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Understanding Long-Term COVID-19 Symptoms and Enhancing Recovery

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RECOVER: Researching COVID to Enhance Recovery. An Initiative Funded by the National Institutes of Health

We are in the third year of the COVID-19 pandemic, and across the world, most restrictions have lifted, and society is trying to get back to “normal.” But for many people—potentially millions globally—there is no getting back to normal just yet.

They are still living with the long-term effects of a COVID-19 infection, known as the post-acute sequelae of SARS-CoV-2 infection (PASC), including Long COVID. These people continue to experience debilitating fatigue, shortness of breath, pain, difficulty sleeping, racing heart rate, exercise intolerance, gastrointestinal and other symptoms, as well as cognitive problems that make it difficult to perform at work or school.

This is a public health issue that is in desperate need of answers. Research is essential to address the many puzzling aspects of Long COVID and guide us to effective responses that protect the nation’s long-term health.

For the past two years, NIH’s National Heart, Lung, and Blood Institute (NHLBI), the National Institute of Allergy and Infectious Diseases (NIAID), and my National Institute of Neurological Disorders and Stroke (NINDS) along with several other NIH institutes and the office of the NIH Director, have been leading NIH’s Researching COVID to Enhance Recovery (RECOVER) initiative, a national research program to understand PASC.

The initiative studies core questions such as why COVID-19 infections can have lingering effects, why new symptoms may develop, and what is the impact of SARS-CoV-2, the virus that causes COVID-19, on other diseases and conditions? Answering these fundamental questions will help to determine the underlying biologic basis of Long COVID. The answers will also help to tell us who is at risk for Long COVID and identify therapies to prevent or treat the condition.

The RECOVER initiative’s wide scope of research is also unprecedented. It is needed because Long COVID is so complex, and history indicates that similar post infectious conditions have defied definitive explanation or effective treatment. Indeed, those experiencing Long COVID report varying symptoms, making it highly unlikely that a single therapy will work for everyone, underscoring the need to pursue multiple therapeutic strategies.

To understand Long COVID fully, hundreds of RECOVER investigators are recruiting more than 17,000 adults (including pregnant people) and more than 18,000 children to take part in cohort studies. Hundreds of enrolling sites have been set up across the country. An autopsy research cohort will also provide further insight into how COVID-19 affects the body’s organs and tissues.

In addition, researchers will analyze electronic health records from millions of people to understand how Long COVID and its symptoms change over time. The RECOVER initiative is also utilizing consistent research protocols across all the study sites. The protocols have been carefully developed with input from patients and advocates, and they are designed to allow for consistent data collection, improve data sharing, and help to accelerate the pace of research.

From the very beginning, people suffering from Long COVID have been our partners in RECOVER. Patients and advocates have contributed important perspectives and provided valuable input into the master protocols and research plans.

Now, with RECOVER underway, individuals with Long COVID, their caregivers, and community members continue to serve a critical role in the Initiative. The National Community Engagement Group (NCEG) has been established to make certain that RECOVER meets the needs of all people affected by Long COVID. The RECOVER Patient and Community Engagement Strategy outlines all the approaches that RECOVER is using to engage with and gather input from individuals impacted by Long COVID.

The NIH recently made more than 40 awards to improve understanding of the underlying biology and pathology of Long COVID. There have already been several important findings published by RECOVER scientists.

For example, in a recent study published in the journal Lancet Digital Health, RECOVER investigators used machine learning to comb through electronic health records to look for signals that may predict whether someone has Long COVID [1]. As new findings, tools, and technologies continue to emerge that help advance our knowledge of the condition, the RECOVER Research Review (R3) Seminar Series will provide a forum for researchers and our partners with up-to-date information about Long COVID research.

It is important to note that post-viral conditions are not a new concept. Many, but not all, of the symptoms reported in Long COVID, including fatigue, post-exertional malaise, chronic musculoskeletal pain, sleep disorders, postural orthostatic tachycardia (POTS), and cognitive issues, overlap with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS).

ME/CFS is a serious disease that can occur following infection and make people profoundly sick for decades. Like Long COVID, ME/CFS is a heterogenous condition that does not affect everybody in the same way, and the knowledge gained through research on Long COVID may also positively impact the understanding, treatment, and prevention of POTS, ME/CFS, and other chronic diseases.

