COVID-19 infections increase risk of long-term brain problems

Authors: Washington University in St. Louis Medical Xpress

COVID-19 infections increase risk of long-term brain problems
A comprehensive analysis of federal data by researchers at Washington University School of Medicine in St. Louis shows people who have had COVID-19 are at an elevated risk of developing neurological conditions within the first year after infection. Movement disorders, memory problems, strokes and seizures are among the complications. Credit: Sara Moser/Washington University School of Medicine

If you’ve had COVID-19, it may still be messing with your brain. Those who have been infected with the virus are at increased risk of developing a range of neurological conditions in the first year after the infection, new research shows. Such complications include strokes, cognitive and memory problems, depression, anxiety and migraine headaches, according to a comprehensive analysis of federal health data by researchers at Washington University School of Medicine in St. Louis and the Veterans Affairs St. Louis Health Care system.

Additionally, the post-COVID brain is associated with movement disorders, from tremors and involuntary muscle contractions to epileptic seizures, hearing and vision abnormalities, and balance and coordination difficulties as well as other symptoms similar to what is experienced with Parkinson’s disease.

The findings are published Sept. 22 in Nature Medicine.

“Our study provides a comprehensive assessment of the long-term neurologic consequences of COVID-19,” said senior author Ziyad Al-Aly, MD, a clinical epidemiologist at Washington University. “Past studies have examined a narrower set of neurological outcomes, mostly in hospitalized patients. We evaluated 44 brain and other neurologic disorders among both nonhospitalized and hospitalized patients, including those admitted to the intensive care unit. The results show the devastating long-term effects of COVID-19. These are part and parcel of long COVID. The virus is not always as benign as some people think it is.”

Overall, COVID-19 has contributed to more than 40 million new cases of neurological disorders worldwide, Al-Aly said.

Other than having a COVID infection, specific risk factors for long-term neurological problems are scarce. “We’re seeing brain problems in previously healthy individuals and those who have had mild infections,” Al-Aly said. “It doesn’t matter if you are young or old, female or male, or what your race is. It doesn’t matter if you smoked or not, or if you had other unhealthy habits or conditions.”

Few people in the study were vaccinated for COVID-19 because the vaccines were not yet widely available during the time span of the study, from March 2020 through early January 2021. The data also predates delta, omicron and other COVID variants.

A previous study in Nature Medicine led by Al-Aly found that vaccines slightly reduce—by about 20%—the risk of long-term brain problems. “It is definitely important to get vaccinated but also important to understand that they do not offer complete protection against these long-term neurologic disorders,” Al-Aly said.

The researchers analyzed about 14 million de-identified medical records in a database maintained by the U.S. Department of Veterans Affairs, the nation’s largest integrated health-care system. Patients included all ages, races and sexes.

They created a controlled data set of 154,000 people who had tested positive for COVID-19 sometime from March 1, 2020, through Jan. 15, 2021, and who had survived the first 30 days after infection. Statistical modeling was used to compare neurological outcomes in the COVID-19 data set with two other groups of people not infected with the virus: a control group of more than 5.6 million patients who did not have COVID-19 during the same time frame; and a control group of more than 5.8 million people from March 2018 to December 31, 2019, long before the virus infected and killed millions across the globe.

The researchers examined brain health over a year-long period. Neurological conditions occurred in 7% more people with COVID-19 compared with those who had not been infected with the virus. Extrapolating this percentage based on the number of COVID-19 cases in the U.S., that translates to roughly 6.6 million people who have suffered brain impairments associated with the virus.

Memory problems—colloquially called brain fog—are one of the most common brain-related, long-COVID symptoms. Compared with those in the control groups, people who contracted the virus were at a 77% increased risk of developing memory problems. “These problems resolve in some people but persist in many others,” Al-Aly said. “At this point, the proportion of people who get better versus those with long-lasting problems is unknown.”

Interestingly, the researchers noted an increased risk of Alzheimer’s disease among those infected with the virus. There were two more cases of Alzheimer’s per 1,000 people with COVID-19 compared with the control groups. “It’s unlikely that someone who has had COVID-19 will just get Alzheimer’s out of the blue,” Al-Aly said. “Alzheimer’s takes years to manifest. But what we suspect is happening is that people who have a predisposition to Alzheimer’s may be pushed over the edge by COVID, meaning they’re on a faster track to develop the disease. It’s rare but concerning.”

Also compared to the control groups, people who had the virus were 50% more likely to suffer from an ischemic stroke, which strikes when a blood clot or other obstruction blocks an artery’s ability to supply blood and oxygen to the brain. Ischemic strokes account for the majority of all strokes, and can lead to difficulty speaking, cognitive confusion, vision problems, the loss of feeling on one side of the body, permanent brain damage, paralysis and death.

“There have been several studies by other researchers that have shown, in mice and humans, that SARS-CoV-2 can attack the lining of the blood vessels and then then trigger a stroke or seizure,” Al-Aly said. “It helps explain how someone with no risk factors could suddenly have a stroke.”

Overall, compared to the uninfected, people who had COVID-19 were 80% more likely to suffer from epilepsy or seizures, 43% more likely to develop mental health disorders such as anxiety or depression, 35% more likely to experience mild to severe headaches, and 42% more likely to encounter movement disorders. The latter includes involuntary muscle contractions, tremors and other Parkinson’s-like symptoms.

COVID-19 sufferers were also 30% more likely to have eye problems such as blurred vision, dryness and retinal inflammation; and they were 22% more likely to develop hearing abnormalities such as tinnitus, or ringing in the ears.

“Our study adds to this growing body of evidence by providing a comprehensive account of the neurologic consequences of COVID-19 one year after infection,” Al-Aly said.

Long COVID’s effects on the brain and other systems emphasize the need for governments and health systems to develop policy, and public health and prevention strategies to manage the ongoing pandemic and devise plans for a post-COVID world, Al-Aly said. “Given the colossal scale of the pandemic, meeting these challenges requires urgent and coordinated—but, so far, absent—global, national and regional response strategies,” he said.

COVID-19 INCREASING STROKE RISKS IN PEOPLE OF ALL AGES

Author: University of Utah Health Communications

The COVID-19 pandemic has been unpredictable as more is learned about the varied side effects of the virus. A typical respiratory infection, such as the flu, usually has a specific set of symptoms and potential complications. With COVID-19, the long-term effects range from neurological complications to loss of taste and smell, trouble focusing (“brain fog”), and chronic fatigue. Another surprising finding from several studies is the heightened risk of stroke and heart attack—and not just for older adults. People under the age of 50 appear to be at much higher risk of these complications too.

One study published in JAMA in April 2021 found that the risk of stroke was more than twice as high for COVID-19 patients when compared to people of the same age, sex, and ethnicity in the general population—82.6 cases per 100,000 people compared to 38.2 cases for those without a COVID-19 diagnosis. 

In another Swedish study published in the August 14, 2021 issue of The Lancet, researchers found that within a week of a COVID-19 diagnosis, a person’s risk of heart attack was three to eight times higher than normal, and their risk of stroke was three to six times higher. The study revealed these risks remained high for at least a month. The average age of people in the study was only 48 years. The data from those diagnosed was compared with 348,000 Swedish people in a similar age range who did not have the virus.

This trend is something Jonathan Kinzinger, DPT, a physical therapist and adjunct assistant professor at University of Utah Health who works with stroke patients at the Craig H. Neilsen Rehabilitation Hospital, has seen up close. 

“We are definitely seeing a huge increase in younger stroke survivors who are post-COVID diagnosis,” Kinzinger says. “We know that vascular complications go along with COVID infections, which can lead to strokes and other cardiovascular issues.”

group of researchers headed by Mark Ellul, PhD, NIHR Clinical Lecturer in Neurology at the Institute of Infection, Veterinary and Ecological Sciences from the University of Liverpool, first observed this in September 2020. They found that the number of patients admitted to the hospital with a large vessel stroke who also had a COVID-19 diagnosis was seven times higher than normal.

Similar findings have also come out of other countries, where the median age for patients who needed thrombectomy surgery to remove a blood clot was down across the board. In one New York Medical Center, the average age of patients with confirmed stroke and COVID-19 diagnosis was 63 years. The average age of stroke patients who tested negative for COVID was much higher (70 years), even when they controlled for age, sex, and other risk factors.

Researchers are still studying the cause of the increased risk. But doctors know that COVID-19 causes an inflammatory response that thickens a person’s blood. Thicker blood is more likely to clot, and clots can lead to stroke. Many of the young people who suffer a stroke after a COVID-19 diagnosis have few (and sometimes no) risk factors normally associated with stroke.

Sometimes these strokes don’t occur for several weeks after a COVID-19 diagnosis, and it’s impossible to predict who might be at risk. For patients recovering from COVID-19 and a stroke, there is the added challenge of an impaired cardio-respiratory system. “Not only are we dealing with strength, motor, and balance deficits that go along with stroke, we also have to work around respiratory issues, tracheostomies, and other complications,” Kinzinger says. Stroke recovery is physically and mentally challenging anyway, and these complications can increase recovery time.

“When someone has a stroke and they are under 50, their whole life is uprooted,” he says. “A lot of people have younger kids or spouses, they may have a career or they’re going to school, so it’s just such a different phase of life than someone who is older.”

What heart and stroke patients need to know about COVID-19 in 2022

Authors: Michael Merschel, American Heart Association News

Two years into the pandemic, researchers have learned a lot about how COVID-19 affects people with heart disease and stroke survivors. But like the coronavirus itself, what everyone needs to know keeps evolving.

“You can’t assume that what was true three months ago is true now,” said Dr. James de Lemos, a cardiologist at UT Southwestern Medical Center in Dallas. Thanks to the omicron variant, “it’s a fundamentally different pandemic than it was at Thanksgiving.”

Early data suggests omicron causes less severe illness but spreads more easily than its predecessors. So heart and stroke patients need to protect themselves, starting with understanding that COVID-19 still is a threat to their health.

“Early on, we recognized that the risk was higher for those with pre-existing cardiovascular disease,” said Dr. Biykem Bozkurt, a cardiologist at Baylor College of Medicine in Houston. According to the Centers for Disease Control and Prevention, people with conditions such as heart failure, coronary artery disease and possibly high blood pressure may be more likely to get severely ill from COVID-19. So can people who have diabetes, are overweight or are recovering from a stroke.

