Pandemic health consequences: Grasping the long COVID tail

Emerging evidence suggests that approximately 10% of people who survive Coronavirus Disease 2019 (COVID-19) will have lingering symptoms that negatively affect their quality of life, ability to work, and function [1,2]. This important group of people with the post-COVID-19 condition may seem small in comparison to the overall number of people with COVID-19 infection [3]. However, many patients who survive COVID-19 are likely to have considerable symptom burden, high resource utilization and health service needs, reduced economic productivity, and possibly a shortened life expectancy. The study by Bhaskaran and colleagues published in PLOS Medicine addresses an evolving, poorly studied, and important area of health policy and planning related to the care of patients who survive hospitalization for COVID-19 [4].

At face value, the scope of the COVID-19 pandemic is enormous. Within 2 years, nearly 300 million people have been infected with the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) virus, and more than 5 million people have died from it [5]. But, there is also a long tail to this statistical distribution of hardship. Studies report that numerous patients will continue to experience fatigue, shortness of breath, pain, sleep disturbances, anxiety, and depression [6]. More serious organ dysfunction such as pulmonary fibrosis, cognitive impairment, myocarditis, and renal failure may also develop [6]. Whether these translate into clinical diagnoses of chronic diseases like interstitial lung disease, dementia, heart failure, and chronic kidney disease remains to be seen. Collectively, the prospect for immense suffering among these individuals will undoubtedly have huge and enduring impacts on healthcare systems globally. As the world continues its largest vaccination effort in history and looks to eliminate the impacts of acute COVID-19, we must not forget that a meaningful minority who survive will transition from an acute to chronic disease state. In turn, management strategies and health resource planning must also appropriately transition. As a multisystem disease, the post-COVID-19 condition will require the involvement of multidisciplinary care teams [7]: Who will help to look after these patients?

Bhaskaran and colleagues studied over 164,000 hospitalized adults with COVID-19 matched to an “active control” group of adults hospitalized with influenza and to general population controls. They compared the medium- and long-term risks of hospital admission and death across the 3 study groups. The main findings were that people discharged following hospitalization for COVID-19 had a 2-fold higher associated risk for rehospitalization and death than the general population and similar risks compared to those hospitalized for influenza. These outcomes were most pronounced in the first 30 days following discharge yet remained substantially elevated over time. Further, those hospitalized with COVID-19 were more likely to be rehospitalized or die from mental health or cognitive-related causes, especially if they had preexisting dementia, compared to those hospitalized with influenza.

Initial hospitalization with COVID-19 represents a crucial touch point within the healthcare system. The study by Bhaskaran and colleagues sheds important light on the health service needs of patients who survive hospitalization for COVID-19. It further helps disentangle the effects of hospitalization from respiratory viral infection on important outcomes. The current work builds on similar findings from a recent study of 47,780 hospitalized adults with COVID-19 who survived to discharge with a mean follow-up of 140 days [8]. In that study, rates of hospital readmission and mortality were 3.5 and 7.7 times greater in the previously hospitalized group of COVID-19 patients, compared to general population controls, respectively. Other studies from the United States and China followed patients hospitalized for COVID-19 and reported lower 60-day and 1-year rehospitalization rates ranging from 13% to 19.9%. However, these studies did not account for the competing risk of death as was done in the current study [911].

There were also noteworthy limitations of Bhaskaran and colleagues’ study. First, cause-specific outcomes among adults with COVID-19 may be artificially higher than those with influenza due to availability bias. Put simply, patients and providers may be much more aware of COVID-19 and its complications, including those related to return to hospital, than might be the case for those with pneumonia or even confirmed influenza. Second, the study used administrative data from primary care. While 98% of the population in England are registered with a general practice (thereby minimizing selection biases due to health-seeking behaviors), there are some geographical differences in the use of the OpenSAFELY platform, which may introduce the potential for selection bias. Third, this study was conducted in a high-income nation with substantial resources to support patients following infection with COVID-19. The generalizability of these findings to middle- and low-income nations, or those with limited resources, is unknown.

The study by Bhaskaran and colleagues has clear applications to healthcare resource planning and policy in the care of individuals who survive COVID-19. This suggests a substantial added burden on global healthcare systems. It further builds on our evolving knowledge of the post-COVID-19 condition and its lingering impacts, including on many previously healthy adults in their prime years of productivity. Still, a wealth of research is required to develop prediction tools to proactively identify and support the healthcare needs of survivors, including end-of-life care, develop new strategies to prevent and treat the post-COVID-19 condition, and encourage interprofessional teams to provide longitudinal care through innovative health policy interventions.

