114 Search Results for "long covid"
RECOVER: What Clinical Research Comes Next for Helping People with Long COVID
“I connected with RECOVER to be a part of the answers that I was looking for when I was at my worst.” Long COVID patient and RECOVER representative, Nitza Rochez (Bronx, NY)
People, like Nitza Rochez, who are living with Long COVID—the wide-ranging health issues that can follow an infection with SARS-CoV-2, the coronavirus that causes COVID-19—experience disabling symptoms with significant physical, emotional and financial consequences.
The NIH has been engaging and listening to Nitza and others living with Long COVID even before the start of its Researching COVID to Enhance Recovery (RECOVER) Initiative. But now, with the launch of RECOVER, patients and those with affected family or community members have joined researchers, clinicians, and experts in their efforts to unlock the mysteries of Long COVID. All have come together to understand what causes the condition, identify who is most at risk, and determine how to prevent and treat it.
RECOVER is unprecedented in its size and scope as the most-diverse, deeply characterized cohort of Long COVID patients. We’ve enlisted the help of many patient volunteers, who have enrolled in observational studies designed to help researchers learn as much as possible about people who have Long COVID.
Indeed, thousands of research participants are now providing health information and undergoing in-depth medical evaluations and tests, enabling investigators to look for trends. Additionally, studies of millions of electronic medical records are providing insights about those who have received care during the pandemic. More than 40 studies are being conducted to identify the causes of disease, potential biomarkers of Long COVID, and new therapeutic targets.
In all, RECOVER’s research assets are voluminous. They involve invaluable contributions from many people and communities, including research volunteers, research investigators, and clinical specialists. In addition, millions of health records and numerous related tissues and specimens are being analyzed for possible leads.
At the center of it all is the National Community Engagement Group (NCEG). The NCEG is comprised of people living with Long COVID and those representing others living with the condition, and it is truly instrumental to the initiative’s progress in understanding how and why SARS-CoV-2 impacts people in different ways. It’s also helping researchers learn why some people recover while others do not.
So far, we’ve learned that people hospitalized with COVID-19 are twice as likely to have Long COVID than those who were not hospitalized for infection. We’ve also learned that members of racial and ethnic minority groups with Long COVID were more likely to have been hospitalized with COVID-19.
Similarly, disparities in Long COVID exist within those living in areas with particular environmental exposures [1], and those who were already burdened by other diseases and conditions—such as diabetes and chronic pulmonary disease [2]. We’ve also discovered that the certain types of symptoms of Long COVID are consistent among patients regardless of which SARS-CoV-2 variant caused their initial infection. Yet, people infected with the earlier variants have a higher number of symptoms than those infected with more recent variants.
Patient experiences have guided and will continue to guide the study designs and trajectory of RECOVER. Now, fueled by the knowledge that we have gained, RECOVER is preparing to advance to the next phase of discovery—testing interventions in clinical trials to see if they can help people with Long COVID.
To prepare, we are beginning to identify potential clinical trial sites. This important step will help us to find the right places with the right staff and capabilities for enrolling the appropriate patient populations needed to implement the studies. We’ll ensure that the public knows when these upcoming clinical trials are ready to enroll.
Of course, the design of these RECOVER clinical trials will be critical, and insights gained from patients have been key in this process. Results from RECOVER study questionnaires, surveys, and discussions with people experiencing Long COVID identified symptom clusters considered to be the most significant and burdensome to patients. These include sleep disorders, “brain fog” (trouble thinking clearly), exercise intolerance and fatigue, and nervous system dysfunction affecting people’s ability to regulate normal body functions like heart rate and body temperature.
These patient observations have effectively guided the design of the clinical trials that will evaluate whether certain interventions and therapies can help alleviate symptoms that are part of these specific clusters. We’re excited to be advancing toward this phase of the initiative and, again, are very grateful to patient representatives like Nitza, quoted above, for getting us to this phase.