Unlike other post-viral conditions, people who experience Long COVID were all infected by the same virus—albeit different variants—at a similar point in time. This creates a unique opportunity for RECOVER researchers to study post-viral conditions in real-time.

The opportunity enables scientists to study many people simultaneously while they are still infected to monitor their progress and recovery, and to try to understand why some individuals develop ongoing symptoms. A better understanding of the transition from acute to chronic disease may offer an opportunity to intervene, identify who is at risk of the transition, and develop therapies for people who experience symptoms long after the acute infection has resolved.

The RECOVER initiative will soon announce clinical trials, leveraging data from clinicians and patients in which symptom clusters were identified and can be targeted by various interventions. These trials will investigate therapies that are indicated for other non-COVID conditions and novel treatments for Long COVID.

Through extensive collaboration across the multiple NIH institutes and offices that contribute to the RECOVER effort, our hope is critical answers will emerge soon. These answers will help us to recognize the full range of outcomes and needs resulting from PASC and, most important, enable many people to make a full recovery from COVID-19. We are indebted to the over 10,000 subjects who have already enrolled in RECOVER. Their contributions and the hard work of the RECOVER investigators offer hope for the future to the millions still suffering from the pandemic.

Reference:

[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 Jul;4(7):e532-e541.

Links:

COVID-19 Research (NIH)

Long COVID (NIH)

RECOVER: Researching COVID to Enhance Recovery (NIH)

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.

Director’s Messages (National Institute of Neurological Disorders and Stroke/NIH)

Note: Dr. Lawrence Tabak, who performs the duties of the NIH Director, has asked the heads of NIH’s Institutes and Centers (ICs) to contribute occasional guest posts to the blog to highlight some of the interesting science that they support and conduct. This is the 18th in the series of NIH IC guest posts that will run until a new permanent NIH director is in place.


Small Study Suggests Approved Insomnia Drug Can Aid in Opioid Recovery

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inset of suvorexant blocking receptors for orexin, a sleeping woman

Opioid use disorders (OUD) now threaten the health and lives of far too many young and adult Americans. While getting treatment is a key first step to recovery, overcoming an opioid addiction often comes with brutal withdrawal symptoms, including bad bouts of insomnia that are often untreatable with traditional prescription sleep medications. These medications act as sedatives, making them unsafe for people in OUD recovery.

But now, researchers have found that an approved drug for insomnia that works differently than other sleep medications could offer some needed help for the sleeplessness that affects those overcoming an opioid addiction [1]. The drug, known as suvorexant (Belsomra ®), was provided in a study to people during and immediately after tapering off opioids, and it allowed them to sleep significantly more during this week-long period. Suvorexant also helped to reduce their opioid withdrawal and craving.

This study, which received support from NIH’s Helping to End Addiction Long-term (HEAL) Initiative certainly offers promising news. The Food and Drug Administration (FDA) approved suvorexant to treat insomnia in 2014, and it is available for off-label use to help people overcoming an OUD.

The good news, however, comes with a major caveat. This early clinical trial had relatively small enrollment numbers, and larger studies are definitely needed to follow up and confirm the initial results.

The latest findings, published in the journal Science Translational Medicine, come from a team at Johns Hopkins University School of Medicine, Baltimore, led by Andrew Huhn. He and colleagues recognized sleep disturbances as a severe problem during recovery. They wondered whether suvorexant might help.

Suvorexant doesn’t actively sedate people like other sleeping medications. Suvorexant works by targeting orexin, a biochemical made in the brain that helps keep you awake [2]. Interestingly, orexin signals also have been implicated in opioid withdrawal symptoms, sleep disturbances, and drug-seeking behaviors.

Thirty-eight people entered the Hopkins study, and 26 completed it. Their average age was about 40, with close to equal numbers of white and Black participants. Most were male, and all were undergoing supervised withdrawal treatment with buprenorphine/naloxone, which is used in combination as a medication-assisted treatment for OUD.

To find out if suvorexant helped, the researchers measured total sleep time nightly using wireless devices that recorded brain activity and movement in people taking either 20 milligrams or 40 milligrams of suvorexant versus a placebo. The researchers also used standard methods to assess symptoms of opioid withdrawal, along with suvorexant’s potential for abuse.

