Skip to main content

Sharing science to find answers

Find RECOVER Publications

Researchers within the RECOVER Initiative share their progress to understand, treat, and prevent Long COVID through research publications. Follow the latest science from RECOVER’s research studies below.

Visit the Research Summaries page to learn about RECOVER’s Long COVID research in a format that’s easy to understand.

Last updated:

54 Results

Filters

54 Results

Filters Applied:
EHR Adult
Reddy, NV; Yeh, HC; Tronieri, JS; et. al.N3C and RECOVER Consortiums, Journal of Clinical and Translational Science
Published:
Journal: Journal of Clinical and Translational Science
Abstract: Long-term sequelae of severe acute respiratory coronavirus-2 (SARS-CoV-2) infection may include increased incidence of diabetes. Here we describe the temporal relationship between new type 2 diabetes and SARS-CoV-2 infection in a nationwide database. We found that while the proportion of newly diagnosed type 2 diabetes increased during the acute period of SARS-CoV-2 infection, the mean proportion of new diabetes cases in the 6 months post-infection was about 83% lower than the 6 months… Continue reading
Authors: Neha V Reddy, Hsin-Chieh Yeh, Jena S Tronieri, Til Stürmer, John B Buse, Jane E Reusch, Steven G Johnson, Rachel Wong, Richard Moffitt, Kenneth J Wilkins, Jeremy Harper, Carolyn T Bramante,
Keywords: COVID-19; PASC; epidemiology; new diabetes; type 2 diabetes
Review Adult
Summary
Bonilla, H; Peluso, MJ; Rodgers, K; et. al., Frontiers in Immunology
Published:
Journal: Frontiers in Immunology
Abstract: Although most individuals recover from acute SARS-CoV-2 infection, a significant number continue to suffer from Post-Acute Sequelae of SARS-CoV-2 (PASC), including the unexplained symptoms that are frequently referred to as long COVID, which could last for weeks, months, or even years after the acute phase of illness. The National Institutes of Health is currently funding large multi-center research programs as part of its Researching COVID to Enhance Recover (RECOVER) initiative to understand… Continue reading
Authors: Hector Bonilla, Michael J Peluso, Kathleen Rodgers, Judith A Aberg, Thomas F Patterson, Robert Tamburro, Lawrence Baizer, Jason D Goldman, Nadine Rouphael, Amelia Deitchman, Jeffrey Fine, Paul Fontelo, Arthur Y Kim, Gwendolyn Shaw, Jeran Stratford, Patricia Ceger, Maged M Costantine, Liza Fisher, Lisa O'Brien, Christine Maughan, John G Quigley, Vilma Gabbay, Sindhu Mohandas, David Williams, Grace A McComsey
Keywords: SARS- CoV-2; clinical trials; long COVID; long haulers; post-acute sequela of SARS-CoV-2 (PASC); recover; treatment
Short Summary

RECOVER researchers reviewed ongoing, planned, and potential future treatment options for Long COVID, based on our current understanding of the biological causes of Long COVID symptoms and conditions. The purpose of this study is to help guide future research by summarizing the current state of the science as a call for urgent and efficient research to help the millions who continue to suffer from Long COVID around the world.

Researchers identified a number of studies that attempted to treat the various symptoms and conditions of Long COVID that may be useful to consider or incorporate when designing a larger research project aimed at treating the underlying biological cause of those symptoms and conditions.

Review Adult
Summary
Sherif, ZA; Gomez, CR; Connors, TJ; et. al.RECOVER Mechanistic Pathway Task Force, eLife
Published:
Journal: eLife
Abstract: COVID-19, with persistent and new onset of symptoms such as fatigue, post-exertional malaise, and cognitive dysfunction that last for months and impact everyday functioning, is referred to as Long COVID under the general category of post-acute sequelae of SARS-CoV-2 infection (PASC). PASC is highly heterogenous and may be associated with multisystem tissue damage/dysfunction including acute encephalitis, cardiopulmonary syndromes, fibrosis, hepatobiliary damages, gastrointestinal dysregulation… Continue reading
Authors: Zaki A Sherif, Christian R Gomez, Thomas J Connors, Timothy J Henrich, William Brian Reeves,
Keywords: Long COVID; PASC; angiotensin-converting enzyme; epidemiology; global health; immunology; inflammation; pathobiological mechanisms; pathophysiological mechanisms; post-viral syndromes; tissue damage
Short Summary

RECOVER researchers conducted a detailed review of published papers that try to explain how the COVID-19 virus causes the symptoms and conditions associated with Long COVID. Researchers compared how Long COVID is similar to other long-standing viral conditions (such as Epstein Barr virus, commonly known as Mono) to see if there is a common method used by COVID-19 and these other viral conditions to cause the associated symptoms and conditions.