SARS-CoV-2, the virus that causes COVID-19, also has been linked to increased risk of several cardiovascular conditions. According to a September 2021 report from the CDC, people with COVID-19 are nearly 16 times more likely to have heart inflammation, or myocarditis, than uninfected people. The report found about 150 cases per 100,000 people with COVID-19 versus about nine cases per 100,000 people without the virus.

In addition, an August 2021 study in the New England Journal of Medicine showed people with the coronavirus may have a significantly higher, albeit rare, risk of intracranial hemorrhage, or brain bleeding; heart attack; and having an arrhythmia, or abnormal heartbeat.

Researchers don’t have full data on omicron’s effects yet, Bozkurt said, but it’s still affecting people who are vulnerable. “And that’s why the hospitals right now are full.”

The risks of any one person having a severe problem from the new variant are relatively small, de Lemos said. “But the flipside is, given how many people are getting infected right now, the cumulative number of people with COVID-19 complications is still very large.”

De Lemos, who helped create the American Heart Association’s COVID-19 Cardiovascular Disease Registry, said omicron “is obviously wildly more infectious and able to evade the vaccine to some extent, although it does appear that the vaccine seems to prevent severe infections and hospitalizations.”

And overall, “we don’t know a ton about specifically why certain patients with heart disease do less well,” he said, although understanding has evolved over time.

In the beginning, de Lemos said, doctors feared the virus directly infected the heart muscle. “That doesn’t really appear to be the case,” he said.

Instead, it appears that in severe cases, the virus is inflaming the lining of blood vessels of the heart and increasing the likelihood of clotting in the smallest vessels, he said.

COVID-19 also can overwhelm the heart by making it work harder to pump oxygenated blood through the body as the lungs are overwhelmed.

But as they’ve learned more about the coronavirus, doctors have gotten better at fighting it. For example, de Lemos said, they now work proactively to treat blood-clotting disorders in hospitalized patients. And although researchers are working to understand lingering effects known as “long COVID,” it appears long-term implications for the heart look favorable.

“The vast majority of people who have mild COVID infections really appear to have nothing to worry about with their hearts,” he said. “That’s good news, I think, and doesn’t get emphasized enough.”

People with existing heart conditions or a history of stroke still need to protect themselves, and have many ways of doing so.

“Number one: Get vaccinated,” said Bozkurt, who has studied COVID-19 vaccine side effects. “And please, do get a booster.” Reports of rare cases of vaccine-related myocarditis, particularly in younger males, should not dissuade anybody with an existing condition. Most people with pre-existing cardiovascular disease are not young adult males, she noted. And regardless of age, the benefits from vaccines outweigh the risks.

Given how the vaccines don’t seem to be as protective against the spread of omicron, de Lemos said if you’re a heart disease or stroke patient, hunker down for the next several weeks until this wave passes, “and then you’ll be able to re-emerge.”

Patients should avoid indoor crowds, he said, and use a KN95 mask or, when possible, an N95 mask instead of cloth masks when being in a crowd is necessary.

Bozkurt said heart and stroke patients should keep in contact with their health care team and continue taking medications as prescribed. Anybody with symptoms that could be heart-related should seek care immediately. “Do not delay,” she said.

Both doctors said it was important to get information from reliable sources. Some false remedies promoted on social media can actually damage the heart, Bozkurt said.

De Lemos acknowledged that even from reliable sources, advice can shift. “I would say that the information is written in pencil, not in pen, because things are changing so fast.” It can be frustrating for him, even as a scientist, when experts disagree or alter their recommendations, but “that’s the way science goes.”

And even as COVID-19 “remains a bizarrely arbitrary virus in terms of who gets sick and who doesn’t,” he’s optimistic.

“Think about all the progress we’ve made in a year or two, and the remarkable effect of the vaccines, the fact that we have drugs” that should help keep people out of hospitals. Heart and stroke patients need to be extra careful right now, but “as frustrating as it is, we will not be in this situation forever. We really won’t.”

Editor’s note: Because of the rapidly evolving events surrounding the coronavirus, the facts and advice presented in this story may have changed since publication. Visit Heart.org for the latest coverage, and check with the Centers for Disease Control and Prevention and local health officials for the most recent guidance.

If you have questions or comments about this story, please email editor@heart.org.

6-month neurological and psychiatric outcomes in 236,379 survivors of COVID-19: a retrospective cohort study using electronic health records

Authors: Maxime Taquet, John R Geddes, Masud Husain, Sierra Luciano, Paul J Harrison

