021) A peculiar case of small bowel stricture in a coronavirus disease 2019 patient with congenital adhesion band and superior mesenteric vein thrombosis. Ann Vasc Surg 70:286–289Article Google Scholar 
  44. Osilli D, Pavlovica J, Mane R, Ibrahim M, Bouhelal A, Jacob S (2020) Case reports: mild COVID-19 infection and acute arterial thrombosis. J Surg Case Rep (9):1–3

Prevalence of organ impairment in Long COVID patients 6 and 12 months after initial symptoms

Authors:  Pooja Toshniwal PahariaMar 24 2022Reviewed by Danielle Ellis, B.Sc.

In a recent study posted to the medRxiv* preprint server, researchers assessed the prevalence of organ impairment in long coronavirus disease 2019 (COVID-19) six months and a year post-COVID-19 at London and Oxford.

Multi-organ impairment associated with long COVID-19 is a significant health burden. Standardized multi-organ evaluation is deficient, especially in non-hospitalized patients. Although the symptoms of long COVID-19, also known as post-acute sequelae of COVID-19 (PASC), are well-established, the natural history is poorly classified by symptoms, organ impairment, and function.

About the study

In the present prospective study, researchers assessed organ impairment in long COVID-19 patients six months and a year after the onset of early symptoms and correlated them to their clinical presentation.

The participants were recruited based on specialist referral or the response to advertisements in sites such as Mayo Clinic Healthcare, Perspectum, and Oxford from April 2020 to August 2021, based on their COVID-19 history.

The study was conducted on COVID-19 patients who recovered from the acute phase of the infection. Their health status, symptoms, and organ impairment were assessed. The symptoms assessed comprised cardiopulmonary, severe dyspnoea, and cognitive dysfunction. Biochemical and physiological parameters were analyzed at baseline and post-organ impairment. The radiological investigation comprised multi-organ magnetic resonance imaging (MRI) performed in the long COVID-19 patients and healthy controls.

Over a year, the team prospectively investigated the symptoms, organ impairment, and function, especially dyspnea, cognitive dysfunction, and health-related quality of life (HRQoL). They also evaluated the association between organ impairment and clinical symptoms.

Patients with symptoms of active pulmonary infections (body temperature >37.8°C or ≥3 coughing episodes in a day) and hospital discharges in the previous week or >4 months were excluded from the study. Asymptomatic patients and those with MRI contraindications such as defibrillators, pacemakers, devices with metal implants, and claustrophobia were removed.

Participants with impaired organs, as diagnosed by blood investigations, incidental findings, or MRI, were included in the follow-up assessments. Every visit comprised blood investigations, MRI scanning, and online questionnaire surveys, which were to be filled out beforehand. In addition, a sensitivity analysis was performed that excluded patients at risk of metabolic disorders (including body mass index (BMI) ≥30 kg/m2, diabetes, and hypertension)

Results

Related Stories

Out of 536 participants, the majority were middle-aged (mean age 45 years), female (73%), White (89%), and healthcare workers (32%). About 13% of the COVID-19 patients hospitalized during the acute phase of the infection completed the baseline evaluation. A total of 331 patients (62%) had incidental findings, organ impairment, or reduction in the symptoms from the baseline at both the time points.

Cognitive dysfunction (50% and 38%), poor HRQoL (EuroQOL <0.7 in 55% and 45%), and severe dyspnea (36% and 30%) were observed at six months and one year, respectively. On follow-up, the symptoms were reduced, especially cardiopulmonary and systemic symptoms, whereas fatigue, dyspnea, and cognitive dysfunction were consistently present. The greatest impact on quality of life was related to pain and difficulties performing routine activities. Almost every patient took time off work due to COVID-19. The symptoms were largely associated with obese women, young age, and impairment of a single organ.

At baseline, fibrous inflammation was observed in the pancreas (9%), heart (9%), liver (11%), and kidney (15%). Additionally, increased volumes of the spleen (8%), kidney (9%), and liver (7%) were observed. Moreover, reduced lung capacity (2%), excess adipose deposits in pancreatic tissues (15%) and liver (25%) were observed. High liver fibro-inflammation was associated with cognitive dysfunction at follow-up in 19% and 12% of patients with and without cognitive dysfunction, respectively. Low liver fat was more likely in those without severe dyspnoea at both time points. Increased liver volumes at follow-up were associated with lower HRQoL scores.

The prevalence of multi and single-organ impairment was 23% and 59% at baseline, respectively, and persisted in 27% and 59% of the participants on follow-up assessments. Most of the organ impairments were mild. However, they did not improve substantially between visits. Notably, participants without organ impairment had the lowest symptom burden.

Most biochemical parameters were normal except creatinine kinase (8% and 13%), lactate dehydrogenase (16% and 22%), mean cell hemoglobin concentration (21% and 15%), and cholesterol (46% and 48%), at six months and a year post-COVID-19, respectively. These biochemical markers increased from the baseline on follow-up assessments.

Conclusion

To summarize, organ impairment was detected in 59% of the patients at six months post-COVID-19 and persisted in 59% at one-year follow-up. This has significant implications on the quality of life, symptoms, and long-term health of the patients. These observations highlight the requirement for enhanced preventive measures and integrated patient care to decrease the long COVID-19 burden.

Journal reference:

Pancreatic damage in COVID‐19: Why? How?

Authors: Ferhat Bacaksız, 1 Berat Ebik, 1 Nazım Ekin, 1 and Jihat Kılıc 2

Int J Clin Pract. 2021 Aug 6 : e14692.doi: 10.1111/ijcp.14692 [Epub ahead of print] PMCID:  PMC8420122PMID: 34331821

Abstract

Object

We aimed to evaluate the elevation of amylase and lipase enzymes in coronavirus disease 2019 (COVID‐19) patients and their relationship with the severity of COVID‐19.

Method

In this study, 1378 patients with COVID‐19 infection were included. Relation of elevated amylase and lipase levels and comorbidities with the severity of COVID‐19 was analysed. The effects of haemodynamic parameters and organ failure on pancreatic enzymes and their relations with prognosis were statistically analysed.

Results

The 1378 patients comprised of 700 (51.8%) men and 678 (%49.2) women. Of all patients, 687 (49.9%) had mild and 691 (50.1%) patients had severe COVID‐19 infection. Amylase elevation at different levels occurred in 316 (%23) out of 1378 patients. In these patients, the amylase levels increased one to three times in 261 and three times in 55 patients. Pancreatitis was detected in only six (%1.89) of these patients according to the Atlanta criteria. According to univariate and multivariate analyses, elevated amylase levels were significantly associated with the severity of COVID‐19 (odds ratio [OR]: 4.37; P < .001). Moreover, diabetes mellitus (DM; OR: 1.82; P = .001), kidney failure (OR: 5.18; P < .001), liver damage (OR: 6.63; P < .001), hypotension (OR: 6.86; P < .001) and sepsis (OR: 6.20; P = .008) were found to be associated with mortality from COVID‐19.

Conclusion

Elevated pancreatic enzyme levels in COVID‐19 infections are related to the severity of COVID‐19 infection and haemodynamic instability. In a similar way to other organs, the pancreas can be affected by severe COVID‐19 infection.

What’s known

  • It has been suggested that COVID‐19 can cause pancreatic damage.
  • There are a limited number of studies related to the possibility of an increase in the level of pancreatic enzymes in COVID‐19 patients.

What’s new

  • COVID‐19 does not directly cause pancreatic damage.
  • Pancreatic enzyme elevation in patients with COVID‐19 develops in the advanced stages of the disease caused by multiple organ dysfunction and shock.

1. INTRODUCTION

Coronavirus disease 2019 (COVID‐19) infection was initially considered to attack only the upper respiratory tract, but was later found to potentially affect almost all systems. This is caused by the angiotensin‐converting enzyme 2 (ACE2) receptors that coronavirus binds to in order to enter the cells. These receptors are also commonly available in the gastrointestinal system such as in hepatic, pancreatic and colonic cells.12

Recent studies have shown that COVID‐19 infection can cause damage to the pancreas caused by the high expression of ACE2 receptors from the pancreatic tissue.3 Additionally, it has also been reported that hyperglycaemia can occur because of pancreatic islet cell damage in patients with COVID‐19 and that severe patients with COVID‐19 should be followed up closely in terms of pancreatic damage.45

In this study, we evaluated the amylase and lipase elevations in patients with COVID‐19 in order to investigate the relationship between pancreatic enzyme elevations and the severity of COVID‐19 infection and to identify the underlying conditions.Go to:

2. PATIENTS AND METHODS

The study included 1378 patients with COVID‐19 infection who presented to our hospital between March and December 2020. Clinical characteristics including temperature, blood pressure, laboratory parameters, treatments and comorbidities were monitored throughout hospitalisation. In addition to other laboratory parameters, amylase and lipase levels were also studied in order to determine the ratio of patients with elevated pancreatic enzymes. Values above 105 U/L for amylase and 65 IU/L for lipase were considered high.6 Patients with pancreatitis were identified according to the Atlanta criteria.7

Additionally, pancreatic enzyme elevation in COVID‐19 infection was investigated with regard to the severity of disease. Patients were divided into two groups based on the severity of their COVID‐19 symptoms: mild (n = 687) and severe (n = 691). Patients with fever, headache, loss of taste and smell and generalised myalgia without tachypnoea (oxygen saturation >92%) were considered to have a mild infection, whereas patients on invasive or non‐invasive respiratory support or with deteriorated haemodynamic conditions were considered to have severe COVID‐19 infection.8

The causes of pancreatic enzyme elevation were compared between patients with mild and severe COVID‐19 infection and between surviving and non‐surviving patients. Relation between elevated pancreatic enzymes and metabolic parameters, haemodynamic findings, single and multiple organ failures was also examined.910

Hypotension was evaluated based on mean arterial pressure (MAP). A MAP value of 60‐110 mmHg was accepted as normal, <60 mmHg as hypotensive and >110 mmHg as hypertensive.11

Liver damage was determined according to the 2019 European Association for the Study of the Liver (EASL) guidelines, based on the upper limits of normal (ULN) serum alanine aminotransferase activity (ALT) and serum alkaline phosphatase activity (ALP), as follows: ALT ≥5 × ULN or ALP ≥2 ULN [in the absence of known bone pathology] or ALT ≥3 ULN with simultaneous increase of total bilirubin concentration ≥2 ULN.12 Kidney injury was determined according to the RIFLE (Risk, Injury, Failure, Loss of kidney function and End‐stage kidney disease) criteria.13

The study was conducted in accordance with the Helsinki Declaration and the study protocol was approved by the local ethics committee (No: 611, Date: 16 October 2020).

2.1. Statistical analysis

Data were analysed using SPSS 26.0 for Windows (Armonk, NY: IBM Corp.). Normal distribution of data was assessed using Kolmogorov‐Smirnov, Shapiro‐Wilk test, coefficient of variation, skewness and kurtosis. Continuous variables were expressed as mean and standard deviation (SD), and categorical variables were expressed as percentages (%). Student t test and Mann‐Whitney U‐test were used in paired groups to compare pancreatic enzymes and disorders of other organs between patients with severe and mild COVID‐19 infection. ANOVA test was used for parameters homogeneously distributed in triple groups. Bonferroni correction was used to determine the significant results in groups. Welch’s ANOVA and Kruskal‐Wallis tests were performed for non‐homogeneous parameters. Pearson and Spearman correlation coefficients were used to analyse the relationship between pancreatic enzyme elevation and other parameters. Univariate and multivariate analyses were performed to determine the factors associated with pancreatic enzyme elevation. All tests were bilateral and a P‐value of <.05 was considered significant.Go to:

3. RESULTS

The 1378 patients comprised of 700 (51.8%) men and 678 (%49.2) women. The prevalence of kidney failure, DM, ischaemic hepatitis and sepsis was significantly higher in patients with severe COVID‐19 compared with patients with mild disease. Moreover, amylase and lipase levels were also higher in patients with severe COVID‐19 (Table 1).

TABLE 1

Demographic data and biochemical parameters of patients with mild and severe COVID‐19

Mild COVID‐19±SDSevere COVID‐19±SDP
N687 (49.9%)691 (50.1%)
Age60.2 (29‐84)65 (51‐86)<.001
Gender F/M356/331322/369.053
Amylase (U/L)82.6 ± 50.4264.7 ± 292.0<.001
Lipase (IU/L)59.7 ± 51.279.0 ± 24.2.045
ALT (IU/L)70.4 ± 60.282.7 ± 56.4<.001
AST (IU/L)61.6 ± 40.7180 ± 135.5<.001
ALP (IU/L)84.1 ± 35.4133.2 ± 107.2.295
GGT (IU/L)54.2 ± 51.579.4 ± 58.9.099
T.Bil (mg/dL)0.67 ± 0.331.95 ± 1.53<.001
LDH (IU/L)411.9 ± 2101137 ± 248.7<.001
Urea (mg/dL)45.7 ± 26.9187.0 ± 92.8<.001
Creatinine (mg/dL)0.89 ± 0.493.74 ± 1.96<.001
Glucose (mg/dL)138 ± 85.0290 ± 135<.001
WBC (cell/µL)9840 ± 448518 422 ± 6039<.001
Lymphocyte (cell/µL)1993 ± 6651655 ± 946<.001
CRP (mg/L)107.8 ± 67.2217.9 ± 69.1<.001
Procalcitonin (ng/mL)1.04 ± 4.658.03 ± 19.7<.001

Open in a separate window

Abbreviations: ALP, alkaline phosphatase, GGT, gamma glutamyl transpeptidase WBC, white blood cell, CRP, C reactive protein; ALT, alanine transaminase; AST, aspartate transaminase; LDH, lactate dehydrogenase; SD, standard deviation.

Amylase elevation at different levels occurred in 316 (%23) out of 1378 patients. In these patients, the amylase levels increased one to three times in 261 and three times in 55 patients. Pancreatitis was detected in only six (%1.89) of these patients according to the Atlanta criteria. Amylase and lipase elevation was found to be related to the severity of COVID‐19 infection in the remaining patients. The development of DM, kidney failure, hypotension and ischaemic hepatitis was found to be related to mortality from COVID‐19 infection. However, there was no relationship between lymphopenia and elevated amylase levels (Table 2). On the other hand, patients older than 65 years were more likely to have (1.89 times) elevated increased enzyme levels.

TABLE 2

Relationship between amylase level in COVID‐19 patients and gender, comorbid status, severity and consequence of COVID‐19, haemodynamic status, other organ failures and laboratory parameters

FeatureAmylase (normal)Amylase (1‐3 times)Amylase (more than 3 times)P‐values
N/%1062 (77.0%)261 (19.0%)55 (4.0%)
Gender
Female (678%‐49.2%)565 (83.3%)100 (14.8%)13 (1.9%)<.001
Male (700%‐50.8%)497 (71.0%)161 (23.0%)42 (6.0%)
COVID‐19 severity
Mild COVID‐19 (687%‐49.9%)612 (89.1%)71 (10.3%)4 (0.6%)<.001
Severe COVID‐19 (691%‐50.1%)450 (65.1%)190 (27.5%)51 (7.4%)
COVID‐19
Healing (909%‐66.0%)793 (87.2%)109 (12.0%)7 (0.8%)<.001
Death (469%‐34.0%)269 (57.4%)152 (32.4%)48 (10.2%)
Diabetes
Absent (866%‐62.8%)703 (81.2%)143 (16.5%)20 (2.3%)<.001
Available (512%‐32.6%)359 (70.1%)118 (23.0%)35 (6.9%)
Kidney failure
Absent (934%‐67.8%)808 (86.5%)114 (12.2%)12 (1.3%)<.001
AKI (316%‐22.9%)186 (58.8%)101 (32.0%)29 (9.2%)
CRF (128%‐9.3%)68 (53.1%)46 (36.0%)14 (10.9%)
Blood pressure
Normal (810%‐58.8%)727 (89.7%)76 (9.4%)7 (0.9%)<.001
Hypotension (466%‐33.8%)260 (55.8%)161 (34.5%)45 (9.7%)
Hypertension (102%‐7.4%)75 (73.6%)24 (23.5%)3 (2.9%)
ALT
Normal (562%‐40.8%)488 (86.8%)65 (11.6%)9 (1.6%)<.001
1‐3 times (488%‐35.4%)389 (79.7%)86 (17.6%)13 (2.7%)
3‐5 times (135%‐9.8%)89 (65.9%)37 (27.4%)9 (6.7%)
5‐10 times (65%‐4.7%)36 (55.4%)20 (30.8%)9 (13.8%)
>10 times (61%‐4.4%)32 (52.5%)26 (42.6%)3 (4.9%)
>1000 (IU/L) (67%‐4.9%)28 (41.8%)27 (40.3%)12 (17.9%)
AST
Normal (468%‐34.0%)428 (91.4%)36 (7.7%)4 (0.9%)<.001
1‐3 times (564%‐40.9%)454 (80.5%)98 (17.4%)12 (2.1%)
3‐5 times (121%‐8.8%)76 (62.8%)38 (31.4%)7 (5.8%)
5‐10 times (71%‐5.1%)35 (49.3%)27 (38.0%)9 (12.7%)
More than 10 times (45%‐3.3%)22 (48.9%)16 (35.6%)7 (15.5%)
>1000 (IU/L) (109%‐7.9%)47 (43.1%)46 (42.2%)16 (14.7%)
ALP
Normal (966%‐70.1%)737 (76.3%)191 (19.8%)38 (3.9%).092
1‐2 times (234%‐17.0%)176 (75.2%)45 (19.2%)13 (5.6%)
More than 2 times(178%‐12.9%)149 (83.7%)25 (14.0%)4 (2.3%)
GGT
Normal (909%‐66%)722 (79.4%)158 (7.4%)29 (3.2%).072
1‐2 times (254%‐18.4%)173 (68.1%)62 (24.4%)19 (7.5%)
More than 2 times (215%‐15.6%)167 (77.7%)41 (19.1%)7 (3.2%)
Total Bilirubin
Normal (1059%‐76.9%)860 (81.2%)171 (16.2%)28 (2.6%)<.001
1‐2 times (257%‐18.6%)172 (66.9%)68 (26.4%)17 (6.7%)
More than 2 times (62%‐4.5%)30 (48.4%)22 (35.5%)10 (16.1%)
LDH
Normal (<225 IU/L) (161%‐11.7%)157 (97.5%)4 (2.5%)0 (0.0%)<.001
Normal‐1000 (IU/L) (969%‐70.3%)788 (81.3%)158 (16.3%)23 (2.4%)
1000‐2250 (IU/L) (148%‐10.7%)79 (53.4%)55 (37.2%)14 (9.4%)
>2250 (IU/L)(100%‐7.3%)38 (38.0%)44 (44.0%)18 (18.0%)
Lymphocyte levels
Normal (724%‐52.5%)581 (80.3%)119 (16.4%)24 (3.3%).120
Mild lymphopenia (489%‐35.5%)360 (73.6%)111 (22.7%)18 (3.7%)
Severe lymphopenia (165%‐12.0%)121 (73.3%)31 (18.8%)13 (7.9%)

Open in a separate window

Abbreviations: AKI, Acute kidney injury; ALP, alkaline phosphatase, GGT, gamma glutamyl transpeptidase; ALT, alanine transaminase; AST, aspartate transaminase; CRF, Chronic renal failure; LDH, lactate dehydrogenase.

The prevalence of elevated amylase was 2.04 times higher in men than that in women. Hypotension (odds ratio [OR]: 6.63), sepsis (OR: 6.20), ischaemia‐related liver damage (OR: 6.63) and renal failure (OR: 5.18) were found to be significantly associated with pancreatic enzyme levels (Table 3).

TABLE 3

Analysis of factors affecting enzyme elevation in COVID‐19 patients with elevated amylase and lipase

FeatureUnivariateMultivariate
OR95% ClP valueOR95% ClP value
Age1.891.46‐2.44.0011.721.40‐2.11.001
Gender2.041.57‐2.64.0011.861.50‐2.31.001
COVID‐19 Severity4.373.28‐5.81<.0013.762.90‐4.88<.001
Death from COVID‐195.083.89‐6.64<.0014.233.33‐5.36<.001
Diabetes1.821.41‐2.35.0011.721.40‐2.11.001
Kidney failure5.183.95‐6.79<.0013.783.00‐4.75<.001
Liver damage6.634.56‐9.64<.0013.092.43‐3.94<.001
Hypotension6.864.50‐10.40<.0015.673.90‐8.22<.001
Sepsis6.203.83‐10.05.0082.882.24‐3.70.003
Pancreatitis21.22.54‐166.7.0058.024.54‐86.3.026

Open in a separate window

A very strong positive correlation was found between amylase and lipase levels in all patients (r: .828, P < .001), which implicates that the increased amylase in COVID‐19 patients is caused by the pancreas. A weak correlation was found between amylase level and age or gender. Likewise, a weak but statistically significant correlation was found between amylase level and DM. A strong correlation was detected between the amylase level and the severity of COVID‐19. Additionally, the presence of liver damage, renal failure, hypotension and multiple organ dysfunction syndrome (MODS) in these patients was moderately correlated with amylase level (Figure 1).FIGURE 1

Correlation between amylase level and risk factors in COVID‐19 patients with hyperamylasaemiaGo to:

4. DISCUSSION

We found that 23% of patients with COVID‐19 infection had pancreatic enzyme elevations, and we also detected a relationship between pancreatic enzyme elevation and the severity of COVID‐19 infection, haemodynamic instability and MODS.

Although 10.9% of patients with mild COVID‐19 infection had elevated amylase levels, this rate was 34.9% in patients with severe COVID‐19 infection. It was also revealed that the causes of pancreatic enzyme elevation were hypotension and ischaemia in patients with severe COVID‐19 infection. Elevated amylase levels were detected in 10.3% and 44.2% of patients with a normal MAP and low MAP (<60 mmHg), respectively. Out of 316 patients with a high amylase level, 36.7% of the patients recovered and 63.3% of them died. Moreover, 53% of patients with ischaemic hepatitis had both amylase and lipase elevations. We consider that after the development of shock in the body, pancreatic damage occurs in addition to hepatic and intestinal injury as a result of the decrease in blood flow to the gastrointestinal system.

A study investigating the relationship between COVID‐19 infection and pancreas reported pancreatic damage in 1%‐2% and 17% of patients with mild and severe infection, respectively. The authors suggested that pancreatic damage can be exacerbated by systemic inflammation.14151617 Amylase and lipase elevation suggestive of pancreatic damage has been reported in 8.5%‐17.3% of patients with COVID‐19. Moreover, higher enzyme levels have been reported in severe COVID‐19 patients.14151617 Likewise, in two previous autopsy studies, five of 11 (45.5%) and two of eight (25%) cases were detected with focal pancreatitis with haemorrhagic and necrotic changes in the pancreas. These changes had no clinical manifestations and were attributed to ischaemia and end‐organ damage.1819 In the light of our data, we consider that pancreatic damage is the most important cause of amylase and lipase elevations. The exact pathophysiology of pancreatic damage remains unclear, while the most widely accepted hypothesis points to pancreatic ischaemia.202122 If septicaemia progresses towards septic shock, not only in COVID‐19 but also in other infections, the resulting hypotension and vasodilation reduce blood flow to organs. To protect blood flow to vital organs such as the brain and heart, blood flow to the celiac, superior and inferior mesenteric arteries are reduced as a part of the protective mechanism. Afterwards, this is followed by renal and iliac arteries. This is the neurohormonal mechanism protecting vital organs. Gastrointestinal system is the target organ of shock and hypotension. As a result, the blood flow to the liver, pancreas and the entire gastrointestinal system is reduced, thereby causing symptoms such as nausea, vomiting, distension, ileus, or diseases such as ischaemic hepatitis.

Pancreas is supplied well by pancreatic arteries that stem from the splenic, gastroduodenal and superior mesenteric arteries. Amylase, lipase, aspartate aminotransferase (AST) and lactate dehydrogenase (LDH) are released into the bloodstream caused by the ischaemia resulting from decreased blood flow to the pancreas.23 This damage is mainly caused by haemodynamic deterioration, not by the virus itself. Similarly, in our study, elevated amylase and lipase levels were found to be associated with haemodynamic parameters and hypotension.

Although increased amylase and lipase levels might have clinical importance, it seems highly unlikely to use these parameters as prognostic indicators in clinical practice, mainly because enzyme elevation occurs during the intensive care period when the disease is severe and requires mechanical ventilation. At this stage, most patients have single or multiple organ failure and require vasopressor support.

In conclusion, although ACE2 receptors are expressed highly in pancreatic tissue, pancreatic enzyme elevations occurring in COVID‐19 infection might be associated with the severity of disease and haemodynamic instability. If the opposite was the case, we would have seen too many cases of pancreatitis, mainly because the pancreas has ACE2 receptors. As a matter of fact, despite the huge number of COVID‐19 cases, which has exceeded 100 million, pancreatitis has remained only at the level of case reports.2425Go to:

Notes

Bacaksız F, Ebik B, Ekin N, Kılıc J. Pancreatic damage in COVID‐19: Why? How? Int J Clin Pract. 2021;00:e14692. 10.1111/ijcp.14692 [PMC free article] [PubMed] [CrossRef] [Google Scholar]

DATA AVAILABILITY STATEMENT

Data may be made available upon request to the corresponding author.

REFERENCES

1. Vedel AG, Holmgaard F, Rasmussen LS, et al. Perfusion Pressure Cerebral Infarct (PPCI) trial ‐ the importance of mean arterial pressure during cardiopulmonary bypass to prevent cerebral complications after cardiac surgery: study protocol for a randomised controlled trial. Trials. 2016;17:247. [PMC free article] [PubMed] [Google Scholar]

2. Chai X, Hu L, Zhang Y, et al. Specific ACE2 expression in cholangiocytes may cause liver damage after 2019‐nCoV infection. BioRxiv. 2020:4–16. [Google Scholar]

3. Furong L, Xin Long BZ, Wanguang ZXC, Zhanguo Z. ACE2 expression in pancreas may cause pancreatic damage after SARS‐CoV‐2 infection. Clin Gastroenterol Hepatol. 2020;18:2128‐2130.e2. [PMC free article] [PubMed] [Google Scholar]

4. Yang JK, Feng Y, Yuan MY, et al. Plasma glucose levels and diabetes are independent predictors for mortality and morbidity in patients with SARS. Diabet Med. 2006;23:623‐628. [PubMed] [Google Scholar]

5. Yang JK, Lin SS, Ji XJ, et al. Binding of SARS coronavirus to its receptor damages islets and causes acute diabetes. Acta Diabetol. 2010;47:193‐199. [PMC free article] [PubMed] [Google Scholar]

6. James PC, Christopher C, Schlz TJ, Arvan DA. Combined serum amylase and lipase determinations for diagnosis of suspected. Clin Chem. 1993;39:2495‐2499. [PubMed] [Google Scholar]

7. Banks PA, Bollen TL, Dervenis C, et al. Classification of acute pancreatitis 2012: revision of the Atlanta classification and definitions by international consensus. Gut. 2013;62:102‐111. [PubMed] [Google Scholar]

8. Clinical management of COVID‐19 . WHO interim guidance. COVID‐19: Clinical care. 2020. https://www.who.int/publications/i/item/clinical‐management‐of‐covid‐19. Accessed January 25, 2021.

