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 . 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.
 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.
 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.
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
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 . 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 . 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.
 Characterizing Long COVID in an international cohort: 7 months of symptoms and their impact. David HE et al. Medrxiv. 27 December 27 2020.
 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.
COVID-19 Research (NIH)