Summary

Background Neurological and psychiatric sequelae of COVID-19 have been reported, but more data are needed to adequately assess the effects of COVID-19 on brain health. We aimed to provide robust estimates of incidence rates and relative risks of neurological and psychiatric diagnoses in patients in the 6 months following a COVID-19 diagnosis. Methods For this retrospective cohort study and time-to-event analysis, we used data obtained from the TriNetX electronic health records network (with over 81 million patients). Our primary cohort comprised patients who had a COVID-19 diagnosis; one matched control cohort included patients diagnosed with influenza, and the other matched control cohort included patients diagnosed with any respiratory tract infection including influenza in the same period. Patients with a diagnosis of COVID-19 or a positive test for SARS-CoV-2 were excluded from the control cohorts. All cohorts included patients older than 10 years who had an index event on or after Jan 20, 2020, and who were still alive on Dec 13, 2020. We estimated the incidence of 14 neurological and psychiatric outcomes in the 6 months after a confirmed diagnosis of COVID-19: intracranial haemorrhage; ischaemic stroke; parkinsonism; Guillain-Barré syndrome; nerve, nerve root, and plexus disorders; myoneural junction and muscle disease; encephalitis; dementia; psychotic, mood, and anxiety disorders (grouped and separately); substance use disorder; and insomnia. Using a Cox model, we compared incidences with those in propensity score-matched cohorts of patients with influenza or other respiratory tract infections. We investigated how these estimates were affected by COVID-19 severity, as proxied by hospitalisation, intensive therapy unit (ITU) admission, and encephalopathy (delirium and related disorders). We assessed the robustness of the differences in outcomes between cohorts by repeating the analysis in different scenarios. To provide benchmarking for the incidence and risk of neurological and psychiatric sequelae, we compared our primary cohort with four cohorts of patients diagnosed in the same period with additional index events: skin infection, urolithiasis, fracture of a large bone, and pulmonary embolism. Findings Among 236 379 patients diagnosed with COVID-19, the estimated incidence of a neurological or psychiatric diagnosis in the following 6 months was 33·62% (95% CI 33·17–34·07), with 12·84% (12·36–13·33) receiving their first such diagnosis. For patients who had been admitted to an ITU, the estimated incidence of a diagnosis was 46·42% (44·78–48·09) and for a first diagnosis was 25·79% (23·50–28·25). Regarding individual diagnoses of the study outcomes, the whole COVID-19 cohort had estimated incidences of 0·56% (0·50–0·63) for intracranial haemorrhage, 2·10% (1·97–2·23) for ischaemic stroke, 0·11% (0·08–0·14) for parkinsonism, 0·67% (0·59–0·75) for dementia, 17·39% (17·04–17·74) for anxiety disorder, and 1·40% (1·30–1·51) for psychotic disorder, among others. In the group with ITU admission, estimated incidences were 2·66% (2·24–3·16) for intracranial haemorrhage, 6·92% (6·17–7·76) for ischaemic stroke, 0·26% (0·15–0·45) for parkinsonism, 1·74% (1·31–2·30) for dementia, 19·15% (17·90–20·48) for anxiety disorder, and 2·77% (2·31–3·33) for psychotic disorder. Most diagnostic categories were more common in patients who had COVID-19 than in those who had influenza (hazard ratio [HR] 1·44, 95% CI 1·40–1·47, for any diagnosis; 1·78, 1·68–1·89, for any first diagnosis) and those who had other respiratory tract infections (1·16, 1·14–1·17, for any diagnosis; 1·32, 1·27–1·36, for any first diagnosis). As with incidences, HRs were higher in patients who had more severe COVID-19 (eg, those admitted to ITU compared with those who were not: 1·58, 1·50–1·67, for any diagnosis; 2·87, 2·45–3·35, for any first diagnosis). Results were robust to various sensitivity analyses and benchmarking against the four additional index health events. Interpretation Our study provides evidence for substantial neurological and psychiatric morbidity in the 6 months after COVID-19 infection. Risks were greatest in, but not limited to, patients who had severe COVID-19. This information could help in service planning and identification of research priorities. Complementary study designs, including prospective cohorts, are needed to corroborate and explain these findings. Funding National Institute for Health Research (NIHR) Oxford Health Biomedical Research Centre. Copyright © 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Articles www.thelancet.com/psychiatry Vol 8 May 2021 417 Introduction Since the COVID-19 pandemic began on March 11, 2020, there has been concern that survivors might be at an increased risk of neurological disorders. This concern, initially based on findings from other coronaviruses,1 was followed rapidly by case series,2–4 emerging evidence of COVID-19 CNS involvement,5–7 and the identification of mechanisms by which this could occur.8–11 Similar concerns have been raised regarding psychiatric sequelae of COVID-19,12,13 with evidence showing that survivors are indeed at increased risk of mood and anxiety disorders in the 3 months after infection.14 However, we need large scale, robust, and longer term data to properly identify and quantify the consequences of the COVID-19 pandemic on brain health. Such information is required both to plan services and identify research priorities. In this study, we used an electronic health records network to investigate the incidence of neurological and psychiatric diagnoses in survivors in the 6 months after documented clinical COVID-19 infection, and we compared the associated risks with those following other health conditions. We explored whether the severity of COVID-19 infection, as proxied by hospitalization, intensive therapy unit (ITU) admission, and encephalopathy, affects these risks. We also assessed the trajectory of hazard ratios (HRs) across the 6-month period. Methods Study design and data collection For this retrospective cohort study, we used The TriNetX Analytics Network, a federated network recording anonymized data from electronic health records in 62 health-care organizations, primarily in the USA, comprising 81 million patients. Available data include demographics, diagnoses (using codes from ICD-10), medications, procedures, and measurements (eg, blood pressure and body-mass index). The health-care organizations are a mixture of hospitals, primary care, and specialist providers, contributing data from uninsured and insured patients. These organizations warrant that they have all necessary rights, consents, approvals, and authority to provide the data to TriNetX, so long as their name remains anonymous as a data source and their data are used for research purposes. By use of the TriNetX user interface, cohorts can be created on the basis of inclusion and exclusion criteria, matched for confounding variables with a built-in propensity score-matching algorithm, and compared for outcomes of interest over specified time periods. Additional details about TriNetX, its data, provenance, and functionalities, are presented in the appendix (pp 1–2). Cohorts The primary cohort was defined as all patients who had a confirmed diagnosis of COVID-19 (ICD-10 code U07.1). We also constructed two matched control cohorts: patients diagnosed with influenza (ICD-10 codes J09–11) and patients diagnosed with any respiratory tract infection including influenza (ICD-10 codes J00–06, J09–18, or J20–22). We excluded patients with a diagnosis of COVID-19 or a positive test for SARS-CoV-2 from the control cohorts. We refer to the diagnosis of COVID-19 (in the primary cohort) and influenza or other respiratory See Online for appendix For the TriNetX Analytics Network see www.trinetx.com Research in context Evidence before this study We searched Web of Science and Medline on Aug 1 and Dec 31, 2020, for studies in English, with the terms “(COVID-19 OR SARS-CoV2 OR SARS-CoV-2) AND (psychiatry* or neurology*) AND (incidence OR epidemiology* OR ‘systematic review’ or ‘meta-analysis’)”. We found case series and reviews of series reporting neurological and neuropsychiatric disorders during acute COVID-19 illness. We found one large electronic health records study of the psychiatric sequelae in the 3 months after a COVID-19 diagnosis. It reported an increased risk for anxiety and mood disorders and dementia after COVID-19 compared with a range of other health events; the study also reported the incidence of each disorder. We are not aware of any large-scale data regarding the incidence or relative risks of neurological diagnoses in patients who had recovered from COVID-19. Added value of this study To our knowledge, we provide the first meaningful estimates of the risks of major neurological and psychiatric conditions in the 6 months after a COVID-19 diagnosis, using the electronic health records of over 236000 patients with COVID-19. We report their incidence and hazard ratios compared with patients who had had influenza or other respiratory tract infections. We show that both incidence and hazard ratios were greater in patients who required hospitalization or admission to the intensive therapy unit (ITU), and in those who had encephalopathy (delirium and other altered mental states) during the illness compared with those who did not. Implications of all the available evidence COVID-19 was robustly associated with an increased risk of neurological and psychiatric disorders in the 6 months after a diagnosis. Given the size of the pandemic and the chronicity of many of the diagnoses and their consequences (eg, dementia, stroke, and intracranial hemorrhage), substantial effects on health and social care systems are likely to occur. Our data provide important evidence indicating the scale and nature of services that might be required. The findings also highlight the need for enhanced neurological follow-up of patients who were admitted to ITU or had encephalopathy during their COVID-19 illness. Articles 418 www.thelancet.com/psychiatry Vol 8 May 2021 tract infections (in the control cohorts) as index events. The cohorts included all patients older than 10 years who had an index event on or after Jan 20, 2020 (the date of the first recorded COVID-19 case in the USA), and who were still alive at the time of the main analysis (Dec 13, 2020). Additional details on cohorts are provided in the appendix (pp 2–3). Covariates We used a set of established and suspected risk factors for COVID-19 and for more severe COVID-19 illness:15,16 age, sex, race, ethnicity, obesity, hypertension, diabetes, chronic kidney disease, asthma, chronic lower respiratory diseases, nicotine dependence, substance use disorder, ischemic heart disease and other forms of heart disease, socioeconomic deprivation, cancer (and hematological cancer in particular), chronic liver disease, stroke, dementia, organ transplant, rheumatoid arthritis, lupus, psoriasis, and disorders involving an immune mechanism. To capture these risk factors in patients’ health records, we used 55 variables. More details, including ICD-10 codes, are provided in the appendix (pp 3–4). Cohorts were matched for all these variables, as described in the following subsections. Outcomes We investigated neurological and psychiatric sequelae of COVID-19 in terms of 14 outcomes occurring 1–180 days after the index event: intracranial hemorrhage (ICD-10 codes I60–62); ischemic stroke (I63); Parkinson’s disease and parkinsonism (G20–21); Guillain-Barré syndrome (G61.0); nerve, nerve root, and plexus disorders (G50–59); myoneural junction and muscle disease (neuromuscular disorders; G70–73); encephalitis (G04, G05, A86, or A85.8); dementia (F01–03, G30, G31.0, or G31.83); psychotic, mood, and anxiety disorders (F20–48), as well as each category separately; substance use disorder (F10–19), and insomnia (F51.0 or G47.0). For outcomes that are chronic illnesses (eg, dementia or Parkinson’s disease), we excluded patients who had the diagnosis before the index event. For outcomes that All patients Patients without hospitalization Patients with hospitalization Patients with ITU admission Patients with encephalopathy Cohort size 236379 (100·0%) 190077 (100·0%) 46302 (100·0%) 8945 (100·0%) 6229 (100·0%) Demographics Age, years 46 (19·7) 43·3 (19·0) 57 (18·7) 59·1 (17·3) 66·7 (17·0) Sex Male 104015 (44·0%) 81 512 (42·9%) 22 503 (48·6%) 5196 (58·1%) 3307 (53·1%) Female 131460 (55·6%) 107 730 (56·7%) 23 730 (51·3%) 