Early pandemic public messaging strategies focused on flattening the peak of the acute COVID-19 infection curve to preserve healthcare system capacity and its ability to deliver high-quality care. These efforts were generally successful. To preserve ongoing system capacity and provide high-quality patient care, the long COVID tail does not require further flattening, but rather demands new clinical and health policy strategies to address its potential for long-term suffering. Here, we must recognize that the head of the pandemic often demands our immediate attention, but we must not ignore its long and deadly tail.


  1. 1.Pizarro-Pennarolli C, Sánchez-Rojas C, Torres-Castro R, Vera-Uribe R, Sanchez-Ramirez DC, Vasconcello-Castillo L, et al. Assessment of activities of daily living in patients post COVID-19: a systematic review. PeerJ. 2021;9:e11026. pmid:33868804
  2. 2.Groff D, Sun A, Ssentongo AE, Ba DM, Parsons N, Poudel GR, et al. Short-term and Long-term Rates of Postacute Sequelae of SARS-CoV-2 Infection. JAMA Netw Open. 2021;4:e2128568. pmid:34643720
  3. 3.Rubin R. As Their Numbers Grow, COVID-19 “Long Haulers” Stump Experts. JAMA. 2020;324:1381–3. pmid:32965460
  4. 4.Bhaskaran K, Rentsch CT, Hickman G, Hulme WJ, Schultze A, Curtis HJ, et al. Overall and cause-specific hospitalisation and death after COVID-19 hospitalisation in England: A cohort study using linked primary care, secondary care and death registration data in the OpenSAFELY platform. PLoS Med. 2022.
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  7. 7.Greenhalgh T, Knight M, A’Court C, Buxton M, Husain L. Management of post-acute COVID-19 in primary care. BMJ. 2020;370:m3026. pmid:32784198
  8. 8.Ayoubkhani D, Khunti K, Nafilyan V, Maddox T, Humberstone B, Diamond I, et al. Post-COVID syndrome in individuals admitted to hospital with COVID-19: retrospective cohort study. BMJ. 2021;372:n693. pmid:33789877
  9. 9.Chopra V, Flanders SA, O’Malley M, Malani AN, Prescott HC. Sixty-Day Outcomes Among Patients Hospitalized With COVID-19. Ann Intern Med. 2020. pmid:33175566
  10. 10.Donnelly JP, Wang XQ, Iwashyna TJ, Prescott HC. Readmission and Death After Initial Hospital Discharge Among Patients With COVID-19 in a Large Multihospital System. JAMA. 2021;325:304–6. pmid:33315057
  11. 11.Huang L, Yao Q, Gu X, Wang Q, Ren L, Wang Y, et al. 1-year outcomes in hospital survivors with COVID-19: a longitudinal cohort study. Lancet. 2021;398:747–58. pmid:34454673

Durability of mRNA-1273 vaccine–induced antibodies against SARS-CoV-2 variants

  1. Authors: ViewAmarendra Pegu1,†, Sarah O’Connell1,† View ORCID ProfileStephen D. Schmidt1,, Sijy O’Dell1,View ORCID ProfileChloe A. Talana1, Lilin Lai2, Jim Albert Science  12 Aug 2021: eabj4176m OI: 10.1126/science.abj4176


SARS-CoV-2 mutations may diminish vaccine-induced protective immune responses, particularly as antibody titers wane over time. Here, we assess the impact of SARS-CoV-2 variants B.1.1.7 (Alpha), B.1.351 (Beta), P.1 (Gamma), B.1.429 (Epsilon), B.1.526 (Iota), and B.1.617.2 (Delta) on binding, neutralizing, and ACE2-competing antibodies elicited by the vaccine mRNA-1273 over seven months. Cross-reactive neutralizing responses were rare after a single dose. At the peak of response to the second vaccine dose, all individuals had responses to all variants. Binding and functional antibodies against variants persisted in most subjects, albeit at low levels, for 6-months after the primary series of the mRNA-1273 vaccine. Across all assays, B.1.351 had the lowest antibody recognition. These data complement ongoing studies to inform the potential need for additional boost vaccinations.