Effective evaluation of those treatments will be important, too. Early in the pandemic, while many clinical trials were launching, most were not large enough or did not have the appropriate objectives to define effective treatments for acute COVID-19. This left clinicians with few clear options when faced with patients needing help.
Learning from this experience, the RECOVER trials will be harmonized to ensure coordinated and efficient evaluation of interventions—in other words, all potential therapies will be using the same protocols platforms and the same data elements. This consistency accelerates our understanding and strengthens the certainty of findings.
Given the widespread and diverse impact that the virus has on the body, it is highly likely that more than one treatment will be needed for each kind of patient experience. Finding solutions for everyone—people of all races, ethnicities, genders, ages, and geographic locations—is paramount.
RECOVER patient representative, Juan Lewis, of San Antonio shared with us, “In April 2020, I was fighting for my life, and today I fight for my quality of life. COVID impacted me physically, mentally, socially, and financially.”
For people like Juan who are experiencing debilitating Long COVID symptoms, we know that finding answers as quickly as possible is critical. As we look ahead to the next 12 months, we’ll continue the studies evaluating the underlying causes, risk factors, and outcomes of Long Covid, and we anticipate significant scientific progress on research leading to Long COVID treatments.
Keep an eye on the RECOVER website for updates on our progress, and published findings.
References:
[1] Identifying environmental risk factors for post-acute sequelae of SARS-CoV-2 infection: An EHR-based cohort study from the recover program. Zhang Y, Hu H, Fokaidis V, V CL, Xu J, Zang C, Xu Z, Wang F, Koropsak M, Bian J, Hall J, Rothman RL, Shenkman EA, Wei WQ, Weiner MG, Carton TW, Kaushal R. Environ Adv. 2023 Apr;11:100352.
[2] Identifying who has long COVID in the USA: a machine learning approach using N3C data. Pfaff ER, Girvin AT, Bennett TD, Bhatia A, Brooks IM, Deer RR, Dekermanjian JP, Jolley SE, Kahn MG, Kostka K, McMurry JA, Moffitt R, Walden A, Chute CG, Haendel MA; N3C Consortium. Lancet Digit Health. 2022 Jul;4(7):e532-e541.
Links:
RECOVER: Researching COVID to Enhance Recovery
Long COVID: Ask NIH Leader about Latest Research (YouTube)
NIH Builds Large Nationwide Study Population of Tens of Thousands to Support Research on Long-Term Effects of COVID-19, NIH News Release, September 15, 2021
Understanding Long-Term COVID-19 Symptoms and Enhancing Recovery, NIH Director’s Blog, October 4, 2022.
NIH RECOVER Research Identifies Potential Long COVID Disparities. NIH News Release, February 16, 2023.
NIH RECOVER Listening Session, June 2021 (NIH Videocast)
NIH RECOVER Listening Session: Understanding Long COVID Across Communities of Color and Those Hardest Hit by COVID, January 21, 2022 (NIH Videocast)
Note: Dr. Lawrence Tabak, who performs the duties of the NIH Director, has asked the heads of NIH’s Institutes, Centers, and Offices to contribute occasional guest posts to the blog to highlight some of the interesting science that they support and conduct. This is the 25th in the series of NIH guest posts that will run until a new permanent NIH director is in place.
Using AI to Advance Understanding of Long COVID Syndrome
Posted on by Lawrence Tabak, D.D.S., Ph.D.
The COVID-19 pandemic continues to present considerable public health challenges in the United States and around the globe. One of the most puzzling is why many people who get over an initial and often relatively mild COVID illness later develop new and potentially debilitating symptoms. These symptoms run the gamut including fatigue, shortness of breath, brain fog, anxiety, and gastrointestinal trouble.