9. Johnson CD, Abu‐Hilal M. Persistent organ failure during the first week as a marker of fatal outcome in acute pancreatitis. Gut. 2004;53:1340‐1344. [PMC free article] [PubMed] [Google Scholar]

10. Mofidi R, Duff MD, Wigmore SJ, et al. Association between early systemic inflammatory response, severity of multiorgan dysfunction and death in acute pancreatitis. Br J Surg. 2006;93:738‐744. [PubMed] [Google Scholar]

11. Jothimani D, Venugopal R, Abedin MF, Kaliamoorthy I, Rela M. COVID‐19 and liver. J Hepatol. 2020:1231–1240. [PMC free article] [PubMed] [Google Scholar]

12. EASL . EASL clinical practice guidelines: drug‐induced liver injury. J Hepatol. 2019;70:1222‐1611. [PubMed] [Google Scholar]

13. Ricci Z, Cruz D, Ronco C. The RIFLE criteria and mortality in acute kidney injury: a systematic review. Kidney Int. 2008;73:538‐546. [PubMed] [Google Scholar]

14. Bruno G, Fabrizio C, Santoro CR, Buccoliero GB. Pancreatic injury in the course of coronavirus disease 2019 (COVID‐19): a not‐so‐rare occurrence. J Med Virol. 2021;93:74–75. [PMC free article] [PubMed] [Google Scholar]

15. McNabb‐Baltar J, Jin DX, Grover AS, et al. Lipase elevation in patients with COVID‐19. Am J Gastroenterol. 2020;115:1286‐1288. [PMC free article] [PubMed] [Google Scholar]

16. Wang F, Wang H, Fan J, Zhang Y, Wang H, Zhao Q. Pancreatic injury patterns in patients with coronavirus disease 19 pneumonia. Gastroenterology. 2020;159:367‐370. [PMC free article] [PubMed] [Google Scholar]

17. Barlass U, Wiliams B, Dhana K, et al. Marked elevation of lipase in COVID‐19 disease: a cohort study. Clin Transl Gastroenterol. 2020;11:e00215. [PMC free article] [PubMed] [Google Scholar]

18. Lax SF, Skok K, Zechner P, et al. Pulmonary arterial thrombosis in COVID‐19 with fatal outcome: results from a prospective, single‐center, clinicopathologic case series. Ann Intern Med. 2020;173:350–361. [PMC free article] [PubMed] [Google Scholar]

19. Hanley B, Naresh KN, Roufosse C, et al. Histopathological findings and viral tropism in UK patients with severe fatal COVID‐19: a post‐mortem study. Lancet Microbe. 2020;1:e245‐e253. [PMC free article] [PubMed] [Google Scholar]

20. Raper RF, Sibbald WJ, Hobson J, Rutledge FS. Effect of PGE1 on altered distribution of regional blood flows in hyperdynamic sepsis. Chest. 1991;100:1703‐1711. [PubMed] [Google Scholar]

21. Hiltebrand LB, Krejci V, Banic A, Erni D, Wheatley AM, Sigurdsson GH. Dynamic study of the distribution of microcirculatory blood flow in multiple splanchnic organs in septic shock. Crit Care Med. 2000;28:3233‐3241. [PubMed] [Google Scholar]

22. Anis C, Karim AH, Kamel B, et al. Pancreatic injury in patients with septic shock: a literature review. World J Gastrointest Oncol. 2016;8:526‐531. [PMC free article] [PubMed] [Google Scholar]

23. Leif J, Per‐Ola C. Pancreatic blood flow with special emphasis on blood perfusion of the islets of Langerhans. Compr Physiol. 2019;9:799‐837. [PubMed] [Google Scholar]

24. Rabice SR, Altshuler PC, Bovet C, Sullivan C, Gagnon AJ. COVID‐19 infection presenting as pancreatitis in a pregnant woman: a case report. Case Rep Womens Health. 2020;27:e00228. [PMC free article] [PubMed] [Google Scholar]

25. Cheung S, Delgado Fuentes A, Fetterman AD. Recurrent acute pancreatitis in a patient with COVID‐19 infection. Am J Case Rep. 2020;21:e9270. [PMC free article] [PubMed] [Google Scholar]

Why are we vaccinating children against COVID-19?

Authors: Ronald N.Kostoffa DanielaCalinab DarjaKanducc Michael B.Briggsd Panayiotis Vlachoyiannopoulose Andrey A.Svistunovf AristidisTsatsakisg

Highlights

• Bulk of COVID-19 per capita deaths occur in elderly with high comorbidities.

•Per capita COVID-19 deaths are negligible in children.

•Clinical trials for these inoculations were very short-term.

•Clinical trials did not address long-term effects most relevant to children.

•High post-inoculation deaths reported in VAERS (very short-term).

Abstract

This article examines issues related to COVID-19 inoculations for children. The bulk of the official COVID-19-attributed deaths per capita occur in the elderly with high comorbidities, and the COVID-19 attributed deaths per capita are negligible in children. The bulk of the normalized post-inoculation deaths also occur in the elderly with high comorbidities, while the normalized post-inoculation deaths are small, but not negligible, in children. Clinical trials for these inoculations were very short-term (a few months), had samples not representative of the total population, and for adolescents/children, had poor predictive power because of their small size. Further, the clinical trials did not address changes in biomarkers that could serve as early warning indicators of elevated predisposition to serious diseases. Most importantly, the clinical trials did not address long-term effects that, if serious, would be borne by children/adolescents for potentially decades.

A novel best-case scenario cost-benefit analysis showed very conservatively that there are five times the number of deaths attributable to each inoculation vs those attributable to COVID-19 in the most vulnerable 65+ demographic. The risk of death from COVID-19 decreases drastically as age decreases, and the longer-term effects of the inoculations on lower age groups will increase their risk-benefit ratio, perhaps substantially.

Graphical abstract

Keywords

COVID-19SARS-CoV-2InoculationmRNA vaccines Viral vector vaccines Adverse events Vaccine safety

1. Introduction

Currently, we are in the fifteenth month of the WHO-declared global COVID-19 pandemic. Restrictions of different severity are still in effect throughout the world [1]. The global COVID-19 mass inoculation is in its eighth month. As of this writing in mid-June 2021, over 800,000,000 people globally have received at least one dose of the inoculation and roughly half that number have been fully inoculated [2]. In the USA, about 170,000,000 people have received at least one dose and roughly 80 % of that number have been fully inoculated [2].

Also, in the USA, nearly 600,000 deaths have been officially attributed to COVID-19. Almost 5,000 deaths following inoculation have been reported to VAERS by late May 2021; specifically, “Over 285 million doses of COVID-19 vaccines were administered in the United States from December 14, 2020, through May 24, 2021. During this time, VAERS received 4,863 reports of death (0.0017 %) among people who received a COVID-19 vaccine.” [3] (the Vaccine Adverse Events Reporting System (VAERS) is a passive surveillance system managed jointly by the CDC and FDA [3]. Historically, VAERS has been shown to report about 1% of actual vaccine/inoculation adverse events [4]. See Appendix 1 for a first-principles confirmation of that result). By mid-June, deaths following COVID-19 inoculations had reached the ˜6000 levels.

A vaccine is legally defined as any substance designed to be administered to a human being for the prevention of one or more diseases [5]. For example, a January 2000 patent application that defined vaccines as “compositions or mixtures that when introduced into the circulatory system of an animal will evoke a protective response to a pathogen.” was rejected by the U.S. Patent Office because “The immune response produced by a vaccine must be more than merely some immune response but must be protective. As noted in the previous Office Action, the art recognizes the term “vaccine” to be a compound which prevents infection” [6]. In the remainder of this article, we use the term ‘inoculated’ rather than vaccinated, because the injected material in the present COVID-19 inoculations prevents neither viral infection nor transmission. Since its main function in practice appears to be symptom suppression, it is operationally a “treatment”.

In the USA, inoculations were administered on a priority basis. Initially, first responders and frontline health workers, as well as the frailest elderly, had the highest priority. Then the campaign became more inclusive of lower age groups. Currently, approval has been granted for inoculation administration to the 12–17 years demographic, and the target for this demographic is to achieve the largest number of inoculations possible by the start of school in the Fall. The schedule for inoculation administration to the 5–11 years demographic has been accelerated to start somewhere in the second half of 2021, and there is the possibility that infants as young as six months may begin to get inoculated before the end of 2021 [7].

The remainder of this article will focus on the USA situation, and address mainly the pros and cons of inoculating children under eighteen. The article is structured as follows:

Section 1 (the present section) introduces the problem.

Section 2 (Background):1) provides the background for the declared COVID-19 “pandemic” that led to the present inoculations;2) describes the clinical trials that provided the justification for obtaining Emergency Use Authorization (EUA) from the FDA to administer the inoculations to the larger population;3)

shows why the clinical trials did not predict either the seriousness of adverse events that have occurred so far (as reported in VAERS) or the potential extent of the underlying pre-symptomatic damage that has occurred as a result of the inoculations.

Section 3 (Mass Inoculation) summarizes the adverse events that have occurred already (through reporting in VAERS) from the mass inoculation and will present biological evidence to support the potential occurrence of many more adverse effects from these inoculations in the mid-and long-term.

Section 4 (Discussion) addresses these effects further

Section 5 (Summary and Conclusions) presents the conclusions of this study.

There are four appendices to this paper.

Appendix A provides some idea of the level of under-reporting of post-inoculation adverse events to VAERS and presents estimations of the actual number of post-inoculation deaths based on extrapolating the VAERS results to real-world experiences.

Appendix B provides a detailed analysis of the major clinical trials that were used to justify EUA for the inoculants presently being administered in the USA.

Appendix C summarizes potential adverse effects shown to have resulted from past vaccines, all of which could potentially occur as a result of the present inoculations.

Appendix D presents a novel best-case scenario cost-benefit analysis of the COVID-19 inoculations that have been administered in the USA.

2. Background

2.1. Pandemic history

In December 2019, a viral outbreak was reported in Wuhan, China, and the responsible coronavirus was termed Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) [8,9]. The associated disease was called Coronavirus Disease 2019, or COVID-2019. The virus spread worldwide, and a global pandemic was declared by the WHO in March 2020 [10,11]. Restrictive measures of differing severity were implemented by countries globally, and included social distancing, quarantining, face masks, frequent hand sanitation, etc. [12,13]. In the USA, these measures were taken as well, differing from state-to-state [14]. At the same time, vaccine development was initiated to control COVID-19 [15]. In the USA, non-vaccine treatments were not encouraged at the Federal level, but different treatment regimens were pursued by some healthcare practitioners on an individual level [11,16,17].

By the end of May 2021, the official CDC death count attributed to COVID-19 was approaching 600,000, as stated previously. This number has been disputed for many reasons. First, before COVID-19 testing began, or in the absence of testing, after it was available, the diagnosis of COVID-19 (in the USA) could be made by the presumption of the healthcare practitioner that COVID-19 existed [4,18]. Second, after testing began, the main diagnostic used was the RT-PCR test. This test was done at very high amplification cycles, ranging up to 45 [[19][20][21]]. In this range, very high numbers of false positives are possible [22].

Third, most deaths attributed to COVID-19 were elderly with high comorbidities [1,22]. As we showed in a previous study [22], attribution of death to one of many possible comorbidities or especially toxic exposures in combinations [23] is highly arbitrary and can be viewed as a political decision more than a medical decision. For over 5 % of these deaths, COVID-19 was the only cause mentioned on the death certificate. For deaths with conditions or causes in addition to COVID-19, on average, there were 4.0 additional conditions or causes per death [24]. These deaths with comorbidities could equally have been ascribed to any of the comorbidities [22]. Thus, the actual number of COVID-19-based deaths in the USA may have been on the order of 35,000 or less, characteristic of a mild flu season.

Even the 35,000 deaths may be an overestimate. Comorbidities were based on the clinical definition of specific diseases, using threshold biomarker levels and relevant symptoms for the disease(s) of interest [25,26]. But many people have what are known as pre-clinical conditions. The biomarkers have not reached the threshold level for official disease diagnosis, but their abnormality reflects some degree of underlying dysfunction. The immune system response (including pre-clinical conditions) to the COVID-19 viral trigger should not be expected to be the same as the response of a healthy immune system [27]. If pre-clinical conditions had been taken into account and coupled with the false positives as well, the CDC estimate of 94 % misdiagnosis would be substantially higher.

2.2. Clinical trials

2.2.1. Clinical trials to gain FDA Emergency Use Authorization (EUA) approval

The unprecedented accelerated development of COVID-19 vaccines in the USA, dubbed Operation Warp Speed, resulted in a handful of substances available for clinical trials by mid-2020 [28]. These clinical trials were conducted to predict the safety and efficacy of the potential vaccines (which have turned out to be treatments/inoculations as stated previously), and thereby gain approval for inoculating the public at large [29]. An overview of the Pfizer clinical trials is presented in this section, and a more detailed description of the main clinical trials is shown in Appendix B.

Two types of inoculants have gained FDA EUA in the US: mRNA-based inoculants and viral vector-based inoculants, with the mRNA inoculants having the widest distribution so far. Comirnaty is the brand name of the mRNA-based inoculant developed by Pfizer/BioNTech, and Moderna COVID-19 Vaccine is the brand name of the mRNA-based inoculant developed by Moderna [30]. Both inoculants contain the genetic information needed for the production of the viral protein S (spike), which stimulates the development of a protective immune response against COVID-19 [31]. Janssen COVID-19 Vaccine is the brand name of the viral vector-based inoculant developed by Johnson and Johnson. Janssen COVID-19 vaccine uses an adenovirus to transport a gene from the coronavirus into human cells, which then produce the coronavirus spike protein. This spike protein primes the immune system to fight off potential coronavirus infection [32].

The results of these trials that allowed granting of EUA by the FDA can be found in the inserts to the inoculation materials. For example, the Pfizer inoculation trial results are contained in the fact sheet for healthcare providers administering vaccine (vaccination providers) [33].

There were two clinical trials conducted to gain FDA EUA for Pfizer: a smaller Phase 1/2 study, and a larger Phase 1/2/3 study. The age demographics for the larger clinical study are as follows (from the Pfizer insert): “Of the total number of Pfizer-BioNTech COVID-19 Vaccine recipients in Study 2 (N = 20,033), 21.4 % (n = 4,294) were 65 years of age and older and 4.3 % (n = 860) were 75 years of age and older.” Additionally: “In an analysis of Study 2, based on data up to the cutoff date of March 13, 2021, 2,260 adolescents (1,131 Pfizer-BioNTech COVID-19 Vaccine; 1,129 placebo) were 12 through 15 years of age. Of these, 1,308 (660 Pfizer-BioNTech COVID-19 Vaccine and 648 placebo) adolescents have been followed for at least 2 months after the second dose of Pfizer-BioNTech COVID-19 Vaccine. The safety evaluation in Study 2 is ongoing.”

The relevant demographics are presented in Table 7 on p.31 of the Pfizer insert. The age component of those demographics is shown below in Table 1.

Table 1. Demographics (population for the primary efficacy endpoint). The number of participants who received vaccine and placebo, stratified by age.

AGE GROUPPfizer-BioNTech COVID-19 Vaccine (N = 18,242) n (%)Placebo (N = 18,379)
n (%)
≥12 through 15 yearsb46 (0.3 %)42 (0.2 %)
≥16 through 17 years66 (0.4 %)68 (0.4 %)
≥16 through 64 years14,216 (77.9 %)14,299 (77.8 %)
≥65 through 74 years3176 (17.4 %)3226 (17.6 %)
≥75 years804 (4.4 %)812 (4.4 %)

Symbols: b: “100 participants 12 through 15 years of age with limited follow-up in the randomized population received at least one dose (49 in the vaccine group and 51 in the placebo group). Some of these participants were included in the efficacy evaluation depending on the population analyzed. They contributed to exposure information but with no confirmed COVID-19 cases, and did not affect efficacy conclusions.”, N: number of test subjects, n: number of controls.

There are very minor differences between most of the data in the above table and the preceding narrative shown, and they are probably due to different time horizons. The major difference is the number of adolescents used and appears to result from a much later reporting time.

Fig. 1 uses the official large CDC numbers (coupled with USA census data estimates from CDC Wonder) to show the COVID-19 deaths per capita as a function of age, circa early June 2021. Unfortunately, the most critical range, 85+, has the least resolution. It is obvious that most of the deaths occurred in the 55 to 100+ range, and the remaining individuals in the other ranges (especially under 35) have negligible risk of dying from the disease.

Fig. 1

The age distribution in Fig. 1 differs substantially from the age distribution in Table 1. Why is this important? When designing a trial for the efficacy and safety of a potential treatment, the focus should be on the target population who could benefit from that treatment. There is little rationale for including participants in a trial for whom the treatment would not be relevant or warranted.

For the COVID-19 Pfizer trials, based on the data from Fig. 1, the trial population should have been limited at most to the 45−100+ age segment, appropriately weighted toward the higher end where the deaths per capita are most frequent. That was almost the exact opposite of what was done in the Pfizer clinical trials. In Fig. 1, approximately 58 % of the deaths occurred in the age range 75+, whereas 4.4 % of the participants in the Pfizer clinical trial were 75 + . Thus, the age range most impacted by COVID-19 deaths was minimally represented in the Pfizer clinical trials, and the age range least impacted by COVID-19 deaths was maximally represented in the Pfizer clinical trials. This skewed sampling has major implications for predicting the expected numbers of deaths for the target population from the clinical trials.

Besides age, the other metric of importance in determining COVID-19 deaths is the presence of comorbidities. The more comorbidities, and the more severe the comorbidities, the greater the chances of death or severe adverse outcomes from COVID-19. It is not clear how well the number and severity of comorbidities in the clinical trial sample matched those reflected in Fig. 1, but the insert does mention the large number of conditions that excluded participation in the trials. In sum, the results from the clinical trials could not be expected to reflect the results that could occur (and have occurred) from mass inoculation of the public, given the unaffected nature of the bulk of the trial population from SARS-CoV-2 exposure.

The prior discussion on the clinical trials has focused on the efficacy and safety of the inoculants, and the relationship of the trial test population to the total target population. We have limited the focus so far to the safety and efficacy issues since these constituted the core of what was presented to the FDA for EUA approval. We have not focused on the trials from an early warning indicator perspective.

We will address summarily the science/early warning indicator issues associated with the Pfizer trials, and how the neglect of these issues has translated into disastrous consequences during the mass inoculation rollout. Standard practice for determining and understanding the impact of new technology (such as mRNA “vaccines”) on a system involves measuring the state and flux variables of the system before the new technology intervention, measuring the state and flux variables of the system after the new technology intervention, and identifying the types and magnitudes of changes in the state and flux variables attributable to the intervention. This would be in addition to evaluating performance metrics before and after the intervention.

In Pfizer’s proposed clinical trials for the mRNA “vaccine” (Study to Describe the Safety, Tolerability, Immunogenicity, and Efficacy of RNA Vaccine Candidates Against COVID-19 in Healthy Individuals – https://clinicaltrials.gov/ct2/show/NCT04368728), the focus was on determining 1) adverse events/symptoms, 2) SARS-CoV-2 serum neutralizing antibody levels, 3) SARS-CoV-2 anti-S1 binding antibody levels and anti-RBD binding antibody levels, and 4) effectiveness. These metrics are all related to safety at the symptom level and performance.

However, symptoms/diseases are typically end points of processes that can take months, years, or decades to surface. During that symptom/disease development period, many biomarker early warning indicators tend to exhibit increasing abnormalities that reflect an increasing predisposition to the eventual symptom/disease. Thus, serious symptoms/diseases that ordinarily take long periods to develop would be expected to be rare events if they occurred shortly following an inoculation. If the clinical trials that were performed by Pfizer and Moderna were designed to focus on efficacy and only adverse effects at the symptom level of description as an indicator of safety, the trial results would be limited to the identification of rare events, and the trial results would potentially under-estimate the actual pre-symptom level damage from the inoculations.

Credible safety science applied to this experiment would have required a much more expansive approach to determining effects on a wide variety of state and flux metrics that could serve as early warning indicators of potentially serious symptoms/disease, and might occur with much higher frequencies at this early stage than the rare serious symptoms. The only mention of these other metrics in the above proposal is in the Phase I trial description: “Percentage of Phase 1 participants with abnormal haematology and chemistry laboratory values”, to be generated seven days after dose 1 and dose 2.

A paper published in NEJM in December 2020 [34] summarized the Phase 1 results. The focus was on local and systemic adverse events and efficacy metrics (antibody responses). The only metrics other than these reported were transiently decreased lymphocyte counts.

We view this level of reporting as poor safety science for the following reasons. Before the clinical trials had started, many published articles were reporting serious effects associated with the presence of the SARS-CoV-2 virus such as hyperinflammation, hypercoagulation, hypoxia, etc. SARS-CoV-2 includes the S1 Subunit (spike protein), and it was not known how much of the damage was associated with the spike protein component of SARS-CoV-2. A credible high-quality safety science experiment would have required state measurements of specific biomarkers associated with each of these abnormal general biomarkers before and after the inoculations, such as d-dimers for evidence of enhanced coagulation/clotting; CRP for evidence of enhanced inflammation; troponins for evidence of cardiac damage; occludin and claudin for evidence of enhanced barrier permeability; blood oxygen levels for evidence of enhanced hypoxia; amyloid-beta and phosphorylated tau for evidence of increased predisposition to Alzheimer’s disease; Serum HMGB1, CXCL13, Dickkopf-1 for evidence of an increased disposition to autoimmune disease, etc. A credible high-quality safety science experiment would have required flux measurements of products resulting from the mRNA interactions, from the LNP shell interactions, from dormant viruses that might have been stimulated by the mRNA-generated spike protein, etc., emitted through the sweat glands, faeces, saliva, exhalation, etc.

Most importantly, these types of measurements would have shown changes in the host that did not reach the symptom level of expression but raised the general level of host abnormality that could predispose the host to a higher probability of serious symptoms and diseases at some point in the future. Instead, in the absence of high-quality safety science reflected in these experiments, all that could be determined were short-term adverse effects and deaths. This focus on symptoms masked the true costs of the mRNA intervention, which would probably include much larger numbers of people whose health could have been degraded by the intervention as evidenced by increased abnormal values of these biomarkers. For example, the trials and VAERS reported clots that resulted in serious symptoms and deaths but gave no indication of the enhanced predisposition to forming serious clots in the future with a higher base of micro-clots formed because of the mRNA intervention. The latter is particularly relevant to children, who have a long future that could be seriously affected by having an increased predisposition to multiple clot-based (and other) serious diseases resulting from these inoculations.

3. Mass inoculation

3.1. Adverse events reported for adults

This section describes the adverse effects that followed COVID-19 mass inoculation in the USA. The main source of adverse effects data used was VAERS. Because VAERS is used to estimate adverse event information by many other countries as well, a short overview of VAERS and its intrinsic problems is summarized in Appendix 1.

The period in the present study covered by the reported inoculations is mid-December 2020 to the end of May 2021. The population inoculated during this period is mainly adults. Child inoculations did not begin until mid-May. Because the different age groups were inoculated starting at different times based on priority, the elapsed times after inoculation will be different, and any adverse event comparisons across age groups will require some type of elapsed post-inoculation time normalization.

We examined VAERS-reported deaths by age group, normalized to:1)

the number of inoculations given2)

the period within seven days after inoculation.

This allows a credible comparison of very short-term adverse effects post-inoculation for all age groups. During this period, which is eight days post-inoculation (where day zero is the day of inoculation), ˜sixty percent of all post-inoculation deaths are reported in VAERS.

Fig. 2 below shows the results circa late May 2021 [3]. The age band ranges are different from those in Fig. 1 because the CDC provides inoculation after-effect age bands differently from COVID-19 death age bands. In general, the inoculation deaths by age per inoculant roughly parallel the COVID-19 deaths by age per capita (the curve structures are very similar), with one exception: the 0–17 demographic. In the normalized COVID-19 death graph (Fig. 1), the deaths per capita in the 0–17 demographic are negligible, while in the normalized inoculant death graphs (Fig. 2) the normalized deaths are small, but not negligible. The members of the 65+ demographic, where the bulk of deaths are occurring in Fig. 1Fig. 2, have been receiving inoculations for ˜five months, whereas the members of the youngest demographic have been receiving inoculations only for a few weeks. More time needs to pass before more definitive conclusions can be drawn about the youngest demographic, and how its members are impacted adversely following the inoculations.

Fig. 2

The high death rates from both COVID-19 and the inoculations in the 65+ demographic should not be surprising. In both cases, the immune system is challenged, and in both cases, a dysfunctional immune system characteristic of many elderly people with multiple comorbidities cannot respond adequately to the challenge.

3.1.1. Specific short-term adverse events reported in VAERS

The most comprehensive single evaluation of VAERS-reported adverse events (mainly for adult recipients of the COVID-19 “vaccines”) we have seen is a non-peer-reviewed collection of possible side effects by Dr. Ray Sahelian [35]. We recommend reading this short data-rich summary of the broad types of events reported already, in the context that these events are very short-term. Dr. Sahelian identifies five mechanisms he believes are responsible for most of these events, with research potentially uncovering other mechanisms. These five mechanisms include:1

“An overreacting inflammatory response is known as systemic inflammatory response syndrome (SIRS). This SIRS reaction, perhaps a cytokine storm, can range from very mild to very severe. It can begin the very first day of the shot or begin days or weeks later as a delayed reaction.”2

“Interaction of the spike proteins with ACE2 receptors on cell membranes. Such cells are found widely in the body including the skin, lungs, blood vessels, heart, mouth, gastrointestinal tract, kidneys, and brain.”3

“Interaction of spike proteins with platelets and/or endothelial cells that line the inside of blood vessels. This can lead to clotting or bleeding (low number of circulating platelets in the bloodstream). Some of the clots, even if tiny, cause certain neurological symptoms if the blood supply to nerves is compromised.”4

“Immediate or delayed release of histamine from mast cells and basophils (mast cell activation syndrome, MCAS).”5

5. “Swelling of lymph nodes in various areas of the body could interfere with blood flow, put pressure on nerves causing pain, or compromise their proper function.”

These reactions can be classified as Hyperinflammation, Hypercoagulation, Allergy, and Neurological, and can contribute to many symptoms and diseases, as VAERS is showing.

An excellent review of acute and potential long-term pathologies resulting from the COVID-19 inoculations [36] showed potential relationships to blood disordersneurodegenerative diseases and autoimmune diseases. This review discussed the relevance of prion-protein-related amino acid sequences within the spike protein.

3.1.2. Potential mid- and long-term events and serious illnesses for adults and children from past vaccines

A detailed description of potential mid- and long-term events and serious illnesses for adults and children from past vaccines is presented in Appendix C. Most of these events and illnesses are not predictable, and most, if not all, would be possible for the COVID-19 inoculations in the mid- and long-term for adults and children.

3.1.3. Potential short-, mid-, and long-term risks of mass COVID-19 inoculation for children

3.1.3.1. Intrinsic inoculant toxicity

Children are unique relative to COVID-19. They have negligible risks of serious effects from the disease, as shown in Fig. 1. Given that the COVID-19 inoculants were only tested for a few months, and mid-or long-term adverse effects are unknown, any mid- or long-term adverse events that emerge could impact children adversely for decades.