SARS-CoV-2, the virus that causes COVID-19, has infected millions of people worldwide fueling the ongoing global pandemic (1). The combination of RNA virus mutation rates, replication and recombination, in a very large number of individuals is conducive to the emergence of viral variants with improved replication capacity and transmissibility, as well as immunological escape. Of particular interest are the Variants of Concern B.1.1.7 (20I/501Y.V1 or Alpha), B.1.351 (20H/501Y.V2 or Beta), P.1 (Gamma; first identified in Brazil), B.1.429 (Cal20 or Epsilon; first identified in California), and B.1.617.2 (Delta; first identified in India); and Variant of Interest B.1.526 (Iota; first identified in New York). In multiple studies, B.1.351 is the most resistant to neutralization by convalescent or vaccinee sera, with 6-15 fold less neutralization activity for sera from individuals immunized with vaccines based on the virus strain first described in January 2020 (Wuhan-Hu-1, spike also called WA1) (29). Most of these prior studies evaluated sera from vaccinated individuals at timepoints soon after the first or second dose, and had limited data on the durability of such responses. Likewise, clinical studies have reported somewhat reduced efficacy and effectiveness against the B.1.1.7, B.1.351, and B.1.617.2 variants (1012). Although such data provide critical insights into the performance of the vaccines against viral variants, they have not fully addressed the durability of cross-reactive binding and functional antibodies.

Here we investigate the impact of SARS-CoV-2 variants on recognition by sera from individuals who received two 100 mcg doses of the SARS-CoV-2 vaccine mRNA-1273. mRNA-1273 encodes the full-length stabilized spike protein of the WA1 and was administered as a two-dose series 28-days apart. We previously described the binding and neutralization activity against the WA1 SARS-CoV-2 spike longitudinally over 7 months from the first vaccination in volunteers from the Phase 1 trial of the mRNA-1273 vaccine (1316). In the current study, we demonstrate the utility of employing multiple methodologies to assess SARS-CoV-2 vaccine-elicited humoral immunity to variant viruses over time. We tested sera from a random sample of 8 volunteers in each of three age groups: 18-55, 55-70, and 71+ years of age, all of whom had samples available from four timepoints: 4 weeks after the first dose, and two weeks, 3 months, and 6 months after the second dose (Days 29, 43, 119, and 209 after the first dose, respectively).

Three functional assays and two binding assays were used to assess the humoral immune response to the SARS-CoV-2 spike protein. SARS-CoV-2 neutralization was measured using both a lentivirus-based pseudovirus assay, and a live-virus focus reduction neutralization test (FRNT) (17). The third functional assay was a MSD-ECLIA (Meso Scale Discovery-Electrochemiluminescence immunoassay)-based ACE2 competition assay. This method measured the ability of mRNA-1273 vaccine-elicited antibodies to compete with labeled soluble ACE2 for binding to the specific RBD (WA1 or variant) spotted onto the MSD plate. Antibody binding to cell-surface expressed full-length spike was analyzed by flow cytometry. Binding to soluble protein was measured by interferometry in the MSD-ECLIA platform. All samples were assessed against WA1 and the B.1.1.7 and B.1.351 variants in each of these orthogonal serology assays. In addition, all samples were tested against WA1 containing the D614G mutation in both neutralization assays, as well as binding in the cell-surface assay. Further variants were tested in binding assays as follows: S-2P and RBD binding, P.1 against all samples; cell-surface spike binding, P.1, B.1.429, B.1.526, and B.1.617.2 against all samples. A subset of samples – Day 43 to capture the peak response, and Day 209 to look at durability – were evaluated by pseudovirus neutralization against P.1, B.1.429, B.1.526, and B.1.617.2. The specific sequences used in each assay are defined in table S1.