People understandably want answers to help them manage this complex condition referred to as Long COVID syndrome. But because Long COVID is so variable from person to person, it’s extremely difficult to work backwards and determine what these people had in common that might have made them susceptible to Long COVID. The variability also makes it difficult to identify all those who have Long COVID, whether they realize it or not. But a recent study, published in the journal Lancet Digital Health, shows that a well-trained computer and its artificial intelligence can help.
Researchers found that computers, after scanning thousands of electronic health records (EHRs) from people with Long COVID, could reliably make the call. The results, though still preliminary and in need of further validation, point the way to developing a fast, easy-to-use computer algorithm to help determine whether a person with a positive COVID test is likely to battle Long COVID.
In this groundbreaking study, NIH-supported researchers led by Emily Pfaff, University of North Carolina, Chapel Hill, and Melissa Haendel, the University of Colorado Anschutz Medical Campus, Aurora, relied on machine learning. In machine learning, a computer sifts through vast amounts of data to look for patterns. One reason machine learning is so powerful is that it doesn’t require humans to tell the computer which features it should look for. As such, machine learning can pick up on subtle patterns that people would otherwise miss.
In this case, Pfaff, Haendel, and team decided to “train” their computer on EHRs from people who had reported a COVID-19 infection. (The records are de-identified to protect patient privacy.) The researchers found just what they needed in the National COVID Cohort Collaborative (N3C), a national, publicly available data resource sponsored by NIH’s National Center for Advancing Translational Sciences. It is part of NIH’s Researching COVID to Enhance Recovery (RECOVER) initiative, which aims to improve understanding of Long COVID.
The researchers defined a group of more than 1.5 million adults in N3C who either had been diagnosed with COVID-19 or had a record of a positive COVID-19 test at least 90 days prior. Next, they examined common features, including any doctor visits, diagnoses, or medications, from the group’s roughly 100,000 adults.
They fed that EHR data into a computer, along with health information from almost 600 patients who’d been seen at a Long COVID clinic. They developed three machine learning models: one to identify potential long COVID patients across the whole dataset and two others that focused separately on people who had or hadn’t been hospitalized.
All three models proved effective for identifying people with potential Long-COVID. Each of the models had an 85 percent or better discrimination threshold, indicating they are highly accurate. That’s important because, once researchers can identify those with Long COVID in a large database of people such as N3C, they can begin to ask and answer many critical questions about any differences in an individual’s risk factors or treatment that might explain why some get Long COVID and others don’t.
This new study is also an excellent example of N3C’s goal to assemble data from EHRs that enable researchers around the world to get rapid answers and seek effective interventions for COVID-19, including its long-term health effects. It’s also made important progress toward the urgent goal of the RECOVER initiative to identify people with or at risk for Long COVID who may be eligible to participate in clinical trials of promising new treatment approaches.
Long COVID remains a puzzling public health challenge. Another recent NIH study published in the journal Annals of Internal Medicine set out to identify people with symptoms of Long COVID, most of whom had recovered from mild-to-moderate COVID-19 [2]. More than half had signs of Long COVID. But, despite extensive testing, the NIH researchers were unable to pinpoint any underlying cause of the Long COVID symptoms in most cases.
So if you’d like to help researchers solve this puzzle, RECOVER is now enrolling adults and kids—including those who have and have not had COVID—at more than 80 study sites around the country.
References:
[1] Identifying who has long COVID in the USA: a machine learning approach using N3C data. Pfaff ER, Girvin AT, Bennett TD, Bhatia A, Brooks IM, Deer RR, Dekermanjian JP, Jolley SE, Kahn MG, Kostka K, McMurry JA, Moffitt R, Walden A, Chute CG, Haendel MA; N3C Consortium. Lancet Digit Health. 2022 May 16:S2589-7500(22)00048-6.