We believe that mid-or long-term adverse effects are possible based on the recent emergence of evidence that would support the probability of mid-and long-term adverse effects from the COVID-19 inoculants, such as:1)

The spike protein itself can be a toxin/pathogenic protein:2)

S protein alone can damage vascular endothelial cells (ECs) by downregulating ACE2 and consequently inhibiting mitochondrial function [37].3)

it is concluded that ACE2 and endothelial damage is a central part of SARS-CoV2 pathology and may be induced by the spike protein alone [38].4)

the spike protein of SARS-CoV-1 (without the rest of the virus) reduces ACE2 expression, increases angiotensin II levels, exacerbates lung injury, and triggers cell signaling events that may promote pulmonary vascular remodeling and Pulmonary Arterial Hypertension (PAH) as well as possibly other cardiovascular complications [39].5)

the recombinant S protein alone elicits functional alterations in cardiac vascular pericytes (PCs) [40]. This was documented as:6)

increased migration7)

reduced ability to support EC network formation on Matrigel8)

secretion of pro-inflammatory molecules typically involved in the cytokine storm9)

production of pro-apoptotic factors responsible for EC death. Furthermore, the S protein stimulates the phosphorylation/activation of the extracellular signal-regulated kinase 1/2 (ERK1/2) through the CD147 receptor, but not ACE2, in cardiac PCs, the S protein may elicit vascular cell dysfunction, potentially amplifying, or perpetuating, the damage caused by the whole coronavirus [40].10)

“even in the absence of the angiotensin-converting enzyme 2 receptors, the S1 subunit from SARS-CoV-2 spike protein binding to neutral phospholipid membranes leads to their mechanical destabilization and permeabilization. A similar cytotoxic effect of the protein was seen in human lung epithelial cells.” [125].11)

The LNP layer encapsulating the mRNA of the inoculant is highly inflammatory in both intradermal and intranasal inoculation [41] and “Polyethylene glycol (PEG) is a cause of anaphylaxis to the Pfizer/BioNTech mRNA COVID-19 vaccine” [42]. “Humans are likely developing PEG antibodies because of exposure to everyday products containing PEG. Therefore, some of the immediate allergic responses observed with the first shot of mRNA-LNP vaccines might be related to pre-existing PEG antibodies. Since these vaccines often require a booster shot, anti-PEG antibody formation is expected after the first shot. Thus, the allergic events are likely to increase upon re-vaccination” [43].

There is also the possibility that the components of the LNP shell could induce the ASIA Syndrome (autoimmune/inflammatory syndrome induced by adjuvants), as shown by studies on post-inoculation thyroid hyperactivity [44] and post-inoculation subacute thyroiditis [45].12

The spike protein has been found in the plasma of post-inoculation individuals, implying that it could circulate to, and impact adversely, any part of the body [46].13

The spike protein of SARS-CoV-2 crosses the blood-brain barrier in mice [47], and “the SARS-CoV-2 spike proteins trigger a pro-inflammatory response on brain endothelial cells that may contribute to an altered state of BBB function” [48].14

The spike proteins manufactured in vivo by the present COVID-19 inoculations could potentially “precipitate the onset of autoimmunity in susceptible subgroups, and potentially exacerbate autoimmunity in subjects that have pre-existing autoimmune diseases”, based on the finding that anti-SARS-CoV-2 protein antibodies cross-reacted with 28 of 55 diverse human tissue antigens [49].15

“The biodistribution of ChaAdOx1 [Astra Zeneca’s recombinant adenovirus vaccine candidate against SARS-CoV-2] in mice confirmed the delivery of vaccine into the brain tissues [50]. The vaccine may therefore spur the brain cells to produce CoViD spike proteins that may lead to an immune response against brain cells, or it may spark a spike protein-induced thrombosis. This may explain the peculiar incidences of the fatal cerebral venous sinus thrombosis (CVST) observed with viral vector-based CoViD-19 vaccines” [51,52].

A complementary perspective to explain adenovirus-based vaccine-induced thrombocytopenia is that “transcription of wildtype and codon-optimized Spike open reading frames enables alternative splice events that lead to C-terminal truncated, soluble Spike protein variants. These soluble Spike variants may initiate severe side effects when binding to ACE2-expressing endothelial cells in blood vessels.” [100].16

A Pfizer Confidential study performed in Japan showed that “modRNA encoding luciferase formulated in LNP comparable to BNT162b2″ injected intramuscularly concentrated in many organs/tissues in addition to the injection site [53]. The main organs/sites identified were adrenal glands, liver, spleen, bone marrow, and ovaries. While damage to any of these organs/sites could be serious (if real for humans), adverse effects on the ovaries could be potentially catastrophic for women of childbearing or pre-childbearing age.

The main objective of credible biodistribution studies (of inoculants for eventual human use) is to identify the spatio-temporal distribution of the actual inoculant in humans; i.e., how much of the final desired product (in this case, expressed protein antigen/spike protein) is produced in different human tissues and organs as a function of time. That’s not what was reported in the Pfizer Confidential study.

Rats were used for the in vivo studies; the relationship of their biodistribution to that of humans is unclear. They were injected in different locations (hindpaw/intramuscular); the relationship to human injections in the deltoid muscle is unclear. They were injected with “modRNA encoding luciferase formulated in LNP comparable to BNT162b2″; it is unclear why they weren’t injected with BNT162b2, it is unclear why spike protein expression wasn’t evaluated rather than LNP concentration, and it is unclear how well the biodistribution from the actual inoculant used in the experiments compares to the biodistribution from BNT162b2.

They were injected once per rat. Given that a second injection would not be in the same exact location as the first, and that the circulatory system might have changed due to clotting effects from the first injection and other potential vascular complications, it is unclear how the biodistribution change with the second injection would compare with the first. If a booster injection is given to counter variants, it is unclear how its biodistribution would be altered as a consequence of the preceding two injections.

Clotting will occur with the highest probability where the blood flow is reduced (and more time is available for LNP-endothelial cell interaction). It is unclear whether the clotting process would show positive feedback behaviour where the initial inoculation constricts the flow in low-velocity regions even further by enhanced clotting, and subsequent inoculations further amplify this reduced flow-enhanced clotting cycle.

The rats were injected under pristine conditions; how that compares with humans, who have been, are being, and will continue to be exposed to multiple toxic substances in combination, is open to question. We know these combinations can act synergistically to adversely impact myriad organs and tissues throughout the body [23]. We don’t know how these toxic exposures in humans affect the permeability of the blood/tissue barriers, and especially the ability of the injected material to diffuse into the bloodstream (and also the ability of the manufactured spike proteins to diffuse from the bloodstream into the surrounding tissue).

Higher-level primates should have been used for these short-term experiments, to obtain a more realistic picture of the biodistribution of inoculant in human organs and tissues. In other words, these laboratory experiments may be just the tip of the iceberg of estimating the amount of inoculant that concentrates in critical organs and tissues of human beings.

The many studies referenced above indicate collectively that the mRNA-based COVID-19 inoculations (the most prolific inoculations used in the USA for COVID-19 so far) consist of (at least) two major toxins: the instructions for the spike protein (mRNA) and the mRNA-encapsulating synthetic fat LNP. The vaccine is injected into the deltoid muscle, at which time it contributes to inflammation at the injection site due in part to the LNP and potentially to anaphylaxis from the LNP PEG-2000 component. Some of the injected material stays at the injection site, where it combines with cells through endocytosis to express spike protein on the cell surface, stimulating the adaptive immune system to eventually produce antibodies to the spike protein [54].

The remainder of the injected material enters the lymphatic system and the bloodstream, and is distributed to tissues and organs throughout the body: e.g., “Drugs administered by the intramuscular (IM) route are deposited into vascular muscle tissue, which allows for rapid absorption into the circulation” [55]. The basis of this process is that the bulky muscles have good vascularity, and therefore the injected drug quickly reaches the systemic circulation and thereafter into the specific region of action, bypassing the first-pass metabolism [56]. The widespread distribution is greatly enhanced by the LNP PEG-2000 coating as follows: building from the success of PEGylating proteins to improve systemic circulation time and decrease immunogenicity [57]. PEG coatings on nanoparticles shield the surface from aggregation, opsonization, and phagocytosis, prolonging systemic circulation time. [57]. PEG coatings on nanoparticles have also been utilized for overcoming various biological barriers to efficient drug and gene delivery associated with other modes of administration. [57]

In the bloodstream, one possible outcome is that the LNPs coalesce with the endothelial cells on the inner lining of the blood vessels and transfer the mRNA to the cells through endocytosis. The endothelial cells would then express the spike protein on their surface. Platelets flowing by the spike protein express ACE2 receptors on their surface; therefore, one possible outcome would be activation of the platelets by the spike protein and initiation of clotting. Another possible outcome would be the modified endothelial cells being recognized by innate immune system cells as foreign. These immune killer cells would then destroy parts of the endothelium and weaken the blood-organ barriers. The LNPs would inflame the endothelium as well, both increasing barrier permeability and increasing the blood vessel diameter. This weakening of the blood-organ barriers would be superimposed on any inflammation due to the myriad toxic contributing factors operable [4]. The newly-formed cells with spike proteins would penetrate the blood-organ barriers and bind to tissue with expressed ACE2 receptors. Any LNPs that did not coalesce with the endothelial cells, but remained intact, could also pass through the permeable blood-organ barrier, and coalesce directly with the organ cells. This could lead to an attack by innate immune system cells, and be a precursor to autoimmunity [4].

In the preceding discussion of the Pfizer biodistribution studies, the issue of multiple inoculations on changes in biodistribution was raised. Similarly, the alteration of effects as described above by multiple inoculations must be considered. Each inoculation will have positive aspects and negative aspects. The positive aspects are the formation of antibodies in the muscle cells and lymphatic system. The negative aspects include, but are not limited to, the potential clotting effects and permeability increases for that fraction of the inoculant that enters the bloodstream. The first inoculant dose can be viewed as priming the immune system. The immune response will be relatively modest. The second inoculant dose can be expected to elicit a more vigorous immune response. This will enhance the desired antibody production in the muscle cells and lymphatic system, but may also enhance the immune response to both the blood vessel-lining endothelial cells displaying the spike protein and the platelets, causing more severe damage. If a booster(s) inoculation is also required, this may further enhance both the positive and negative immune responses resulting from the second inoculation. While the positive effects are reversible (antibody levels decrease with time), adverse effects may be cumulative and irreversible, and therefore injury and death rates may increase with every additional inoculation [58].

These effects can occur throughout the body in the short term, as we are seeing with the VAERS results. They can occur in the mid- and long-term as well, due to the time required for destructive processes to have full effect and the administration of further inoculations. For example, micro-clots resulting from the inoculation that were insufficient to cause observable symptoms could in effect raise the baseline for thrombotic disease [92]. Lifestyle activities that contribute to enhanced blood clotting would have less distance to travel to produce observable symptoms, and thus the serious effects of clotting would have been accelerated [59,60]. As an example: the risk of venous thrombosis is approximately 2- to 4-fold increased after air travel [61]. How much this rate would increase after the inoculations, where microthrombi have formed in some recipients, is unknown. These potential baseline-raising effects could impact the interpretation of the VAERS results, as we show at the end of Appendix 1.

3.1.3.2. Adverse inoculant effects on children

What are the potential mid- and long-term adverse health effects from the COVID-19 inoculation on children specifically, taking into account that they will be exposed not only to the spike protein component of the SARS-CoV-2 virus but also to the toxic LNP encapsulating-shell? This toxic combination will have bypassed many defensive safeguards (typically provided by the innate immune system) through direct injection [62]. As we have shown, the main reasons why we believe the spike protein could be harmful to children even though they don’t seem to get sick from exposure to SARS-CoV-2 are 1) the bypassing of the innate immune system by inoculation, 2) the larger volume of spike protein that enters the bloodstream, and 3) the additional toxic effects of the encapsulating LNP layer.

3.1.3.2.1. Potential mid-term adverse health effects

Examination of the myriad post-COVID-19 inoculation symptoms/biomarker changes for the 0–17 age demographic reported to VAERS circa mid-June 2021 provides some indication of very early damage [84]. Main regions/systems affected adversely (VAERS symptoms/biomarkers shown in parentheses) include:•

Cardiovascular (blood creatine phosphokinase increased, cardiac imaging procedure abnormal, echocardiogram abnormal, electrocardiogram abnormal, heart rate increased, myocarditispalpitationspericarditistachycardiatroponin I increased, troponin increased, fibrin D-Dimer increased, platelet count decreased, blood pressure increased, bradycardiabrain natriuretic peptide increased, ejection fraction decreased, migraine)•

Gastrointestinal (abdominal pain, diarrhoea, vomiting, alanine aminotransferase increased, aspartate aminotransferase increased.)•

Neural (gait disturbance, mobility decreased, muscle spasms, muscle twitching, seizure, tremor, Bell’s Palsy, dyskinesia)•

Immune (C-Reactive Protein increased, red blood cell sedimentation rate increased, white blood cell counts increased, inflammation, anaphylactic reaction, pruritis, rash, lymphadenopathy)•

Endocrine (heavy menstrual bleeding, menstrual disorder)

In addition, there were large numbers of different vision and breathing problems reported.

All the major systems of the body are impacted, and many of the major organs as well. Given the lag times in entering data into VAERS and the fact that inoculations of children started fairly recently, we would expect the emphasis to be immediate symptomatic and biomarker reactions. More time is required for organ and system damage to develop and emerge. Cardiovascular problems dominate, as our model for spike protein/LNP circulation and damage predicts, and it is unknown how reversible such problems are. Many of the VAERS symptoms listed above were also found in COVID-19 adult patients [64].

Consider the example of Multisystem Inflammatory Syndrome in Children (MIS-C). It has emerged in VAERS with modest frequency so far, and it also occurred about a month after COVID-19 infection [65]. In both cases, the presence of the spike protein was a common feature. Many of its characteristic symptoms are those listed above from VAERS. MIS-C has similarities with known disease entities like Kawasaki Disease (KD), toxic shock syndrome (TSS) and macrophage activation syndrome (MAS)/secondary hemophagocytic lymphohistiocytosis (HLH) [66]. One presentation of MIS-C is in adolescents with a high disease burden as evidenced by more organ systems involved, almost universally including cardiac and gastrointestinal systems, and with a higher incidence of shock, lymphopenia, and elevated cardiac biomarkers indicating myocarditis [67]. Since the first reports of children developing MIS-C, it was evident that others presented with some of the classic symptoms of the well-recognized childhood illness KD [68]. Further, despite KD being ordinarily incredibly rare in adults, patients with MIS-A have also been reported with KD-like features. [68] Thus, an examination of the adverse effects from COVID-19 as evidenced through these diseases might shed some light on what can be expected further down the line from the inoculations.

The following section addresses Kawasaki disease (KD) and Multisystem Inflammatory Syndrome in Children (MIS-C) [65].

KD is an acute vasculitis and inflammation that predominantly affects the coronary arteries and can cause coronary artery aneurysms. Other KD manifestations include systemic inflammation of arteries, organs, and tissues, with consequent hepatitis and abdominal pain; lung interstitial pneumonitisaseptic meningitis due to brain membrane inflammations; myocarditis, pericarditis, and valvulitis; urinary tract pyuriapancreatitis; and lymph-node enlargement [69]. In general, although almost all children fully recover, some of them later develop coronary artery dilation or aneurysm [70]. Etiologically and pathologically, numerous studies indicate that KD is triggered by an abnormal autoimmune response caused by an infection [71]. The infection hypothesis is supported by epidemiology data showing that an infectious disease is involved at least as a starting point. Previously proposed infectious agents include Herpesviridaeretroviruses, Parvovirus B19, bocavirus, and bacterial infections such as staphylococci, streptococci, Bartonella, and Yersinia infections [72].

SARS-CoV-2 adds to these infectious agents by eliciting autoantibodies likely via molecular mimicry and cross-reactivity with autoantigens [72,73].

Then, the formation of antigen–antibody immune complexes can lead to KD symptoms via activation of the receptors of mast cells, neutrophils, and macrophages with consequent release of pro-inflammatory cytokines and increase of blood vessel permeability; activation of the complement system, stimulation of neutrophils and macrophages to secrete proteases and more proinflammatory cytokines [74], thus merging into the “cytokine storm” that characterizes MIS-C [75]. Indeed, features of KD are raised levels of Interleukin (IL)-6, IL-8, IL-15, and IL-17, with the cytokine level predicting coronary aneurysm formation in KD patients [76,77]

3.1.3.2.2. Potential long-term adverse health effects

In the long-term, SARS-CoV-2-induced KD vasculitis can lead to severe pathologies. Vasculitis has a predilection for coronary arteries with a high complication rate across the lifespan for those with medium to large coronary artery aneurysms [78]. The cytokine-induced inflammation produces endothelial dysfunction and damage to the vascular wall, leading to aneurysmal dilatation. Successively, vascular remodeling can also occur, but this does not imply resolution of the disease or reduction of risk for future complications. A rigorous follow-up to detect progressive stenosis, thrombosis and luminal occlusion that may lead to myocardial ischemia and infarction becomes mandatory [78]. Of equal importance, among other long-term outcomes, children with KD may have increased risks not only for ischemic heart disease, but also for autoimmune disorders, cancer as well as an increased all-cause mortality [71].

Additional questions regarding mass inoculation of children and adolescents include:

a)

Do children, being asymptomatic carriers of SARS-CoV-2, transmit the virus?b)

Do recently vaccinated people, infected with SARS-CoV-2, transmit the virus?

There is evidence of children transmitting SARS-CoV-2 in community settings, but the existing literature is heterogeneous with regards to the relative rate at which they do so compared to adults [79].

Studies from South Korea and Thailand found a very limited number of secondary cases [80,81]. On the contrary, a large contact tracing study from India concluded that the highest probability of transmission was between case-contact pairs of similar age and that this pattern of enhanced transmission risk was highest among children 0–4 years of age as well as adults 65 years of age and older [80]

With regard to the second question, it was shown that household members of healthcare workers inoculated with a single dose of either Pfizer or Astra Zeneca COVID-19 inoculant were at significantly reduced risk of PCR-confirmed SARS-CoV-2 infection but at non-statistically significant reduced risk of hospitalization, compared to household members of uninoculated healthcare workers, fourteen days after inoculation [82]. This finding again underlines the association of severe disease to the characteristics of the infected person and not directly to the transmission, implying that the elderly should be inoculated and not the children.

3.2. Novel best-case scenario cost-benefit analysis of COVID-19 inoculations for most vulnerable

Traditional cost-benefit analyses are typically financial tools used to estimate the potential value of a proposed project. They involve generating cost streams over time, benefit streams over time, and then comparing the net present value of these two streams (including risk) to see whether the risk-adjusted discounted benefits outweigh the risk-adjusted discounted costs. Appendix D presents a detailed non-traditional best-case scenario pseudo-cost-benefit analysis of inoculating people in the 65+ demographic in the USA. In this incarnation of a cost-benefit analysis, the costs are the number of deaths resulting from the inoculations, and the benefits are the lives saved by the inoculations. The time range used was from December 2019 to end-of-May 2021. No discounting was done; an inoculation-based death occurring immediately post-inoculation was given the same importance/weighting as an inoculation-based death months after inoculation.

Why was this non-traditional approach selected for a cost-benefit analysis? In a traditional non-financial cost-benefit analysis relative to inoculations, the adverse events prevented by the inoculations would be compared with the adverse events resulting from the inoculations. Presently, in the USA, definitions, test criteria, and reporting incentives for COVID-19 and its inoculants have shifted over time, and we believe a standard approach could not be performed credibly. Appendix Da presents some of the problems with the COVID-19 diagnostic criteria on which the above statements are based.

In contrast to the pandemic buildup phase, where many who died with COVID-19 were assumed to have died from COVID-19 by the medical community and the CDC, the post-inoculation deaths reported in VAERS are assumed by the CDC to be mostly from causes other than the inoculations. We wanted to use a modified cost-benefit analysis that would have less dependence on arbitrary criteria and subjective judgments.

The approach selected can be viewed as a best-case scenario pseudo-cost-benefit analysis. We assume the inoculations prevent all the deaths truly attributable to COVID-19 (these are the total deaths attributed to COVID-19 officially minus 1) the number of false positives resulting from the PCR tests run at very high amplification cycles and 2) the number of deaths that could have been attributed to one of the many comorbidities that were typical of those who succumbed, as shown in our results section) over the period December 2019 to end-of-May 2021, and relate that number to the deaths truly attributable to the inoculation (from January 2021 to end-of-May 2021) based on our computations in the results section. The results show conservatively that there are five times the number of deaths truly attributable to each inoculation vs those truly attributable to COVID-19 in the 65+ demographic. As age decreases, and the risk for COVID-19 decreases, the cost-benefit increases. Thus, if the best-case scenario looks poor for benefits from the inoculations, any realistic scenario will look very poor. For children the chances of death from COVID-19 are negligible, but the chances of serious damage over their lifetime from the toxic inoculations are not negligible.

4. Discussion

Two issues arise from these results.

First, where is the data justifying inoculation for children, much less most people under forty? It’s not found on Fig. 1, where the most vulnerable are almost exclusively the elderly with many comorbidities [83]. Yet, in the USA, Pfizer has been approved to inoculate children 12–17, and the goal is to accomplish this by the start of the school year in the Fall. As stated previously, there are plans to inoculate children as young as six months starting before the end of 2021.

What is the rush for a group at essentially zero risks? Given that the inoculations were tested only for a few months, only very short-term adverse effects could be obtained. It is questionable how well even these short-term effects obtained from the clinical trials reflect the short-term effects from the initial mass inoculation results reported in VAERS.

Fig. 1Fig. 2 reflect only these very short-term results. A number of researchers have suggested the possibility of severe longer-term autoimmune, Antibody-Dependent Enhancement, neurological, and other potentially serious effects, with lag periods ranging from months to years. If such effects do turn out to be real, the children are the ones who will have to bear the brunt of the suffering. There appear to be no benefits for the children and young adults from the inoculations and only Costs!

The second issue is why the deaths shown on Fig. 2 were not predicted by the clinical trials. We examined the Pfizer trial results (based on a few months of testing) and did not see how (potentially) hundreds of thousands of deaths could have been predicted from the trials’ mortality results. Why this gap?

As we showed in the clinical trials section, 17.4 % of the Pfizer sample members were over 65, and 4.4 % were over 75. When the later phases of the trials started in late July 2020, the managers knew the COVID-19 age demographics affected from the July 2020 analog of Fig. 1. Rather than sampling from the age region most affected, they sampled mainly from the age region least affected! And even in the very limited sampling from the oldest groups, it is unclear whether they selected from those with the most serious comorbidities. Our impression is that the sickest were excluded from the trials, but were first in line for the inoculants.

It is becoming clear that the central ingredient of the injection, the recipe for the spike protein, will produce a product that can have three effects. Two of the three occur with the production of antibodies to the spike protein. These antibodies could allegedly offer protection against the virus (although with all the “breakthrough” cases reported, that is questionable), or could suppress serious symptoms to some extent. They could also cross-react with human tissue antigen, leading to potential autoimmune effects. The third occurs when the injected material enters the bloodstream and circulates widely, which is enabled by the highly vascular injection site and the use of the PEG-2000 coating.

This allows spike protein to be manufactured/expressed in endothelial cells at any location in the body, both activating platelets to cause clotting and causing vascular damage. It is difficult to believe this effect is unknown to the manufacturer, and in any case, has been demonstrated in myriad locations in the body using VAERS data. There appears to be modest benefit from the inoculations to the elderly population most at risk, no benefit to the younger population not at risk, and much potential for harm from the inoculations to both populations. It is unclear why this mass inoculation for all groups is being done, being allowed, and being promoted.

5. Overall conclusions

The people with myriad comorbidities in the age range where most deaths with COVID-19 occurred were in very poor health. Their deaths did not seem to increase all-cause mortality as shown in several studies. If they hadn’t died with COVID-19, they probably would have died from the flu or many of the other comorbidities they had. We can’t say for sure that many/most died from COVID-19 because of: 1) how the PCR tests were manipulated to give copious false positives and 2) how deaths were arbitrarily attributed to COVID-19 in the presence of myriad comorbidities.

The graphs presented in this paper indicate that the frail injection recipients receive minimal benefit from the inoculation. Their basic problem is a dysfunctional immune system, resulting in part or in whole from a lifetime of toxic exposures and toxic behaviors. They are susceptible to either the wild virus triggering the dysfunctional immune system into over-reacting or under-reacting, leading to poor outcomes or the injection doing the same.

This can be illustrated by the following analogy. A person stands in a bare metal enclosure. What happens when the person lights a match and drops it on the floor depends on what is on the floor. If the floor remains bare metal, the match burns for a few seconds until extinguished. If there is a sheet of paper on the floor under the match, the match and the paper will burn for a short time until both are extinguished. If, however, the floor is covered with ammonium nitrate and similar combustible/explosive materials, a major explosion will result! For COVID-19, the wild virus is the match. The combustible materials are the toxic exposures and toxic behaviors. If there are no biomarker ‘footprints’ from toxic exposures and toxic behaviors, nothing happens. If there are significant biomarker ‘footprints’ from toxic exposures and toxic behaviors, bad outcomes result.

Adequate safety testing of the COVID-19 inoculations would have provided a distribution of the outcomes to be expected from ‘lighting the match’. Since adequate testing was not performed, we have no idea how many combustible materials are on the floor, and what the expected outcomes will be from ‘lighting the match’.

The injection goes two steps further than the wild virus because 1) it contains the instructions for making the spike protein, which several experiments are showing can cause vascular and other forms of damage, and 2) it bypasses many front-line defenses of the innate immune system to enter the bloodstream directly in part. Unlike the virus example, the injection ensures there will always be some combustible materials on the floor, even if there are no other toxic exposures or behaviors. In other words, the spike protein and the surrounding LNP are toxins with the potential to cause myriad short-, mid-, and long-term adverse health effects even in the absence of other contributing factors! Where and when these effects occur will depend on the biodistribution of the injected material. Pfizer’s own biodistribution studies have shown the injected material can be found in myriad critical organs throughout the body, leading to the possibility of multi-organ failure. And these studies were from a single injection. Multiple injections and booster shots may have cumulative effects on organ distributions of inoculant!

The COVID-19 reported deaths are people who died with COVID-19, not necessarily from COVID-19. Likewise, the VAERS deaths are people who have died following inoculation, not necessarily from inoculation.

As stated before, CDC showed that 94 % of the reported deaths had multiple comorbidities, thereby reducing the CDC’s numbers attributed strictly to COVID-19 to about 35,000 for all age groups. Given the number of high false positives from the high amplification cycle PCR tests, and the willingness of healthcare professionals to attribute death to COVID-19 in the absence of tests or sometimes even with negative PCR tests, this 35,000 number is probably highly inflated as well.

On the latter issue, both Virginia Stoner [85] and Jessica Rose [86] have shown independently that the deaths following inoculation are not coincidental and are strongly related to inoculation through strong clustering around the time of injection. Our independent analyses of the VAERS database reported in Appendix 1 confirmed these clustering findings.

Additionally, VAERS historically has under-reported adverse events by about two orders-of-magnitude, so COVID-19 inoculation deaths in the short-term could be in the hundreds of thousands for the USA for the period mid-December 2020 to the end of May 2021, potentially swamping the real COVID-19 deaths. Finally, the VAERS deaths reported so far are for the very short term. We have no idea what the death numbers will be in the intermediate and long-term; the clinical trials did not test for those.

The clinical trials used a non-representative younger and healthier sample to get EUA for the injection. Following EUA, the mass inoculations were administered to the very sick (and first responders) initially, and many died quite rapidly. However, because the elderly who died following COVID-19 inoculation were very frail with multiple comorbidities, their deaths could easily be attributed to causes other than the injection (as should have been the case for COVID-19 deaths as well).

Now the objective is the inoculation of the total USA population. Since many of these potential serious adverse effects have built-in lag times of at least six months or more, we won’t know what they are until most of the population has been inoculated, and corrective action may be too late.

All the authors contributed equally and approved the final version of the manuscript.

Author’s contribution

Kostoff RN contributed to this paper with conception, data analysis, and writing the manuscript; Calina D contributed to data analysis, writing the manuscript, and editing; Kanduc D participated in data analysis and writing the manuscript; Briggs MB participated in data analysis, results validation, and graphics development; Vlachoyiannopoulos P participated in writing the manuscript; Svistunov AA participated in editing and reviewing the manuscript; Tsatsakis A participated in editing and reviewing the manuscript; all the authors contributed equally and approved the final version of the manuscript.

Ethical approval

Not applicable.

Declaration of Competing Interest

The authors declare that they have no competing interests. Aristides Tsatsakis is the Editor-in-Chief for the journal but had no personal involvement in the reviewing process, or any influence in terms of adjudicating on the final decision, for this article.

Acknowledgement

Not applicable.