3743 (41·8%) 2909 (46·7%) Other 904 (0·4%) 835 (0·4%) 69 (0·1%) 10 (0·1%) 13 (0·2%) Race White 135 143 (57·2%) 109635 (57·7%) 25 508 (55·1%) 4918 (55·0%) 3331 (53·5%) Black or African American 44459 (18·8%) 33868 (17·8%) 10591 (22·9%) 2184 (24·4%) 1552 (24·9%) Unknown 48085 (20·3%) 39841 (21·0%) 8244 (17·8%) 1457 (16·3%) 1071 (17·2%) Ethnicity Hispanic or Latino 37 772 (16·0%) 29155 (15·3%) 8617 (18·6%) 2248 (25·1%) 895 (14·4%) Not Hispanic or Latino 134075 (56·7%) 106844 (56·2%) 27 231 (58·8%) 5041 (56·4%) 3873 (62·2%) Unknown 64532 (27·3%) 54078 (28·5%) 10454 (22·6%) 1656 (18·5%) 1461 (23·5%) Comorbidities Overweight and obesity 42871 (18·1%) 30198 (15·9%) 12673 (27·4%) 3062 (34·2%) 1838 (29·5%) Hypertensive disease 71014 (30·0%) 47 516 (25·0%) 23498 (50·7%) 5569 (62·3%) 4591 (73·7%) Type 2 diabetes 36696 (15·5%) 22 518 (11·8%) 14178 (30·6%) 3787 (42·3%) 2890 (46·4%) Asthma 25 104 (10·6%) 19834 (10·4%) 5270 (11·4%) 1132 (12·7%) 755 (12·1%) Nicotine dependence 17 105 (7·2%) 12639 (6·6%) 4466 (9·6%) 1042 (11·6%) 803 (12·9%) Substance use disorder 24870 (10·5%) 18173 (9·6%) 6697 (14·5%) 1620 (18·1%) 1316 (21·1%) Ischemic heart diseases 21082 (8·9%) 11815 (6·2%) 9267 (20·0%) 2460 (27·5%) 2200 (35·3%) Other forms of heart disease 42431 (18·0%) 26066 (13·7%) 16365 (35·3%) 4678 (52·3%) 3694 (59·3%) Chronic kidney disease 15908 (6·7%) 8345 (4·4%) 7563 (16·3%) 1941 (21·7%) 1892 (30·4%) Neoplasms 45 255 (19·1%) 34362 (18·1%) 10893 (23·5%) 2339 (26·1%) 1793 (28·8%) Data are n (%) or mean (SD). Only characteristics with a prevalence higher than 5% in the whole population are displayed. Additional baseline characteristics are presented in the appendix (pp 25–27). ITU=intensive therapy unit. Table 1: Baseline characteristics for the whole COVID-19 cohort and for the non-hospitalization, hospitalization, ITU admission, and encephalopathy cohorts during the illness Articles www.thelancet.com/psychiatry Vol 8 May 2021 419 tend to recur or relapse (eg, ischaemic strokes or psychiatric diagnoses), we estimated separately the incidence of first diagnoses (ie, excluding those who had a diagnosis before the index event) and the incidence of any diagnosis (ie, including patients who had a diagnosis at some point before the index event). For other outcomes (eg, Guillain-Barré syndrome), we estimated the incidence of any diagnosis. More details, and a full list of ICD-10 codes, are provided in the appendix (pp 4–5). Finally, to assess the overall risk of neurological and psychiatric outcomes after COVID-19, we estimated the incidence of any of the 14 outcomes, and the incidence of a first diagnosis of any of the outcomes. This is lower than the sum of incidences of each outcome because some patients had more than one diagnosis. Secondary analyses We investigated whether the neurological and psychiatric sequelae of COVID-19 were affected by the severity of the illness. The incidence of outcomes was estimated separately in four subgroups: first, in those who had required hospitalization within a time window from 4 days before their COVID-19 diagnosis (taken to be the time it might take between clinical presentation and confirmation) to 2 weeks afterwards; second, in those who had not required hospitalization during that window; third, in those who had been admitted to an intensive therapy unit (ITU) during that window; and fourth, in those who were diagnosed with delirium or other forms of altered mental status during that window; we use the term encephalopathy to describe this group of patients (appendix p 5).17,18 Differences in outcome incidence between these subgroups might reflect differences in their baseline characteristics. Therefore, for each outcome, we estimated the HR between patients requiring hospitalization (or ITU) and a matched cohort of patients not requiring hospitalization (or ITU), and between patients with encephalopathy and a matched cohort of patients without encephalopathy. Finally, HRs were calculated for patients who had not required hospitalization for COVID-19, influenza, or other respiratory tract infections. To provide benchmarks for the incidence and risk of neurological and psychiatric sequelae, patients after COVID-19 were compared with those in four additional matched cohorts of patients diagnosed with health events selected to represent a range of acute presentations during the same time period. These additional four index events were skin infection, urolithiasis, fracture of a large bone, and pulmonary embolism. More details are presented in the appendix (pp 5–6). We assessed the robustness of the differences in outcomes between cohorts by repeating the analysis in three scenarios: one including patients who had died by All patients Patients without hospitalization Patients with hospitalization Patients with ITU admission Patients with encephalopathy Intracranial hemorrhage (any) 0·56% (0·50–0·63) 0·31% (0·25–0·39) 1·31% (1·14–1·52) 2·66% (2·24–3·16) 3·61% (2·97–4·39) Intracranial hemorrhage (first) 0·28% (0·23–0·33) 0·14% (0·10–0·20) 0·63% (0·50–0·80) 1·05% (0·79–1·40) 1·19% (0·82–1·70) Ischemic stroke (any) 2·10% (1·97–2·23) 1·33% (1·22–1·46) 4·38% (4·05–4·74) 6·92% (6·17–7·76) 9·35% (8·23–10·62) Ischemic stroke (first) 0·76% (0·68–0·85) 0·43% (0·36–0·52) 1·60% (1·37–1·86) 2·82% (2·29–3·47) 3·28% (2·51–4·27) Parkinsonism 0·11% (0·08–0·14) 0·07% (0·05–0·12) 0·20% (0·15–0·28) 0·26% (0·15–0·45) 0·46% (0·28–0·78) Guillain-Barré syndrome 0·08% (0·06–0·11) 0·05% (0·03–0·07) 0·22% (0·15–0·32) 0·33% (0·21–0·54) 0·48% (0·20–1·14) Nerve, nerve root, or plexus disorders 2·85% (2·69–3·03) 2·69% (2·51–2·89) 3·35% (3·02–3·72) 4·24% (3·58–5·03) 4·69% (3·81–5·77) Myoneural junction or muscle disease 0·45% (0·40–0·52) 0·16% (0·12–0·20) 1·24% (1·05–1·46) 3·35% (2·76–4·05) 3·27% (2·54–4·21) Encephalitis 0·10% (0·08–0·13) 0·05% (0·03–0·08) 0·24% (0·17–0·33) 0·35% (0·19–0·64) 0·64% (0·39–1·07) Dementia 0·67% (0·59–0·75) 0·35% (0·29–0·43) 1·46% (1·26–1·71) 1·74% (1·31–2·30) 4·72% (3·80–5·85) Mood, anxiety, or psychotic disorder (any) 23·98% (23·58–24·38) 23·59% (23·12–24·07) 24·50% (23·76–25·26) 27·78% (26·33–29·29) 36·25% (34·16–38·43) Mood, anxiety, or psychotic disorder (first) 8·63% (8·28–8·98) 8·15% (7·75–8·57) 8·85% (8·22–9·52) 12·68% (11·28–14·24) 12·96% (11·13–15·07) Mood disorder (any) 13·66% (13·35–13·99) 13·10% (12·73–13·47) 14·69% (14·09–15·32) 15·43% (14·27–16·68) 22·52% (20·71–24·47) Mood disorder (first) 4·22% (3·99–4·47) 3·86% (3·60–4·14) 4·49% (4·05–4·99) 5·82% (4·86–6·97) 8·07% (6·56–9·90) Anxiety disorder (any) 17·39% (17·04–17·74) 17·51% (17·09–17·93) 16·40% (15·76–17·06) 19·15% (17·90–20·48) 22·43% (20·65–24·34) Anxiety disorder (first) 7·11% (6·82–7·41) 6·81% (6·47–7·16) 6·91% (6·38–7·47) 9·79% (8·65–11·06) 9·24% (7·70–11·07) Psychotic disorder (any) 1·40% (1·30–1·51) 0·93% (0·83–1·04) 2·89% (2·62–3·18) 2·77% (2·31–3·33) 7·00% (6·01–8·14) Psychotic disorder (first) 0·42% (0·36–0·49) 0·25% (0·19–0·33) 0·89% (0·72–1·09) 0·70% (0·46–1·06) 2·12% (1·53–2·94) Substance use disorder (any) 6·58% (6·36–6·80) 5·87% (5·63–6·13) 8·56% (8·10–9·04) 10·14% (9·25–11·10) 11·85% (10·55–13·31) Substance use disorder (first) 1·92% (1·77–2·07) 1·74% (1·58–1·91) 2·09% (1·82–2·40) 3·15% (2·60–3·82) 2·58% (1·91–3·47) Insomnia (any) 5·42% (5·20–5·64) 5·16% (4·91–5·42) 5·95% (5·53–6·39) 7·50% (6·66–8·44) 9·82% (8·57–11·24) Insomnia (first) 2·53% (2·37–2·71) 2·23% (2·05–2·43) 3·14% (2·81–3·51) 4·24% (3·55–5·07) 5·05% (4·10–6·20) Any outcome 33·62% (33·17–34·07) 31·74% (31·22–32·27) 38·73% (37·87–39·60) 46·42% (44·78–48·09) 62·34% (60·14–64·55) Any first outcome 12·84% (12·36–13·33) 11·51% (10·98–12·07) 15·29% (14·32–16·33) 25·79% (23·50–28·25) 31·13% (27·29–35·36) Data are percentage at 6 months (95% CI). Additional outcomes are presented in the appendix (pp 27–28). ITU=intensive therapy unit. Table 2: Major outcomes for the whole COVID-19 cohort, and for the non-hospitalization, hospitalization, ITU admission, and encephalopathy cohorts during the illness Articles 420 www.thelancet.com/psychiatry Vol 8 May 2021 the time of the analysis, another restricting the COVID-19 diagnoses to patients who had a positive RNA or antigen test (and using antigen test as an index event), and another comparing the rates of sequelae of patients with COVID-19 with those observed in patients with influenza before the pandemic (ie, in 2019 or 2018). Details of these analyses are provided in the appendix (p 6). Finally, to test whether differences in sequelae between cohorts could be accounted for by differences in extent of follow-up, we counted the average number of health visits that each cohort had during the follow-up period. Statistical analysis We used propensity score matching19 to create cohorts with matched baseline characteristics, done within the TriNetX network. Propensity score with 1:1 matching used a greedy nearest neighbor matching approach with a caliper distance of 0·1 pooled SDs of the logit of the propensity score. Any characteristic with a standardized mean difference between cohorts lower than 0·1 was considered well matched.20 The incidence of each outcome was estimated by use of the KaplanMeier estimator. Comparisons between cohorts were made with a log-rank test. We calculated HRs with 95% CIs using a proportional hazard model wherein the cohort to which the patient belonged was used as the independent variable. The proportional hazard assumption was tested with the generalized Schoenfeld approach. When the assumption was violated, the time varying HR was assessed with natural cubic splines fitted to the log cumulative hazard.21 Additional details are presented in the appendix (p 6). Statistical analyses were done in R, version 3.4.3, except for the log-rank tests, which were done within TriNetX. Statistical significance was set at two-sided p-value <0⋅05. Our study was reported according to the Reporting of studies Conducted using Observational Routinely collected health Data (RECORD, appendix pp 55–60). Role of the funding source The funder of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the manuscript. Results Our primary cohort comprised 236 379 patients diagnosed with COVID-19, and our two propensity-score matched control cohorts comprised 105579 patients diagnosed with influenza and 236 038 patients diagnosed with any respiratory tract infection including influenza. The COVID-19 cohort was divided into subgroups of patients who were not hospitalized (190077 patients), those who were hospitalized (46 302 patients), those who required ITU admission (8945 patients), and those who received a diagnosis of encephalopathy (6229 patients). The main demographic features and comorbidities of the COVID-19 cohort are summarized in table 1, with additional demographic details presented in the appendix (pp 25–27). Matched baseline characteristics of the two control cohorts are also presented in the appendix (pp 29–30 for patients with influenza, and pp 31–32 for patients with other respiratory tract infections). Adequate propensity-score matching (standardized mean dif­ference <0·1) was achieved for all comparisons and baseline characteristics. We estimated the diagnostic incidence of the neurological and psychiatric outcomes of the primary cohort in the 6 months after a COVID-19 diagnosis. In the whole cohort, 33·62% (95% CI 33·17–34·07) of patients received a diagnosis (table 2). For the cohort subgroups, these estimates were 38·73% (37·87–39·60) for patients who were hospitalized, 46·42% (44·78–48·09) for those admitted to ITU, and 62·34% (60·14–64·55) for those diagnosed with COVID-19 vs influenza (N=105 579)* COVID-19 vs other RTI (N=236038)* HR (95% CI) p value HR (95% CI) p value Intracranial hemorrhage (any) 2·44 (1·89–3·16) <0·0001 1·26 (1·11–1·43) 0·0003 Intracranial hemorrhage (first) 2·53 (1·68–3·79) <0·0001 1·56 (1·27–1·92) <0·0001 Ischemic stroke (any) 1·62 (1·43–1·83) <0·0001 1·45 (1·36–1·55) <0·0001 Ischemic stroke (first) 1·97 (1·57–2·47) <0·0001 1·63 (1·44–1·85) <0·0001 Parkinsonism 1·42 (0·75–2·67) 0·19 1·45 (1·05–2·00) 0·020 Guillain-Barré syndrome 1·21 (0·72–2·04) 0·41 2·06 (1·43–2·96) <0·0001 Nerve, nerve root, or plexus disorders 1·64 (1·50–1·81) <0·0001 1·27 (1·19–1·35) <0·0001 Myoneural junction or muscle disease 5·28 (3·71–7·53) <0·0001 4·52 (3·65–5·59) <0·0001 Encephalitis 1·70 (1·04–2·78) 0·028 1·41 (1·03–1·92) 0·028 Dementia 2·33 (1·77–3·07) <0·0001 1·71 (1·50–1·95) <0·0001 Mood, anxiety, or psychotic disorder (any) 1·46 (1·43–1·50) <0·0001 1·20 (1·18–1·23) <0·0001 Mood, anxiety, or psychotic disorder (first) 1·81 (1·69–1·94) <0·0001 