[2] A longitudinal study of COVID-19 sequelae and immunity: baseline findings. Sneller MC, Liang CJ, Marques AR, Chung JY, Shanbhag SM, Fontana JR, Raza H, Okeke O, Dewar RL, Higgins BP, Tolstenko K, Kwan RW, Gittens KR, Seamon CA, McCormack G, Shaw JS, Okpali GM, Law M, Trihemasava K, Kennedy BD, Shi V, Justement JS, Buckner CM, Blazkova J, Moir S, Chun TW, Lane HC. Ann Intern Med. 2022 May 24:M21-4905.
Links:
COVID-19 Research (NIH)
National COVID Cohort Collaborative (N3C) (National Center for Advancing Translational Sciences/NIH)
Emily Pfaff (University of North Carolina, Chapel Hill)
Melissa Haendel (University of Colorado, Aurora)
NIH Support: National Center for Advancing Translational Sciences; National Institute of General Medical Sciences; National Institute of Allergy and Infectious Diseases
Breakthrough Infections in Vaccinated People Less Likely to Cause ‘Long COVID’
Posted on by Dr. Francis Collins
There’s no question that vaccines are making a tremendous difference in protecting individuals and whole communities against infection and severe illness from SARS-CoV-2, the coronavirus that causes COVID-19. And now, there’s yet another reason to get the vaccine: in the event of a breakthrough infection, people who are fully vaccinated also are substantially less likely to develop Long COVID Syndrome, which causes brain fog, muscle pain, fatigue, and a constellation of other debilitating symptoms that can last for months after recovery from an initial infection.
These important findings published in The Lancet Infectious Diseases are the latest from the COVID Symptom Study [1]. This study allows everyday citizens in the United Kingdom to download a smartphone app and self-report data on their infection, symptoms, and vaccination status over a long period of time.
Previously, the study found that 1 in 20 people in the U.K. who got COVID-19 battled Long COVID symptoms for eight weeks or more. But this work was done before vaccines were widely available. What about the risk among those who got COVID-19 for the first time as a breakthrough infection after receiving a double dose of any of the three COVID-19 vaccines (Pfizer, Moderna, AstraZeneca) authorized for use in the U.K.?
To answer that question, Claire Steves, King’s College, London, and colleagues looked to frequent users of the COVID Symptom Study app on their smartphones. In its new work, Steves’ team was interested in analyzing data submitted by folks who’d logged their symptoms, test results, and vaccination status between December 9, 2020, and July 4, 2021. The team found there were more than 1.2 million adults who’d received a first dose of vaccine and nearly 1 million who were fully vaccinated during this period.
The data show that only 0.2 percent of those who were fully vaccinated later tested positive for COVID-19. While accounting for differences in age, sex, and other risk factors, the researchers found that fully vaccinated individuals who developed breakthrough infections were about half (49 percent) as likely as unvaccinated people to report symptoms of Long COVID Syndrome lasting at least four weeks after infection.
The most common symptoms were similar in vaccinated and unvaccinated adults with COVID-19, and included loss of smell, cough, fever, headaches, and fatigue. However, all of these symptoms were milder and less frequently reported among the vaccinated as compared to the unvaccinated.
Vaccinated people who became infected were also more likely than the unvaccinated to be asymptomatic. And, if they did develop symptoms, they were half as likely to report multiple symptoms in the first week of illness. Another vaccination benefit was that people with a breakthrough infection were about a third as likely to report any severe symptoms. They also were more than 70 percent less likely to require hospitalization.
We still have a lot to learn about Long COVID, and, to get the answers, NIH has launched the RECOVER Initiative. The initiative will study tens of thousands of COVID-19 survivors to understand why many individuals don’t recover as quickly as expected, and what might be the cause, prevention, and treatment for Long COVID.
In the meantime, these latest findings offer the encouraging news that help is already here in the form of vaccines, which provide a very effective way to protect against COVID-19 and greatly reduce the odds of Long COVID if you do get sick. So, if you haven’t done so already, make a plan to protect your own health and help end this pandemic by getting yourself fully vaccinated. Vaccines are free and available near to you—just go to vaccines.gov or text your zip code to 438829.