Appendix A

EXPECTED DEATHS IN 65+ DEMOGRAPHIC VS COVID-19 INOCULATION DEATHS

The goal of this appendix is to estimate the number of actual deaths from the COVID-19 inoculation based on the number of deaths following inoculation reported in VAERS [93,94,101]. The approach used will: 1) identify the number of deaths following COVID-19 inoculation that would have been expected without COVID-19 inoculation (i.e., pre-COVID-19 death statistics);2)

relate the VAERS expected death data to the actual number of deaths expected based on historical death statistics; and3) apply this ratio to scale-up the deaths attributed to COVID-19 inoculation reported in VAERS to arrive at actual deaths attributable to COVID-19 inoculation.

For example, if ten deaths could be shown in VAERS to reflect expected pre-COVID-19 deaths, and the actual number of expected pre-COVID-19 deaths from historical data was 100, the scaling factor of deaths would be ten to translate VAERS-reported deaths to actual deaths. Then, the deaths reported in VAERS that can be attributed to the COVID-19 inoculation will be multiplied by the expected deaths scaling factor, ten, to arrive at the actual number of deaths resulting from the COVID-19 inoculation. Thus, if VAERS shows fifty deaths that can be attributed to the COVID-19 inoculation, then the actual number of deaths attributed to COVID-19 will be 500 with these assumptions [3].

The basis for our approach is the following statement from the USA Federal government: “Healthcare providers are required to report to VAERS the following adverse events after COVID-19 vaccination [33] and other adverse events if later revised by FDA” [96,102,103]. “Serious AEs regardless of causality.”, including death [3,95].

If there had been full compliance with this requirement in VAERS, then the VAERS-reported deaths would have equaled the sum of1)

actual expected deaths (based on past statistics)2)

actual deaths over and above expected deaths that could be attributed to the COVID-19 inoculations.

Based on this requirement, we will generate a rough estimate (in the simplest form possible) of the number of deaths that would have occurred in the 65+ demographic if there had been no COVID-19 “pandemic”. Then, we will relate this number to the number of deaths reported to VAERS following COVID-19 inoculations in the 65+demographic. This would provide a “floor” for estimating the fraction of actual deaths reported to VAERS. This will be followed by parameterizing potential deaths attributable to the COVID-19 inoculations and displaying the effects on ratio of reported deaths to actual deaths. We will perform a global analysis and a local analysis, to see whether major or minor differences occur. The local analysis (Section A1-a2) may be somewhat easier to comprehend than the global analysis, but both come to similar conclusions.

A1-a Deaths Following COVID-19 Inoculations Reported to VAERS Compared to Expected Deaths

A1-a . Problems with VAERS

Before we discuss numbers of adverse events reported by VAERS, we need to identify potential shortcomings of, and problems with, VAERS, so these numbers of adverse events can be understood in their proper context. As stated previously, VAERS is a passive surveillance system managed jointly by the CDC and FDA, and historically has been shown to report about 1% of actual vaccine/inoculation adverse events (confirmed by the first principles analysis that follows in this appendix). There is no evidence that even the 1% reported have been selected randomly.

Some of this gross underreporting of adverse events reflects a major conflict-of-interest of CDC with respect to VAERS. CDC provides funding for administration of many vaccines, including the COVID-19 inoculations. Prior to COVID-19, the CDC provided about five billion dollars annually to the Vaccines for Children Program alone [102].

For COVID-19, the CDC has received many billions of dollars in supplemental funding for myriad activities, including vaccine distribution. It is difficult to separate out the CDC funding available for vaccine distribution from other CDC COVID-19 related activities, but one budget item (of many) should illustrate the magnitude of the effort: “Coronavirus Response and Relief Supplemental Appropriations Act, 2021 (P.L. 116–260): P.L. 116–260 provided $8.75 billion to CDC to plan, prepare for, promote, distribute, administer, monitor, and track coronavirus vaccines to ensure broad-based distribution, access, and vaccine coverage.” [3]. Low reporting rates of actual adverse events in VAERS should not be surprising, since the same organization that receives multi-billions of dollars in funding annually for promoting and administering vaccines also has responsibility for monitoring the safety of these products (whose liability has been waived).

In addition, the 1% reporting rates came from a thirty-day tracking study [22], and therefore are strictly applicable to very near-term adverse events. For mid-term and especially long-term events, the reporting rates would be much lower, since the links between inoculation and adverse events would be less obvious. That doesn’t mean these non-very-short-term adverse events don’t exist; it just means they haven’t been tracked. Absence of evidence is not evidence of absence. Thus, the VAERS numbers should be viewed as a very low “floor’ of the numbers and types of adverse events from COVID-19 inoculations that exist in the real-world.

A1-a2 Global analysis

We used 2019 death statistics from CDC to start the analysis. According to search results from CDC Wonder [104] obtained 11 June 2021, there were 2,117,332 deaths from all causes for people aged 65+ in the United States in 2019. Assuming uniformity throughout the year, there would have been ˜882,000 deaths occurring the first five months of the year, and that number will be used as the expected deaths for the first five months of 2021. From the same source, the population estimate is ˜54,000,000 for the 65+ age range. From CDC COVID-19 data tracker, the number of people 65+ vaccinated with at least one dose is ˜44,000,000 [24]

For those who were inoculated somewhere in the time frame 1 January 2021 to 31 May 2021, the number who would have been expected to die in the period from inoculation to 31 May will be a function of the duration of this period. For example, if all 44,000,000 people had been fully inoculated on 1 January 2021, then the number expected to die post-inoculation from non-COVID-19 inoculation causes would be simply (44,000,000/54,000,000) x 882,000, or ˜723,000 deaths. Conversely, if all 44,000,000 people had been fully inoculated on 31 May 2021, then the number expected to die post-inoculation from non-COVID-19 inoculation causes would be extremely small [24].

For an accurate estimation of the number expected to die post-inoculation from non-COVID-19 causes, one would need to integrate the time between inoculation and 31 May over the inoculation temporal distribution function. For present purposes, we will do a very rough approximation by modeling the inoculation distribution function as a delta function occurring at a mean temporal location. In other words, we compress all inoculations an individual receives into one, identify the mean temporal location from the actual inoculation distribution function, and compute the expected deaths based on the distance from 31 May to the temporal mean point.

From a graph of inoculation trends in the CDC data tracker [101] the distribution appears to be non-symmetrical pyramidal, rising to a peak in mid-April. This is slightly over the 2/3 point in the five-month range of interest. We will approximate the mean time point as 2/3 of the distance.

Table A1 displays the mean time normalized to the five-month study window vs potential deaths from COVID-19 inoculation (not expected from prior census data) normalized to the deaths expected from prior census data. Each cell represents the percent of deaths reported in VAERS following inoculation relative to total deaths (number of deaths expected from prior census data plus number of deaths following COVID-19 inoculation not contained in the expected death group). The model on which the table is based is as follows: there are two classes of deaths for the period following COVID-19 inoculation. One is the deaths expected from prior census data, and the other is deaths attributable mainly to COVID-19 inoculation. There would be potentially substantial overlap between the two in this age group (and perhaps other age groups as well). We assume that we can tag those individuals who would be expected to die based on prior census data. The remaining deaths attributable to COVID-19 inoculation not contained within the tagged group are classified as potential COVID deaths in Table A1.

Table A1. Expected deaths from non-COVID-19 causes for inoculees (Thousands).

Potential covid deaths/#
non-covid expected
Mean time location/five months
0%REP1/3%REP1/2%REP2/3%REP1%REP
07230.54820.743620.982421.474.7775
.510850.337230.55430.663630.987.1450
114460.259640.377240.494840.749.5137

Consider the cell (2/3,0). The mean time is about mid-April 2021 and the only deaths occurring are those expected (some may have died because of the inoculation, but they were sufficiently ill that they would have died during that period without the inoculation). There were 723,000 expected deaths and ˜3560 reported, yielding a ratio of deaths reported in VAERS to actual deaths of ½%.

Consider the cell (1/2,1). The mean time would have been about mid-March 2021 and the inoculation distribution would have resembled an isosceles triangle. The total deaths occurring are those expected and an equal number whose deaths were attributed to COVID-19 inoculation but did not overlap with those in the tagged expected group (there still could have been some/many in the latter group that may have died because of the inoculation, but they were sufficiently ill that they would have died during that period without the inoculation). There were 724,000 total deaths that occurred during that period and ˜3560 reported, yielding a ratio of deaths reported in VAERS to actual deaths of ½%. [3]

So, according to Table A1, focusing on the parameter most closely reflecting the actual inoculation distribution (2/3), the reporting percentages of actual to total are about 1%. This mirrors the Harvard Pilgrim study results (referenced in our vaccine safety study) which were obtained through an entirely different empirical approach [4]. At least for deaths reporting, there appears to be an approximately two order of magnitude difference between actual and reported deaths in VAERS.

Table A1 used two parameters to examine a broad spectrum of possible results, the mean time and the number of deaths solely attributable to COVID-19 inoculation. The mean time parameter was fairly well known and constrained in interpretation, because it was based on an empirical inoculation distribution function. The number of deaths solely attributable to COVID-19 inoculation is completely unknown.

As will be shown in the next section, the numbers of deaths reported in VAERS are strongly related to the inoculation date by clustering, but those who died might also have been those who would have died anyway because they were expected to die. There were probably some of each in that group reported. But we have no idea of the total number whose death could be directly attributed to COVID-19 inoculation and who were not in the group expected to die. For all we know, there could have been ten million people in that group, and only an extremely small fraction of that total group was reported in VAERS.

Suppose, for example, that the actual number of deaths reported in VAERS came from two groups: 90 % were from the inoculation-attributable death group and 10 % were from the expected death group. Assume there is no overlap between the two groups. In that case, what VAERS shows is not that 1% of actual expected deaths were reported, but rather that 1/10 of one percent of the expected deaths were reported. If that metric is used as the standard to scale up to total deaths, then the number in the actual inoculation-attributable death group is not 100 times the VAERS reported deaths, but rather 1000 times the VAERS-reported deaths! The point is we can’t “reverse-engineer” the reported VAERS death numbers to get the actual inoculation-attributable deaths because it depends on the unknown contribution of each of the two groups (expected deaths and inoculation-attributable deaths) to the VAERS reported deaths, and we can’t separate those out.

All this analysis shows is that, at best, only about 1% of the number expected to die was reported, and because the number reported in VAERS included deaths from both groups, the fraction from each actual group of deaths could not be determined. Realistically, we may have to wait until mid-2022, when the 2021 total deaths for each age group are finalized, to ascertain whether we can see increases in all-cause mortality that could have come from the inoculation-attributable deaths.

A1-a3 Local Analysis

Another way of estimating VAERS reporting efficiency is to perform a local analysis, focused on clustering about date of COVID-19 inoculation. For the 65+demographic, the post-inoculation deaths cluster near the vaccination date, providing evidence of a strong link to the inoculation.

Following the approach in the first section of this appendix, we calculate the deaths expected in any ten-day period based on 2019 pre-COVID-19 death statistics. For the inoculated group, the number of deaths expected for any ten-day period are (2,117, 332 deaths/per year) x (44,000,000/54,000,000 fraction of population in age range inoculated) x (10/365 fraction of year), or ˜47,270 deaths.

˜BEST-CASE SCENARIO
Consider the ten days following inoculation (including day of inoculation). Approximately 2,000 deaths were reported in VAERS. Assume hypothetically that all these deaths were in the expected category; this can be viewed as a best-case scenario. In this ˜best-case scenario, where the concentration of deaths is the highest and is normalized to the expected number of non-COVID-19 inoculation deaths (excluding deaths due solely to COVID-19 inoculation), 2,000/47,270 % of actual deaths (inoculation-related or not), or 4.23%, are reported in VAERS. Thus, at best, VAERS is underreporting by a factor of ˜20.

Suppose in that ten-day interval there had been 10,000 deaths that could be directly attributed to COVID-19 inoculation in addition to the expected deaths. This would have given a ratio of 2,000/57,270 actual total deaths, or 3.5 % reported in VAERS. This latter approach requires less assumptions than the former approach, but still yields results of only a few percent actual deaths reported in VAERS.

The Harvard Pilgrim electronic tracking study of post-vaccination events reported to VAERS performed in 2010 [4] showed a 1 % reporting rate for a thirty-day period. In the present case, ˜2900 post-inoculation deaths were reported to VAERS within thirty days of inoculation, or ˜82 % of total deaths for the 65+demographic. Substituting thirty days for ten in the above computation yields 141,810 expected non-COVID-19 post-inoculation deaths for the thirty-day period, or 2% that are reported in VAERS. The Harvard study used an electronic system that automatically tracked every event that occurred, no matter how small. Because of the effort (time and cost) required to submit event reports to VAERS, we suspect that only the more serious events, such as death, would be reported, and even in this case, the numbers reported are miniscule.

We also did an analysis for sixty days post-inoculation. In the present case, ˜3300 post-inoculation deaths were reported to VAERS within sixty days of inoculation, or ˜93 % of total deaths for the 65+demographic. Substituting sixty days for ten in the above computation yields 283620 expected non-COVID-19 post-inoculation deaths for the thirty-day period, or 1.2 % that are reported in VAERS. Remember, this normalization is based only on expected deaths. If 100,000 deaths attributable mainly to the COVID-19 inoculation beyond those that overlapped with the expected group occurred during this period, then the denominator would have to be increased by 100,000, yielding a VAERS reporting rate of 0.86 %.

Thus, both the global and local analyses, and the Harvard Pilgrim empirical analysis, are converging on the same two orders-of-magnitude difference between the actual number of deaths that occurred in the USA and those reported in VAERS. Depending on how many people have really died as a result of the COVID-19 inoculation, this reporting rate could well be a fraction of a percent!

A1-a3a Local Clustering Analysis

We end this appendix with one more example from the local analysis. Some background perspective is required. In the buildup to the pandemic (putting aside the issue of high false positives from PCR tests run at high numbers of amplification cycles), almost anyone who died with COVID-19 was assumed to have died from COVID-19, irrespective of the number of potentially lethal comorbidities they had. The CDC admitted later that about 94 % of the deaths attributed to COVID-19 would ordinarily have been attributed to one of the comorbidities.

For this example, we adopt a similar philosophy for the COVID-19 inoculations. People in the 65+ demographic who have died following inoculation are divided into two groups: those who died from the inoculation and those who died as expected based on pre-COVID-19 death data. The two groups range from being entirely separate to completely overlapping. We will examine two cases: entirely separate and completely overlapping.

How are the members of each group determined? The death from inoculation group consists of those whose deaths cluster significantly around the date of inoculation. The deaths expected group are the number who would have died in the absence of COVID-19. We allow for overlap, where each person who died can be double-valued (a member of both groups), but not double-counted.

To obtain a relatively precise estimate of expected deaths, we would want to select a region of time where the distribution function has substantially leveled off. From Fig. A1, the thirty-sixty-day range appears reasonable. However, there is a time issue here. Given the lag time in data reported by VAERS, most of the data in this range will probably have come from inoculations in January and February, and early-mid March, approximately 35 percent of the total inoculations. Therefore, we could multiply the thirty-sixty-day average number of deaths by ˜3 to obtain ˜40 expected deaths per day. An even simpler way to estimate the expected deaths reported in VAERS is to use the 15−30-day average shown, which will represent most of the range. This value is ˜37, which is close to the ˜40 obtained with the above approximation. This analysis should be re-run in three-four months, when more of the long-range data has been filled in.

Fig. A1

Table A2 shows the results of our analysis. As stated previously, two separate cases were analyzed: completely separate groups and completely overlapping groups. Two values of daily expected deaths were used: the 37 as described above, and 20 to account for potentially lower expected death reporting when the VAERS data has filled in more completely.

Thus, based on the deaths reported in VAERS following COVID-19 inoculation, and assuming the inoculation-related deaths are reported in the same ratio as expected deaths, the actual number of deaths strongly related to the COVID-19 inoculation should be scaled up by factors of 100−200. For the broadest definition of VAERS coverage provided by CDC Wonder, which includes the USA and all territories, protectorates, and possessions, the total deaths following COVID-19 were ˜5200 in early June 2021. Using our scaling factors, this translates into somewhere between one-half million and one-million deaths, and this has not taken into account the lag times associated with entering data into VAERS. Compared with the ˜28,000 deaths the CDC stated were due to COVID-19 and not associated morbidities for the 65+ age range, the inoculation-based deaths are an order-of-magnitude greater than the COVID-19 deaths! It should be remembered these are only the very-short-term inoculation-based deaths, and could increase dramatically if mid- and long-term adverse effects come to fruition.

We end this appendix with an even more unsettling possibility. The main assumption upon which the results in Table A2 were based is that the post-inoculation temporal distribution function shown in Fig. A1 could be divided into two regions. The strongly varying region originating from the inoculation date reflected deaths from the inoculation, and the essentially flat region that followed reflected expected deaths (that flat region also started at the inoculation date, and formed the base on which the highly varying region is positioned). This model excludes the possibility that deaths from the inoculation extend well beyond the limits of the highly varying region.

Table A2. Actual COVID-19 inoculation-based deaths.

Actual COVID-19 inoculation-based deaths from vaers reporting
Separate GroupsOverlapping Groups
Expected Deaths Reported37203720
Range Of Days Inoculation Deaths0−300−300−300−30
Total Reported Deaths Over Range2901290129012901
Total Expected Deaths Over Range11476201147620
Inoculation-Based Deaths Reported1754228129012901
Expected Deaths Reported/Total Expected.0077.0041.0077.0041
Total Actual Inoculation-Based Deaths Using Expected Ratio (Above)227792556341376753707561

We know in general this is not true. There can be lag effects such as ADE in the Fall viral season, and longer-term effects such as autoimmune diseases. We postulate that there are other effects from the inoculation that could result in the same flat death profile as that for expected deaths.

Consider the following. Some of the damage we have seen following the inoculations in VAERS includes coagulation/clotting effects and neurological effects of all types [63]. If these effects are not lethal initially, they raise the level of dysfunction. Thus, platelet aggregation has increased to a new base level, and micro-clots have raised the probability of serious clots forming from other lifestyle factors [105]. Death of specific neurons can increase the risk of Alzheimer’s disease or Parkinson’s disease, and can accelerate the onset of these and many other diseases. Thus, the adverse impacts of the COVID-19 inoculations could be viewed as raising the level of expected deaths in the future. Any deaths of this nature reported in VAERS would need to be viewed as inoculation-driven, and the expected deaths used in the computations would be reduced accordingly.

Consider Table A3 below. The “expected deaths reported” have been reduced below their counterparts in Table A2 to illustrate parametrically how the total inoculation-based deaths would change from VAERS reporting if this baseline effect is operable. While Table A2 used values of 37 and 20 for expected deaths, Table A3 uses values of 10 and 15.

Table A3. Possible COVID-19 inoculation-based deaths.

Possible COVID-19 inoculation-based deaths from vaers reporting
Separate GroupsOverlapping Groups
Expected Deaths Reported10151015
Range Of Days Inoculation Deaths0−300−300−300−30
Total Reported Deaths Over Range2901290129012901
Total Expected Deaths Over Range310465310465
Inoculation-Based Deaths Reported2591243629012901
Expected Deaths Reported/Total Expected.0021.0031.0021.0031
Total Actual Inoculation-Based Deaths Using Expected Ratio (Above)12338107858061381429935806

Thus, if the baseline of the host for coagulation/clotting, inflammation, hypoxia, neurodegeneration, etc., has been raised by the inoculations, translating into an increase in expected deaths and accelerated deaths, then it is entirely plausible that the VAERS death numbers reflect over a million deaths from COVID-19 inoculations so far. These are very short-term-effects only, and time will tell whether the large potential waves of ADE-driven deaths and autoimmune-driven deaths come to pass.

Appendix B

DETAILED ANALYSIS OF MAJOR COVID-19 INOCULANT CLINICAL TRIALS

A2-a Clinical Trials in the Mainly Adult Population

Definitions

Efficacy is the degree to which a vaccine prevents disease, and possibly also transmission, under ideal and controlled circumstances – comparing a vaccinated group with a placebo group [106].

Effectiveness refers to how well a vaccine performs in the real world [107]

Relative Risk (RR) is computed by dividing the percentage of patients that contracted disease in the vaccine arm by the percentage of patients that contracted disease in the placebo arm.

Relative Risk Reduction (RRR) is computed by subtracting the RR from 1.

Absolute Risk Reduction (ARR) is computed by subtracting the percentage that contracted disease in the vaccine arm from the percentage that contracted disease in the placebo arm.

Absolute Risk = probability = incidence.

Cumulative Incidence represents the number of new cases in a period of time / population at risk.

Incidence Density is the number of new cases of a given disease during a given period in specified population; also, the rate at which new events occur in a defined population.

Immunogenicity is the ability of a molecule or substance to provoke an immune response or the strength or magnitude of an immune response. It can be a positive (wanted) or negative (unwanted) effect, depending on the context.

Immune Response is an integrated systemic response to an antigen (Ag), especially one mediated by lymphocytes and involving recognition of Ags by specific antibodies (Abs) or previously sensitized lymphocytes [108]

Safety data for Pfizer and Moderna trials:

There were two major COVID-19 inoculant clinical trials: Pfizer/BioNTech and Moderna.

The Pfizer clinical trials were titled officially “a phase 1/2/3, placebo-controlled, randomized, observer-blind, dose-finding study to evaluate the safety, tolerability, immunogenicity, and efficacy of sars-cov-2 rna vaccine candidates against covid-19 in healthy individuals” [98]. The “Actual Study Start Date” was 29 April 2020, the “Estimated Primary Completion Date” was 2 November 2020, and the “Estimated Study Completion Date” is 2 May 2023. Thus, the mass inoculation rollout so far has been conducted in parallel with the Pfizer Phase III Clinical Trial. For all practical purposes, the mass global inoculation of the Pfizer inoculant recipients can be considered Phase III 2.0 of the Clinical Trials! The inclusion criteria for the official Phase III Clinical Trials incorporated (as stated in the title and in the protocol document) healthy individuals, while the criteria for mass inoculation went well beyond healthy individuals. In essence, we have an official Phase III Clinical Trial with ˜43,000+ healthy individuals, and an unofficial Phase III Clinical Trial with billions of individuals covering a wide spectrum of health levels [98].

The Pfizer Phase III trials were initiated July 2020, the efficacy data were submitted to the FDA for EUA approval in November 2020, and FDA approval was granted in December 2020. Six deaths occurred in the Pfizer trial, two in the inoculated group and four in the placebo group (which received saline) [33]. The two inoculated, both over the age of 55, died of cardiovascular causes. One died three days after inoculation and the other died 62 days after inoculation [109]. These two deaths were comparable (in frequency and cause) to placebo group deaths and perhaps more importantly, similar to the general population at that age. In the case of Moderna, there were 13 deaths, six in the inoculated group, seven in the placebo group (normal saline placebo, a mixture of sodium chloride in water 0.90 % w/v) at 21–57 days after the inoculation ([103]b).

In a report by the Norwegian National Medicines Association, published on 15 January 2021, there were 23 elderly people (all over the age of 75 and frail) in nursing homes, who died at various intervals from the time of inoculation with mRNA inoculant The report then suggested that, following the assessment, 13 of the 23 deaths would have been a direct result of the side effects of inoculation. It is possible that the other 10 deaths were post-inoculation, but not directly related to side effects, so not necessarily related to the inoculant itself [109].

It is no surprise that frail elderly people can be fatally destabilized by adverse reactions associated with post-inoculation inflammation, which in a young adult would have been considered minor. It is also no surprise that frail elderly people with comorbidities can be fatally destabilized from COVID-19 infection, which in a young adult or child would have been considered minor. A frail elderly person can be fatally destabilized by a simple coughing fit! This does not mean that these deaths are not events that need to be taken very seriously; on the contrary, if confirmed, they should guide inoculation policies in this category of patients from now on. Specifically, each case should be carefully assessed and an inoculation decision made based on the risk-benefit ratio [110].

In light of these data, the question may arise as to why there were no inoculant-attributed deaths in clinical testing of inoculants. The answer is that neither Pfizer nor Moderna included frail patients and included only a small number of very elderly patients – those over 75 accounted for 4.4 % of the total tested for Pfizer and 4.1 % for Moderna. While they could not in fact determine a causal relationship between inoculation and death, they also could not rule out that the inoculations had accelerated the deterioration of the condition of those patients [33].

Effectiveness data

As defined previously, the effectiveness of a vaccine lies in its ability to prevent a particular disease. If designed, tested, and administered correctly, authorized vaccines are effective in preventing disease and protecting the population. Like medicines, vaccines are not 100 % effective in all vaccinated people. Their effectiveness in a person depends on several factors. These include: age; other possible diseases or conditions; time elapsed since vaccination; previous contact with the disease.

To be declared safe and effective, a vaccine against COVID-19 infection must pass a series of tests and must meet regulatory standards, like any other vaccine or drug approved on the pharmaceutical market [111].

Regarding Pfizer and Moderna trials: The first important note is that maximum efficiency does not come immediately, because the immune response needs time.

In the case of Pfizer, the chance of developing COVID-19 becoming virtually the same between the inoculated and placebo groups increases up to 12 days after the first inoculation, then gradually decreases for those inoculated. The inoculum efficiency between the first and second doses is 52 % [106], but it is unclear what long-term protection a single dose provides. After the second dose, the effectiveness rises to 91 % and only beyond 7 days after the second dose is 95 % reached. However, the ARR for the latter case is only 0.7 % [112]. In other words, within 12 days after the first dose we can get COVID-19 as if we had not been inoculated. Another important aspect is that we still do not know if the Pfizer inoculant prevents severe cases. Seven days after the second dose, there were four severe cases of COVID-19, one in the inoculated group and three in the placebo group, which is far too low for us to make a statistical assessment. There are as yet no data on the inoculant’s ability to prevent community transmission. Realistically, the effectiveness of the inoculant in preventing asymptomatic cases has not been tested.

For Moderna, the effectiveness is only 50 % in the first 14 days after the first dose and reaches a maximum of 92.1 % on the edge of the second dose (ARR of 1.1 %, which is 28 days, not 21 as in the case of Pfizer) [46]. Moderna also did not test the long-term efficacy of a single dose. Then, 14 days after the second dose, the effectiveness rises to 94.1 %, with the amendment being an average. Thus, in people over 65 it was 86.4 %, compared to 95.6 % in the 18–65 age range ([103]). It is a minor difference from Pfizer, which declares equal efficiency in all age groups. An important observation is the statement by Moderna that their inoculant prevents severe cases, but only more than 14 days after both doses [126]. All 30 severe cases were in the placebo group, suggesting 100 % efficacy. After a single dose, there were two severe cases among those inoculated and four in the placebo group [33]. Last, but not least, unlike Pfizer, Moderna tested the presence of asymptomatic infection by RT-PCR before the second dose: there were 39 asymptomatic cases in the placebo group and 15 in the inoculated group. It is difficult to draw definitive conclusions due to the small number of cases. These data suggest that the inoculant reduces, but does not prevent, asymptomatic transmission [126].

A2-b Ongoing Clinical Trials in the Pediatric Population

In a recent Phase III study performed in the pediatric population, Comirnaty (Pfizer) was tested on a group of 2,260 children, aged 12–15, years who had no previous clinical signs of SARS-CoV-2 infection. They were divided into two groups, one placebo (978 children) and the other with Comirnaty (1005 children). In the Comirnaty group, of the 1005 children in whom the serum was administered, none developed COVID-19 disease, compared with the placebo group in which 16 children in 978 had clinical signs of the disease. The Pfizer study showed that the children’s immune response was comparable to the immune response in the 16–25 age group (measured by the level of antibodies against SARS-CoV-2). It could be concluded that in this study, Comirnaty was 100 % effective in preventing SARS-CoV-2 infection, although the actual rate could be between 75 % and 100 %. [63]. The results will be evaluated by the FDA and EMA.

