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Long COVID syndrome

Using AI to Advance Understanding of Long COVID Syndrome

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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)

RECOVER Initiative

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 Occur in Those with Lower Antibody Levels, Israeli Study Shows

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A wall of bricks with antibody symbols on them. Where one brick is missing, viruses flood through.

To see how COVID-19 vaccines are working in the real world, Israel has provided particularly compelling data. The fact that Israel is relatively small, keeps comprehensive medical records, and has a high vaccination rate with a single vaccine (Pfizer) has contributed to its robust data collection. Now, a new Israeli study offers some insight into those relatively uncommon breakthrough infections. It confirms that breakthrough cases, as might be expected, arise most often in individuals with lower levels of neutralizing antibodies.

The findings reported in The New England Journal of Medicine focused on nearly 1,500 of about 11,500 fully vaccinated health care workers at Sheba Medical Center, Ramat Gan, Israel [1]. All had received two doses of the Pfizer mRNA vaccine. But, from December 19, 2020 to April 28, 2021, they were tested for a breakthrough infection due to a known exposure to someone with COVID-19 or possible symptoms of the disease.

Just 39 confirmed breakthrough cases were found, indicating a breakthrough infection rate of just 0.4 percent. That’s consistent with rates reported in previous studies. Most in the Israeli study who tested positive for COVID-19 had mild or no symptoms and none required hospitalization.

In the new study, researchers led by Gili Regev-Yochay at Sheba Medical Center’s Infection Control and Prevention Unit, characterized as many breakthrough infections as possible among the health care workers. Almost half of the infections involved members of the hospital nursing staff. But breakthrough cases also were found in hospital administration, maintenance workers, doctors, and other health professionals.

The average age of someone with a breakthrough infection was 42, and it’s notable that only one person was known to have a weakened immune system. The most common symptoms were respiratory congestion, muscle aches (myalgia), and loss of smell or taste. Most didn’t develop a fever. At six weeks after diagnosis, 19 percent reported having symptoms of Long COVID syndrome, including prolonged loss of smell, persistent cough, weakness, and fatigue. About a quarter stayed home from work for longer than the required 10 days, and one had yet to return to work at six weeks.

For 22 of the 39 people with a breakthrough infection, the researchers had results of neutralizing antibody tests from the week leading up to their positive COVID-19 test result. To look for patterns in the antibody data, they matched those individuals to 104 uninfected people for whom they also had antibody test results. These data showed that those with a breakthrough infection had consistently lower levels of neutralizing antibodies circulating in their bloodstream to SARS-CoV-2, the coronavirus that causes COVID-19. In general, higher levels of neutralizing antibodies are associated with greater protection and lower infectivity—though other aspects of the immune system (memory B cells and cell-mediated immunity) also contribute.

Importantly, in all cases for which there were relevant data, the source of the breakthrough infection was thought to be an unvaccinated person. In fact, more than half of those who developed a breakthrough infection appeared to have become infected from an unvaccinated member of their own household.

Other cases were suspected to arise from exposure to an unvaccinated coworker or patient. Contact tracing found no evidence that any of the 39 health care workers with a breakthrough infection passed it on to anyone else.

The findings add to evidence that full vaccination and associated immunity offer good protection against SARS-CoV-2 infection and severe illness. Understanding how SARS-CoV-2 immunity changes over time is key for charting the course of this pandemic and making important decisions about COVID-19 vaccine boosters.

Many questions remain. For instance, it’s not clear from the study whether lower neutralizing antibodies in those with breakthrough cases reflect waning immunity or, for reasons we don’t yet understand, those individuals may have had a more limited immune response to the vaccine. Also, this study was conducted before the Delta variant became dominant in Israel (and now in the whole world).

Overall, these findings provide more reassurance that these vaccines are extremely effective. Breakthrough infections, while they can and do occur, are a relatively uncommon event. Here in the U.S., the Centers for Disease Control and Prevention (CDC) has recently estimated that infection is six times less likely for vaccinated than unvaccinated persons [2]. That those with immunity tend to have mild or no symptoms if they do develop a breakthrough case, however, is a reminder that these cases could easily be missed, and they could put vulnerable populations at greater risk. It’s yet another reason for all those who can to get themselves vaccinated as soon as possible or consider a booster shot when they become eligible.

References:

[1] Covid-19 breakthrough infections in vaccinated health care workers. Bergwerk M, Gonen T, Lustig Y, Amit S, Lipsitch M, Cohen C, Mandelboim M, Levin EG, Rubin C, Indenbaum V, Tal I, Zavitan M, Zuckerman N, Bar-Chaim A, Kreiss Y, Regev-Yochay G. N Engl J Med. 2021 Oct 14;385(16):1474-1484.