We first assessed the patterns of antibody activity over time. Consistently across assays, low-level recognition of all variants was observed after a single dose (Day 29) (Fig. 1). Activity against all variants peaked two weeks after the second dose (Day 43) with moderate declines over time through Day 209 (Fig. 1). Notably, the values obtained for each assay on a per-sample basis correlated with each other (fig. S1). We next evaluated the relative impact of each variant, considering all timepoints together. Employing the pseudovirus assay, the neutralizing activity was highest against D614G and lowest against B.1.351, with values for all other variants tested falling in between those two variants (Fig. 1A and Fig. 2A). Similar to previous reports from our group (15) and others (18), pseudovirus neutralization ID50s to D614G were 3-fold higher than to WA1 (Fig. 2G). In contrast, using the live-virus FRNT neutralization assay (Fig. 1B and Fig. 2B), titers to WA1 were higher than to D614G, consistent with previous reports for that assay (19). For all other variants, the impact in the live-virus and pseudovirus neutralization assays were concordant: titers against B.1.1.7 were similar to D614G and lower against B.1.351. ACE2 competition was highest for WA1 RBD, intermediate for B.1.1.7, and lowest for B.1.351 (Fig. 1C and Fig. 2C). Spike-binding antibodies were measured using two different methodologies. In the cell-surface spike binding assay, serum antibodies were bound to full-length, membrane-embedded spike on the surface of transfected cells and measured by flow cytometry (20). In this assay (Fig. 1D and Fig. 2D), WA1 and D614G were nearly indistinguishable, with ~1.5-fold reduced binding to B.1.1.7, B.1.526, B.1.617.2, and 2.4 to 3.0-fold reduced binding to P.1, and B.1.429, and B.1.351. We also used the MSD-ECLIA multiplex binding assay to simultaneously measure IgG binding against both the stabilized soluble spike protein S-2P (21) and RBD proteins derived from WA1 and the B.1.1.7, B.1.351, and P.1 variants. The ECLIA assay showed slightly reduced binding to the variant S-2P (Fig. 1E and Fig. 2E) and RBD (Fig. 1F and Fig. 2F) proteins, with the rank order of highest to lowest binding as follows: WA1, B.1.1.7, P.1, and B.1.351. The overall effect of each variant in each assay is tabulated in Fig. 2G, which shows the geometric mean of the ratios between values for WA1 and variant or D614G and variant. In all assays, B.1.351 was the variant that caused the greatest reduction in titers compared to WA1 or D614G.

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Can we predict the severe course of COVID-19 – a systematic review and meta-analysis of indicators of clinical outcome?

  1. Authors: Stephan Katzenschlager ,Alexandra J. Zimmer ,Claudius Gottschalk, Jürgen Grafeneder,Stephani Schmitz, Sara Kraker, Marlene Ganslmeier, Amelie Muth, Alexander Seitel, Lena Maier-Hein, Andrea Benedetti, Jan Larmann, Markus A. Weigand, Sean McGrath , Claudia M. Denkinger  



COVID-19 has been reported in over 40million people globally with variable clinical outcomes. In this systematic review and meta-analysis, we assessed demographic, laboratory and clinical indicators as predictors for severe courses of COVID-19.


This systematic review was registered at PROSPERO under CRD42020177154. We systematically searched multiple databases (PubMed, Web of Science Core Collection, MedRvix and bioRvix) for publications from December 2019 to May 31st 2020. Random-effects meta-analyses were used to calculate pooled odds ratios and differences of medians between (1) patients admitted to ICU versus non-ICU patients and (2) patients who died versus those who survived. We adapted an existing Cochrane risk-of-bias assessment tool for outcome studies.


Of 6,702 unique citations, we included 88 articles with 69,762 patients. There was concern for bias across all articles included. Age was strongly associated with mortality with a difference of medians (DoM) of 13.15 years (95% confidence interval (CI) 11.37 to 14.94) between those who died and those who survived. We found a clinically relevant difference between non-survivors and survivors for C-reactive protein (CRP; DoM 69.10 mg/L, CI 50.43 to 87.77), lactate dehydrogenase (LDH; DoM 189.49 U/L, CI 155.00 to 223.98), cardiac troponin I (cTnI; DoM 21.88 pg/mL, CI 9.78 to 33.99) and D-Dimer (DoM 1.29mg/L, CI 0.9 to 1.69). Furthermore, cerebrovascular disease was the co-morbidity most strongly associated with mortality (Odds Ratio 3.45, CI 2.42 to 4.91) and ICU admission (Odds Ratio 5.88, CI 2.35 to 14.73).