The predictive value (for mass inoculation results) of the Comirnaty trial for the children aged 12–15 years is questionable. There were 1005 children who were inoculated with Comirnaty. Using the rule of three in statistics, where to obtain a predictive result of 1/x with high confidence (e.g., 1 in a thousand), 3x participants are required for the test sample. For the Comirnaty test sample of 1005, an adverse event of about 1/340 could be detected with high confidence.

What does this mean in the real world? In the USA, there are approximately 4,000,000 children in each age year for adolescents. Thus, there are ˜16,000,000 children in the 12–15 age band. A serious adverse event, including death, that occurred at a 1/800 rate would not be detectable with high confidence in a sample of 1005 people. Thus, the results of the trials for 1005 children would allow for 20,000 children to suffer a non-trial-detected serious adverse event, including death, when extrapolated to potential inoculation of all children in the 12–15 age group! Given that the risk of contracting COVID-19 with serious outcomes is negligible in this population, proceeding with mass inoculation of children 12–15 years old based on the trials that were conducted cannot be justified on any cost-benefit ratio findings.

Also, the evaluation of efficacy in children aged 6 months to 11 years has recently begun and continues [24]. Pfizer began enrolling children under 12 to evaluate the COVID-19 mRNA inoculant. Also, Comirnaty will be evaluated in a new clinical trial for children aged 6 months to 11 years. In the first phase, the study will enroll 144 people and will identify the required dose for 3 age groups (6 months – 2 years, 2–5 years and 5–11 years). After a 6-month follow-up period, the parents/guardians of children in the placebo group will have the option of allowing their children to receive the inoculation. The results are expected in the second half of 2021.

Moderna also began a study to evaluate the mRNA inoculation in children aged 6 months to 12 years. Both companies have already started testing vaccines in 14-year-olds. In the US, children make up 23 % of the population [113].

Data on the risks and benefits of possible inoculation in children and adolescents are currently insufficient and no recommendation can be made. Specifically, mass child inoculations cannot be recommended until the benefits and minimal projected risks have been demonstrated in a sufficiently large trial to provide confidence that mass inoculation will have an acceptable level of adverse effects relative to the demonstrated benefits. On the other hand, children often experience COVID-19 asymptomatically, and the SARS-CoV-2 infection progresses harmlessly. Currently, in the context of limited inoculation capacities, there is no indication of urgent inoculation of children. In the context of declining incidences of SARS-CoV-2 infections and demonstrated low serious adverse effects from COVID-19 infections for children and adolescents, the issue of inoculating children and adolescents is no longer paramount. Authorized forums must calculate what prevails for children and adolescents: the benefits or risks.

A2-c Clinical Trial Issues for Other Categories

Although people with severe comorbidities such as obesity or oncological conditions were not initially included in the clinical trials that led to obtaining EUA, they were included in subsequent studies, some even ongoing. In their case, it seems that the efficacy was lower compared to the results obtained initially with healthy adults.

The interim analysis of data from a prospective observational study indicates the need to prioritize cancer patients for timely (respectively 21-day) booster administration in the case of administration against COVID-19 with Comirnaty. According to the study, the effectiveness of a single dose of Comirnaty among cancer patients is low, but the immunogenicity of patients with solid cancers increased at 2 weeks after receiving the second dose of inoculant 21 days after the first dose. Because the study was conducted in the UK, participants inoculated before December 29, 2020 received two doses of Comirnaty 21 days apart, and those who started the regimen after this date were scheduled to receive a second dose of Comirnaty 12 weeks apart. first administration. Thus, the study continues to collect data from participants receiving Comirnaty 12 weeks after the first dose.

Approximately 21 days after a single dose of Comirnaty, the proportion of study participants who tested positive for anti-S IgG antibodies was [114]:

94 % among healthy participants;

38 % among patients with solid cancers;

18 % among patients with hematological cancers.

Among participants who received the 21-day booster and for whom biological samples were available two weeks after the second dose, the following proportions of confirmation as seropositive for anti-S IgG antibodies were reported [114].

100 % of healthy participants, compared to 86 % of the same group of participants who did not receive the second dose;

95 % of patients with solid cancers, compared with 30 % of the same group of participants who did not receive the second dose;

60 % of patients with hematological cancers, compared with 11 % of the same group of participants who did not receive the second dose.

Two other studies suggest low immunogenicity in the context of Comirnaty administration in patients with hematological cancers. In one study, patients with chronic lymphocytic leukemia (CLL) had significantly reduced immune response rates to COVID-19 inoculation compared to healthy participants of the same age. Considerable variations in post-administration immune response have been reported among patients with CLL depending on their stage of treatment

The effectiveness of Comirnaty administration was also evaluated in elderly patients with multiple myeloma [115]. 21 days after administration of the first dose of Comirnaty inoculation (before receiving the second dose), 20.5 % of patients with multiple myeloma compared to 32.5 % of control participants had neutralizing antibodies against SARS-CoV-2. One possible explanation could be that the therapy negatively affects the production of antibodies. However, the administration of the second dose is important for the development of the immune response in these patients [115].

Preliminary data from the v-safe surveillance system, the v-safe pregnancy registry and the Vaccine Adverse Event Reporting System (VAERS) do not indicate obvious safety signals regarding pregnancy or the associated neonatal implications with mRNA injections against COVID-19 in the third trimester of pregnancy [3]. The study included 35,691 pregnant women [116]. Compared to non-pregnant women, pregnant women reported more frequent pain at the injection site as an adverse event associated with mRNA COVID-19 vaccination, and headache, myalgia, chills, and fever were reported less frequently. In the context where initial clinical trials of messenger RNA-based inoculants have not evaluated the efficacy and safety of innovative technology among pregnant women, these preliminary data from the third trimester only help to inform both pregnant women and health professionals in making the inoculation decision. However, continuous monitoring through large-scale longitudinal studies remains necessary to investigate the effects associated with maternal anti-COVID-19 inoculation on mothers, pregnancies, the neonatal period and childhood.

On the other hand, the inoculation landscape has become even more complex due to new circulating viral variants. Authorities recommend genomic surveillance and adaptation in order to be effective against new variants (different from the initial strain that was detected at the end of 2019). The efficacy data of Comirnaty against circulating viral variants are highlighted in a very recent study in Israel which showed that the protection offered by the Pfizer inoculant against variant B.1.351 (first identified in South Africa) is lower [112].

The results have not yet been submitted to the expertise of specialists. The study compared nearly 400 adults who were diagnosed with COVID-19 at least 14 days after receiving one or two doses of the inoculant to the same number of uninoculated people. It was found that B.1.351 represents approximately 1 % of the COVID-19 cases studied. But among patients who received two doses of inoculant, the prevalence rate of the variant was eight times higher than in those not inoculated – 5.4 % compared to 0.7 %. This suggests that Comirnaty is less effective against variant B.1.351, compared to the original variant and variant B.1.1.7. The limitation of the study comes from the small number of adult people studied, but it is an alarm signal for a closer study of these cases. In addition, it seems that at present, the prevalence of this variant is low. On the other hand, in early April, Pfizer announced that according to the results of the Phase III study in the adult population, Comirnaty also demonstrated 100 % efficacy in the prevention of Covid-19 disease caused by SARS-CoV-2 variant B.1.351 (9 cases of Covid-19 were recorded, all in the placebo group, and after sequencing it was found that 6 had been determined by B.1.351) [117].

Appendix C

MID- AND LONG-TERM ADVERSE EFFECTS FROM PRIOR VACCINES

A 2020 study emphasizing mid- and long-term adverse effects from prior vaccines [4] identified the following sixteen mid- and longer-term potential issues concerning vaccines. These include:

3.1. Antibody-Dependent Enhancement (where enhanced virus entry and replication in a number of cell types is enabled by antibodies);

-1a. Intrinsic Antibody-Dependent Enhancement (where non-neutralizing antibodies raised by natural infection with one virus may enhance infection with a different virus);

-1b. Immune Enhancement (enhancement of secondary infections via immune interactions);

-1c. Cross-Reactivity (an antibody raised against one specific antigen has a competing high affinity toward a different antigen.);

-1d. Cross-Infection Enhancement (infection enhancement of one virus by antibodies from another virus);

3. 2. Vaccine-Associated Virus Interference (where vaccinated individuals may be at increased risk for other respiratory viruses because they do not receive the non-specific immunity associated with natural infection);

3. Vaccine-Associated Imprinting Reduction (where vaccinations could also reduce the benefits of ‘imprinting’, a protection conferred upon children who experienced infection at an early age)

4. Non-Specific Vaccine Effects on Immune System (where previous infections can alter an individual’s susceptibility to unrelated diseases);

5. Impact of Infection Route on Immune System (where immune protection can be influenced by the route of exposure/delivery);

6. Impact of Combinations of Toxic Stimuli (where people are exposed over their lifetime to myriad toxic stimuli that may impact the influence of any vaccine);

7. Antigenic Distance Hypothesis (negative interference from prior season’s influenza vaccine (v1) on the current season’s vaccine (v2) protection may occur when the antigenic distance is small between v1 and v2 (v1 ≈ v2) but large between v1 and the current epidemic (e) strain (v1 ≠ e).);

8. Bystander Activation (activation of T cells specific for an antigen X during an immune response against antigen Y);

9. Gut Microbiota (Impact of gut microbial composition on vaccine response);

10. Homologous Challenge Infection Enhancement (the strain of challenge virus used in the testing assay is very closely related to the seed virus strain used to produce the vaccine that a subject received);

11. Immune Evasion (evasion of host response to viral infection);

12. Immune Interference (interference from circulating antibody to the vaccine virus);

­12a. Original Antigenic Sin (propensity of the body’s immune system to preferentially utilize immunological memory based on a previous infection when a second slightly different version of that foreign entity (e.g. a virus or bacterium) is encountered.);

13. Prior Influenza Infection/Vaccination (effects of prior influenza infection/vaccination on severity of future disease symptoms);

14. Timing between Viral Exposures (elapsed time between viral exposures);

15. Vaccine-Associated Enhanced Respiratory Disease (where vaccination enhances respiratory disease); and

16. Chronic Immune Activation (continuous innate immune responses).

Most of these events are not predictable, and most, if not all, would be possible for the COVID-19 inoculant in the mid- and long-term for adults and children.

3.3. Mid- and Long-Term Serious Illnesses for Adults and Children from Past Vaccines

As stated in the aforementioned 2020 study on vaccine safety: “The biomedical literature is very sparse with studies on long-term vaccine effects, especially long-term adverse effects. Large numbers of people and long periods of time are required to identify such adverse events, and draw statistically-valid connections between vaccinations and disease. These efforts would be very resource-intensive, and there appears to be little motivation among the vaccine producers and regulators to make these resources available for such studies. Thus, the following examples reflect the extremely small tip of an extremely large iceberg of long-term adverse vaccine effects.” [4]

“The two main categories of diseases reported in the biomedical literature triggered by past vaccinations are “Autoimmune (e.g., Systemic Lupus Erythematosus, Psoriasis, Arthritis, Multiple Sclerosis, Hepatitis, UveitisPseudolymphoma, Guillain-Barre Syndrome, Thrombocytopenic Purpura, etc.) and Neurological (e.g., Central Demyelinating Diseases, Developmental Disability, Febrile seizuresNarcolepsyEncephalomyelitisAutonomic Dysfunction, etc.). Others include Diabetes, Gastrointestinal, Joint-related, Necrobiotic GranulomaNeutropeniaPulmonary Fibrosis, etc.”

“Vaccinations may also contribute to the mosaic of autoimmunity [118]. Infrequently reported post-vaccination autoimmune diseases include systemic lupus erythematosus, rheumatoid arthritisinflammatory myopathies, multiple sclerosis, Guillain-Barre syndrome, and vasculitis”.

“Studies have demonstrated a latency period of years between HiB vaccination and diabetes mellitus, and between HBV vaccination and demyelinating events [118] latency periods can range from days to years for postinfection and postvaccination autoimmunity”.

“Most of the extra cases of IDDM appeared in statistically significant clusters that occurred in periods starting approximately 38 months after immunization and lasting approximately 6–8 months. Immunization with pediatric vaccines increased the risk of insulin diabetes in NOD mice.Exposure to HiB immunization is associated with an increased risk of IDDM.” [4]

Thus, even the sparse past vaccine studies that went beyond the short-term showed latency effects of serious diseases occurring three years or more post-vaccination.

Appendix D

COST-BENEFIT ANALYSIS OF COVID-19 INOCULATIONS

This appendix presents a non-traditional best-case scenario pseudo-cost-benefit analysis of the COVID-19 inoculations for the 65+ demographic in the USA. In this incarnation of a cost-benefit analysis, the costs are the number of deaths resulting from the inoculations, and the benefits are the lives saved by the inoculations. The time range used was from December 2019 to end-of-May 2021.

It is assumed, in this best-case scenario, that all the deaths truly attributable to COVID-19 only could have been eliminated by the inoculations given (about half the USA population has been inoculated at this time) [88,119]. It can be conceptualized as the vaccines having been available in Summer 2019, and subsequent administration having eliminated all the deaths experienced that were truly attributable to COVID-19. If the cost-benefit ratio is poor for this best-case scenario, it will be very poor for any real-world scenario [120].

We will use Fig. 1Fig. 2 as starting points to conduct a cost-benefit analysis of COVID-19 inoculations for the most vulnerable demographic, those 65 + . We start with the official government numbers for COVID-19 and post-inoculation deaths, and modify them to arrive at actual deaths resulting from COVID-19 and the inoculations. We compare the two numbers (appropriately normalized) to ascertain costs vs benefits .

As Fig. 1 shows, there are three age bands that comprise the 65+ demographic. We weight the COVID-19 deaths per capita in each band by the band’s population, and divide the sum of these three products by the total 65+ population to arrive at an average COVID-19 deaths per capita of 0.0087 for the total 65+ demographic.

Fig. 2 contains two normalizations. First, the deaths were normalized by total inoculations given, not by people inoculated or people who had completed the full series of inoculations. We will retain the normalization by total inoculations given, since it will provide the most conservative results (largest denominator) for estimation purposes. Second, the deaths were normalized/restricted to those occurring within seven days post-inoculation. This normalization was done to compare across age bands, where the inoculations started at very different points in time. For the present cost-benefit purpose, where we are concentrating on the 65+ band, we remove this latter normalization, and include all post-inoculation deaths. Removing this normalization increases deaths per inoculation by about 40 % to a value of 0.000032, and offers a more credible comparison to the numbers from Fig. 1.

Thus, based on the CDC’s official numbers, there are an average COVID-19 deaths per capita of 0.0087 and an average deaths per inoculation of 0.000032 for the 65+ demographic. The chances of a person 65+ dying from an inoculation relative to their chances of dying from COVID-19 are approximately 0.0037, or about 1/270, based on these official CDC figures.

However, as we have shown previously, three corrections to these numbers are required to convert them to real-world effects. First, as the Harvard Pilgrim study has shown and as our results in Appendix 1 confirm, VAERS is underreporting actual deaths by about two orders of magnitude. Applying this correction alone to the above 1/270 ratio changes the risk benefit to about 1/3., Second, as the CDC has stated, approximately 94 % of the COVID-19 deaths could have been attributed to any of the comorbidities these patients had, and only 6% of the deaths could actually be attributed to COVID-19. As we pointed out, if pre-clinical comorbidities had been included, this number of 6% would probably be decreased further. For conservative purposes, we will remain with the 6%. Applying this correction to the 1/3 risk-benefit ratio changes it to 5/1! Third, as a comprehensive survey of false positives from RT-PCR tests concluded: “evidence from external quality assessments and real-world data indicate enough a high enough false positive rate to make positive results highly unreliable over a broad range of scenarios” [127]. Because of the myriad RT-PCR tests performed in the USA to screen for/diagnose COVID-19 using different values for Ct and different procedures, a specific number for false positives cannot be obtained at this point in time. Again, these false positives would reduce the 6% number, perhaps substantially. And again, for conservative purposes, we will remain with the 6% number.

Thus, our extremely conservative estimate for risk-benefit ratio is about 5/1. In plain English, people in the 65+ demographic are five times as likely to die from the inoculation as from COVID-19 under the most favorable assumptions! This demographic is the most vulnerable to adverse effects from COVID-19. As the age demographics go below about 35 years old, the chances of death from COVID-19 become very small, and when they go below 18, become negligible.

It should be remembered that the deaths from the inoculations shown in VAERS are short-term only (˜six months for those inoculated initially), and for children, extremely short-term (˜one month) [3]. Intermediate and long-term deaths remain to be identified, and are possible from ADE, autoimmune effects, further clotting and vascular diseases, etc., that take time to develop. Thus, the long-term cost-benefit ratio under the best-case scenario could well be on the order of 10/1, 20/1, or more for all the demographics, increasing with decreasing age, and an order-of-magnitude higher under real-world scenarios! In summary, the value of these COVID-19 inoculations is not obvious from a cost-benefit perspective for the most vulnerable age demographic, and is not obvious from any perspective for the least vulnerable age demographic.

Appendix Da

PROBLEMS WITH TEST CRITERIA FOR DETERMINING COVID-19

Consider the criteria for determining whether an RT-PCR test result is positive for SARS-CoV-2. The CDC instruction (until 1 May 2021) specifies running the RT-PCR tests for 45 amplification cycles. Then, to interpret the data: when all controls exhibit the expected performance, a specimen is considered positive for SARS-CoV-2 if all SARS-CoV-2 marker (N1, N2) cycle threshold growth curves cross the threshold line within 40.00 cycles (< 40.00 Ct). The RNase P may or may not be positive as described above, but the SARS-CoV-2 result is still valid ([103]a).

Many false positives are possible in the upper part of this cycle threshold range, especially in areas of low prevalence. In particular, virus culture has been found to be unfeasible in cases with a Ct value exceeding 33. A prospective cohort study involving the first 100 COVID-19 patients in Singapore also showed that attempts to culture the virus failed in all PCR-positive samples with a Ct value >30” [121]. During mass testing in Germany, it was found “that more than half of individuals with positive PCR test results are unlikely to have been infectious” [122]. Another study found that tests with low specificity (deriving from use of many cycles) cannot provide strong evidence for the presence of an infection [123]. A systematic review of PCR testing concluded “Complete live viruses are necessary for transmission, not the fragments identified by PCR. Prospective routine testing of reference and culture specimens and their relationship to symptoms, signs and patient co-factors should be used to define the reliability of PCR for assessing infectious potential. Those with high cycle threshold are unlikely to have infectious potential.” [89].

As skeptics have argued, in the buildup of the pandemic, the rapid increase in numbers of COVID-19 cases was due in part to the high values of cycle threshold used in the tests. Unfortunately, the true numbers of false positives will probably be unobtainable if an audit were performed, since these values are not reported with the test results: all currently-available nucleic acid tests for SARS-CoV-2 are FDA-authorized as qualitative tests, and Ct values from qualitative tests should never be used to direct or inform patient management decisions. Therefore, it is not good for laboratories to include Ct values on patient reports [124].

After mass inoculations started, a large number of “breakthrough” cases emerged, and a total of 10,262 SARS-CoV-2 vaccine breakthrough infections had been reported from 46 U.S. states and territories as of April 30, 2021 [18]; the number of reported COVID-19 vaccine breakthrough cases is likely a substantial undercount of all SARS-CoV-2 infections among fully vaccinated persons. The national surveillance system relies on passive and voluntary reporting, and data might not be complete or representative. Many persons with vaccine breakthrough infections, especially those who are asymptomatic or who experience mild illness, might not seek testing [18].

This negative outcome of increased “breakthrough” cases motivated the CDC to change a number of reporting and test procedures and issue new regulations for identifying and investigating hospitalized or fatal vaccine breakthrough cases starting 1 May 2021, stating: “For cases with a known RT-PCR cycle threshold (Ct) value, submit only specimens with Ct value ≤28 to CDC for sequencing. (Sequencing is not feasible with higher Ct values.)”. Thus, the Ct values for sequencing were lowered from the high false positive range allowed during the pandemic buildup to a limit that would eliminate many of these false positives in the ‘breakthrough case’ identification phase [101].

References

[1]D. Calina, T. Hartung, I. Mardare, M. Mitroi, K. Poulas, A. Tsatsakis, I. Rogoveanu, A.O. DoceaCOVID-19 pandemic and alcohol consumption: impacts and interconnections Toxicol. Rep., 8 (2021), pp. 529-535ArticleDownload PDFView Record in ScopusGoogle Scholar[2] Coronavirus (COVID-19) Vaccinations. https://ourworldindata.org/covid-vaccinations [Accessed 2021].Google Scholar[3]CDC

Vaccine Adverse Event Reporting System (VAERS)[Online]. Available: Vaccine Adverse Event Reporting System (VAERS) [Accessed 2021](2021)Google Scholar[4] R.N. Kostoff,  D. Kanduc,  A.L. Porter, Y. Shoenfeld, D. Calina, M.B. Briggs, D.A. Spandidos, A. Tsatsakis

Vaccine- and natural infection-induced mechanisms that could modulate vaccine safetyToxicol. Rep., 7 (2020), pp. 1448-1458ArticleDownload PDFView Record in ScopusGoogle Scholar[5]CORNELL

Definitions Relating to Taxable Vaccines[Online]. Available: https://www.law.cornell.edu/uscode/text/26/4132#a_2 [Accessed 4.06.2021](2021) Google Scholar[6] D.E. Martin

The Fauci/COVID-19 Dossier[Online]. Available: https://f.hubspotusercontent10.net/hubfs/8079569/The%20FauciCOVID-19%20Dossier.pdf [Accessed July 12, 2021](2021)Google Scholar[7] H. Levine

When Will Babies and Children Get the COVID-19 Vaccine?[Online]. Available:  https://www.whattoexpect.com/news/first-year/covid19-vaccine-babies-children [Accessed 12 June 2021](2021)Google Scholar[8 ]A.O. Docea,  A. Tsatsakis,  D. Albulescu,  O. Cristea,  O. Zlatian,  M. Vinceti, S.A. Moschos, D. Tsoukalas, M. Goumenou, N. Drakoulis, J.M. Dumanov, V.A. Tutelyan, G.G. Onischenko, M. Aschner, D.A. Spandidos, D. Calina

A new threat from an old enemy: Re‑emergence of coronavirus (Review)Int. J. Mol. Med., 45 (2020), pp. 1631-1643 View PDFView Record in ScopusGoogle Scholar[9] A.L. Arsene,  I.B. Dumitrescu,  C.M. Dragoi, D.I. Udeanu, D. Lupuliasa, V. Jinga, D. Draganescu, C.E. Dinu-Pirvu,  G. Dragomiroiu,  I.E. Blejan,  R.E. Moisi,  A.C. Nicolae,  H. Moldovan,  D.E. Popa,  B.S. Velescu, S. Ruta

A new era for the therapeutic management of the ongoing COVID-19 pandemicFarmacia, 68 (2020), pp. 185-196 View PDFCrossRefView Record in ScopusGoogle Scholar[10] M. Goumenou,  D. Sarigiannis,  A. Tsatsakis, O. Anesti, A.O. Docea, D. Petrakis, D. Tsoukalas, R. Kostoff, V. Rakitskii, D.A. Spandidos, M. Aschner, D. Calina

COVID‑19 in Northern Italy: an integrative overview of factors possibly influencing the sharp increase of the outbreak (Review)Mol. Med. Rep., 22 (2020), pp. 20-32 View PDFView Record in ScopusGoogle Scholar[11]M.T. Islam, M. Hossen, Z. Kamaz, A. Zali, M. Kumar, A.O. Docea, A.L. Arsene, D. Calina, J. Sharifi-Rad

The role of HMGB1 in the immune response to SARS-COV-2 infection: From pathogenesis towards A new potential therapeutic targetFarmacia, 69 (2021), pp. 621-634View Record in ScopusGoogle Scholar[12]P. Sidiropoulou, A.O. Docea, V. Nikolaou, M.S. Katsarou, D.A. Spandidos, A. Tsatsakis, D. Calina, N. Drakoulis

Unraveling the roles of vitamin D status and melanin during COVID-19 (Review)Int. J. Mol. Med., 47 (2021), pp. 92-100 View PDFView Record in ScopusGoogle Scholar[13] K. Farsalinos,  K. Poulas, D. Kouretas, A. Vantarakis, M. Leotsinidis, D. Kouvelas, A.O. Docea, R. Kostoff, G.T. Gerotziafas, M.N. Antoniou, R. Polosa, A. Barbouni, V. Yiakoumaki, T.V. Giannouchos, P.G. Bagos, G. Lazopoulos, B.N. Izotov, V.A. Tutelyan, M. Aschner, T. Hartung, H.M. Wallace, F. Carvalho, J.L. Domingo, A. Tsatsakis

Improved strategies to counter the COVID-19 pandemic: lockdowns vs. Primary and community healthcareToxicol. Rep., 8 (2021), pp. 1-9 ArticleDownload PDFView Record in ScopusGoogle Scholar[14]A. Tsatsakis, D. Petrakis, T.K. Nikolouzakis, A.O. Docea, D. Calina, M. Vinceti, M. Goumenou, R.N. Kostoff, C. Mamoulakis, M. Aschner, A.F. Hernández

COVID-19, an opportunity to reevaluate the correlation between long-term effects of anthropogenic pollutants on viral epidemic/pandemic events and prevalenceFood Chem. Toxicol., 141 (2020), p. 111418ArticleDownload PDFView Record in ScopusGoogle Scholar[15] D. Calina,  C. Sarkar,  A.L. Arsene,  B. Salehi, A.O. Docea, M. Mondal, M.T. Islam, A. Zali, J. Sharifi-Rad

Recent advances, approaches and challenges in targeting pathways for potential COVID-19 vaccines developmentImmunol. Res., 68 (2020), pp. 315-324 View PDFCrossRefView Record in ScopusGoogle Scholar[16]M.T. Islam, C. Quispe, M. Martorell, A.O. Docea, B. Salehi, D. Calina, Ž. Reiner, J. Sharifi-Rad

Dietary supplements, vitamins and minerals as potential interventions against viruses: perspectives for COVID-19Int. J. Vitam. Nutr. Res. (2021), pp. 1-18Google Scholar[17]J. Sharifi-Rad, C.F. Rodrigues, Z. Stojanovic-Radic, M. Dimitrijevic, A. Aleksic, K. Neffe-Skocinska,  D. Zielinska, D. Kolozyn-Krajewska,  B. Salehi,  S.M. Prabu,  F. Schutz,  A.O. Docea,  N. Martins, D. Calina

Probiotics: versatile bioactive components in promoting human healthMedicina-Lithuania, 56 (2020), p. 30Google Scholar[18]CDC

COVID-19 Vaccine Breakthrough Case Investigation and Reporting[Online]. Available:  https://www.cdc.gov/vaccines/covid-19/health-departments/breakthrough-cases.html [Accessed 2021](2021)Google Scholar[19] M. Neagu,  D. Calina,  A.O. Docea,  C. Constantin,  T. Filippini,  M. Vinceti, N. Drakoulis, K. Poulas, T.K. Nikolouzakis, D.A. Spandidos, A. Tsatsakis

Back to basics in COVID-19: antigens and antibodies-completing the puzzleJ. Cell. Mol. Med., 25 (2021), pp. 4523-4533 View PDFCrossRefView Record in ScopusGoogle Scholar[20] A. Mandavilli

Your Coronavirus Test Is Positive. Maybe It Shouldn’t Be[Online]. Available: https://www.nytimes.com/2020/08/29/health/coronavirus-testing.html [Accessed 11 May 2021](2020)Google Scholar[21]J. Mercola