The data showed that people taking suvorexant over four days while tapering off opioids slept about 90 minutes longer per night on average. They also continued to sleep for an extra hour a night on average in the four days following the tapering period. The researchers note that these increases in sleep duration far exceed the American Academy of Sleep Medicine’s threshold for clinically meaningful improvement.

The researchers also didn’t see any differences in adverse events between those taking suvorexant versus a placebo. They also note that the main side effect of suvorexant in general is feeling sleepy the next day as the drug wears off slowly. There also wasn’t any evidence that suvorexant might come with a risk for drug abuse.

However, because the study was small, it lacked the needed statistical power to determine meaningful differences between the two doses of suvorexant. The study also didn’t include many women. But overall, the evidence that suvorexant or even other medications that target orexin could improve OUD treatment appears quite promising.

The NIH’s HEAL Initiative has launched over 600 research projects across the country. These studies cover a range of science and health care needs. But a common thread running through these projects is a desire to enhance the evidence base for lifesaving OUD interventions. Another is a commitment to discover better ways to help people recover from an OUD, and these latest data on suvorexant show this commitment in action.

References:

[1] Suvorexant ameliorated sleep disturbance, opioid withdrawal, and craving during a buprenorphine taper. Huhn AS, Finan PH, Gamaldo CE, Hammond AS, Umbricht A, Bergeria CL, Strain EC, Dunn KE. Sci Transl Med. 2022 Jun 22;14(650):eabn8238.

[2] The hypocretin/orexin system. Ebrahim IO, et al. J R Soc Med. 2002 May;95(5):227-30.

Links:

SAMHSA’s National Helpline (Substance Abuse and Mental Health Services Administration, Rockville, MD)

Opioids (National Institute on Drug Abuse/NIH)

Helping to End Addiction Long-term (HEAL) Initiative (NIH)

Andrew Huhn (Johns Hopkins School of Medicine, Baltimore)

NIH Support: National Institute on Drug Abuse


Months After Recovery, COVID-19 Survivors Often Have Persistent Lung Trouble

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Lung function test
Caption: Testing breathing capacity with a spirometer. Credit: iStock/Koldunov

The pandemic has already claimed far too many lives in the United States and around the world. Fortunately, as doctors have gained more experience in treating coronavirus disease 2019 (COVID-19), more people who’ve been hospitalized eventually will recover. This raises an important question: what does recovery look like for them?

Because COVID-19 is still a new condition, there aren’t a lot of data out there yet to answer that question. But a recent study of 55 people recovering from COVID-19 in China offers some early insight into the recovery of lung function [1]. The results make clear that—even in those with a mild-to-moderate infection—the effects of COVID-19 can persist in the lungs for months. In fact, three months after leaving the hospital about 70 percent of those in the study continued to have abnormal lung scans, an indication that the lungs are still damaged and trying to heal.

The findings in EClinicalMedicine come from a team in Henan Province, China, led by Aiguo Xu, The First Affiliated Hospital of Zhengzhou University; Yanfeng Gao, Zhengzhou University; and Hong Luo, Guangshan People’s Hospital. They’d heard about reports of lung abnormalities in patients discharged from the hospital. But it wasn’t clear how long those problems stuck around.

To find out, the researchers enrolled 55 men and women who’d been admitted to the hospital with COVID-19 three months earlier. Some of the participants, whose average age was 48, had other health conditions, such as diabetes or heart disease. But none had any pre-existing lung problems.

Most of the patients had mild or moderate respiratory illness while hospitalized. Only four of the 55 had been classified as severely ill. Fourteen patients required supplemental oxygen while in the hospital, but none needed mechanical ventilation.

Three months after discharge from the hospital, all of the patients were able to return to work. But they continued to have lingering symptoms of COVID-19, including shortness of breath, cough, gastrointestinal problems, headache, or fatigue.

Evidence of this continued trouble also showed up in their lungs. Thirty-nine of the study’s participants had an abnormal result in their computed tomography (CT) lung scan, which creates cross-sectional images of the lungs. Fourteen individuals (1 in 4) also showed reduced lung function in breathing tests.