Reference:
[1] Risk factors and disease profile of post-vaccination SARS-CoV-2 infection in UK users of the COVID Symptom Study app: a prospective, community-based, nested, case-control study. Antonelli M, Penfold RS, Merino J, Sudre CH, Molteni E, Berry S, Canas LS, Graham MS, Klaser K, Modat M, Murray B, Kerfoot E, Chen L, Deng J, Österdahl MF, Cheetham NJ, Drew DA, Nguyen LH, Pujol JC, Hu C, Selvachandran S, Polidori L, May A, Wolf J, Chan AT, Hammers A, Duncan EL, Spector TD, Ourselin S, Steves CJ. Lancet Infect Dis. 2021 Sep 1:S1473-3099(21)00460-6.
Links:
COVID-19 Research (NIH)
Claire Steves (King’s College London, United Kingdom)
Predicting ‘Long COVID Syndrome’ with Help of a Smartphone App
Posted on by Dr. Francis Collins
As devastating as this pandemic has been, it’s truly inspiring to see the many innovative ways in which researchers around the world have enlisted the help of everyday citizens to beat COVID-19. An intriguing example is the COVID Symptom Study’s smartphone-based app, which already has been downloaded millions of times, mostly in the United States and United Kingdom. Analyzing data from 2.6 million app users, researchers published a paper last summer showing that self-reported symptoms can help to predict infection with SARS-CoV-2, the coronavirus that causes COVID-19 [1].
New work from the COVID Symptom Study now takes advantage of the smartphone app to shed more light on Long COVID Syndrome [2], in which people experience a constellation of symptoms long past the time that they’ve recovered from the initial stages of COVID-19 illness. Such symptoms, which can include fatigue, shortness of breath, “brain fog,” sleep disorders, fevers, gastrointestinal symptoms, anxiety, and depression, can persist for months and can range from mild to incapacitating
This latest findings, published in the journal Nature Medicine, come from a team led by Claire Steves and Tim Spector, King’s College London, and their colleagues, and that includes NIH grantee Andrew Chan, Massachusetts General Hospital, Boston, and others supported by the Massachusetts Consortium on Pathogen Readiness. The team began by looking at data recorded between March 24-Sept. 2, 2020 from about 4.2 million app users with an average age of 45, about 90 percent of whom lived in the U.K., with smaller numbers from the U.S. and Sweden.
For this particular study, the researchers decided to focused on 4,182 app users, all with confirmed COVID-19, who had consistently logged in their symptoms. Because these individuals also started using the app when they still felt physically well, the researchers could assess their COVID-19-associated symptoms over the course of the illness.
While most people who developed COVID-19 were back to normal in less than two weeks, the data suggest that one in 20 people with COVID-19 are likely to suffer symptoms of Long COVID that persist for eight weeks or more. About one in 50 people continued to have symptoms for 12 weeks or more. That suggests Long COVID could potentially affect many hundreds of thousands of people in the U.K. alone and millions more worldwide.
The team found that the individuals most likely to develop Long COVID were older people, women, and especially those who experienced five or more symptoms. The nature and order of symptoms, which included fatigue, headache, shortness of breath, and loss of smell, didn’t matter. People with asthma also were more likely to develop long-lasting symptoms, although the study found no clear links to any other pre-existing health conditions.
Using this information, the researchers developed a model to predict which individuals were most likely to develop Long COVID. Remarkably, this simple algorithm—based on age, gender, and number of early symptoms–accurately predicted almost 70 percent of cases of Long COVID. It was also about 70 percent effective in avoiding false alarms.
The team also validated the algorithm’s predictive ability in data from an independent group of 2,472 people with confirmed COVID-19 and a range of symptoms. In this group, having more than five symptoms within the first week also proved to be the strongest predictor of Long COVID. And, again, the model worked quite well in identifying those most likely to develop Long COVID.