1·48 (1·42–1·55) <0·0001 Mood disorder (any) 1·47 (1·42–1·53) <0·0001 1·23 (1·20–1·26) <0·0001 Mood disorder (first) 1·79 (1·64–1·95) <0·0001 1·41 (1·33–1·50) <0·0001 Anxiety disorder (any) 1·45 (1·40–1·49) <0·0001 1·17 (1·15–1·20) <0·0001 Anxiety disorder (first) 1·78 (1·66–1·91) <0·0001 1·48 (1·42–1·55) <0·0001 Psychotic disorder (any) 2·03 (1·78–2·31) <0·0001 1·66 (1·53–1·81) <0·0001 Psychotic disorder (first) 2·16 (1·62–2·88) <0·0001 1·82 (1·53–2·16) <0·0001 Substance use disorder (any) 1·27 (1·22–1·33) <0·0001 1·09 (1·05–1·12) <0·0001 Substance use disorder (first) 1·22 (1·09–1·37) 0·0006 0·92 (0·86–0·99) 0·033 Insomnia (any) 1·48 (1·38–1·57) <0·0001 1·15 (1·10–1·20) <0·0001 Insomnia (first) 1·92 (1·72–2·15) <0·0001 1·43 (1·34–1·54) <0·0001 Any outcome 1·44 (1·40–1·47) <0·0001 1·16 (1·14–1·17) <0·0001 Any first outcome 1·78 (1·68–1·89) <0·0001 1·32 (1·27–1·36) <0·0001 Additional details on cohort characteristics and diagnostic subcategories are presented in the appendix (pp 29–33). HR=hazard ratio. RTI=respiratory tract infection. *Matched cohorts. Table 3: HRs for the major outcomes in patients after COVID-19 compared with those after influenza and other RTIs Articles www.thelancet.com/psychiatry Vol 8 May 2021 421 encephalopathy. A similar, but more marked, increasing trend was observed for patients receiving their first recorded neurological or psychiatric diagnosis (table 2). Results according to sex, race, and age are shown in the appendix (p 28). The baseline characteristics of the COVID-19 cohort divided into those who did versus those who did not have a neurological or psychiatric outcome are also shown in the appendix (p 7). We assessed the probability of the major neurological and psychiatric outcomes in patients diagnosed with COVID-19 compared with the matched cohorts diagnosed with other respiratory tract infections and with influenza (table 3; figure 1, appendix pp 8–10). Most diagnostic categories were more common in patients who had COVID-19 than in those who had influenza (HR 1·44, 95% CI 1·40–1·47 for any diagnosis; 1·78, 1·68–1·89 for any first diagnosis) and those who had other respiratory tract infections (1·16, 1·14–1·17 for any diagnosis; 1·32, 1·27–1·36 for any first diagnosis). Hazard rates were also higher in patients who were admitted to ITU than in those who were not (1·58, 1·50–1·67 for any diagnosis; 2·87, 2·45–3·35 for any first diagnosis). HRs were significantly greater than 1 for all diagnoses for patients who had COVID-19 compared with those who had influenza, except for parkinsonism and Guillain-Barré syndrome, and significantly greater than 1 for all diagnoses compared with patients who had respiratory tract infections (table 3). Similar results were observed when patients who had COVID-19 were compared with those who had Figure 1: Kaplan-Meier estimates for the incidence of major outcomes after COVID-19 compared with other RTIs Shaded areas are 95% CIs. For incidences of first diagnoses, the number in brackets corresponds to all patients who did not have the outcome before the follow-up period. For diagnostic subcategories, see appendix (pp 8–10). RTI=respiratory tract infection. Number at risk COVID-19 Other RTI 0 50 100 150 200 92579 131885 67102 116315 Intracranial haemorrhage (any) 50172 103261 32705 90066 20679 77005 12775 65909 0 0·2 0·6 0·4 0·8 Outcome probability (%) 30 60 90 120 150 180 0 50 100 150 200 91998 131352 66499 115264 48528 102599 32265 89412 20361 76367 11415 63334 0 0·5 2·0 1·5 2·5 30 60 90 120 150 180 0 50 100 150 200 92193 131363 66587 115073 48488 102233 32186 88929 19962 75806 11585 62702 0 1·0 3·0 2·0 4·0 30 60 90 120 150 180 COVID-19 (n=236038) Other RTI (n=236038) COVID-19 (n=236038) Other RTI (n=236038) COVID-19 (n=236038) Other RTI (n=236038) Ischaemic stroke (any) Nerve, nerve root, or plexus disorder Number at risk COVID-19 Other RTI 0 50 100 Time since index event (days) Time since index event (days) Time since index event (days) 150 200 91646 133203 66346 115207 Myoneural junction or muscle disease 50653 102653 34259 90454 21522 76919 11895 63909 0 0·2 0·1 0·5 0·4 0·3 0·6 Outcome probability (%) 30 60 90 120 150 180 0 50 100 150 200 89958 128680 65186 113623 47578 101313 32182 88082 19593 75359 12242 62553 0 0·2 0·6 0·4 0·8 30 60 90 120 150 180 0 50 100 150 200 84435 122790 58504 103824 41026 89662 26310 75998 15885 63173 8741 51033 0 10 5 20 15 25 30 60 90 120 150 180 Dementia Mood, anxiety, or psychotic disorder COVID-19 (n=234527) Other RTI (n=234810) COVID-19 (n=230151) Other RTI (n=230495) COVID-19 (n=236038) Other RTI (n=236038) Articles 422 www.thelancet.com/psychiatry Vol 8 May 2021 one of the four other index events (appendix pp 11–14, 34), except when an outcome had a predicted relationship with the comparator condition (eg, intracranial hemorrhage was more common in association with fracture of a large bone). HRs for diagnostic subcategories are presented in the appendix (p 33). There were no violations of the proportional hazards assumption for most of the neurological outcomes over the 6 months of follow-up (appendix pp 15, 35). The only exception was for intracranial hemorrhage and ischemic stroke in patients who had COVID-19 when compared with patients who had other respiratory tract infections (p=0·012 for intracranial hemorrhage and p=0·032 for ischemic stroke). For the overall psychiatric disorder category (ICD-10 F20–48), the HR did vary with time, declining but remaining significantly higher than 1, indicating that the risk was attenuated but maintained 6 months after COVID-19 diagnosis (appendix p 9). HRs for COVID-19 diagnosis compared with the additional four index events showed more variation with time, partly reflecting the natural history of the comparator condition (appendix, pp 16–19, 36). We explored the effect of COVID-19 severity in four ways. First, we restricted analyses to matched cohorts of patients who had not required hospitalization (matched baseline characteristics in the appendix, pp 37–40). HRs remained significantly greater than 1 in this subgroup, with an overall HR for any diagnosis of 1·47 (95% CI 1·44–1·51) for patients who had COVID-19 compared with patients who had influenza, and 1·16 (1·14–1·17) compared with those who had other respiratory tract infections (table 4, appendix pp 20–21). For a first diagnosis, the HRs were 1·83 (1·71–1·96) versus patients who had influenza and 1·28 (1·23–1·33) versus those who had other respiratory tract infections. Second, we calculated HRs for the matched cohorts of patients with COVID-19 requiring hospitalization versus those who did not require hospitalization (44 927 matched patients; matched baseline characteristics are presented in the appendix, pp 41–42). This comparison showed greater hazard rates for all outcomes in the hospitalized group than in the non-hospitalized group, except for nerve, nerve root, or plexus disorders (table 5, figure 2), with an overall HR of 1·33 (1·29–1·37) for any diagnosis and 1·70 (1·56–1·86) for any first diagnosis. Third, we calculated HRs for the matched cohorts of patients with COVID-19 requiring ITU admission versus those not COVID-19 vs influenza in patients without hospitalization (N=96803)* COVID-19 vs other RTI in patients without hospitalization (N=183 731)* HR (95% CI) p value HR (95% CI) p value Intracranial hemorrhage (any) 1·87 (1·25–2·78) 0·0013 1·38 (1·11–1·73) 0·0034 Intracranial hemorrhage (first) 1·66 (0·88–3·14) 0·082 1·63 (1·11–2·40) 0·010 Ischemic stroke (any) 1·80 (1·54–2·10) <0·0001 1·61 (1·45–1·78) <0·0001 Ischemic stroke (first) 1·71 (1·26–2·33) 0·0003 1·69 (1·38–2·08) <0·0001 Parkinsonism 2·22 (0·98–5·06) 0·028 1·20 (0·73–1·96) 0·42 Guillain-Barré syndrome 0·90 (0·44–1·84) 0·99 1·44 (0·85–2·45) 0·10 Nerve, nerve root, or plexus disorders 1·69 (1·53–1·88) <0·0001 1·23 (1·15–1·33) <0·0001 Myoneural junction or muscle disease 3·46 (2·11–5·67) <0·0001 2·69 (1·91–3·79) <0·0001 Encephalitis 1·77 (0·86–3·66) 0·095 2·29 (1·28–4·10) 0·0046 Dementia 1·88 (1·27–2·77) 0·0008 1·95 (1·55–2·45) <0·0001 Mood, anxiety, or psychotic disorder (any) 1·49 (1·45–1·54) <0·0001 1·18 (1·15–1·21) <0·0001 Mood, anxiety, or psychotic disorder (first) 1·85 (1·72–1·99) <0·0001 1·40 (1·32–1·48) <0·0001 Mood disorder (any) 1·49 (1·43–1·55) <0·0001 1·22 (1·19–1·26) <0·0001 Mood disorder (first) 1·78 (1·61–1·96) <0·0001 1·37 (1·27–1·47) <0·0001 Anxiety disorder (any) 1·48 (1·43–1·54) <0·0001 1·16 (1·13–1·19) <0·0001 Anxiety disorder (first) 1·80 (1·67–1·94) <0·0001 1·37 (1·30–1·45) <0·0001 Psychotic disorder (any) 1·93 (1·63–2·28) <0·0001 1·44 (1·27–1·62) <0·0001 Psychotic disorder (first) 2·27 (1·56–3·30) <0·0001 1·49 (1·15–1·93) 0·0016 Substance use disorder (any) 1·26 (1·19–1·33) <0·0001 1·11 (1·07–1·17) <0·0001 Substance use disorder (first) 1·21 (1·05–1·38) 0·0054 0·89 (0·81–0·97) 0·013 Insomnia (any) 1·52 (1·42–1·63) <0·0001 1·18 (1·12–1·24) <0·0001 Insomnia (first) 2·06 (1·82–2·33) <0·0001 1·51 (1·38–1·66) <0·0001 Any outcome 1·47 (1·44–1·51) <0·0001 1·16 (1·14–1·17) <0·0001 Any first outcome 1·83 (1·71–1·96) <0·0001 1·28 (1·23–1·33) <0·0001 Details on cohort characteristics are presented in the appendix (pp 37–40). HR=hazard ratio. RTI=respiratory tract infection. *Matched cohorts. Table 4: HRs for the major outcomes in patients without hospitalization after COVID-19 compared with those after influenza or other RTIs Articles www.thelancet.com/psychiatry Vol 8 May 2021 423 requiring ITU admission (8942 patients; matched baseline characteristics presented in the appendix, pp 43–44), with a HR of 1·58 (1·50–1·67) for any diagnosis and 2·87 (2·45–3·35) for any first diagnosis (table 5, appendix p 22). Fourth, we calculated HRs for the matched cohorts of patients with COVID-19 who had encephalopathy diagnosed during acute illness versus those who did not (6221 patients; matched baseline characteristics presented in the appendix, pp 45–46). HRs for all diagnoses were greater for the group who had encephalopathy than for the matched cohort who did not, with an overall HR of 1·85 (1·73–1·98) for any diagnosis and 3·19 (2·54–4·00) for any first diagnosis (table 5, figure 2). We inspected other factors that might influence the findings. The results regarding hospitalization, ITU admission, or encephalopathy (which we had defined as occurring up to 14 days after diagnosis) could be confounded by admissions due to an early complication of COVID-19 rather than to COVID-19 itself. This was explored by excluding outcomes during this period, with the findings remaining similar, albeit with many HRs being reduced (appendix pp 47–49). Additionally, COVID-19 survivors had fewer health-care visits during the 6-month period compared with the other cohorts (appendix p 50). Hence the higher incidence of many diagnoses was not simply due to having had more diagnostic opportunities. The increased rates of neurological and psychiatric sequelae were robust in all three sensitivity analyses: when patients who had died by the time of the analysis were included (appendix p 51), when the COVID-19 diagnosis was confirmed by use of an RNA or antigen test (appendix p 52), and when the sequelae were compared with those observed in patients who had influenza in 2019 or 2018 (appendix pp 53). Discussion Various adverse neurological and psychiatric outcomes occurring after COVID-19 have been predicted and COVID-19 with vs without hospitalization (N=45167) COVID-19 with vs without ITU admission (N=8942) COVID-19 with vs without encephalopathy (N=6221) HR (95% CI) p value HR (95% CI) p value HR (95% CI) p value Intracranial hemorrhage (any) 3·09 (2·43–3·94) <0·0001 5·06 (3·43–7·47) <0·0001 4·73 (3·15–7·11) <0·0001 Intracranial hemorrhage (first) 3·75 (2·49–5·64) <0·0001 5·12 (2·68–9·77) <0·0001 5·00 (2·33–10·70) <0·0001 Ischemic stroke (any) 1·65 (1·48–1·85) <0·0001 1·93 (1·62–2·31) <0·0001 1·65 (1·38–1·97) <0·0001 Ischemic stroke (first) 2·82 (2·22–3·57) <0·0001 3·51 (2·39–5·15) <0·0001 3·39 (2·17–5·29) <0·0001 Parkinsonism 2·63 (1·45–4·77) 0·0016 3·90 (1·29–11·79) 0·024 1·64 (0·75–3·58) 0·24 Guillain-Barré syndrome 2·94 (1·60–5·42) 0·00094 11·01 (2·55–47·61) 0·0007 2·27 (0·76–6·73) 0·24 Nerve, nerve root, or plexus disorders 0·94 (0·83–1·06) 0·29 1·16 (0·92–1·45) 0·21 1·41 (1·07–1·87) 0·018 Myoneural junction or muscle disease 7·76 (5·15–11·69) <0·0001 11·53 (6·38–20·83) <0·0001 5·40 (3·21–9·07) <0·0001 Encephalitis 3·26 (1·75–6·06) 0·0002 1·78 (0·75–4·20) 0·22 9·98 (2·98–33·43) <0·0001 Dementia 2·28 (1·80–2·88) <0·0001 1·66 (1·12–2·46) 0·018 4·25 (2·79–6·47) <0·0001 Mood, anxiety, or psychotic