RECOVER researchers believe that there is no one common method by which the COVID-19 virus causes the symptoms and conditions associated with Long COVID. Because there was no observed common method causing these Long COVID symptoms, researchers recommend that treatments are customized to each individual patient's specific symptoms and conditions.

EHR Adult
Summary
Pfaff, ER; Madlock-Brown, C; Baratta, JM; et. al.N3C ConsortiumRECOVER Consortium, BMC Medicine
Published:
Journal: BMC Medicine
Abstract: Background: Naming a newly discovered disease is a difficult process; in the context of the COVID-19 pandemic and the existence of post-acute sequelae of SARS-CoV-2 infection (PASC), which includes long COVID, it has proven especially challenging. Disease definitions and assignment of a diagnosis code are often asynchronous and iterative. The clinical definition and our understanding of the underlying mechanisms of long COVID are still in flux, and the deployment of an ICD-10-CM code for long… Continue reading
Authors: Emily R Pfaff, Charisse Madlock-Brown, John M Baratta, Abhishek Bhatia, Hannah Davis, Andrew Girvin, Elaine Hill, Elizabeth Kelly, Kristin Kostka, Johanna Loomba, Julie A McMurry, Rachel Wong, Tellen D Bennett, Richard Moffitt, Christopher G Chute, Melissa Haendel, ,
Keywords: Electronic health records; Health disparities; Long COVID
Short Summary

RECOVER researchers looked at the use of a code to diagnose Long COVID in electronic health records (EHRs). They used EHR data from over 8,000 people and compared people who had the ICD-10 code for Long COVID (which is U09.9) in their EHR on or after October 1, 2021. They also looked at other codes in their EHR for health conditions, symptoms, tests, and treatments within 60 days after their Long COVID diagnosis.

Researchers found that many doctors use the Long COVID code along with other codes. People with Long COVID had a mix of symptoms and other health conditions, tests, and treatments. This suggests there may be different types of Long COVID. The researchers concluded that for now, doctors should look at a person’s mix of symptoms and other health conditions to diagnose Long COVID.

EHR Adult
Varma, JK; Zang, C; Carton, TW; et. al., medRxiv
Information
Caution: Preprints are preliminary reports of work that have not been certified by peer review. They should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Published:
Journal: medRxiv
Abstract: Importance: The frequency and characteristics of post-acute sequelae of SARS-CoV-2 infection (PASC) may vary by SARS-CoV-2 variant. Objective: To characterize PASC-related conditions among individuals likely infected by the ancestral strain in 2020 and individuals likely infected by the Delta variant in 2021. Design: Retrospective cohort study of electronic medical record data for approximately 27 million patients from March 1, 2020-November 30, 2021. Setting: Healthcare… Continue reading
Authors: Jay K Varma, Chengxi Zang, Thomas W Carton, Jason P Block, Dhruv J Khullar, Yongkang Zhang, Mark G Weiner, Russell L Rothman, Edward J Schenck, Zhenxing Xu, Kristin Lyman, Jiang Bian, Jie Xu, Elizabeth A Shenkman, Christine Maughan, Leah Castro-Baucom, Lisa O'Brien, Fei Wang, Rainu Kaushal
Keywords: Not available
EHR Adult
Summary
Reese, JT; Blau, H; Casiraghi, E; et. al.N3C ConsortiumRECOVER Consortium, eBioMedicine
Published:
Journal: eBioMedicine
Abstract: Background: Stratification of patients with post-acute sequelae of SARS-CoV-2 infection (PASC, or long COVID) would allow precision clinical management strategies. However, long COVID is incompletely understood and characterised by a wide range of manifestations that are difficult to analyse computationally. Additionally, the generalisability of machine learning classification of COVID-19 clinical outcomes has rarely been tested. Methods: We present a method for computationally modelling… Continue reading
Authors: Justin T Reese, Hannah Blau, Elena Casiraghi, Timothy Bergquist, Johanna J Loomba, Tiffany J Callahan, Bryan Laraway, Corneliu Antonescu, Ben Coleman, Michael Gargano, Kenneth J Wilkins, Luca Cappelletti, Tommaso Fontana, Nariman Ammar, Blessy Antony, T M Murali, J Harry Caufield, Guy Karlebach, Julie A McMurry, Andrew Williams, Richard Moffitt, Jineta Banerjee, Anthony E Solomonides, Hannah Davis, Kristin Kostka, Giorgio Valentini, David Sahner, Christopher G Chute, Charisse Madlock-Brown, Melissa A Haendel, Peter N Robinson, ,
Keywords: COVID-19; Human Phenotype Ontology; Long COVID; Machine learning; Precision medicine; Semantic similarity
Short Summary

In this study, RECOVER researchers used a computer program to identify possible types of Long COVID based on electronic health records (EHRs). They used the computer program to review EHRs of people diagnosed with Long COVID and group them based on patterns in their symptoms and health conditions.