Asymptomatic ‘Casedemic’ Is a Perpetuation of Needless Fear[Online]. Available: https://articles.mercola.com/sites/articles/archive/2020/11/19/covid-testing-fraud-fuels-casedemic.aspx?eType=EmailBlastContent&eId=0b802463-f128-49db-83f8-ecb922534dc4 [Accessed 22 March 2021](2020)Google Scholar[22]v R.N. Kostoff,  M.B. Briggs,  A.L. Porter,  A.F. Hernández,  M. Abdollahi, M. Aschner, A. Tsatsaki

The role of toxic stimuli combinations in determining safe exposure limitsToxicol. Rep., 5 (2018), pp. 1169-1172ArticleDownload PDFView Record in ScopusGoogle Scholar[24]Weekly Updates by Select Demographic and Geographic Characteristics.  https://www.cdc.gov/nchs/nvss/vsrr/covid_weekly/index.htm?fbclid=IwAR3-wrg3tTKK5-9tOHPGAHWFVO3DfslkJ0KsDEPQpWmPbKtp6EsoVV2Qs1Q.Google Scholar[25] M. Torequl Islam, M. Nasiruddin, I.N. Khan, S.K. Mishra, E.Z.M. Kudrat, T. Alam Riaz, E.S.  Ali, M.S. Rahman,  M.S. Mubarak, M. Martorell, W.C. Cho, D. Calina, A.O. Docea, J. Sharifi-Rad

A perspective on emerging therapeutic interventions for COVID-19Front. Public Health, 8 (2020), p. 281 View PDFView Record in ScopusGoogle Scholar[26]H. Pott-Junior, M.M.B. Paoliello, A.D.Q.C. Miguel, A.F. Da Cunha, C.C. De Melo Freire, F.F. Neves, L.R. Da Silva De Avó, M.G. Roscani, S.D.S. Dos Santos, S.G.F. Chachá

Use of ivermectin in the treatment of Covid-19: a pilot trialToxicol. Rep., 8 (2021), pp. 505-510ArticleDownload PDFView Record in ScopusGoogle Scholar[27]D. Calina, A.O. Docea, D. Petrakis, A.M. Egorov, A.A. Ishmukhametov, A.G. Gabibov, M.I. Shtilman, R. Kostoff, F. Carvalho, M. Vinceti, D.A. Spandidos, A. Tsatsakis

Towards effective COVID‑19 vaccines: updates, perspectives and challenges (Review)Int. J. Mol. Med., 46 (2020), pp. 3-16 View PDFCrossRefView Record in ScopusGoogle Scholar[28]C. Sarkar, M. Mondal, M. Torequl Islam, M. Martorell, A.O. Docea, A. Maroyi, J. Sharifi-Rad, D. Calina

Potential therapeutic options for COVID-19: current status, challenges, and future perspectivesFront. Pharmacol., 11 (2020), p. 572870 View PDFView Record in ScopusGoogle Scholar[29]D. Calina, T. Hartung, A.O. Docea, D.A. Spandidos, A.M. Egorov, M.I. Shtilman, F. Carvalho, A. Tsatsakis

COVID-19 vaccines: ethical framework concerning human challenge studiesDaru, 28 (2020), pp. 807-812 View PDFCrossRefView Record in ScopusGoogle Scholar[30]D. Calina, A.F. Hernández, T. Hartung, A.M. Egorov, B.N. Izotov, T.K. Nikolouzakis, A. Tsatsakis, P.G. Vlachoyiannopoulos, A.O. Docea

Challenges and scientific prospects of the newest generation of mRNA-Based vaccines against SARS-CoV-2Life, 11 (2021), p. 907 View PDFCrossRefView Record in ScopusGoogle Scholar[31]A.F. Hernández, D. Calina, K. Poulas, A.O. Docea, A.M. Tsatsakis

Safety of COVID-19 vaccines administered in the EU: Should we be concerned?Toxicol. Rep., 8 (2021), pp. 871-879ArticleDownload PDFView Record in ScopusGoogle Scholar[32]C. Wang, X. Zhou, M. Wang, X. Chen

The impact of SARS-CoV-2 on the human immune system and microbiomeInfect. Microbes Dis., 3 (2020), pp. 14-21 View PDFCrossRefGoogle Scholar[33]FDA

Pfizer-BioNTech COVID-19 Vaccine[Online]. Available: https://www.fda.gov/emergency-preparedness-and-response/coronavirus-disease-2019-covid-19/pfizer-biontech-covid-19-vaccine [Accessed 19 June 2021](2021)Google Scholar[34] E.E. Walsh,  R.W. Frenck  Jr., A.R. Falsey,  N. Kitchin, J. Absalon, A. Gurtman, S. Lockhart, K. Neuzil, M.J. Mulligan, R. Bailey, K.A. Swanson, P. Li, K. Koury, W. Kalina, D. Cooper, C. Fontes-Garfias,  P.Y. Shi,  Ö. Türeci,  K.R. Tompkins,  K.E. Lyke, V. Raabe,  P.R. Dormitzer, K.U. Jansen, U. Şahin, W.C. Gruber

Safety and immunogenicity of two RNA-Based Covid-19 vaccine candidatesN. Engl. J. Med.,  383 (2020), pp. 2439-2450 View PDFCrossRefView Record in ScopusGoogle Scholar[35]R. Sahelian

Covid Vaccine Side Effects[Online]. Available:  https://www.raysahelian.com/covidvaccinesideeffects.html [Accessed 15 July 2021](2021)Google Scholar[36]S. Seneff, G. Nigh

Worse than the disease? Reviewing some possible unintended consequences of the mRNA vaccines against COVID-19Int. J. Vacc. Theory Practice Res., 2 (1) (2021), pp. 38-79View Record in ScopusGoogle Scholar[37]Y. Lei, J. Zhang, Schiavon Cr, M. He, L. Chen, H. Shen, Y. Zhang, Q. Yin, Y. Cho, L. Andrade, Shadel Gs, M. Hepokoski, T. Lei, H. Wang, J. Zhang, Yuan Jx, A. Malhotra, U. Manor, S. Wang, Yuan Zy, Shyy Jy

SARS-CoV-2 spike protein impairs endothelial function via downregulation of ACE 2Circ. Res., 128 (April (9)) (2021), pp. 1323-1326, 10.1161/CIRCRESAHA.121.318902 View PDFView Record in Scopus Google Scholar[38] G.J. Nuovo,  C. Magro,  T. Shaffer,  H. Awad,  D. Suster,  S. Mikhail,  B. He, J.J. Michaille, B. Liechty, E. Tili

Endothelial cell damage is the central part of COVID-19 and a mouse model induced by injection of the S1 subunit of the spike proteinAnn. Diagn. Pathol., 51 (2021), p. 151682ArticleDownload PDFView Record in ScopusGoogle Scholar[39]Y.J. Suzuki, S.G. Gychka

SARS-CoV-2 spike protein elicits cell signaling in human host cells: implications for possible consequences of COVID-19 vaccinesVaccines, 9 (2021), p. 36ArticleDownload PDFCrossRefView Record in ScopusGoogle Scholar[40] E. Avolio,  M. Gamez,  K. Gupta,  R. Foster,  I. Berger,  M. Caputo,  A. Davidson, D. Hill, P. Madeddu

The SARS-CoV-2 Spike Protein Disrupts the Cooperative Function of Human Cardiac Pericytes – Endothelial Cells Through CD147 Receptor-mediated Signalling: a Potential Non-infective Mechanism of COVID-19 Microvascular DiseasebioRxiv, 2020.12.21.423721(2020)Google Scholar[41]S. Ndeupen, Z. Qin, S. Jacobsen, H. Estanbouli, A. Bouteau, B.Z. Igyártó

The mRNA-LNP Platform’s Lipid Nanoparticle Component Used in Preclinical Vaccine Studies Is Highly InflammatorybioRxiv(2021)Google Scholar[42]P. Sellaturay, S. Nasser, S. Islam, P. Gurugama, P.W. Ewan

Polyethylene glycol (PEG) is a cause of anaphylaxis to the Pfizer/BioNTech mRNA COVID-19 vaccineClin. Exp. Allergy, 51 (2021), pp. 861-863 View PDFCrossRefView Record in ScopusGoogle Scholar[43]B.Z. Igyártó, S. Jacobsen, S. Ndeupen

Future considerations for the mRNA-lipid nanoparticle vaccine platformCurr. Opin. Virol., 48 (2021), pp. 65-72ArticleDownload PDFView Record in ScopusGoogle Scholar[44]O. Vera-Lastra, A. Ordinola Navarro, M.P. Cruz Domiguez, G. Medina, T.I. Sánchez Valadez, L.J. Jara

Two cases of graves’ disease following SARS-CoV-2 vaccination: an Autoimmune/Inflammatory syndrome induced by adjuvantsThyroid (2021)Google Scholar[45]B.G. İremli, S.N. Şendur, U. Ünlütürk

Three cases of subacute thyroiditis following SARS-CoV-2 vaccine: postvaccination ASIA syndromeJ. Clin. Endocrinol. Metab. (2021)Google Scholar[46]A.F. Ogata, C.A. Cheng, M. Desjardins, Y. Senussi, A.C. Sherman, M. Powell, L. Novack, S. Von, X. Li, L.R. Baden, D.R. Walt

Circulating SARS-CoV-2 vaccine antigen detected in the plasma of mRNA-1273 vaccine recipients Clin. Infect. Dis. (2021)Google Scholar[47] E.M. Rhea,  A.F. Logsdon,  K.M. Hansen,  L.M. Williams, M.J. Reed, K.K. Baumann, S.J. Holden, J. Raber, W.A. Banks, M.A. Erickson

The S1 protein of SARS-CoV-2 crosses the blood–brain barrier in miceNat. Neurosci., 24 (2021), pp. 368-378 View PDFCrossRefView Record in ScopusGoogle Scholar[48 ] T.P. Buzhdygan,  B.J. Deore, A.  Baldwin-Leclair,  T.A. Bullock,  H.M. Mcgary,  J.A. Khan,  R. Razmpour,  J.F. Hale,  P.A. Galie, R. Potula, A.M. Andrews, S.H. Ramirez

The SARS-CoV-2 spike protein alters barrier function in 2D static and 3D microfluidic in-vitro models of the human blood-brain barrierNeurobiol. Dis., 146 (2020), p. 105131ArticleDownload PDFView Record in ScopusGoogle Scholar[49]A. Vojdani, E. Vojdani, D. Kharrazian

Reaction of human monoclonal antibodies to SARS-CoV-2 proteins with tissue antigens: implications for autoimmune diseasesFront. Immunol., 11 (2020), Article 617089 View PDFView Record in ScopusGoogle Scholar[50]EMA

Signal Assessment Report on Embolic and Thrombotic Events (SMQ) With COVID-19 Vaccine (ChAdOx1-S [recombinant]) – Vaxzevria (previously COVID-19(2021)Google Scholar[51]P.R. Hunter

Thrombosis after covid-19 vaccinationBMJ, 373 (2021), p. n958 View PDFCrossRefView Record in ScopusGoogle Scholar[52]H.A. Merchant

CoViD vaccines and thrombotic events: EMA issued warning to patients and healthcare professionalsJ. Pharm. Policy Pract., 14 (2021), p. 32 View PDFView Record in ScopusGoogle Scholar[53]Pfizer

SARS-CoV-2 mRNA Vaccine (BNT162, PF-07302048)[Online]. Available: https://www.pmda.go.jp/drugs/2021/P20210212001/672212000_30300AMX00231_I100_1.pdf [Accessed](2021)Google Scholar[54]S.M. Moghimi

Allergic reactions and anaphylaxis to LNP-Based COVID-19 vaccinesMol. Ther., 29 (2021), pp. 898-900ArticleDownload PDFView Record in ScopusGoogle Scholar[55]E. Shepherd

Injection Technique 1: Administering Drugs via the Intramuscular Route[Online]. Available: https://www.nursingtimes.net/clinical-archive/assessment-skills/injection-technique-1-administering-drugs-via-the-intramuscular-route-23-07-2018/ [Accessed 12 March 2021](2018)Google Scholar[56] J.J. Polania Gutierrez, S. Munakomi

Intramuscular injectionStatPearls, StatPearls Publishing LLC, Treasure Island (FL) (2021)StatPearls Publishing Copyright © 2021Google Scholar[57] J.S. Suk,  Q. Xu,  N. Kim,  J. Hanes,  L.M. Ensign

PEGylation as a strategy for improving nanoparticle-based drug and gene deliveryAdv. Drug Deliv. Rev., 99 (2016), pp. 28-51ArticleDownload PDFGoogle Scholar[58]G. Vogel

Mixing vaccines may boost immune responsesScience, 372 (2021), p. 1138 View PDFCrossRefView Record in ScopusGoogle Scholar[59] J. Sharifi-Rad, C.F.  Rodrigues,  F. Sharopov,  A.O. Docea,  A.C. Karaca, M. Sharifi-Rad, D. Kahveci Karincaoglu,  G. Gulseren,  E. Senol,  E. Demircan,  Y. Taheri,  H.A.R. Suleria, B. Ozcelik, K.N. Kasapoglu, M. Gultekin-Ozguven, C. Daskaya-Dikmen,  W.C. Cho,  N. Martins, D. Calina

Diet, lifestyle and cardiovascular diseases: linking pathophysiology to cardioprotective effects of natural bioactive compoundsInt. J. Environ. Res. Public Health, 17 (2020), p. 31Google Scholar[60] M. Sharifi-Rad, N.V.A.  Kumar, P. Zucca,  E.M. Varoni,  L. Dini,  E. Panzarini,  J. Rajkovic,  P.V.T. Fokou,  E. Azzini, I. Peluso, A.P. Mishra, M. Nigam, Y. El Rayess, M. El Beyrouthy,  L. Polito, M. Iriti, N. Martins, M. Martorell, A.O. Docea, W.N. Setzer, D. Calina, W.C. Cho, J. Sharifi-Rad

Lifestyle, oxidative stress, and antioxidants: back and forth in the pathophysiology of chronic diseasesFront. Physiol., 11 (2020), p. 21Google Scholar[61] S. Kuipers,  S.C. Canneg ieter,  S. Middeldorp,  L. Robyn, H.R. Büller, F.R. Rosendaal

The absolute risk of venous thrombosis after air travel: a cohort study of 8,755 employees of international organisationsPLoS Med., 4 (2007)e290-e290Google Scholar[62] R. Yang,  Y. Deng,  B. Huang, L. Huang, A. Lin, Y. Li, W. Wang, J. Liu, S. Lu, Z. Zhan, Y. Wang, A, R, W. Wang,  P. Niu,  L. Zhao, S. Li, X. Ma, L. Zhang, Y. Zhang, W. Yao, X. Liang, J. Zhao, Z. Liu, X. Peng, H. Li, W. Tan

A core-shell structured COVID-19 mRNA vaccine with favorable biodistribution pattern and promising immunitySignal Transduct. Target. Ther., 6 (2021), p. 213 View PDFView Record in ScopusGoogle Scholar[63]Novel coronavirus (COVID-19) https://www.cdc.gov/budget/fact-sheets/covid-19/index.html.Google Scholar[64 ]C.C.E. Lee,  K. Ali, D. Connell,  I.R. Mordi,  J. George,  E.M. Lang, C.C. Lang

COVID-19-associated cardiovascular complicationsDiseases (2021), p. 9 View PDFCrossRefGoogle Scholar[65]C. Matucci-Cerinic, R. Caorsi, A. Consolaro, S. Rosina, A. Civino, A. Ravelli

Multisystem inflammatory syndrome in children: unique disease or part of the Kawasaki disease spectrum?Front. Pediatr. (2021), p. 9Google Scholar[66]N.A. Nakra, D.A. Blumberg, A. Herrera-Guerra, S. Lakshminrusimha

Multi-system inflammatory syndrome in children (MIS-C) following SARS-CoV-2 infection: review of clinical presentation, hypothetical pathogenesis, and proposed managementChildren (Basel, Switzerland), 7 (2020), p. 69 View PDFCrossRefView Record in ScopusGoogle Scholar[67]A.  Farooq,  F. Alam, A. Saeed, F. Butt, M.A. Khaliq, A. Malik, M. Chaudhry, M. Abdullah

Multisystem inflammatory syndrome in children and adolescents (MIS-C) under the setting of COVID-19: a review of clinical presentation, workup and managementInfect. Dis. (Auckl),  14 (2021) 11786337211026642 Google Scholar[68] T.P. Vogel,  K.A. Top,  C. Karatzios,  D.C. Hilmers,  L.I. Tapia, P. Moceri, L. Giovannini-Chami,  N. Wood,  R.E. Chandler,  N.P.  Klein,  E.P. Schlaudecker,  M.C. Poli, E. Muscal, F.M. Munoz

Multisystem inflammatory syndrome in children and adults (MIS-C/A): case definition & guidelines for data collection, analysis, and presentation of immunization safety dataVaccine, 39 (2021), pp. 3037-3049ArticleDownload PDFView Record in ScopusGoogle Scholar[69] R.K. Pilania,  S. Singh

Kawasaki Disease. Periodic and Non-Periodic Fevers(2019), pp. 45-63Google Scholar[70] R.P. Sundel, R.E. Petty

KAWASAKI DISEASE Textbook of Pediatric Rheumatology (2011), pp. 505-520ArticleDownload PDFView Record in ScopusGoogle Scholar[71]T.M. Nielsen, N.H. Andersen, C. Torp-Pedersen,  P. Søgaard,  K.H. Kragholm

Kawasaki disease, autoimmune disorders, and cancer: a register-based studyEur. J. Pediatr., 180 (2021), pp. 717-723 View PDFCrossRefView Record in ScopusGoogle Scholar[72]M.D. Hicar

Antibodies and immunity during Kawasaki diseaseFront. Cardiovasc. Med., 7 (2020), p. 94 View PDFView Record in ScopusGoogle Scholar[73]D. Kanduc, Y. Shoenfeld

Molecular mimicry between SARS-CoV-2 spike glycoprotein and mammalian proteomes: implications for the vaccineImmunol. Res., 68 (2020), pp. 310-313 View PDFCrossRefView Record in ScopusGoogle Scholar[74]K. Roe

Potential new treatments for Kawasaki disease, its variations, and multisystem inflammatory syndromeSN Comprehensive Clinical Medicine (2021), pp. 1-5View Record in ScopusGoogle Scholar[75]J. Kabeerdoss, R.K. Pilania, R. Karkhele, T.S. Kumar, D. Danda, S. Singh

Severe COVID-19, multisystem inflammatory syndrome in children, and Kawasaki disease: immunological mechanisms, clinical manifestations and managementRheumatol. Int., 41 (2021), pp. 19-32 View PDFCrossRefView Record in ScopusGoogle Scholar[76]Y. Wu, F.F. Liu, Y. Xu, J.J. Wang, S. Samadli, Y.F. Wu, H.H. Liu, W.X. Chen, H.H. Luo, D.D. Zhang, W. Wei, P. Hu

Interleukin-6 is prone to be a candidate biomarker for predicting incomplete and IVIG nonresponsive Kawasaki disease rather than coronary artery aneurysmClin. Exp. Med., 19 (2019), pp. 173-181 View PDFCrossRefView Record in ScopusGoogle Scholar[77]H. Chaudhary, J. Nameirakpam, R. Kumrah, V. Pandiarajan, D. Suri, A. Rawat, S. Singh

Biomarkers for Kawasaki disease: clinical utility and the challenges aheadFront. Pediatr. (2019), p. 7 View PDFCrossRefView Record in ScopusGoogle Scholar[78]K.J. Denby, D.E. Clark, L.W. Markham

Management of Kawasaki disease in adultsHeart, 103 (2017), pp. 1760-1769 View PDFCrossRefView Record in ScopusGoogle Scholar[79]ECDC

COVID-19 in Children and the Role of School Settings in Transmission – Second Update[Online]. Available: https://www.ecdc.europa.eu/sites/default/files/documents/COVID-19-in-children-and-the-role-of-school-settings-in-transmission-second-update.pdf [Accessed 10 July 2021](2021)Google Scholar[80]F. Busa, F. Bardanzellu, M.C. Pintus, V. Fanos, M.A. Marcialis

COVID-19 and school: to open or not to open, that is the question. the first review on current knowledgePediatr. Rep., 13 (2021), pp. 257-278 View PDFCrossRefView Record in ScopusGoogle Scholar[81]J. Jung, M.J. Hong, E.O. Kim, J. Lee, M.N. Kim, S.H. Kim

Investigation of a nosocomial outbreak of coronavirus disease 2019 in a paediatric ward in South Korea: successful control by early detection and extensive contact tracing with testingClin. Microbiol. Infect., 26 (2020), pp. 1574-1575ArticleDownload PDFView Record in ScopusGoogle Scholar[82]J. Lopez Bernal, N. Andrews,  C. Gower,  C. Robertson,  J. Stowe,  E. Tessier,  R. Simmons,  S. Cottrell, R. Roberts, M. O’doherty, K. Brown, C. Cameron, D. Stockton, J. Mcmenamin, M. Ramsay

Effectiveness of the Pfizer-BioNTech and Oxford-AstraZeneca vaccines on covid-19 related symptoms, hospital admissions, and mortality in older adults in England: test negative case-control studyBMJ (Clin. Res. Ed.), 373 (2021)n1088-n1088Google Scholar[83] T. Powell,  E. Bellin,  A.R. Ehrlich

Older adults and Covid-19: the most vulnerable, the hardest hitHastings Cent. Rep., 50 (2020), pp. 61-63  View PDFCrossRefView Record in ScopusGoogle Scholar[84] CDC Wonder  https://wonder.cdc.gov/controller/datarequest/D8;jsessionid=9B19C44D4E84BCEF41D794D1A6DF.Google Scholar[85] V. Stoner

The Deadly COVID-19 Vaccine Coverup[Online]. Available: https://www.virginiastoner.com/writing/2021/5/4/the-deadly-covid-19-vaccine-coverup [Accessed June 4th 2021](2021)Google Scholar[86]J. Rose

A report on the US Vaccine Adverse Events Reporting System (VAERS) of the COVID-19 messenger ribonucleic acid (mRNA) biologicalsSci. Publ. Health Pol. Law, 2 (2021), pp. 59-80View Record in ScopusGoogle Scholar[88]M.T. Islam, B. Salehi, O. Karampelas, J. Sharifi-Rad, A.O. Docea,  M. Martorell, D. Calina

HIGH SKIN MELANIN CONTENT, VITAMIN D DEFICIENCY AND IMMUNITY: POTENTIAL INTERFERENCE FOR SEVERITY OF COVID-19Farmacia, 68 (2020), pp. 970-983 View PDFCrossRefView Record in ScopusGoogle Scholar[89]T. Jefferson, E.A. Spencer, J. Brassey, C. Heneghan

Viral cultures for COVID-19 infectious potential assessment – a systematic reviewClin. Infect. Dis. (2020), 10.1093/cid/ciaa1764ciaa1764 View PDFGoogle Scholar[92]CDC

About The Vaccine Adverse Event Reporting System (VAERS)[Online]. Available:  https://wonder.cdc.gov/vaers.html [Accessed 12 April, 2021](2021)Google Scholar[93]CDC

COVID-19 Vaccine Safety Updates [Online]Available: https://www.cdc.gov/vaccines/acip/meetings/downloads/slides-2021-06/03-COVID-Shimabukuro-508.pdf [Accessed 2 July 2021](2021)Google Scholar[94]CDC

COVID-19 Vaccine Breakthrough Infections Reported to CDC — United States, January 1–April 30, 2021[Online]. Available: https://www.cdc.gov/mmwr/volumes/70/wr/mm7021e3.htm [Accessed May 29, 2021](2021)Google Scholar[95]CDC

COVID Data Tracker[Online]. Available: https://covid.cdc.gov/covid-data-tracker/#datatracker-home [Accessed](2021)Google Scholar[96]FDA

Vaccines and related biological products advisory committee December 102020 Meeting Announcement [Online] (2020)Available: https://www.fda.gov/advisory-committees/advisory-committee-calendar/vaccines-and-related-biological-products-advisory-committee-december-10-2020-meeting-announcementVaccines [Accessed 3.05.2021]Google Scholar[98]Clinicaltrials.Gov

Study to Describe the Safety, Tolerability, Immunogenicity, and Efficacy of RNA Vaccine Candidates Against COVID-19 in Healthy Individuals[Online]. Available:  https://clinicaltrials.gov/ct2/show/NCT04368728 [Accessed June 12, 2021](2021)Google Scholar[100]Eric Kowarz, L.K. Jenny Reis, Silvia Bracharz, Stefan Kochanek, Rolf Marschalek

Vaccine-Induced Covid-19 Mimicry” Syndrome: splice reactions within the SARS-CoV-2 Spike open reading frame result in Spike protein variants that may cause thromboembolic events in patients immunized with vector-based vaccinesResearch Square (2021), 10.21203/rs.3.rs-558954/v1 View PDFGoogle Scholar[101]CDC

Demographic Characteristics of People Receiving COVID-19 Vaccinations in the United States[Online]. Available: https://covid.cdc.gov/covid-data-tracker/#vaccination-demographic [Accessed July 11, 2021](2021)Google Scholar[102]CDC

Selected Adverse Events Reported After COVID-19 Vaccination[Online]. Available: https://www.cdc.gov/coronavirus/2019-ncov/vaccines/safety/adverse-events.html [Accessed 5.06.2021](2021)Google Scholar[103]FDA

CDC 2019-Novel Coronavirus (2019-nCoV) Real-Time RT-PCR Diagnostic Panel[Online]. Available: https://www.fda.gov/media/134922/download [Accessed 21 May 2021](2020)Google Scholar[104]CDC

Clinical Questions about COVID-19: Questions and Answers[Online]. Available: https://www.cdc.gov/coronavirus/2019-ncov/hcp/faq.html [Accessed 14.04.2021](2021)Google Scholar[105]V.V. Wojciechowski, D. Calina, K. Tsarouhas, A.V. Pivnik, A.A. Sergievich, V.V. Kodintsev, E.A. Filatova, E. Ozcagli, A.O. Docea, A.L. Arsene, E. Gofita, C. Tsitsimpikou, A.M. Tsatsakis, K.S. Golokhvast

A guide to acquired vitamin K coagulophathy diagnosis and treatment: the Russian perspectiveDaru, 25 (2017), p. 10 View PDFView Record in ScopusGoogle Scholar[106]F.P. Polack, S.J. Thomas, N. Kitchin, J. Absalon, A. Gurtman, S. Lockhart, J.L. Perez, G. Pérez Marc, E.D. Moreira,  C. Zerbini, R. Bailey,  K.A. Swanson,  S. Roychoudhury,  K. Koury,  P. Li, W.V. Kalina, D. Cooper, R.W. Frenck Jr., L.L. Hammitt, Ö. Türeci, H. Nell, A. Schaefer, S. Ünal, D.B. Tresnan, S. Mather, P.R. Dormitzer, U. Şahin, K.U. Jansen, W.C. Gruber

Safety and efficacy of the BNT162b2 mRNA Covid-19 vaccineN. Engl. J. Med., 383 (2020), pp. 2603-2615 View PDF CrossRefGoogle Scholar[107] S.H. Hodgson,  K. Mansatta,  G. Mallett,  V. Harris,  K.R.W. Emary,  A.J. Pollard

What defines an efficacious COVID-19 vaccine? A review of the challenges assessing the clinical efficacy of vaccines against SARS-CoV-2 Lancet Infect. Dis., 21 (2021), pp. e26-e35ArticleDownload PDFView Record in ScopusGoogle Scholar[108]C. Melenotte, A. Silvin, A.-G. Goubet,  I. Lahmar,  A. Dubuisson, A. Zumla, D. Raoult, M. Merad, B. Gachot, C. Hénon, E. Solary, M. Fontenay, F. André, M. Maeurer, G. Ippolito, M. Piacentini, F.-S. Wang,  F. Ginhoux,  A. Marabelle,  G. Kroemer,  L. Derosa,  L. Zitvoge

lImmune responses during COVID-19 infectionOncoimmunology, 9 (2020), p. 1807836 View PDFView Record in ScopusGoogle Scholar[109]E.M. Agency