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Long covid—mechanisms, risk factors, and management

Authors: Harry Crook, research assistant1,  Sanara Raza, research assistant1,  Joseph Nowell, research assistant1,  Megan Young, clinical research officer1,  Paul Edison, clinical senior lecturer, honorary professor12


Since its emergence in Wuhan, China, covid-19 has spread and had a profound effect on the lives and health of people around the globe. As of 4 July 2021, more than 183 million confirmed cases of covid-19 had been recorded worldwide, and 3.97 million deaths. Recent evidence has shown that a range of persistent symptoms can remain long after the acute SARS-CoV-2 infection, and this condition is now coined long covid by recognized research institutes. Studies have shown that long covid can affect the whole spectrum of people with covid-19, from those with very mild acute disease to the most severe forms. Like acute covid-19, long covid can involve multiple organs and can affect many systems including, but not limited to, the respiratory, cardiovascular, neurological, gastrointestinal, and musculoskeletal systems. The symptoms of long covid include fatigue, dyspnea, cardiac abnormalities, cognitive impairment, sleep disturbances, symptoms of post-traumatic stress disorder, muscle pain, concentration problems, and headache. This review summarizes studies of the long term effects of covid-19 in hospitalized and non-hospitalized patients and describes the persistent symptoms they endure. Risk factors for acute covid-19 and long covid and possible therapeutic options are also discussed.


Coronavirus disease 2019 (covid-19) has spread across the world. As of 4 July 2021, more than 183 million confirmed cases of covid-19 have been recorded worldwide, and more than 3.97 million deaths have been reported by the World Health Organization .1 The clinical spectrum of covid-19 ranges from asymptomatic infection to fatal disease.23 The virus responsible for causing covid-19, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), enters cells via the angiotensin-converting enzyme 2 (ACE2) receptor.4 Once internalized, the virus undergoes replication and maturation, provoking an inflammatory response that involves the activation and infiltration of immune cells by various cytokines in some patients.5 The ACE2 receptor is present in numerous cell types throughout the human body, including in the oral and nasal mucosa, lungs, heart, gastrointestinal tract, liver, kidneys, spleen, brain, and arterial and venous endothelial cells, highlighting how SARS-CoV-2 can cause damage to multiple organs.67

The impact of covid-19 thus far has been unparalleled, and long term symptoms could have a further devastating effect.8 Recent evidence shows that a range of symptoms can remain after the clearance of the acute infection in many people who have had covid-19, and this condition is known as long covid. The National Institute for Health and Care Excellence (NICE) defines long covid as the symptoms that continue or develop after acute covid-19 infection and which cannot be explained by an alternative diagnosis. This term includes ongoing symptomatic covid-19, from four to 12 weeks post-infection, and post-covid-19 syndrome, beyond 12 weeks post-infection.9 Conversely, The National Institutes of Health (NIH) uses the US Centers for Disease Control and Prevention (CDC) definition of long covid, which describes the condition as sequelae that extend beyond four weeks after initial infection.10 People with long covid exhibit involvement and impairment in the structure and function of multiple organs.11121314 Numerous symptoms of long covid have been reported and attributed to various organs, an overview of which can be seen in fig 1. Long term symptoms following covid-19 have been observed across the spectrum of disease severity. This review examines the long term impact of symptoms reported following covid-19 infection and discusses the current epidemiological understanding of long covid, the risk factors that may predispose a person to develop the condition, and the treatment and management guidelines aimed at treating it.

Multi-organ complications of covid-19 and long covid. The SARS-CoV-2 virus gains entry into the cells of multiple organs via the ACE2 receptor. Once these cells have been invaded, the virus can cause a multitude of damage ultimately leading to numerous persistent symptoms, some of which are outlined here.

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Predictors of COVID-19 severity: A literature review

Authors: Benjamin Gallo Marin,1Ghazal Aghagoli,1Katya Lavine,1Lanbo Yang,1Emily J. Siff,2Silvia S. Chiang,3,4Thais P. Salazar-Mather,1,5Luba Dumenco,1,5Michael C Savaria,1Su N. Aung,6Timothy Flanigan,6 and Ian C. Michelow3,4


The coronavirus disease 2019 (COVID-19) pandemic is a rapidly evolving global emergency that continues to strain healthcare systems. Emerging research describes a plethora of patient factors—including demographic, clinical, immunologic, hematological, biochemical, and radiographic findings—that may be of utility to clinicians to predict COVID-19 severity and mortality. We present a synthesis of the current literature pertaining to factors predictive of COVID-19 clinical course and outcomes. Findings associated with increased disease severity and/or mortality include age > 55 years, multiple pre-existing comorbidities, hypoxia, specific computed tomography findings indicative of extensive lung involvement, diverse laboratory test abnormalities, and biomarkers of end-organ dysfunction. Hypothesis-driven research is critical to identify the key evidence-based prognostic factors that will inform the design of intervention studies to improve the outcomes of patients with COVID-19 and to appropriately allocate scarce resources.