These findings come as yet another important reminder of the profound impact of the COVID-19 pandemic on public health. This includes not only people who are hospitalized with severe COVID-19 but, all too often, those who get through the initial period of infection relatively unscathed.
Recently, NIH announced a $1.15 billion investment to identify the causes of Long COVID, to develop ways of treating individuals who don’t fully recover, and, ultimately, to prevent the disorder. We’ve been working diligently in recent weeks to identify the most pressing questions and areas of greatest opportunity to address this growing public health threat. As a first step, NIH is funding an effort to track the recovery paths of at least 40,000 adults and children infected with SARS-CoV-2, to learn more about who develops long-term effects and who doesn’t. If you’d like to find a way to pitch in and help, getting involved in the COVID Symptom Study is as easy as downloading the app.
References:
[1] Real-time tracking of self-reported symptoms to predict potential COVID-19. Menni C, Valdes AM, Freidin MB, Sudre CH, Nguyen LH, Drew DA, Ganesh S, Varsavsky T, Cardoso MJ, El-Sayed Moustafa JS, Visconti A, Hysi P, Bowyer RCE, Mangino M, Falchi M, Wolf J, Ourselin S, Chan AT, Steves CJ, Spector TD. Nat Med. 2020 Jul;26(7):1037-1040. doi: 10.1038/s41591-020-0916-2. Epub 2020 May 11.
[2] Attributes and predictors of long COVID. Sudre CH, Murray B, Varsavsky T, Graham MS, Penfold RS, Bowyer RC, Pujol JC, Klaser K, Antonelli M, Canas LS, Molteni E, Modat M, Jorge Cardoso M, May A, Ganesh S, Davies R, Nguyen LH, Drew DA, Astley CM, Joshi AD, Merino J, Tsereteli N, Fall T, Gomez MF, Duncan EL, Menni C, Williams FMK, Franks PW, Chan AT, Wolf J, Ourselin S, Spector T, Steves CJ. Nat Med. 2021 Mar 10.
Links:
NIH launches new initiative to study to “Long COVID”. 2021 Feb 23. (NIH)
COVID-19 Research (NIH)
Massachusetts Consortium on Pathogen Readiness (Boston)
Claire Steves (King’s College London, United Kingdom)
Tim Spector (King’s College London)
Andrew Chan (Massachusetts General Hospital, Boston)
NIH Support: National Institute of Diabetes and Digestive and Kidney Diseases
Trying to Make Sense of Long COVID Syndrome
Posted on by Dr. Francis Collins
More than 400,000 Americans have now lost their lives to COVID-19. But thousands of others who’ve gotten sick and survived COVID-19 are finding that a full recovery can be surprisingly elusive. Weeks and months after seemingly recovering from even mild cases of COVID-19, many battle a wide range of health problems.
Indeed, new results from the largest global study of this emerging “Long COVID syndrome” highlight just how real and pressing this public health concern really is. The study, reported recently as a pre-print on medRxiv, is based on survey results from more than 3,700 self-described COVID “Long Haulers” in 56 countries [1]. They show nearly half couldn’t work full time six months after unexpectedly developing prolonged symptoms of COVID-19. A small percentage of respondents, thankfully, seemed to have bounced back from brief bouts of Long COVID, though time will tell whether they have fully recovered.
These findings are the second installment from the online Body Politic COVID-19 Support Group and its Patient-Led Research for COVID-19, which consists of citizen scientists with a wide range of expertise in the arts and sciences who are struggling with the prolonged effects of COVID-19 themselves. In an earlier survey, this group provided a first-draft description of Long COVID syndrome, based on the self-reported experiences of 640 respondents.
In the new survey-based study led by Athena Akrami, with Patient-Led Research for COVID-19 and University College London, England, the goal was to characterize the experiences of many more people with Long COVID syndrome. They now define the syndrome as a collection of symptoms lasting for more than 28 days.