Assessment Report COVID-19 Vaccine Moderna. Procedure No. EMEA/H/C/005791/0000[Online]. Available:(2021)https://www.ema.europa.eu/en/documents/assessment-report/covid-19-vaccine-moderna-Google Scholar[110]W.E. Beyer, J. Mcelhaney, D.J. Smith, A.S. Monto, J.S. Nguyen-Van-Tam, A.D. Osterhaus

Cochrane re-arranged: support for policies to vaccinate elderly people against influenzaVaccine, 31 (2013), pp. 6030-6033ArticleDownload PDFView Record in ScopusGoogle Scholar[111]S.P. Kaur, V. Gupta

COVID-19 vaccine: a comprehensive status reportVirus Res., 288 (2020), p. 198114ArticleDownload PDFGoogle Scholar[112] S.A. Madhi,  V. Baillie,  C.L. Cutland,  M. Voysey,  A.L. Koen,  L. Fairlie,  S.D. Padayachee, K. Dheda, S.L. Barnabas, Q.E. Bhorat, C. Briner, G. Kwatra, K. Ahmed, P. Aley, S. Bhikha, J.N. Bhiman,  A.E. Bhorat, J. Du Plessis,  A. Esmail,  M. Groenewald,  E. Horne,  S.H. Hwa,  A. Jose, T. Lambe, M. Laubscher, M. Malahleha, M. Masenya, M. Masilela, S. Mckenzie, K. Molapo, A. Moultrie, S. Oelofse, F. Patel, S. Pillay, S. Rhead, H. Rodel, L. Rossouw, C. Taoushanis, H. Tegally, A. Thombrayil, S. Van Eck, C.K. Wibmer, N.M. Durham, E.J. Kelly, T.L. Villafana, S. Gilbert, A.J. Pollard, T. De Oliveira, P.L. Moore, A. Sigal, A. Izu

Efficacy of the ChAdOx1 nCoV-19 Covid-19 vaccine against the B.1.351 variantN. Engl. J. Med., 384 (2021), pp. 1885-1898 View PDFCrossRefView Record in ScopusGoogle Scholar[113] A.T. Mccarty

Child poverty in the United States: a tale of devastation and the promise of hopeSociol. Compass, 10 (2016), pp. 623-639 View PDFCrossRefView Record in ScopusGoogle Scholar[114] L. Monin, A.G. Laing, M. Muñoz-Ruiz, D.R. Mckenzie, I. Del Molino Del Barrio, T. Alaguthurai,  C. Domingo-Vila, T.S. Hayday, C. Graham, J. Seow, S. Abdul-Jawad, S. Kamdar, E. Harvey-Jones, R. Graham,  J. Cooper, M. Khan, J. Vidler, H. Kakkassery, S. Sinha, R. Davis, L. Dupont, I. Francos Quijorna, C. O’brien-Gore, P.L. Lee, J. Eum, M. Conde Poole, M. Joseph,  D. Davies,  Y. Wu,  A. Swampillai, B.V. North, A. Montes, M. Harries, A. Rigg, J. Spicer, M.H. Malim, P. Fields, P. Patten, F. Di Rosa, S. Papa, T. Tree, K.J. Doores, A.C. Hayday, S. Irshad

Safety and immunogenicity of one versus two doses of the COVID-19 vaccine BNT162b2 for patients with cancer: interim analysis of a prospective observational studyLancet Oncol., 22 (2021), pp. 765-778ArticleDownload PDFView Record in ScopusGoogle Scholar[115]M. Gavriatopoulou, I. Ntanasis-Stathopoulos, E. Korompoki, E. Terpos, M.A. Dimopoulos

SARS-CoV-2 vaccines in patients with multiple myelomaHemaSphere, 5 (2021)e547-e547Google Scholar[116]T.T. Shimabukuro, S.Y. Kim, T.R. Myers, P.L. Moro, T. Oduyebo, L. Panagiotakopoulos, P.L. Marquez, C.K. Olson, R. Liu, K.T. Chang, S.R. Ellington, V.K. Burkel, A.N. Smoots, C.J. Green, C. Licata, B.C. Zhang, M. Alimchandani, A. Mba-Jonas, S.W. Martin, J.M. Gee, D.M. Meaney-Delman

Preliminary findings of mRNA Covid-19 vaccine safety in pregnant personsN. Engl. J. Med., 384 (2021), pp. 2273-2282 View PDFCrossRefView Record in ScopusGoogle Scholar[117]Y. Yan, Y. Pang, Z. Lyu, R. Wang, X. Wu, C. You, H. Zhao, S. Manickam, E. Lester, T. Wu, C.H. Pang

The COVID-19 vaccines: recent development, challenges and prospectsVaccines, 9 (2021), p. 349 View PDFCrossRefView Record in ScopusGoogle Scholar[118]M. Vadalà, D. Poddighe, C. Laurino, B. Palmieri

Vaccination and autoimmune diseases: is prevention of adverse health effects on the horizon?EPMA J., 8 (2017), pp. 295-311 View PDFCrossRefView Record in ScopusGoogle Scholar[119] M.S. Islam,  A.M. Kamal, A. Kabir, D.L. Southern, S.H. Khan, S.M.M. Hasan, T. Sarkar, S. Sharmin, S. Das, T. Roy, M.G.D. Harun, A.A. Chughtai, N. Homaira, H. Seale

COVID-19 vaccine rumors and conspiracy theories: the need for cognitive inoculation against misinformation to improve vaccine adherencePLoS One, 16 (2021), Article e0251605 View PDFCrossRefView Record in ScopusGoogle Scholar[120]M.S. Islam, T. Sarkar, S.H. Khan, A.H. Mostofa Kamal, S.M.M. Hasan, A. Kabir, D. Yeasmin, M.A. Islam, K.I. Amin Chowdhury, K.S. Anwar, A.A. Chughtai, H. Seale

COVID-19-Related infodemic and its impact on public health: a global social media analysisAm. J. Trop. Med. Hyg., 103 (2020), pp. 1621-1629 View PDFCrossRefView Record in ScopusGoogle Scholar[121] T.P. Velavan, C.G. MeyerCOVID-19: a PCR-defined pandemicInt. J. Infect. Dis.: IJID, 103 (2021), pp. 278-279ArticleDownload PDFView Record in ScopusGoogle Scholar[122] A. Stang,  J. Robers,  B. Schonert, K.H. Jöckel, A. Spelsberg, U. Keil, P. Cullen

The performance of the SARS-CoV-2 RT-PCR test as a tool for detecting SARS-CoV-2 infection in the populationJ. Infect., 83 (2021), pp. 237-279 ArticleDownload PDFView Record in ScopusGoogle Scholar[123]R.J. Klement, P.S. Bandyopadhyay

The epistemology of a positive SARS-CoV-2 testActa Biotheor. (2020), pp. 1-17View Record in ScopusG oogle Scholar[124]D. Romero-Alvarez, D. Garzon-Chavez, F. Espinosa,  E. Ligña,  E. Teran,  F. Mora, E. Espin, C. Albán, J.M. Galarza, J. Reyes

Cycle threshold values in the context of multiple RT-PCR testing for SARS-CoV-2Risk Manag. Healthc. Policy, 14 (2021), pp. 1311-1317 View PDFCrossRefView Record in ScopusGoogle Scholar[125] A. Asandei,  L. Mereuta, I. Schiopu, J. Park, C.H. Seo, Y. Park, et al.

Non-receptor-mediated lipid membrane permeabilization by the SARS-CoV-2 spike protein S1 subunitACS Appl. Mater. Interfaces, 12 (50) (2020), pp. 55649-55658 View PDFCrossRefView Record in ScopusGoogle Scholar[126]L.R. Baden, H.M. ElSahly, B. Essink, K. Kotloff, S. Frey, R. Novak, et al.

Efficacy and safety of the mRNA-1273 SARS-CoV-2 vaccineN. Engl. J. Med., 384 (5) (2021), pp. 403-416 View PDFCrossRefGoogle Scholar[127]A.N. Cohen, B. Kessel, M.G. MilgroomDiagnosing SARS-CoV-2 infection: the danger of over-reliance on positive test results (2021), 10.1101/2020.04.26.20080911

Gastrointestinal perforation secondary to COVID-19

Authors: Case reports and literature review Reem J. Al Argan, MBBS, SB-Med, SF-Endo, FACE, ECNU,Safi G. Alqatari, MBBS, MRCPI, MMedSc, CFP (Rheum), Abir H. Al Said, MBBS, SB-Med, CFP (Pulmo.), Raed M. Alsulaiman, MBBS, SB-Med, Abdulsalam Noor, MBBS, SB-Med, ArBIM, SF-Nephro, Lameyaa A. Al Sheekh, MD, SB-med, and Feda’a H. Al Beladi, MD

Introduction:

Corona virus disease-2019 (COVID-19) presents primarily with respiratory symptoms. However, extra respiratory manifestations are being frequently recognized including gastrointestinal involvement. The most common gastrointestinal symptoms are nausea, vomiting, diarrhea and abdominal pain. Gastrointestinal perforation in association with COVID-19 is rarely reported in the literature.

Patient concerns and diagnosis:

In this series, we are reporting 3 cases with different presentations of gastrointestinal perforation in the setting of COVID-19. Two patients were admitted with critical COVID-19 pneumonia, both required intensive care, intubation and mechanical ventilation. The first one was an elderly gentleman who had difficult weaning from mechanical ventilation and required tracheostomy. During his stay in intensive care unit, he developed Candidemia without clear source. After transfer to the ward, he developed lower gastrointestinal bleeding and found by imaging to have sealed perforated cecal mass with radiological signs of peritonitis. The second one was an obese young gentleman who was found incidentally to have air under diaphragm. Computed tomography showed severe pneumoperitoneum with cecal and gastric wall perforation. The third case was an elderly gentleman who presented with severe COVID-19 pneumonia along with symptoms and signs of acute abdomen who was confirmed by imaging to have sigmoid diverticulitis with perforation and abscess collection.

Interventions:

The first 2 cases were treated conservatively. The third one was treated surgically.

Outcome:

Our cases had a variable hospital course but fortunately all were discharged in a good clinical condition.

Conclusion:

Our aim from this series is to highlight this fatal complication to clinicians in order to enrich our understanding of this pandemic and as a result improve patients’ outcome.

Keywords: acute abdomen, acute diverticulitis, cecal mass, corona virus disease-2019, gastrointestinal perforation. 

Introduction

Corona virus disease-2019 (COVID-19) had been declared pandemic in March 2020.[1] It presents most commonly with fever in more than 80% of cases followed by respiratory symptoms which could progress to adult respiratory distress syndrome in critical cases.[2] However, extra respiratory manifestations are being frequently recognized in association with COVID-19.[3] The gastrointestinal (GI) manifestations have been reported in descriptive studies from China.[2] The most frequently reported GI symptoms are nausea, vomiting, diarrhoea, and abdominal pain.[2,4,5] However, it is rarely reported for COVID-19 to present with GI perforation. To the date of writing this report, there have been only 13 reported of GI perforation in association with COVID-19.

In this series, we are reporting 3 cases who developed GI perforation in association with COVID-19. The first 2 cases developed this fatal complication after presenting with critical COVID-19 pneumonia which required intensive care unit (ICU) admission and mechanical ventilation. The third case presented with severe COVID-19 pneumonia and was diagnosed to have GI perforation at the time of presentation. The first 2 cases were managed conservatively, and the third case was managed surgically. All of the 3 cases recovered and were discharged in good condition. We are reporting this series in order to highlight this rare but fatal complication of COVID-19. This will enhance awareness of clinicians to such complication where early diagnosis and management is crucial in order to improve the patients’ outcome.

2. Case reports

2.1. The patients provided informed consent for publication of their cases

2.1.1. First case

A 70-year old male patient known to have type 2 diabetes mellitus (T2DM), presented to our emergency department (ED) on 1st of June 2020 complaining of 3-day history of dry cough and fever. On examination: Vital signs were remarkable for tachypnea with respiratory rate (RR): 28/min and desaturation with oxygen saturation (O2 sat):81% on room air (RA) but maintained >94% on 15 litres of oxygen via a non-rebreather mask. Nasopharyngeal swab tested positive for SARS-CoV-2 polymerase chain reaction (PCR). Chest X-ray (CXR) showed bilateral lower lung fields air apace opacities (Fig. ​(Fig.1A)1A) consistent with COVID-19 pneumonia. Laboratory investigations were remarkable for high Lactate dehydrogenase (LDH), inflammatory markers, D-dimer and markedly elevated Ferritin (Table ​(Table1).1). He was started on Methylprednisolone 40 mg IV BID, Hydroxychloroquine, Ceftriaxone, Azithromycin, Oseltamivir, and Enoxaparin. After 5 days of hospital admission, he deteriorated and could not maintain saturation on non-rebreather mask, so he was shifted to ICU, intubated and mechanically ventilated. Ceftriaxone was upgraded to Meropenem in addition to same previous therapy. COVID-19 therapy was stopped after completing 10 days, but he was continued on steroids. Figure 1

The chest X-ray (CXR) of the 3 cases at the time of presentation. (A): CXR of the 1st case showing bilateral lower lung fields air apace opacities. (B): CXR of the 2nd case showing bilateral scattered air space consolidative patches throughout the lung fields predominantly over peripheral and basal lungs. (C): CXR of the 3rd case showing bilateral middle and lower zones peripheral ground glass opacities.

Table 1

The laboratory investigations of the 3 cases on presentation.

TestFirst caseSecond caseThird caseNormal range
Complete Blood Count
 White Blood cells6.44.25.7(4.0–11.0) K/uI
 Hemoglobin15.112.113.4(11.6–14.5) g/dL
 Platelets147232283(140–450) K/uI
Renal Profile
 Blood urea nitrogen101411(8.4–21) mg/dL
 Creatinine0.920.820.82(0.6–1.3) mg/dL
Liver Profile
 Total Bilirubin0.50.51.0(0.2–1.2) mg/dL
 Direct Bilirubin0.30.20.3(0.1–0.5) mg/dL
 Alanine Transferase (ALT)265241(7–55) U/L
 Aspartate transferase (AST)425052(5–34) U/L
 Alkaline phosphatase (ALP)745574(40–150) U/L
 Gamma-glutamyl transpeptidase (GGTP)532139(12–64) U/L
 Lactate dehydrogenase (LDH)434442617(81–234) U/L
Inflammatory Markers
 Erythrocyte Sedimentation rate (ESR)63101490–10 mm/h
 C-Reactive Protein (CRP)7.9218.3210.780–5 mg/dL
Others
 Ferritin1114.72565.86654.87(21.81–274.66) ng/mL
 D-Dimer0.60.411.66<=0.5 ug/mL

Open in a separate window

Multiple trials of weaning from mechanical ventilation failed. So, tracheostomy was carried out on 20th day of ICU admission and then he was successfully extubated. During his stay in ICU, urine analysis was persistently positive for urinary tract infection secondary to Candida Abican. So, he was started on Caspofungin. At that time, blood culture was negative. After 4 days of Caspofungin, urine analysis and culture became negative. On 32nd day of hospital admission, he was stable clinically, requiring 40% FiO2 through tracheostomy mask, so he was transferred to COVID-19 isolation ward. Meropenem was stopped after 20 days of treatment. Steroid was tapered after transfer to the ward till it was discontinued after 28 days of therapy.

After 14 days of treatment with Caspofungin, follow up C-reactive protein was persistently high. Thus, full septic workup was requested and revealed Candida Albican bacteremia. At that time, urine analysis and culture were negative, Caspofungin was continued for additional 14 days. However, Candidemia persisted, so he was shifted to Anidulafungin for another 14 days. Patient at that time did not have any GI symptoms or signs. For work up of Candidemia, echocardiogram could not be done due to the hospital policy of isolation rooms. Bed side ophthalmology examination was unremarkable.

On 44th day of hospital admission, he developed fresh bleeding per rectum. Hemodynamics were stable. The bleeding resulted in acute drop of 2 g/dL of hemoglobin over 24 hours. He denied abdominal pain, abdominal examination was negative for signs of peritonitis and per rectum examination was unremarkable. Therefore, computed tomography (CT) scan of the abdomen with contrast was carried out. It showed a well-defined mass within the posterior wall of the cecum measuring 3.1 × 3.2 cm associated with discontinuous enhancement and extra-luminal air foci suggestive of complicated perforated sealed cecal mass. This is in addition to radiological findings of peritonitis (Fig. ​(Fig.22A).Figure 2

The contrast enhanced computed tomography (CT) of the abdomen of the 3 cases. (A): CT scan abdomen of the 1st case (Coronal image) showing a well-defined rounded heterogeneous enhanced soft tissue mass lesion within the posterior wall of the cecum measuring (3.1 × 3.2 cm) in anteroposterior and transverse diameter associated with discontinuous enhancement of posterior cecum wall and extra-luminal air foci suggestive of complicated perforated sealed cecum mass. This is in addition to adjacent fat stranding with free fluid as well as enhancement of peritoneal reflection suggestive of peritonitis. (B &C): CT scan abdomen of the 2nd case (Axial & Coronal images). (2B): Axial image showing moderate to severe pneumoperitoneum with air seen more tracking along the ascending colon suggestive of a wall defect in the anterior aspect of the cecum. (2C): Coronal image showing a second defect in the stomach wall. (D): CT scan abdomen of the 3rd case (Coronal image) showing severe sigmoid diverticulosis with circumferential bowel wall thickening compatible with acute diverticulitis, small amount of free air compatible with bowel perforation likely arising from the sigmoid colon and a well-defined 3.3 × 1.5 cm abscess collection adjacent to the sigmoid colon.

In consideration of his stable clinical status, absent signs of peritonitis clinically and being a sealed perforation, he was managed conservatively. So, Meropenem was resumed and Clindamycin was started. 2 days later, bleeding stopped, and he stayed stable clinically without clinical signs of peritonitis. Feeding through nasogastric tube was introduced gradually as tolerated. Antibiotics were continued for a total of 8 days. Trial of weaning from oxygen was attempted gradually which he tolerated till he was maintained on RA. After closure of tracheostomy, on 70th day of hospital admission, the patient was discharged in a good condition with a plan of follow up of cecal mass progression. However, the patient did not follow up in outpatient clinics after discharge.

2.1.2. Second case

A 37-year old male patient, morbidly obese, negative past history, presented to our ED on 11th June 2020. He reported 3-day history of shortness of breath. Vital signs were remarkable for Temperature (Temp.): 38.5 C, pulse rate (PR): 111/min, RR: 30/min and O2 sat: 80% on RA. Laboratory investigations showed high LDH, inflammatory markers and Ferritin (Table ​(Table1).1). He had positive SARS-CoV-2 PCR and CXR showed bilateral air space consolidative patches scattered throughout the lung predominantly over peripheral and basal lungs (Fig. ​(Fig.1B).1B). He was admitted to COVID-19 isolation ward as a case of COVID-19 pneumonia and started on: Triple therapy in the form of: Interferon B1, Lopinavir/Ritonavir and Ribavirin, in addition to Hydroxychloroquine, Ceftriaxone, Azithromycin, Oseltamivir, Dexamethasone 6 mg IV OD and Enoxaparin.

On the 3rd day of admission, his condition deteriorated so, he was shifted to ICU and intubated because of respiratory failure. He was maintained on same treatment for COVID-19. On 2nd day postintubation, clinically he was vitally stable without active clinical GI signs but a routine follow-up CXR showed air under the diaphragm. Therefore, abdomen CT scan with contrast was carried out and showed moderate to severe pneumoperitoneum with air tracking along the ascending colon suggestive of wall defect at the cecum, in addition to another defect noted in the stomach wall (Fig. ​(Fig.2B2B & 2C). Ceftriaxone was upgraded to Piperacillin-Tazobactam and Caspofungin was added to cover for possibility of peritonitis. Again, the patient was managed conservatively, since he was asymptomatic. He remained vitally stable without signs of peritonitis. Enteral feeding was started gradually 3 days later and on the 10th day of hospital admission, he was extubated and shifted to COVID-19 isolation ward. COVID-19 therapy was continued for 12 days.

He tolerated feeding very well. Gradual weaning of oxygen supplementation was carried out till it was discontinued. After 14 days of antibiotics, a follow up CT scan of abdomen showed interval resolution of previously seen pneumoperitoneum. He was discharged on 30th day of hospitalization in a good condition.

2.1.3. Third case

A 74-year old male patient known case of T2DM presented to our ED on 17th July 2020. He gave 3-day history of dry cough, shortness of breath and generalized colicky abdominal pain. No other pulmonary or GI symptoms. He had negative past surgical history. Vital signs were remarkable for Temp: 38.4 C, PR: 105/min, RR: 22/min and O2 sat: 90% on RA, required 3 L/min O2 through nasal cannula. Chest examination was remarkable for reduced breath sound intensity bilaterally without added sounds. Abdomen was distended with generalized tenderness and guarding. Blood tests were remarkable for high LDH, inflammatory markers, Ferritin and D-dimer (Table ​(Table1).1). PCR for SARS-COV-2 was positive and CXR showed bilateral peripheral ground glass opacities at middle and lower lung lobes (Fig. ​(Fig.1C).1C). Due to the presence of abdominal pain along with signs of acute abdomen on examination, a CT scan of the abdomen was done. It showed severe sigmoid diverticulosis with radiological findings of acute diverticulitis, free air compatible with bowel perforation likely at the sigmoid colon with 3.3 cm adjacent abscess collection (Fig. ​(Fig.22D).

Therefore, the patient was started on Piperacillin-Tazobactam, Metronidazole in addition to COVID-19 therapy. He underwent emergency exploratory laparotomy. Intra-operatively, pus and fecal peritonitis along with perforation of 0.5 cm at the distal sigmoid colon were found. So, a Hartmann’s procedure was performed. Pathology result of resected sigmoid colon revealed diverticular disease with surrounding fibrosis, moderate mucosal inflammation with mixed acute and chronic inflammatory cells, negative for malignancy.

He had smooth postoperative course. Enteral feeding was started on 3rd day postoperation and he improved clinically. After a total of 10 days of hospitalization, supplemental oxygen and antibiotics were discontinued. He was discharged on 11th day of hospitalization in a good condition.

3. Discussion

The GI manifestations are the most frequently reported extra-pulmonary manifestations of COVID-19[2] with a prevalence of 10% to 50%.[4,5] The most commonly reported GI symptoms are nausea, vomiting, diarrhoea and abdominal pain.[2,4,5] However, there have been case reports of COVID-19 cases presenting with other GI manifestations. Those include acute surgical abdomen,[6] lower GI bleeding[7] and nonbiliary pancreatitis.[8] In fact, the GI manifestations could be the presenting symptoms of COVID-19 as was reported in a case report by Siegel et al where the patient presented with abdominal pain and upon abdominal imaging, the patient was found to have pulmonary manifestations of COVID-19 in the CT scan of the lung bases.[9]

GI perforation is a surgical emergency, carries a significant mortality rate that could reach up to 90% due to peritonitis especially if complicated by multiple organ failure.[10] It can be caused by many reasons. Those include foreign body perforation, extrinsic bowel obstruction like in cases of GI tumors, intrinsic bowel obstruction like in cases of diverticulitis/appendicitis, loss of GI wall integrity such as peptic ulcer and inflammatory bowel disease in addition to GI ischemia and infections.[11] Several infections have been reported to result in GI perforation like Clostridium difficile, Mycobacterium tuberculosis, Cytomegalovirus and others.[1214] COVID-19 have been rarely reported to result in GI perforation. Till the date of writing this report only 13 cases[1523] have been reported in the literature (Table ​(Table2).2). In addition, Meini et al reported a case of pneumatosis intestinalis in association with COVID-19 but without perforation.[25]

Table 2

Summary of the previously published cases of gastrointestinal perforation in association with COVID-19.

First Author [Reference]Age/ SexCo-morbid ConditionsPresenting symptomsSeverity of COVID-19 pneumoniaCOVID-19 TherapySymptoms prompted investigations for GI perforationSite of PerforationTiming of Perforation post admissionManagement of PerforationOutcome
1Gonzalvez Guardiola et al [15]66 Y/ MMetabolic syndromeNot mentionedCriticalMethylprednisoloneTocilizumab Hydroxychloroquine AzithromycinLopinavir/RitonavirAbdominal painIncreased WBC and CRP.CecumNot mentionedRight colectomyNot mentioned
2De Nardi et al [16]53 Y/MHypertension Supra-ventricular tachycardiaFeverCoughDyspneaCriticalAnakinra Lopinavir/Ritonavir Hydroxychloroquine + AntibioticsAbdominal pain Abdominal distentionSigns of PeritonitisCecum11th day of admissionRight colectomy & ileo-transverse anastomosisDischarged Home
3Kangas-Dick et al [17]74 Y/MNegativeFeverDyspneaDry coughCriticalHydroxychloroquine +AntibioticsIncreased Oxygen requirementMarkedly distended abdomenNot specified (CT scan: Not done)5th day of admissionConservativeDied
4Galvez et al [18]59 Y/MStatus post laparoscopic Roux-en-Y gastric bypass surgeryFeverDry coughMyalgiaHeadacheDyspneaModerateMethylprednisolone + COVID-19 protocol (Not specified)Acute abdominal painWorsening dyspneaGastro-jejunal anastomosis5th day of admissionLaparoscopy& Graham Patch RepairDischarged Home
5Poggiali et al [19]54 Y/ F§HypertensionFeverDry coughGERD symptomsSevereCOVID-19 therapy (Not specified) +AntibioticsAcute chest pain Painful abdomenDiaphragm StomachAt presentationSurgical RepairNot mentioned
6Corrêa Neto et al [20]80 Y/FHypertensionCoronary artery diseaseDry coughFeverDyspneaCriticalCOVID-19 therapy(Not specified) +AntibioticsDiffuse abdominal pain & stiffnessSigmoidAt PresentationLaparotomy with recto-sigmoidectomy & terminal colostomyDied
7Rojo et al [21]54 Y/FHypertensionObesityDyslipidemiaEpilepsyCough,MyalgiaCostal painCriticalHydroxychloroquine Lopinavir/Ritonavir MethylprednisoloneTocilizumabFeverHemodynamic instabilityAnemiaCecum15th day of admissionLaparotomy with right colectomy and ileostomyDied
8Kühn et al [22]59 Y/MNot mentionedFeverNauseaAbdominal pain Fatigue, HeadacheNot specifiedNot mentionedAbdominal painJejunal diverticulumAt presentationOpen small bowel segmental resection & anastomosisDischarged Home
9Seeliger et al [23]31Y/MNot mentionedDyspneaSevereNot mentionedNot mentionedLeft colonAt presentationLeft HemicolectomyDischarged Home
1082 Y/FDyspnea, DiarrhoeaCriticalSigmoidAt presentationOpen drainage of peritonitisDied
1171 Y/FFeverSevereGangrenous appendixAt presentationLaparoscopic appendectomyDischarged Home
1280Y/MNot mentionedSevereSigmoiditisAt presentationHartmann procedureDischarged Home
1377 Y/MDyspneaCriticalDuodenal ulcer23rd day of admissionOpen duodenal exclusion, omega gastro-enteric anastomosisDied
14This Report70Y/MT2DMFeverCoughCriticalMethylprednisolone HydroxychloroquineOseltamivir Enoxaparin+AntibioticsBleeding per rectumHemoglobin DropCecal mass44th day of admissionConservativeDischarged Home
1537Y/MMorbid obesityDyspneaCriticalInterferon B1Lopinavir/RitonavirRibavirinHydroxychloroquineOseltamivirDexamethasone+AntibioticsAir under diaphragm was found incidentally in a follow up CXRCecum4th day of admissionConservativeDischarged Home
1674Y/MT2DMCoughDyspnea Abdominal pain.SevereLopinavir/RitonavirRibavirinMethylprednisolone+AntibioticsAbdominal painSigns of peritonitisSigmoid diverticulosis/diverticulitisAt presentationExploratory laparotomy with Hartmann’s procedureDischarged Home

Open in a separate window

Severity of COVID-19 pneumonia is based on classification of severity by Ministry of Health-Saudi Arabia.[24]†Y = Year.M = Male.§F = Female.