disorder (any) 1·23 (1·18–1·28) <0·0001 1·34 (1·24–1·46) <0·0001 1·73 (1·58–1·90) <0·0001 Mood, anxiety, or psychotic disorder (first) 1·55 (1·40–1·71) <0·0001 2·27 (1·87–2·74) <0·0001 2·28 (1·80–2·89) <0·0001 Mood disorder (any) 1·21 (1·15–1·28) <0·0001 1·15 (1·03–1·27) 0·010 1·51 (1·35–1·70) <0·0001 Mood disorder (first) 1·53 (1·33–1·75) <0·0001 2·06 (1·57–2·71) <0·0001 2·09 (1·55–2·80) <0·0001 Anxiety disorder (any) 1·16 (1·10–1·22) <0·0001 1·39 (1·26–1·53) <0·0001 1·64 (1·45–1·84) <0·0001 Anxiety disorder (first) 1·49 (1·34–1·65) <0·0001 2·22 (1·82–2·71) <0·0001 1·91 (1·48–2·45) <0·0001 Psychotic disorder (any) 2·22 (1·92–2·57) <0·0001 1·48 (1·14–1·92) 0·0028 3·84 (2·90–5·10) <0·0001 Psychotic disorder (first) 2·77 (1·99–3·85) <0·0001 1·77 (0·98–3·20) 0·072 5·62 (2·93–10·77) <0·0001 Substance use disorder (any) 1·53 (1·42–1·64) <0·0001 1·62 (1·41–1·85) <0·0001 1·45 (1·24–1·70) <0·0001 Substance use disorder (first) 1·68 (1·40–2·01) <0·0001 2·53 (1·83–3·50) <0·0001 2·03 (1·32–3·11) 0·0015 Insomnia (any) 1·08 (0·99–1·18) 0·088 1·40 (1·19–1·66) <0·0001 1·73 (1·42–2·11) <0·0001 Insomnia (first) 1·49 (1·28–1·74) <0·0001 1·93 (1·46–2·55) <0·0001 3·44 (2·35–5·04) <0·0001 Any outcome 1·33 (1·29–1·37) <0·0001 1·58 (1·50–1·67) <0·0001 1·85 (1·73–1·98) <0·0001 Any first outcome 1·70 (1·56–1·86) <0·0001 2·87 (2·45–3·35) <0·0001 3·19 (2·54–4·00) <0·0001 Details on cohort characteristics are presented in the appendix (pp 41–46). HR=hazard ratio. ITU=intensive therapy unit. *Matched cohorts. Table 5: HRs for the major outcomes after COVID-19 for patients with vs those without hospitalization, patients with vs without ITU admission, and patients with vs without encephalopathy Articles 424 www.thelancet.com/psychiatry Vol 8 May 2021 Encephalopathy Matched cohort without encephalopathy Number at risk Encephalopathy Matched cohort without encephalopathy Hospitalization Matched cohort without hospitalization 0 50 100 150 200 Intracranial hemorrhage (any) 0 1 4 3 2 Outcome probability (%) 30 60 90 120 150 180 Ischemic stroke (any) Total 6221 6221 45167 45167 3214 3424 20486 20010 2296 2372 14717 14696 1746 2372 11818 11185 1269 1244 7766 7344 1032 1244 5232 4799 733 642 4030 3598 0 50 100 150 200 0 2·5 10·0 7·5 5·0 Total 30 60 90 120 150 180 6221 6221 45167 45167 3133 2989 20218 19587 2201 2187 14429 14515 1639 1641 10786 10792 1177 1221 7566 7464 821 758 5083 4714 634 758 3551 3133 Number at risk Encephalopathy Matched cohort without encephalopathy Hospitalization Matched cohort without hospitalization 0 50 100 150 200 Nerve, nerve root, or plexus disorder 0 1 5 4 3 2 Outcome probability (%) 30 60 90 120 150 180 Myoneural junction or muscle disease Total 0 50 100 150 200 0 1 4 3 2 Total 30 60 90 120 150 180 6221 6221 45167 45167 3277 3125 20453 19636 2317 2225 14614 14537 1701 1701 10902 10775 1231 1314 7737 7447 881 825 5062 4549 602 596 3378 2606 5906 6109 44481 44788 2996 3067 20044 20069 2127 2236 14345 16550 1836 1916 10853 13067 1292 1916 8206 10185 790 1139 5270 10185 604 635 3320 4092 Number at risk Encephalopathy Matched cohort without encephalopathy Hospitalization Matched cohort without hospitalization 0 50 100 Time since index event (days) Time since index event (days) 150 200 Dementia 0 1 5 4 3 2 Outcome probability (%) 30 60 90 120 150 180 Mood, anxiety, or psychotic disorder Total 0 50 100 150 200 0 10 40 30 20 Total 30 60 90 120 150 180 4704 5094 42434 42877 2627 2562 19428 18719 1929 2010 13970 13904 1425 1419 10567 10329 1036 986 7611 7017 717 986 5427 5174 583 986 3616 2697 6221 6221 45167 45167 2640 2729 18072 18092 1734 1910 12352 12874 1217 1417 8933 9170 888 955 6068 5925 575 633 3976 3653 351 437 2501 2001 Hospitalization Matched cohort without hospitalization Articles www.thelancet.com/psychiatry Vol 8 May 2021 425 reported.1–5,14 The data presented in this study, from a large electronic health records network, support these predictions and provide estimates of the incidence and risk of these outcomes in patients who had COVID-19 compared with matched cohorts of patients with other health conditions occurring contemporaneously with the COVID-19 pandemic (tables 2, 3, figure 1). The severity of COVID-19 had a clear effect on subsequent neurological diagnoses (tables 4, 5, figure 2). Overall, COVID-19 was associated with increased risk of neurological and psychiatric outcomes, but the incidences and HRs of these were greater in patients who had required hospitalization, and markedly so in those who had required ITU admission or had developed encephalopathy, even after extensive propensity score matching for other factors (eg, age or previous cerebrovascular disease). Potential mechanisms for this association include viral invasion of the CNS,10,11 hypercoagulable states,22 and neural effects of the immune response.9 However, the incidence and relative risk of neurological and psychiatric diagnoses were also increased even in patients with COVID-19 who did not require hospitalization. Some specific neurological diagnoses merit individual mention. Consistent with several other reports,23,24 the risk of cerebrovascular events (ischemic stroke and intracranial hemorrhage) was elevated after COVID-19, with the incidence of ischemic stroke rising to almost one in ten (or three in 100 for a first stroke) in patients with encephalopathy. A similarly increased risk of stroke in patients who had COVID-19 compared with those who had influenza has been reported.25 Our previous study reported preliminary evidence for an association between COVID-19 and dementia.14 The data in this study support this association. Although the estimated incidence was modest in the whole COVID-19 cohort (table 2), 2·66% of patients older than 65 years (appendix p 28) and 4·72% who had encephalopathy (table 2), received a first diagnosis of dementia within 6 months of having COVID-19. The associations between COVID-19 and cerebrovascular and neurodegenerative diagnoses are concerning, and information about the severity and subsequent course of these diseases is required. Whether COVID-19 is associated with Guillain-Barré syndrome remains unclear;26 our data were also equivocal, with HRs increased with COVID-19 compared with other respiratory tract infections but not with influenza (table 3), and increased compared with three of the four other index health events (appendix p 34). Concerns have also been raised about post-COVID-19 parkinsonian syndromes, driven by the encephalitis lethargica epidemic that followed the 1918 influenza pandemic.27 Our data provide some support for this possibility, although the incidence was low and not all HRs were significant. Parkinsonism might be a delayed outcome, in which case a clearer signal might emerge with a longer follow-up. The findings regarding anxiety and mood disorders were broadly consistent with 3-month outcome data from a study done in a smaller number of cases than our cohort, using the same network,14 and showed that the HR remained elevated, although decreasing, at the 6-month period. Unlike the earlier study, and in line with previous suggestions,28 we also observed a significantly increased risk of psychotic disorders, probably reflecting the larger sample size and longer duration of follow-up reported here. Substance use disorders and insomnia were also more common in COVID-19 survivors than in those who had influenza or other respiratory tract infections (except for the incidence of a first diagnosis of substance use disorder after COVID-19 compared with other respiratory tract infections). Therefore, as with the neurological outcomes, the psychiatric sequelae of COVID-19 appear widespread and to persist up to, and probably beyond, 6 months. Compared with neurological disorders, common psychiatric disorders (mood and anxiety disorders) showed a weaker relationship with the markers of COVID-19 severity in terms of incidence (table 2) or HRs (table 5). This might indicate that their occurrence reflects, at least partly, the psychological and other implications of a COVID-19 diagnosis rather than being a direct manifestation of the illness. HRs for most neurological outcomes were constant, and hence the risks associated with COVID-19 persisted up to the 6-month timepoint. Longer-term studies are needed to ascertain the duration of risk and the trajectory for individual diagnoses. Our findings are robust given the sample size, the propensity score matching, and the results of the sensitivity and secondary analyses. Nevertheless, they have weaknesses inherent to an electronic health records study,29 such as the unknown completeness of records, no validation of diagnoses, and sparse information on socioeconomic and lifestyle factors. These issues primarily affect the incidence estimates, but the choice of cohorts against which to compare COVID-19 outcomes influenced the magnitude of the HRs (table 3, appendix p 34). The analyses regarding encephalopathy (delirium and related conditions) deserve a note of caution. Even among patients who were hospitalized, only about 11% received this Figure 2: Kaplan-Meier estimates for the incidence of major outcomes after COVID-19 comparing patients requiring hospitalization with matched patients not requiring hospitalization, and comparing those who had encephalopathy with matched patients who did not have encephalopathy 95% CIs are omitted for clarity but are shown in the appendix (p 23). For incidences of first diagnoses, the total number corresponds to all patients who did not have the outcome before the follow-up period. The equivalent figure showing the comparison between patients with intensive therapy unit admission versus those without is presented in the appendix (p 22). Articles 426 www.thelancet.com/psychiatry Vol 8 May 2021 diagnosis, whereas much higher rates would be expected.18,30 Under-recording of delirium during acute illness is well known and probably means that the diagnosed cases had prominent or sustained features; as such, results for this group should not be generalized to all patients with COVID-19 who experience delirium. We also note that encephalopathy is not just a severity marker but a diagnosis in itself, which might predispose to, or be an early sign of, other neuropsychiatric or neurodegenerative outcomes observed during follow-up. The timing of index events was such that most infections with influenza and many of the other respiratory tract infections occurred earlier on during the pandemic, whereas the incidence of COVID-19 diagnoses increased over time (appendix p 24). The effect of these timing differences on observed rates of sequelae is unclear but, if anything, they are likely to make the HRs an underestimate because COVID-19 cases were diagnosed at a time when all other diagnoses were made at a lower rate in the population (appendix p 24). Some patients in the comparison cohorts are likely to have had undiagnosed COVID-19; this would also tend to make our HRs an underestimate. Finally, a study of this kind can only show associations; efforts to identify mechanisms and assess causality will require prospective cohort studies and additional study designs. In summary, the present data show that COVID-19 is followed by significant rates of neurological and psychiatric diagnoses over the subsequent 6 months. Services need to be configured, and resourced, to deal with this anticipated need. Contributors PJH and MT were granted unrestricted access to the TriNetX Analytics network for the purposes of research, and with no constraints on the analyses done or the decision to publish; they designed the study and directly accessed the TriNetX Analytics web interface to do it. MT, JRG, MH, and PJH defined cohort inclusion and exclusion criteria, and the outcome criteria and analytical approaches. MT did the data analyses, assisted by SL and PJH. All authors contributed to data interpretation. MT and PJH wrote the paper with input from JRG, MH, and SL. MT and PJH verified the data. PJH is the guarantor. PJH and MT had full access to all the data in the study, and the corresponding author had final responsibility for the decision to submit for publication. Declaration of interests SL is an employee of TriNetX. All other authors declare no competing interests. Data sharing The TriNetX system returned the results of these analyses as .csv files, which were downloaded and archived. Data presented in this paper can be freely accessed online. Additionally, TriNetX will grant access to researchers if they have a specific concern (through a third-party agreement option).