The newly described coronavirus disease (COVID-19), caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has strained healthcare systems around the world. The viral spread has been amplified not only by the occurrence of asymptomatic infections but also by limited widespread testing and personal protective equipment (PPE) for healthcare providers across the world.1 The overwhelming influx of COVID19-infected patients to many hospitals presents a need to thoroughly understand the clinical, radiological, and laboratory findings associated with greater disease severity and mortality. Here, we synthesize the current literature to describe early demographic, clinical, virologic, immunologic, hematological, biochemical, and radiographic factors that may correlate with COVID-19 disease severity. In this paper, we will use the World Health Organization’s (WHO) definition of severe pneumonia to categorize severe disease. As of 27 May 2020, the WHO’s most recent clinical guidelines define “severe disease” as adults with clinical signs of pneumonia (fever, dyspnea, cough, and fast breathing) accompanied by one of the following: respiratory rate > 30 breaths/min; severe respiratory distress; or oxygen saturation (SpO2) ≤ 90% on room air.2 The precise determinants of severe disease are not known, but it appears that primarily host factors rather than viral genetic mutations drive the pathogenesis.3 However, emerging data from a non-peer-reviewed paper suggest that a D614G mutation in the viral spike (S) protein of strains from Europe and the United States, but not China, is associated with more efficient transmission.4 Identification of potential risk factors that predict the disease course may be of great utility for healthcare professionals to efficiently triage patients, personalize treatment, monitor clinical progress, and allocate proper resources at all levels of care to mitigate morbidity and mortality. Here, we present a review of the current literature on patient factors that have been proposed as predictors for COVID-19 severity and mortality.

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COVID-19-Associated Bronchiectasis and Its Impact on Prognosis

Authors: Aasir M. SulimanBassel W. BitarAmer A. FarooqiAnam M. ElarabiMohamed R. AboukamarAhmed S. Abdulhadi


Coronavirus disease 2019 (COVID-19), which initially emerged in Wuhan, China, has rapidly swept around the world, causing grave morbidity and mortality. It manifests with several symptoms, on a spectrum from asymptomatic to severe illness and death. Many typical imaging features of this disease are described, such as bilateral multi-lobar ground-glass opacities (GGO) or consolidations with a predominantly peripheral distribution. COVID-19-associated bronchiectasis is an atypical finding, and it is not a commonly described sequel of the disease. Here, we present a previously healthy middle-aged man who developed progressive bronchiectasis evident on serial chest CT scans with superimposed bacterial infection following COVID-19 pneumonia. The patient’s complicated hospital course of superimposed bacterial infection in the setting of presumed bronchiectasis secondary to COVID-19 is alleged to have contributed to his prolonged hospital stay, with difficulty in weaning off mechanical ventilation. Clinicians should have high suspicion and awareness of such a debilitating complication, as further follow-up and management might be warranted.


Beginning in December 2019, a series of pneumonia cases were reported in Wuhan City, Hubei Province, China. Further investigations revealed that it was a new type of viral pneumonia caused by severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2), which was termed coronavirus disease 2019 (COVID-19). Symptoms are variable, nonspecific, and include dry cough, fever, fatigue, myalgia, dyspnea, anosmia, and ageusia [1]. The real-time reverse transcription-polymerase chain reaction (rRT-PCR) test is the current gold standard for confirming infection and is performed using nasal or pharyngeal swab specimens.

Computerized tomography of the thorax (CT thorax), as a routine imaging tool for pneumonia diagnosis, is of great importance in the early detection and treatment of patients affected by COVID-19. Chest CT may detect the early parenchymal abnormalities in the absence of positive rRT-PCR at initial presentation [2]. Since chest CT was introduced as a diagnostic tool for COVID-19 pneumonia, many typical features of this disease were described such as bilateral multi-lobar ground-glass opacification (GGO) with a prevalent peripheral or posterior distribution, mainly in the lower lobes; sometimes, consolidative opacities superimposed on GGOs could be found [3]. To our knowledge, bronchiectasis is not a classical finding in COVID-19 pneumonia, with a paucity of reporting on its development and progression during the disease course.