[2] Rates of COVID-19 cases and deaths by vaccination status, COVID Data Tracker, Centers for Disease and Prevention. Accessed October 25, 2021.

Links:

COVID-19 Research (NIH)

Sheba Medical Center (Ramat Gan, Israel)


Breakthrough Infections in Vaccinated People Less Likely to Cause ‘Long COVID’

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Long Covid. Two syringes in an arrow pointed down. symptoms of long covid in the background

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)

COVID Symptom Study


Study Finds 1 in 10 Healthcare Workers with Mild COVID Have Lasting Symptoms

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People showing symtoms of anosmia, fatigue, and ageusia
Credit: Getty Images

It’s become increasingly clear that even healthy people with mild cases of COVID-19 can battle a constellation of symptoms that worsen over time—or which sometimes disappear only to come right back. These symptoms are part of what’s called “Long COVID Syndrome.”

Now, a new study of relatively young, healthy adult healthcare workers in Sweden adds needed information on the frequency of this Long COVID Syndrome. Published in the journal JAMA, the study found that just over 1 in 10 healthcare workers who had what at first seemed to be a relatively mild bout of COVID-19 were still coping with at least one moderate to severe symptom eight months later [1]. Those symptoms—most commonly including loss of smell and taste, fatigue, and breathing problems—also negatively affected the work and/or personal lives of these individuals.

These latest findings come from the COVID-19 Biomarker and Immunity (COMMUNITY) study, led by Charlotte Thålin, Danderyd Hospital and Karolinska Institutet, Stockholm. The study, launched a year ago, enlisted 2,149 hospital employees to learn more about immunity to SARS-CoV-2, the coronavirus that causes COVID-19.

After collecting blood samples from participants, the researchers found that about 20 percent already had antibodies to SARS-CoV-2, evidence of a past infection. Thålin and team continued collecting blood samples every four months from all participants, who also completed questionnaires about their wellbeing.

Intrigued by recent reports in the medical literature that many people hospitalized with COVID-19 can have persistent symptoms for months after their release, the researchers decided to take a closer look in their COMMUNITY cohort. They did so last January during their third round of follow up.

This group included 323 mostly female healthcare workers, median age of 43. The researchers compared symptoms in this group following mild COVID-19 to the 1,072 mostly female healthcare workers in the study (median age 47 years) who hadn’t had COVID-19. They wanted to find out if those with mild COVID-19 coped with more and longer-lasting symptoms of feeling unwell than would be expected in an otherwise relatively healthy group of people. These symptoms included familiar things such as fatigue, muscle pain, trouble sleeping, and problems breathing.

Their findings show that 26 percent of those who had mild COVID-19 reported at least one moderate to severe symptom that lasted more than two months. That’s compared to 9 percent of participants without COVID-19. What’s more, 11 percent of the individuals with mild COVID-19 had at least one debilitating symptom that lasted for at least eight months. In the group without COVID-19, any symptoms of feeling unwell resolved relatively quickly.

The most common symptoms in the COVID-19 group were loss of taste or smell, fatigue, and breathing problems. In this group, there was no apparent increase in other symptoms that have been associated with COVID-19, including “brain fog,” problems with memory or attention, heart palpitations, or muscle and joint pain.

The researchers have noted that the Swedish healthcare workers represent a relatively young and healthy group of working individuals. Yet, many of them continued to suffer from lasting symptoms related to mild COVID-19. It’s a reminder that COVID-19 can and, in fact, is having a devastating impact on the lives and livelihoods of adults who are at low risk for developing severe and life-threatening COVID-19. If we needed one more argument for getting young people vaccinated, this is it.

At NIH, efforts have been underway for some time to identify the causes of Long COVID. In fact, a virtual workshop was held last winter with more than 1,200 participants to discuss what’s known and to fill in key gaps in our knowledge of Long COVID syndrome, which is clinically known as post-acute sequelae of COVID-19 (PASC). Recently, a workshop summary was published [2]. As workshops and studies like this one from Sweden help to define the problem, the hope is to learn one day how to treat or prevent this terrible condition. The NIH is now investing more than $1 billion in seeking those answers.

References:

[1] Symptoms and functional impairment assessed 8 Months after mild COVID-19 among health care workers. Havervall S, Rosell A, Phillipson M, Mangsbo SM, Nilsson P, Hober S, Thålin C. JAMA. 2021 Apr 7.

[2] Toward understanding COVID-19 recovery: National Institutes of Health workshop on postacute COVID-19. Lerner A, et al. Ann Intern Med, 2021 March 30.

Links:

COVID-19 Research (NIH)

Charlotte Thålin (Karolinska Institutet, Stockholm, Sweden)


Predicting ‘Long COVID Syndrome’ with Help of a Smartphone App

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Zoe COVID Sympton Study Tracker app
Credit: Zoe Global

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)

COVID Symptom Study

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


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