Most of the previously reported cases presented initially with respiratory symptoms, 4 cases had also GI symptoms at presentation in the form of abdominal pain, stiffness, nausea and diarrhoea[19,20,22,23] [Table ​[Table2].2]. Eleven out of the 13 cases had severe-critical pneumonia that required either high flow oxygen, intubation or mechanical ventilation which is similar to our first 2 cases. This may indicate that GI perforation is more common in severe and critically ill COVID-19 cases. The most common symptoms which prompted investigations for bowel perforation were abdominal pain and distention [Table ​[Table2].2]. Other indications were signs of peritonitis,[16] worsening hemodynamics[17,18,21] and rising inflammatory markers.[15]

Only one of our cases had abdominal pain and tenderness at presentation. Another developed anemia due to active lower GI bleeding which is similar to the case published by Rojo et al[21] where the patient developed anemia and found to have hemoperitoneum with pericecal hematoma. This is probably explained by the site of perforation since both had cecal perforation. Our other case was diagnosed incidentally after demonstration of air under diaphragm in routine CXR. GI perforation was diagnosed from first day up to 23rd day of presentation with COVID-19 [Table ​[Table2].2]. Our patients had similar variable timing of GI perforation in relation to presentation with COVID-19. It ranged from the first day of diagnosis up to 40 days after presentation with COVID-19 pneumonia. This may tell us that GI perforation could happen at any time during the course of the infection. Our report demonstrates different presentation of GI perforation with COVID-19 since in 2 of the 3 cases, the infection predisposed to having perforation of an underlying GI lesions (cecal mass and diverticulosis). Only Kuhn et al reported similar presentation where the patient had perforation of jejunal diverticulum.[22] This may tell us that having COVID-19 predispose patients with underlying GI lesions to perforation. In addition, in our first case, we think that the source of Candidemia was most probably the bowel since it was persistent even after clearance of Candida Albican from the urine, but it was overlooked due to the absence of GI symptoms at the time of developing the Candidemia. In a study of 62 cases with peritonitis secondary to gastric perforation, Candida species was isolated in 23 cases in peritoneal fluid culture.[26] Therefore, in presence of Candidemia especially in absence of clear source, evaluation of the bowel as a potential source should always be kept in mind.

The effect of SARS-COV-2 virus on the GI system can be explained by different mechanisms. First, the virus uses the same access to enter respiratory and GI tract epithelium which are Angiotensin converting enzyme 2 receptors giving the virus the chance to replicate inside GI cells.[27] In addition, faecal-oral transmission has also been postulated, due to the presence of viral RNA in stool samples.[28] Perforation could result from altered colonic motility due to neuronal damage by the virus[29] in addition to local ischemia resulting from hypercoagulable state caused by the virus especially in critically ill patients.[30] Corrêa Neto et al reported finding ischemia of the entire GI tract during exploratory laparotomy for sigmoid perforation with COVID-19.[20] In addition, Rojo et al reported presence of microthrombi and wall necrosis in the pathology examination of his COVID-19 case with bowel perforation.[21] Other possible implicating factors are the use of Tocilizumab and high dose steroids.[21,31] Both are indicated in severe and critically ill COVID-19 cases. Steroids were used in all of our 3 cases since it is indicated in severe COVID-19 pneumonia according Saudi Arabian Ministry of health guidelines[24] but none of our patients received Tocilizumab. Some of these mechanisms could explain the higher risk of GI perforation in severe and critically ill COVID-19 patients.

The diagnosis of GI perforation is based mainly on radiological findings on CT scan. The most specific findings are segmental bowel wall thickening, focal bowel wall defect, or bubbles of extraluminal gas concentrated in close proximity to the bowel wall.[32] Treatment of GI perforation is mainly surgical in order to improve survival.[33] This is in line with the previously published cases where all were managed surgically except the one reported by Kangas-Dick et al due to the patient’s critical condition, so he was managed conservatively but unfortunately, he died.[17] However, in selected cases where there are no active signs of peritonitis, abdominal sepsis or having sealed perforation, conservative treatment is an acceptable management strategy.[34,35] This was the case in 2 of our cases who were managed conservatively. Fortunately, they did very well and had good outcome.

4. Conclusion

GI manifestations are common in patients with COVID-19. However, GI perforation is rarely reported in the literature. Severe and critically ill COVID-19 patients seem to be at a higher risk of this complication. It has a variable presentation in patients with COVID-19 ranging from incidental finding discovered only radiographically to acute abdomen. The presence of underlying GI lesion predisposes patients with COVID-19 to perforation. High index of suspicion is required in order to manage those patients further and thus, improve their outcome.

Author contributions

Conceptualization: Reem J. Al Argan, Safi G. Alqatari

Data curation: Reem J. Al Argan, Abdulsalam Noor, Lameyaa A. Al Sheekh

Writing – original draft: Reem J. Al Argan, Lameyaa A. Al Sheekh, Feda’a H. Al Beladi

Writing – review & editing: Reem J. Al Argan, Safi G. Alqatari, Abir H. Al Said, Raed M. AlsulaimanGo to:

Footnotes

Abbreviations: COVID-19 = corona virus disease-2019, CT = computed tomography, CXR = chest X-ray, ED = emergency department, GI = gastrointestinal, ICU = intensive care unit, LDH = lactate dehydrogenase, O2 sat = oxygen saturation, PCR = polymerase chain reaction, PR = Pulse rate, RA = room air, RR = respiratory rate, Temp = Temperature, T2DM = Type 2 diabetes mellitus.

How to cite this article: Al Argan RJ, Alqatari SG, Al Said AH, Alsulaiman RM, Noor A, Al Sheekh LA, Al Beladi FH. Gastrointestinal perforation secondary to COVID-19: Case reports and literature review. Medicine. 2021;100:19(e25771).

The authors have no funding and conflicts of interests to disclose.

Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.

References

[1] https://www.who.int/news-room/detail/27-04-2020-who-timeline—covid-19 (Accessed September 23rd 2020). [Google Scholar][2] Guan WJ, Ni ZY, Hu Y, et al. . Clinical characteristics of coronavirus disease 2019 in China. N Eng J Med 2020;382:1708–20. [PMC free article] [PubMed] [Google Scholar][3] Lai CC, Ko WC, Lee PI, et al. . Extra-respiratory manifestations of COVID-19. Int J Anti microb Agents 2020;56:106024. [PMC free article] [PubMed] [Google Scholar][4] Pan L, Mu M, Yang P, et al. . Clinical characteristics of COVID-19 patients with digestive symptoms in Hubei, China: a descriptive, cross-sectional, multicenter study. Am J Gastroenterol 2020;115:766–73. [PMC free article] [PubMed] [Google Scholar][5] Rokkas T. Gastrointestinal involvement in COVID-19: a systematic review and meta-analysis. Ann Gastroenterol 2020;33:355–65. [PMC free article] [PubMed] [Google Scholar][6] Ashcroft J, Hudson VE, Davies RJ. COVID-19 gastrointestinal symptoms mimicking surgical presentations. Ann Med Surg (Lond) 2020;56:108–9. [PMC free article] [PubMed] [Google Scholar][7] Guotao L, Xingpeng Z, Zhihui D, et al. . SARS-CoV-2 infection presenting with hematochezia. Med Mal Infect 2020;50:293–6. [PMC free article] [PubMed] [Google Scholar][8] Hadi A, Werge M, Kristiansen KT, et al. . Coronavirus disease-19 (COVID-19) associated with severe acute pancreatitis: case report on three family members. Pancreatology 2020;20:665–7. [PMC free article] [PubMed] [Google Scholar][9] Siegel A, Chang PJ, Jarou ZJ, et al. . Lung base findings of coronavirus disease (COVID-19) on abdominal CT in patients with predominant gastrointestinal symptoms. AJR Am J Roentgenol 2020;215:1–3. [PubMed] [Google Scholar][10] Koperna T, Schulz F. Prognosis and treatment of peritonitis. Do we need new scoring systems? Arch Surg 1996;131:180–6. [PubMed] [Google Scholar][11] Langell JT, Mulvihill SJ. Gastrointestinal perforation and the acute abdomen. Med Clin North Am 2008;92:599–ix. [PubMed] [Google Scholar][12] Hayetian FD, Read TE, Brozovich M, et al. . Ileal perforation secondary to Clostridium difficult enteritis. Arch S 2006;141:97–9. [PubMed] [Google Scholar][13] Aguayo W, Gálvez P, Acosta P, et al. . Intestinal perforation due to intestinal and colonic tuberculosis in a patient with HIV, a nearly lethal complication due to lack of adequate treatment and control in a limited resource country, a case report. Int J Surg Case Rep 2019;64:45–9. [PMC free article] [PubMed] [Google Scholar][14] Kato K, Cooper M. Small bowel perforation secondary to CMV-positive terminal ileitis postrenal transplant. BMJ Case Rep 2019;12:e231662. [PMC free article] [PubMed] [Google Scholar][15] Gonzálvez Guardiola P, Díez Ares JÁ, Peris Tomás N, et al. . Intestinal perforation in patient with COVID-19 infection treated with tocilizumab and corticosteroids. Report of a clinical case. Cir Esp 2020;99:156–7. [PMC free article] [PubMed] [Google Scholar][16] De Nardi P, Parolini DC, Ripa M, et al. . Bowel perforation in a Covid-19 patient: case report. Int J Colorectal Dis 2020;35:1797–800. [PMC free article] [PubMed] [Google Scholar][17] Kangas-Dick A, Prien C, Rojas K, et al. . Gastrointestinal perforation in a critically ill patient with COVID-19 pneumonia. SAGE Open Med Case Rep 2020;8: 2050313X20940570. [PMC free article] [PubMed] [Google Scholar][18] Galvez A, King K, El Chaar M, et al. . Perforated marginal ulcer in a COVID-19 patient. Laparoscopy in these trying times. Obes Surg 2020;30:1–4. [PMC free article] [PubMed] [Google Scholar][19] Poggiali E, Vercelli A, Demichele E, et al. . Diaphragmatic rupture and gastric perforation in a patient with COVID-19 pneumonia. Eur J Case Rep Intern Med 2020;7:001738. [PMC free article] [PubMed] [Google Scholar][20] Corrêa Neto IJF, Viana KF, Silva MBSD, et al. . Perforated acute abdomen in a patient with COVID-19: an atypical manifestation of the disease. J Coloproctol 2020;40:269–72. [Google Scholar][21] Rojo M, Cano-Valderrama O, Picazo S, et al. . Gastrointestinal perforation after treatment with tocilizumab: an unexpected consequence of COVID-19 pandemic. Am Surg 2020;86:565–6. [PubMed] [Google Scholar][22] Kühn F, Klein M, Laven H, et al. . Specific management of patients with acute abdomen during the COVID-19 pandemic: a surgical perspective from Germany. Visc Med 2020;36:1–4. [PMC free article] [PubMed] [Google Scholar][23] Seeliger B, Philouze G, Cherkaoui Z, et al. . Acute abdomen in patients with SARS-CoV-2 infection or co-infection. Langenbecks Arch Surg 2020;405:861–6. [PMC free article] [PubMed] [Google Scholar][24] https://www.moh.gov.sa/Ministry/MediaCenter/Publications/Documents/MOH-therapeutic-protocol-for-COVID-19.pdf(Accessed September 5th 2020). [Google Scholar][25] Meini S, Zini C, Passaleva MT, et al. . Pneumatosis intestinalis in COVID-19. BMJ Open Gastro 2020;7:e000434. [PMC free article] [PubMed] [Google Scholar][26] Lee SC, Fung CP, Chen HY, et al. . Candida peritonitis due to peptic ulcer perforation: incidence rate, risk factors, prognosis and susceptibility to fluconazole and amphotericin B. Diagn Microbiol Infect Dis 2002;44:23–7. [PubMed] [Google Scholar][27] Zhang H, Kang Z, Gong H, Xu D,Wang J, Zifu Li Z, et al. The Digestive System Is A Potential Route of 2019-Covid infection: Bioinformatics Analysis Based On Single-Cell Transcriptomes. bioRxiv,.01.30.927806. [Google Scholar][28] Cheung KS, Hung IFN, Chan PPY, et al. . Gastrointestinal manifestations of SARS-CoV-2 infection and virus load in fecal samples from a Hong Kong Cohort: systematic review and meta-analysis. Gastroenterology 2020;59:81–95. [PMC free article] [PubMed] [Google Scholar][29] Conde G, Quintana Pájaro LD, Quintero Marzola ID, et al. . Neurotropism of SARS- CoV 2: mechanisms and manifestations. J Neurol Sci 2020;412:116824. [PMC free article] [PubMed] [Google Scholar][30] Klok FA, Kruip MJHA, van der Meer NJM, et al. . Incidence of thrombotic complications in critically ill ICU patients with COVID-19. Thromb Res 2020;191:145–7. [PMC free article] [PubMed] [Google Scholar][31] Xie F, Yun H, Bernatsky S, et al. . Brief report: risk of gastrointestinal perforation among rheumatoid arthritis patients receiving tofacitinib, tocilizumab, or other biologic treatments. Arthritis Rheumatol 2016;68:2612–7. [PMC free article] [PubMed] [Google Scholar][32] Del Gaizo AJ, Lall C, Allen BC, et al. . From esophagus to rectum: a comprehensive review of alimentary tract perforations at computed tomography. Abdom Imaging 2014;39:802–23. [PubMed] [Google Scholar][33] Hecker A, Schneck E, Röhrig R, et al. . The impact of early surgical intervention in free intestinal perforation: a time-to-intervention pilot study. World J Emerg Surg 2015;10:54. [PMC free article] [PubMed] [Google Scholar][34] Castellví J, Pi F, Sueiras A, et al. . Colonoscopic perforation: useful parameters for early diagnosis and conservative treatment. Int J Colorectal Dis 2011;26:1183–90. [PubMed] [Google Scholar][35] Donovan AJ, Berne TV, Donovan JA. Perforated duodenal ulcer: an alternative therapeutic plan. Arch Surg 1998;133:1166–71. [PubMed] [Google Scholar]

‘We Made a Big Mistake’ — COVID Vaccine Spike Protein Travels From Injection Site, Can Cause Organ Damage

Authors:  Children’s Health Defense

COVID vaccine researchers had previously assumed mRNA COVID vaccines would behave like traditional vaccines. The vaccine’s spike protein — responsible for infection and its most severe symptoms — would remain mostly in the injection site at the shoulder muscle or local lymph nodes.

But new research obtained by a group of scientists contradicts that theory, a Canadian cancer vaccine researcher said last week.

“We made a big mistake. We didn’t realize it until now,” said Byram Bridle, a viral immunologist and associate professor at University of Guelph, Ontario. “We thought the spike protein was a great target antigen, we never knew the spike protein itself was a toxin and was a pathogenic protein. So by vaccinating people we are inadvertently inoculating them with a toxin.”

Bridle, who was awarded a $230,000 grant by the Canadian government last year for research on COVID vaccine development, said he and a group of international scientists filed a request for information from the Japanese regulatory agency to get access to Pfizer’s “biodistribution study.”

Biodistribution studies are used to determine where an injected compound travels in the body, and which tissues or organs it accumulates in.

“It’s the first time ever scientists have been privy to seeing where these messenger RNA [mRNA] vaccines go after vaccination,” Bridle said in an interview with Alex Pierson where he first disclosed the data. “Is it a safe assumption that it stays in the shoulder muscle? The short answer is: absolutely not. It’s very disconcerting.”

The Sars-CoV-2 has a spike protein on its surface. That spike protein is what allows it to infect our bodies, Bridle explained. “That is why we have been using the spike protein in our vaccines,” Bridle said. “The vaccines we’re using get the cells in our bodies to manufacture that protein. If we can mount an immune response against that protein, in theory we could prevent this virus from infecting the body. That is the theory behind the vaccine.”

“However, when studying the severe COVID-19, […] heart problems, lots of problems with the cardiovascular system, bleeding and clotting, are all associated with COVID-19,”  he added. “In doing that research, what has been discovered by the scientific community, the spike protein on its own is almost entirely responsible for the damage to the cardiovascular system, if it gets into circulation.”

When the purified spike protein is injected into the blood of research animals, they experience damage to the cardiovascular system and the protein can cross the blood-brain barrier and cause damage to the brain, Bridle explained.

The biodistribution study obtained by Bridle shows the COVID spike protein gets into the blood where it circulates for several days post-vaccination and then accumulates in organs and tissues including the spleen, bone marrow, the liver, adrenal glands and in “quite high concentrations” in the ovaries.

“We have known for a long time that the spike protein is a pathogenic protein, Bridle said. “It is a toxin. It can cause damage in our body if it gets into circulation.”

A large number of studies have shown the most severe effects of SARS-CoV-2, the virus that causes COVID, such as blood clotting and bleeding, are due to the effects of the spike protein of the virus itself.

A recent study in Clinical and Infectious Diseases led by researchers at Brigham and Women’s Hospital and the Harvard Medical School measured longitudinal plasma samples collected from 13 recipients of the Moderna vaccine 1 and 29 days after the first dose and 1-28 days after the second dose.

Out of these individuals, 11 had detectable levels of SARS-CoV-2 protein in blood plasma as early as one day after the first vaccine dose, including three who had detectable levels of spike protein. A “subunit” protein called S1, part of the spike protein, was also detected.

Spike protein was detected an average of 15 days after the first injection, and one patient had spike protein detectable on day 29 –– one day after a second vaccine dose –– which disappeared two days later.

The results showed S1 antigen production after the initial vaccination can be detected by day one and is present beyond the injection site and the associated regional lymph nodes.

Assuming an average adult blood volume of approximately 5 liters, this corresponds to peak levels of approximately 0.3 micrograms of circulating free antigen for a vaccine designed only to express membrane-anchored antigen.

In a study published in Nature Neuroscience, lab animals injected with purified spike protein into their bloodstream developed cardiovascular problems. The spike protein also crossed the blood-brain barrier and caused damage to the brain.

It was a grave mistake to believe the spike protein would not escape into the blood circulation, according to Bridle. “Now, we have clear-cut evidence that the vaccines that make the cells in our deltoid muscles manufacture this protein — that the vaccine itself, plus the protein — gets into blood circulation,” he said.

Bridle said the scientific community has discovered the spike protein, on its own, is almost entirely responsible for the damage to the cardiovascular system, if it gets into circulation.

Once in circulation, the spike protein can attach to specific ACE2 receptors that are on blood platelets and the cells that line blood vessels, Bridle said. “When that happens it can do one of two things. It can either cause platelets to clump, and that can lead to clotting — that’s exactly why we’ve been seeing clotting disorders associated with these vaccines. It can also lead to bleeding,” he added.

Both clotting and bleeding are associated with vaccine-induced thrombotic thrombocytopenia (VITT). Bridle also said the spike protein in circulation would explain recently reported heart problems in vaccinated teens.

Stephanie Seneff, senior research scientists at Massachusetts Institute of Technology, said it is now clear vaccine content is being delivered to the spleen and the glands, including the ovaries and the adrenal glands, and is being shed into the medium and then eventually reaches the bloodstream causing systemic damage.

“ACE2 receptors are common in the heart and brain,” she added. “And this is how the spike protein causes cardiovascular and cognitive problems.”

Dr. J. Patrick Whelan, a pediatric rheumatologist, warned the U.S. Food and Drug Administration (FDA) in December mRNA vaccines could cause microvascular injury to the brain, heart, liver and kidneys in ways not assessed in safety trials.

In a public submission, Whelan sought to alert the FDA to the potential for vaccines designed to create immunity to the SARS-CoV-2 spike protein to instead cause injuries.

Whelan was concerned the mRNA vaccine technology utilized by Pfizer and Moderna had “the potential to cause microvascular injury (inflammation and small blood clots called microthrombi) to the brain, heart, liver and kidneys in ways that were not assessed in the safety trials.”

Study Finds Teenage Boys Six Times More Likely To Suffer Heart Problems From Vaccine Than Be Hospitalized by COVID

Authors; Paul Joseph Watson via Summit News,

Research conducted by the University of California has found that teenage boys are six times more likely to suffer from heart problems caused by the COVID-19 vaccine than to be hospitalized as a result of COVID-19 itself.

“A team led by Dr Tracy Hoeg at the University of California investigated the rate of cardiac myocarditis – heart inflammation – and chest pain in children aged 12-17 following their second dose of the vaccine,” reports the Telegraph.

“They then compared this with the likelihood of children needing hospital treatment owing to Covid-19, at times of low, moderate and high rates of hospitalisation.”

Researchers found that the risk of heart complications for boys aged 12-15 following the vaccine was 162.2 per million, which was the highest out of all the groups they looked at.

This compares to the risk of a healthy boy being hospitalized as a result of a COVID infection, which is around 26.7 per million, meaning the risk they face from the vaccine is 6.1 times higher.

Even during high risk rates of COVID, such as in January this year, the threat posed by the vaccine is 4.3 times higher, while during low risk rates, the risk of teenage boys suffering a “cardiac adverse event” from the vaccine is a whopping 22.8 times higher.

The research data was based on a study of adverse reactions suffered by teens between January and June this year.

In a sane world, such data should represent the nail in the coffin for the argument that teenagers and children should be mandated to take the coronavirus vaccine, but it obviously won’t.

In the UK, the government is pushing to vaccinate 12-15-year-olds, even without parental consent, despite the Joint Committee on Vaccination and Immunisation (JCVI) advising against it.

Meanwhile, in America, Los Angeles County school officials voted unanimously to mandate COVID shots for all

Blood molecular markers associated with COVID-19 immunopathology and multi-organ damage

Authors: Yan-Mei ChenYuanting ZhengYing YuYunzhi WangQingxia HuangFeng QianLei SunZhi-Gang SongZiyin ChenJinwen FengYanpeng AnJingcheng YangZhenqiang SuShanyue SunFahui DaiQinsheng ChenQinwei LuPengcheng LiYun LingZhong YangHuiru TangLeming ShiLi JinEdward C HolmesChen DingTong-Yu ZhuYong-Zhen Zhang

Abstract

COVID-19 is characterized by dysregulated immune responses, metabolic dysfunction and adverse effects on the function of multiple organs. To understand host responses to COVID-19 pathophysiology, we combined transcriptomics, proteomics, and metabolomics to identify molecular markers in peripheral blood and plasma samples of 66 COVID-19-infected patients experiencing a range of disease severities and 17 healthy controls. A large number of expressed genes, proteins, metabolites, and extracellular RNAs (exRNAs) exhibit strong associations with various clinical parameters. Multiple sets of tissue-specific proteins and exRNAs varied significantly in both mild and severe patients suggesting a potential impact on tissue function. Chronic activation of neutrophils, IFN-I signaling, and a high level of inflammatory cytokines were observed in patients with severe disease progression. In contrast, COVID-19-infected patients experiencing milder disease symptoms showed robust T-cell responses. Finally, we identified genes, proteins, and exRNAs as potential biomarkers that might assist in predicting the prognosis of SARS-CoV-2 infection. These data refine our understanding of the pathophysiology and clinical progress of COVID-19.

Proteomics, metabolomics and RNAseq data map immune responses in COVID-19 patients with different disease severity, revealing molecular makers associated with disease progression and alterations of tissue-specific proteins.

  • A multi-omics profiling of the host response to SARS-CoV2 infection in 66 clinically diagnosed and laboratory confirmed COVID-19 patients and 17 uninfected controls.
  • Significant correlations between multi-omics data and key clinical parameters.
  • Alteration of tissue-specific proteins and exRNAs.
  • Enhanced activation of immune responses is associated with COVID-19 pathogenesis.
  • Biomarkers to predict COVID-19 clinical outcomes pending clinical validation as prospective marker.

Introduction

Coronaviruses (family Coronaviridae) are a diverse group of positive-sense single-stranded RNA viruses with enveloped virions (Masters & Perlman, 2013; Cui et al2019). Coronaviruses are well known due to the emergence of Severe Acute Respiratory Syndrome (SARS) in 2002–2003 and Middle East Respiratory Syndrome (MERS) in 2012, both of which caused thousands of cases in multiple countries (Ksiazek et al2003; Bermingham et al2012; Cui et al2019). Coronaviruses naturally infect a broad range of vertebrate hosts including mammals and birds (Cui et al2019). As coronavirus primarily target epithelial cells, they are generally associated with gastrointestinal and respiratory infections (Masters & Perlman, 2013; Cui et al2019). In addition, they cause hepatic and neurological diseases of varying severity (Masters & Perlman, 2013).

The world is currently experiencing a disease pandemic (COVID-19) caused by a newly identified coronavirus called SARS-CoV-2 (Wu et al2020a). At the time of writing, there have been more than ~25 million cases of SARS-CoV-2 and ~830,000 deaths globally (WHO, 2020). The disease leads to both mild and severe respiratory manifestations, with the latter prominent in the elderly and those with underlying medical conditions such as cardiovascular and chronic respiratory disease, diabetes, and cancer (Guan et al., 2020). In addition to respiratory syndrome, mild gastrointestinal and/or cardiovascular symptoms and neurological manifestations have been documented in hospitalized COVID-19-infected patients (Gupta et al2020; Mao et al2020). These data point to the complexity of COVID-19 pathogenesis, especially in patients experiencing severe disease.

SARS-CoV-2 is able to use angiotensin-converting enzyme 2 (ACE 2) as a receptor for cell entry (Hoffmann et al2020; Zheng et al2020a; Zhou et al2020b). Aside from lungs, ACE2 is expressed in other organs including heart, liver, kidney, pancreas, and small intestines (Li et al2020; Liu et al2020; Zou et al2020; Chen et al2020a). More recently, ACE2 expression has also been found in Leydig cells in the testes (Li et al2020; Wang & Xu, 2020) and neurological tissue (Baig et al2020; Bullen et al2020; Xu & Lazartigues, 2020). As such, it is possible that these organs might also be infected by SARS-CoV-2, and recent autopsy studies have also revealed multi-organ damage including heart, liver, intestine, pancreas, brain, kidney, and spleen in fatal COVID-19-infected patients (Lax et al2020; Menter et al2020; Varga et al2020; Wichmann et al2020; Wang et al2020c). The host immune response to SARS-CoV-2 may also impact pathogenicity, resulting in severe tissue damage and, occasionally, death (Tay et al2020). Indeed, several studies have reported lymphopenia, exhausted lymphocytes, and cytokine storms in COVID-19-infected patients, especially those with severe symptoms (Blanco-Melo et al2020; Cao, 2020; Chua et al2020; Liao et al2020). Numerous clinical studies have also observed the elevation of lactate dehydrogenase (LDH), IL-6, troponin I, inflammatory markers, and D-dimer in COVID-19-infected patients (Zhou et al2020a; Wang et al2020b). However, despite the enormous burden of morbidity and mortality due to COVID-19, we know little about its pathophysiology, even though this establishes the basis for successful clinical practice, vaccine development, and drug discovery.

Using a multi-omics approach employing cutting-edge transcriptomic, proteomic, and metabolomic technologies, we identified significant molecular alterations in patients with COVID-19 compared with uninfected controls in this study. Our results refine the molecular view of COVID-19 pathophysiology associated with disease progression and clinical outcome.

For More Information: https://www.embopress.org/doi/full/10.15252/embj.2020105896