The computer program found 6 different types of Long COVID, which were related to 1) many symptoms and health conditions with unusual lab test results, 2) the lungs, 3) the brain, 4) the heart, 5) pain and feeling weak and tired (fatigue), and 6) many symptoms and conditions with pain. Each type of Long COVID also differed based on health conditions people had before COVID and how severe their COVID infection was. This research could help identify people with different types of Long COVID to better diagnose and treat them and invite them to join research studies.

EHR Adult
Summary
Zhang, H; Zang, C; Xu, Z; et. al., Nature Medicine
Published:
Journal: Nature Medicine
Abstract: The post-acute sequelae of SARS-CoV-2 infection (PASC) refers to a broad spectrum of symptoms and signs that are persistent, exacerbated or newly incident in the period after acute SARS-CoV-2 infection. Most studies have examined these conditions individually without providing evidence on co-occurring conditions. In this study, we leveraged the electronic health record data of two large cohorts, INSIGHT and OneFlorida+, from the national Patient-Centered Clinical Research Network. We created a… Continue reading
Authors: Hao Zhang, Chengxi Zang, Zhenxing Xu, Yongkang Zhang, Jie Xu, Jiang Bian, Dmitry Morozyuk, Dhruv Khullar, Yiye Zhang, Anna S Nordvig, Edward J Schenck, Elizabeth A Shenkman, Russell L Rothman, Jason P Block, Kristin Lyman, Mark G Weiner, Thomas W Carton, Fei Wang, Rainu Kaushal
Keywords: Humans; COVID-19/epidemiology; SARS-CoV-2; Post-Acute COVID-19 Syndrome; Anxiety; Anxiety Disorders; Disease Progression
Short Summary

RECOVER researchers wanted to learn if there are different types of Long COVID based on symptoms and health problems that often happen together. Researchers used data from electronic health records (EHRs) of about 35,000 people diagnosed with COVID. The EHRs were from 2 healthcare systems in PCORnet, the National Patient-Centered Clinical Research Network. They used a computer program to look for patterns in people’s new symptoms and health problems that started 30 to 180 days after having COVID.

The researchers found 4 main types of Long COVID based on symptoms and health problems that happen together. The 4 types of Long COVID are related to the 1) heart and kidneys, 2) breathing, sleep, and anxiety, 3) muscles and nerves, and 4) digestive tract and breathing. This research could help define types of Long COVID to give people more specific diagnoses and treatment plans.

EHR Adult
Hadley, E; Yoo, YJ; Patel, S; et. al.N3C and RECOVER consortia On behalf of the N3C and RECOVER consortia, medRxiv
Information
Caution: Preprints are preliminary reports of work that have not been certified by peer review. They should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Published:
Journal: medRxiv
Abstract: Although the COVID-19 pandemic has persisted for over 2 years, reinfections with SARS-CoV-2 are not well understood. We use the electronic health record (EHR)-based study cohort from the National COVID Cohort Collaborative (N3C) as part of the NIH Researching COVID to Enhance Recovery (RECOVER) Initiative to characterize reinfection, understand development of Long COVID after reinfection, and compare severity of reinfection with initial infection. We validate previous findings of reinfection… Continue reading
Authors: Emily Hadley, Yun Jae Yoo, Saaya Patel, Andrea Zhou, Bryan Laraway, Rachel Wong, Alexander Preiss, Rob Chew, Hannah Davis, Christopher G Chute, Emily R Pfaff, Johanna Loomba, Melissa Haendel, Elaine Hill, Richard Moffitt,
Keywords: Not available
Pathobiology Adult
Jason, LA; Dorri, JA, Neurology International
Published:
Journal: Neurology International
Abstract: This study sought to ascertain the prevalence of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) among a sample of 465 patients with Long COVID. The participants completed three questionnaires: (1) a new questionnaire measuring both the frequency and severity of 38 common symptoms of COVID and Long COVID, (2) a validated short form questionnaire assessing ME/CFS, and (3) a validated questionnaire measuring post-exertional malaise. The population was predominantly white, female, and… Continue reading
Authors: Leonard A Jason, Joseph A Dorri
Keywords: COVID-19; Long COVID; ME/CFS; case definition
Back to Top