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The Impact of COVID-19 on Developing Neurologic Disorders

Authors: Piotr Tekiela,  View ORCID ProfileJennifer J. Majersik

One of the greatest challenges of treating a new virus is the lack of information about it. When little is known about a virus, patients affected by it, as well as their families, are left with uncertainty. In an article appearing in this issue of Neurology®, Dr. Frontera and her team aimed to determine how often patients hospitalized with coronavirus disease 2019 (COVID-19) developed new neurologic disorders.1 They then compared several key outcomes in treatment between patients who developed a new neurologic disorder due to COVID-19 and those who did not. These included discharges to home, ventilator use, length of hospital stay, and in-hospital deaths. These findings can help us understand which groups of people may be more likely to develop more severe disease after having COVID-19, as well as what their prognosis is likely to be.

How Was the Study Done?

The study was run during the first wave of the COVID-19 pandemic, from March 10 through May 20, 2020, in 4 hospitals in the New York City metropolitan area. The researchers set strict guidelines for the type of patients they would include in the study. Patients had to be adults with a laboratory-confirmed severe acute respiratory syndrome coronavirus (SARS-CoV-2) infection. They also had to have been admitted to the hospital at some point during the duration of their illness. Patients who were only seen in an emergency department or at an outpatient clinic were not included in the study.

There are 3 major strengths of this study that set it apart from other studies. First, patients were excluded if they were not tested for SARS-CoV-2 or if they tested negative for the virus. Second, all of the neurologic diagnoses made during the study were determined by a neurologist. Lastly, only new diagnoses of neurologic disease were included in the study. If someone had a neurologic disorder that was known before hospitalization due to COVID-19, that diagnosis was not counted in the study results. This improved the accuracy of diagnosing new neurologic complications that appeared to be caused by COVID-19.

What Were the Results?

A total of 4,491 patients were hospitalized with COVID-19 at the 4 hospitals involved in the study. Of those patients, 606 (13.5%) developed a new neurologic disorder, as diagnosed by a neurologist. These disorders included a confused state in 51% (called a toxic-metabolic encephalopathy), stroke in 14%, seizures in 12%, and brain injury due to lack of oxygen or blood flow (called hypoxic or ischemic disorders) in 11% (see below to learn more about these disorders). The researchers did not find any infections in the brain (such as meningitis or encephalitis) or in the spinal cord (myelitis) in these patients. The patients at highest risk of developing a neurologic disease were older and more likely to be male, White, or diabetic.

For most patients (54%) who developed a neurologic disorder, the disorder appeared about 2 days after the initial COVID-19 symptoms (fever, cough, nausea, vomiting, or diarrhea) arose. In 43% of patients, neurologic problems developed at approximately the same time as their initial COVID-19 symptoms. Only 2% of patients developed neurologic symptoms before onset of the common COVID-19 symptoms.

Development of new neurologic disease was associated with worse outcomes overall. Patients who developed a neurologic disorder along with COVID-19 were 28% less likely to be discharged home from the hospital and 38% more likely to die (either from the illness or from the neurologic disorder). Further, they spent 6 more days on a ventilator and 4 more days in the hospital than patients who did not develop a new neurologic disorder.

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Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Infection in Children and Adolescents A Systematic Review

Authors: Riccardo Castagnoli, MD1,2Martina Votto, MD1,2Amelia Licari, MD1,2et al

Key Points

Question  What are the clinical features of pediatric patients with coronavirus disease 2019 (COVID-19)?

Findings  In this systematic review of 18 studies with 1065 participants, most pediatric patients with SARS-CoV-2 infection presented with fever, dry cough, and fatigue or were asymptomatic; 1 infant presented with pneumonia, complicated by shock and kidney failure, and was successfully treated with intensive care. Most pediatric patients were hospitalized, and symptomatic children received mainly supportive care; no deaths were reported in the age range of 0 to 9 years.

Meaning  Most children with COVID-19 presented with mild symptoms, if any, generally required supportive care only, and typically had a good prognosis and recovered within 1 to 2 weeks.

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Can COVID-19 Immunity Last for Years?

Authors: Christina Aungst, PharmD

Key takeaways:

  • People who were sick with COVID-19 and recovered might have long-term immunity that lasts for months or years.
  • We don’t know how long vaccine immunity lasts yet, but it is much safer to gain immunity from the vaccine than from getting COVID-19.
  • Experts believe the vaccine will still work against the new strains from the U.K. and South Africa, but antibody treatments might not.

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