Acknowledgments

This work was supported by the NIHR Oxford Health Biomedical Research Centre (grant BRC-1215–20005). MT is an NIHR Academic Clinical Fellow. MH is supported by a Wellcome Trust Principal Research Fellowship and the NIHR Oxford Biomedical Research Centre. The views expressed are those of the authors and not necessarily those of the UK National Health Service, NIHR, or the UK Department of Health.

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Ischemic stroke can follow COVID-19 vaccination but is much more common with COVID-19 infection itself

Authors: http://orcid.org/0000-0002-9794-5996 Hugh S Markus

Correspondence to Professor Hugh S Markus, Department of Clinical Neurosciences, Cambridge University, Cambridge CB2 1TN, UK; hsm32@medschl.cam.ac.uk

Thrombotic complications occurring as part of COVID-19 related vaccine-induced immune thrombotic thrombocytopaenia (VITT) can include ischaemic stroke as well as cerebral venous thrombosis

The COVID-19 pandemic has had a major impact on stroke. While there was marked drop in hospitalised stroke cases worldwide particularly during the first wave,1 2 epidemiological data have shown a real increase in stroke incidence with cases primarily occurring out of hospital and especially in care homes.3 Therefore, COVID-19 infection itself is a risk factor for stroke, and a recent systematic review reported it occured in 1.4% of COVID-19 infections.4 A characteristic pattern is found with increased large artery occlusion, and an increased proportion of cryptogenic strokes often affecting multiple arterial territories, while small artery stroke is less common.4 Both stroke severity and mortality are increased compared with non-COVID-19 related stroke. A major factor underlying this increased risk is the generalised prothrombotic state seen in some patients with COVID-19, with activation of the coagulation pathway and elevated D-dimer and fibrinogen being common features. This ‘sepsis-induced coagulopathy’ is related to the infection-induced systemic inflammatory response.4 Antiphospholipid antibodies have also been reported in some patients with COVID-19 and stroke. However, a reduction in platelet count does not appear a common feature.

Recently, reports of coagulopathy have appeared associated with COVID-19 vaccination and particularly the ChAdOx1 nCoV-19 vaccine. These have been characterised by thrombocytopaenia, similar to that seen in heparin-induced thrombocytopaenia but in the absence of heparin and with antibodies to platelet factor 4. In one series of 23 patients, 13 had cerebral venous thrombosis and 5 pulmonary emboli.5 Median age was 46 with an age range of 21–77, and median time after vaccine was 12 days (range 6–24). Why the cerebral venous sinuses are preferentially affected remains uncertain.

The clinical spectrum is further extended by the paper from Al-Mayhani et al 6 describing three cases of ischaemic stroke associated with COVID-19 vaccination. In all cases, the ischaemic stroke was associated with large artery occlusion, both carotid and middle cerebral artery, while two also had venous thrombosis involving the portal and cerebral venous system. This report emphasises that the immune-mediated coagulopathy can also cause arterial thrombosis including ischaemic stroke, although venous thrombosis and especially CVST appear more frequent.

Treating cerebral venous thrombosis and ischaemic stroke associated with vaccine-induced immune thrombotic thrombocytopaenia (VITT) presents a challenge. Current guidelines, such as those from the Expert Haematology Panel on COVID-19 VITT,7 recommend the use of a non-heparin anticoagulant agent such as direct oral anticoagulants (DOACs, fondaparinux, danaparoid or argatraban depending on the clinical picture, along with intravenous immunoglobulin infusions, and possibly plasma exchange. It has been suggested platelet infusions may exacerbate the condition.7 Despite optimal therapy, a high mortality has been reported and complications are common, as illustrated in the first case reported by Al-Mayhami et al, in which fatal haemorrhagic transformation occurred into a large ischaemic infarct.5

During the current period of COVID-19 vaccination, a high index of suspicion is required to identify thrombotic episodes following vaccination. However, it is important to remember that these side effects are rare and much less common than both cerebral venous thrombosis and ischaemic stroke associated with COVID-19 infection itself, as illustrated by a recent large epidemiological study.8

Ethics statements

Patient consent for publication

Not required.