This second survey emphasizes the course and severity of more than 200 symptoms over time, including those affecting the heart, lungs, gastrointestinal system, muscles, and joints. It took a particularly in-depth look at neurological and neuropsychiatric symptoms, along with the ability of COVID-19 survivors to return to work and participate in other aspects of everyday life.
The 3,762 individuals who responded to the survey were predominately white females, between the ages of 30 and 60, who lived in the United States. As in the previous survey, the study included adults with symptoms consistent with COVID-19, whether or not the infection had been confirmed by a viral or antibody test. That is a potential weakness of the study, as some of these individuals may have had some other inciting illness. But many of the study’s participants developed symptoms early on in the pandemic, when testing was much more limited than it is now.
More than half never sought hospital care. Only 8 percent said that they’d been admitted to the hospital for COVID-19. And yet, 2,464 respondents reported COVID-19 symptoms lasting six months or longer. Most of the remaining respondents also continued to have symptoms, although they had not yet reached the six-month mark.
Among the most common symptoms were fatigue, worsening of symptoms after physical or mental activity, shortness of breath, trouble sleeping, and “brain fog,” or difficulty thinking clearly. The majority—88 percent—said they coped with some form of cognitive dysfunction or memory loss that to varying degrees affected their everyday lives. That includes the ability to make decisions, have conversations, follow instructions, and drive.
Those who had prolonged symptoms of COVID-19 for more than six months reported contending with about 14 symptoms on average. Most also reported that they’d had a relapse of symptoms, seemingly triggered by exercise, mental activity, or just everyday stress. When surveyed, nearly half of respondents said they’d had to reduce their hours at work due to the severity of their symptoms. Another 22 percent weren’t working at all due to their Long COVID.
The findings show that—even in those people who don’t require hospitalization for severe COVID-19—the condition’s prolonged symptoms are having a major impact on lives and livelihoods, both here and around the world. While the number of people affected isn’t yet known, if even a small proportion of the vast numbers of people infected with COVID-19 develop Long COVID syndrome, it represents a significant public health concern.
Another recent study from China further documents the tendency of COVID-19-related symptoms to linger past the usual recovery time for a respiratory virus [2]. The study, published in Lancet, showed that six months after the onset of illness, more than 75 percent of people hospitalized with COVID-19 in Wuhan between January and May 2020 continued to report at least one symptom. Fatigue, muscle weakness, sleep difficulties, anxiety, and depression all were common. More than half of individuals also had significant persistent lung abnormalities, which were more common in those who’d been more severely ill.
It’s essential for us to learn all we can about how SARS-CoV-2, which is the coronavirus that causes COVID-19, leads to such widespread symptoms. It’s also essential that we develop ways to better treat or prevent these symptoms. The NIH held a workshop last month to summarize what is known and fill in key gaps in our knowledge about Long COVID syndrome, which is clinically known as post-acute sequelae of COVID-19 (PASC). In December, Congress authorized funding for continued research on PASC, including an appropriation of funds for NIH to support continued study of these prolonged health consequences.
As these efforts and others proceed in the coming months, the hope is that we’ll gain much more insight and get some answers soon. And, if you’ve had or are currently experiencing symptoms of COVID-19, there’s still time to share your data by participating in the Patient-Led Research for COVID-19’s second survey.
References:
[1] Characterizing Long COVID in an international cohort: 7 months of symptoms and their impact. David HE et al. Medrxiv. 27 December 27 2020.
[2] 6-month consequences of COVID-19 in patients discharged from hospital: a cohort study. Huang C, Huang L, et al. Lancet. 2021 Jan 16;397(10270):220-232.
Links:
COVID-19 Research (NIH)
Akrami Lab (Sainsbury Wellcome Center, University College London, England)
Patient-led Research for COVID-19
Video: Workshop on Post-Acute Sequelae of COVID-19 (NIH)
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