Interestingly, the researchers found that those who went on to have more lasting lung problems also had elevated levels of D-dimer, a protein fragment that arises when a blood clot dissolves. They suggest that a D-dimer test might help to identify those with COVID-19 who would benefit from pulmonary rehabilitation to rebuild their lung function, even in the absence of severe respiratory symptoms.

This finding also points to the way in which the SARS-CoV-2 virus seems to enhance a tendency toward blood clotting—a problem addressed in our Accelerating COVID-19 Therapeutic Interventions and Vaccines (ACTIV) public-private partnership. The partnership recently initiated a trial of blood thinners. That trial will start out by focusing on newly diagnosed outpatients and hospitalized patients, but will go on to include a component related to convalescence.

Moving forward, it will be important to conduct larger and longer-term studies of COVID-19 recovery in people of diverse backgrounds to continue to learn more about what it means to survive COVID-19. The new findings certainly indicate that for many people who’ve been hospitalized with COVID-19, regaining normal lung function may take a while. As we learn even more about the underlying causes and long-term consequences of this new infectious disease, let’s hope it will soon lead to insights that will help many more COVID-19 long-haulers and their concerned loved ones breathe easier.

Reference:

[1] Follow-up study of the pulmonary function and related physiological characteristics of COVID-19 survivors three months after recovery. Zhao YM, Shang YM, Song WB, Li QQ, Xie H, Xu QF, Jia JL, Li LM, Mao HL, Zhou XM, Luo H, Gao YF, Xu AG. EClinicalMedicine.2020 Aug 25:100463

Links:

Coronavirus (COVID-19) (NIH)

How the Lungs Work (National Heart, Lung, and Blood Institute/NIH)

Computed Tomography (CT) (National Institute of Biomedical Imaging and Bioengineering/NIH)

Zhengzhou University (Zhengzhou City, Henan Province, China)

Accelerating COVID-19 Therapeutic Interventions and Vaccines (ACTIV) (NIH)


Gratitude for Biomedical Progress and All Those Who Make It Possible

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Group of people holding hands around a dinner table
Credit: Shutterstock/Rawpixel.com

It’s good for our health to eat right, exercise, and get plenty of rest. Still, many other things contribute to our sense of wellbeing, including making it a point to practice gratitude whenever we can. With this in mind, I can’t think of a better time than Thanksgiving to recognize just a few of the many reasons that I—and everyone who believes in the mission of the National Institutes of Health (NIH)—have to be grateful.

First, I’m thankful for the many enormously talented people with whom I’ve worked over the past year while performing the duties of the NIH Director. Particular thanks go to those on my immediate team within the Office of the Director. I could not have taken on this challenge without their dedicated support.

I’m also gratified by the continued enthusiasm and support for biomedical research from so many different corners of our society. This includes the many thousands of unsung, patient partners who put their time, effort, and, in some cases, even their lives on the line for the sake of medical progress and promising treatment advances. Without them, clinical research—including the most pivotal clinical trials—simply wouldn’t be possible.

I am most appreciative of the continuing efforts at NIH and across the broader biomedical community to further enable diversity, equity, inclusion, and accessibility within the biomedical research workforce and in all the work that NIH supports.

High on my Thanksgiving list is the widespread availability of COVID-19 bivalent booster shots. These boosters not only guard against older strains of the coronavirus, but also broaden immunity to the newer Omicron variant and its many subvariants. I’m also tremendously grateful for everyone who has—or soon will—get boosted to protect yourself, your loved ones, and your communities as the winter months fast approach.

Another big “thank you” goes out to all the researchers studying Long COVID, the complex and potentially debilitating constellation of symptoms that strikes some people after recovery from COVID-19. I look forward to more answers as this work continues and we certainly couldn’t do it without our patient partners.

I’d also like to express my appreciation for the NIH’s institute and center directors who’ve contributed to the NIH Director’s Blog to showcase NIH’s broad and diverse portfolio of promising research.

Finally, a special thanks to all of you who read this blog. As you gather with family and friends to celebrate this Thanksgiving holiday, I hope the time you spend here gives you a few more reasons to feel grateful and appreciate the importance of NIH in turning scientific discovery into better health for all.


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


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