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Footnotes

  • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
  • Competing interests None declared.

Some COVID-19 patients have brain complications, study suggests

Authors: Mary Van Beusekom | News Writer | CIDRAP News  | Jun 26, 2020

Some COVID-19 patients, including those younger than 60 years old, appear to develop neurologic and neuropsychiatric complications such as stroke, brain inflammation, psychosis, and dementia-like symptoms, according to a study published yesterday in The Lancet Psychiatry.

The early-stage study of 153 hospitalized patients with confirmed, probable, or possible COVID-19 in the United Kingdom (UK) from Apr 2 to 26 identified 125 patients with complete data, of whom 77 (62%) had a stroke.

Of 125 patients, 114 (92%) had confirmed coronavirus infection, 5 (4%) had probable infection, and 5 (4%) were classified as possibly infected.

Stroke, encephalopathy, psychiatric diagnoses

Fifty-seven of 77 stroke patients (74%) had an ischemic stroke caused by a blood clot in the brain, 9 (12%) had a stroke caused by a brain hemorrhage, and 1 (1%) had a stroke caused by inflammation in the brain’s blood vessels. Sixty-one of the 77 stroke patients for whom age was available (82%) were older than 60 years.

Thirty-nine of 125 patients (31%) had behavioral changes indicative of an altered mental state, of whom 9 (23%) had unspecified brain dysfunction known as encephalopathy, and 7 (18%) had brain inflammation, or encephalitis.

The remaining 23 patients with altered mental states had psychiatric diagnoses, including 10 with new-onset psychosis, 7 with depression or anxiety, and 6 with a dementia-like syndrome. Only 2 patients (9%) had exacerbations of a chronic mental illness, although the authors noted that they cannot exclude the possibility that cases classified as new were simply undiagnosed before the pandemic.

Of the 37 of 39 COVID-19 patients with an altered mental state for whom age was available, 18 (49%) were younger than 60 years, which could be because they were more likely to be referred to a psychiatrist or other specialist, while physicians may be likely to attribute confusion or behavioral changes in older patients to delirium without further investigation, the authors said.

Altered mental states in younger patients

While altered mental states are not uncommon in hospitalized patients with infections, especially those requiring intensive care, they occur most often in older patients.

“In this study, we observed a disproportionate number of neuropsychiatric presentations in younger patients and a predominance of cerebrovascular complications in older patients, which might reflect the state of health of the cerebral vasculature and associated risk factors, exacerbated by critical illness in older patients,” the authors said.

For More Information: https://www.cidrap.umn.edu/news-perspective/2020/06/some-covid-19-patients-have-brain-complications-study-suggests

Coronavirus and the Nervous System

What is SARS-CoV-2 and COVID-19?

Coronaviruses are common causes of usually mild to moderate upper respiratory tract illnesses like the common cold, with symptoms that may include runny nose, fever, sore throat, cough, or a general feeling of being ill. However, a new coronavirus called Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) emerged and spread to cause the COVID-19 pandemic.

COVID-19, which means Coronavirus disease 2019, is an infectious disease that can affect people of all ages in many ways. It is most dangerous when the virus spreads from the upper respiratory tract into the lungs to cause viral pneumonia and lung damage leading to Acute Respiratory Distress Syndrome (ARDS). When severe, this impairs the body’s ability to maintain critical levels of oxygen in the blood stream—which can cause multiple body systems to fail and can be fatal.

What do we know about the effects of SARS-CoV-2 and COVID-19 on the nervous system?

Much of the research to date has focused on the acute infection and saving lives. These strategies have included preventing infection with vaccines, treating COVID-19 symptoms with medicines or antibodies, and reducing complications in infected individuals.

Research shows the many neurological symptoms of COVID-19 are likely a result of the body’s widespread immune response to infection rather than the virus directly infecting the brain or nervous system. In some people, the SARS-CoV-2 infection causes an overreactive response of the immune system which can also damage body systems. Changes in the immune system have been seen in studies of the cerebrospinal fluid, which bathes the brain, in people who have been infected by SARS-CoV-2. This includes the presence of antibodies—proteins made by the immune system to fight the virus—that may also react with the nervous system. Although still under intense investigation, there is no evidence of widespread viral infection in the brain. Scientists are still learning how the virus affects the brain and other organs in the long-term. Research is just beginning to focus on the role of autoimmune reactions and other changes that cause the set of symptoms that some people experience after their initial recovery. It is unknown if injury to the nervous system or other body organs cause lingering effects that will resolve over time, or whether COVID-19 infection sets up a more persistent or even chronic disorder.

What are the immediate (acute) effects of SARS-CoV-2 and COVID-19 on the brain?

Most people infected with SARS-CoV-2 virus will have no or mild to moderate symptoms associated with the brain or nervous system. However, most individuals hospitalized due to the virus do have symptoms related to the brain or nervous system, most commonly including muscle aches, headaches, dizziness, and altered taste and smell. Some people with COVID-19 either initially have, or develop in the hospital, a dramatic state of confusion called delirium. Although rare, COVID-19 can cause seizures or major strokes. Muscular weakness, nerve injury, and pain syndromes are common in people who require intensive care during infections. There are also very rare reports of conditions that develop after SARS-CoV-2 infection, as they sometimes do with other types of infections. These disorders of inflammation in the nervous system include Guillain-Barré syndrome (which affects nerves), transverse myelitis (which affects the spinal cord), and acute necrotizing leukoencephalopathy (which affects the brain).

Bleeding in the brain, weakened blood vessels, and blood clots in acute infection

The SARS-CoV-2 virus attaches to a specific molecule (called a receptor) on the surface of cells in the body. This molecule is concentrated in the lung cells but is also present on certain cells that line blood vessels in the body. The infection causes some arteries and veins—including those in the brain—to  become thin, weaken, and leak. Breaks in small blood vessels have caused bleeding in the brain (so-called microbleeds) in some people with COVID-19 infection. Studies in people who have died due to COVID-19 infection show leaky blood vessels in different areas of the brain that allow water and a host of other molecules as well as blood cells that are normally excluded from the brain to move from the blood stream into the brain. This leak, as well as the resulting inflammation around blood vessels, can cause multiple small areas of damage. COVID-19 also causes blood cells to clump and form clots in arteries and veins throughout the body. These blockages reduce or block the flow of blood, oxygen, and nutrients that cells need to function and can lead to a stroke or heart attack.

stroke is a sudden interruption of continuous blood flow to the brain. A stroke occurs either when a blood vessel in the brain becomes blocked or narrowed or when a blood vessel bursts and spills blood into the brain. Strokes can damage brain cells and cause permanent disability. The blood clots and vascular (relating to the veins, capillaries, and arteries in the body) damage from COVID-19 can cause strokes even in young healthy adults who do not have the common risk factors for stroke.

COVID-19 can cause blood clots in other parts of the body, too. A blood clot in or near the heart can cause a heart attack. A heart attack orInflammation in the heart, called myocarditis, can causeheart failure, and reduce the flow of blood to other parts of the body. A blood clot in the lungs can impair breathing and cause pain. Blood clots also can damage the kidneys and other organs.

Low levels of oxygen in the body (called hypoxia) can permanently damage the brain and other vital organs in the body. Some hospitalized individuals require artificial ventilation on respirators. To avoid chest movements that oppose use of the ventilator it may be necessary to temporarily “paralyze” the person and use anesthetic drugs to put the individual to sleep. Some individuals with severe hypoxia require artificial means of bringing oxygen into their blood stream, a technique called extra corporeal membrane oxygenation (ECMO). Hypoxia combined with these intensive care unit measure generally cause cognitive disorders that show slow recovery.

Diagnostic imaging of some people who have had COVID-19 show changes in the brain’s white matter that contains the long nerve fibers, or “wires,” over which information flows from one brain region to another. These changes may be due to a lack of oxygen in the brain, the inflammatory immune system response to the virus, injury to blood vessels, or leaky blood vessels. This “diffuse white matter disease” might contribute to cognitive difficulties in people with COVID-19. Diffuse white matter disease is not uncommon in individuals requiring intensive hospital care but it not clear if it also occurs in those with mild to moderate severity of COVID-19 illness.

For More Information: https://www.ninds.nih.gov/Current-Research/Coronavirus-and-NINDS/nervous-system

The Impact of the Covid 19 Pandemic on Cerebrovascular Disease: CORD-Papers-2021-06-28

Abstract:           

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes a systemic disease that affects nearly all organ systems through infection and subsequent dysregulation of the vascular endothelium. One of the most striking phenomena has been a coronavirus disease 2019 (COVID-19)associated coagulopathy. Given these findings, questions naturally emerged about the prothrombotic impact of COVID-19 on cerebrovascular disease and whether ischemic stroke is a clinical feature specific to COVID-19 pathophysiology. Early reports from China and several sites in the northeastern United States seemed to confirm these suspicions. Since these initial reports, many cohort studies worldwide observed decreased rates of stroke since the start of the pandemic, raising concerns for a broader impact of the pandemic on stroke treatment. In this review, we provide a comprehensive assessment of how the pandemic has affected stroke presentation, epidemiology, treatment, and outcomes to better understand the impact of COVID-19 on cerebrovascular disease. Much evidence suggests that this decline in stroke admissions stems from the global response to the virus, which has made it more difficult for patients to get to the hospital once symptoms start. However, there does not appear to be a demonstrable impact on quality metrics once patients arrive at the hospital. Despite initial concerns, there is insufficient evidence to ascribe a causal relationship specific to the pathogenicity of SARS-CoV-2 on the cerebral vasculature. Nevertheless, when patients infected with SARS-CoV-2 present with stroke, their presentation is likely to be more severe, and they have a markedly higher rate of in-hospital mortality than patients with either acute ischemic stroke or COVID-19 alone.

For More Information: https://covid19-data.nist.gov/pid/rest/local/paper/the_impact_of_the_covid_19_pandemic_on_cerebrovascular_disease