The Researching COVID to Enhance Recovery (RECOVER) Post-Acute Sequelae of SARS-CoV-2 (PASC) Electronic Health Record (EHR) Cohort Study
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Study to understand, prevent, and treat post-acute sequelae of SARS-CoV-2 (PASC), including Long COVID.
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Investigators from two of the nation’s top health research institutions, Weill Cornell Medicine (WCM) and Children’s Hospital of Philadelphia (CHOP), are spearheading a new study aimed at understanding more about long-haul COVID-19. Dr. Christopher Forrest, professor of pediatrics and health care management at CHOP and principal investigator (PI) of the PEDSnet Clinical Research Network (CRN); and Dr. Rainu Kaushal, senior associate dean for clinical research and chair of the Department of Population Health Sciences at WCM and PI of the INSIGHT Clinical Research Network (CRN) were selected as two of the three leaders of the Electronic Health Record (EHR) Cohort Studies for the NIH Researching COVID to Enhance Recovery (RECOVER) Initiative (https://recovercovid.org). Drs. Forrest and Kaushal will lead the PCORnet-based EHR cohort alongside mPIs Dr. L. Charles Bailey (CHOP); Dr. Thomas Carton (Louisiana Public Health Institute); Dr. Grace Lee (Stanford Children’s Health); and Dr. Mark Weiner (WCM). The PCORnet Adult and Pediatric RECOVER EHR cohorts are enabled by the infrastructure of PCORnet, the National Patient-Centered Clinical Research Network.
The NIH RECOVER Initiative has awarded PCORnet researchers $20 million over one year to study the Post-Acute Sequelae of SARS-CoV-2 infection (PASC), often referred to as long-haul COVID-19, in children and adults. This novel research opportunity leverages standardized and quality-assured clinical data, hundreds of scientists, streamlined processes, and clinical research infrastructure to rapidly generate evidence for PASC in both adult and pediatric populations. The EHR cohorts contribute to the RECOVER Initiative in several meaningful ways, including the creation of new computable phenotypes and models that define PASC in children and adults. These computable patient characteristics can then be leveraged by clinical sites to identify and recruit eligible patients into studies which will help us gain valuable information about PASC. Finally, the EHR cohorts help develop models and algorithms that predict risk of PASC while examining disparities between different populations and will further help to illustrate the effects of vaccines on PASC.
The PCORnet-RECOVER EHR cohort is a collaboration between all eight PCORnet Clinical Research Networks (https://pcornet.org), representing 41 institutions across the United States. PCORnet provides an unprecedented breadth and depth of real-world data, nationally renowned investigators including informaticians, clinicians, and learning health system experts, and a robust track record for large-scale observational research, comparative effectiveness studies, surveys, and pragmatic clinical trials.
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Forrest C, Burrows E, Mejias A, Razzaghi H et al. April 2022. “Severity of Acute COVID-19 in Children <18 Years Old March 2020 to December 2021.” Pediatrics 149 (4): e2021055765. DOI: 10.1542/peds.2021-055765
Rao S, Lee GM, Razzaghi H, et al.2022. “Clinical Features and Burden of Postacute Sequelae of SARS-CoV-2 Infection in Children and Adolescents.” JAMA Pediatrics. 176(10):1000 - 1009. DOI:10.1001/jamapediatrics.2022.2800
Mejias A, Schuchard J, Rao S, Bennett TD, Jhaveri R, et al. June 2023. “Leveraging Serologic Testing to Identify Children at Risk For Post-Acute Sequelae of SARS-CoV-2 Infection: An Electronic Health Record-Based Cohort Study from the RECOVER Program.” J Pediatr. 257:113358. DOI: 10.1016/j.jpeds.2023.02.005
Lorman V, Rao S, Jhaveri R, Case A, et al. April 2023. “Understanding pediatric long COVID using a tree-based scan statistic approach: an EHR-based cohort study from the RECOVER Program.” JAMIA Open. Volume 6. Issue 1. ooad016. DOI: 10.1093/jamiaopen/ooad016
Prahalad, P , Lorman, V, Wu Q, Razzaghi H. 2023. “Consortium, on behalf of the RECOVER, Impact of SARS-CoV-2 Infection on Disease Trajectory in Youth with T1D: An EHR-Based Cohort Study from the RECOVER Program.” Pediatric Diabetes. 8798997, 10 pages. DOI: doi.org/10.1155/2023/8798997
Lorman V, Razzaghi H, Song X, Morse K, Utidjian L, et al. 2023. “A machine learning-based phenotype for long COVID in children: An EHR-based study from the RECOVER program.” PLOS ONE 18(8): e0289774. DOI: doi.org/10.1371/journal.pone.0289774
Rao, S., Jing, N., Liu, X. et al. 2023. “Spectrum of severity of multisystem inflammatory syndrome in children: an EHR-based cohort study from the RECOVER program.” Sci Rep 13, 21005. DOI: 10.1038/s41598-023-47655-y
Razzaghi H, Forrest C, Hirabayashi K, Wu Q, et al. April 2024. “RECOVER CONSORTIUM; Vaccine Effectiveness Against Long COVID in Children.” Pediatrics. 153 (4): e2023064446. DOI: 10.1542/peds.2023-064446
Schuchard J, Thacker D, Webb R, Bailey C, et al. 2022. “Changes in Treatment and Severity of Multisystem Inflammatory Syndrome in Children: An EHR-based cohort study from the RECOVER program.” medRxiv
DOI: doi.org/10.1101/2022.10.19.22281256
Bose-Brill S, Hirabayashi K, Pajor NM, Rao S, Mejias A, Jhaveri R, Forrest CB, et al. 2022. “Pediatric Nirmatrelvir/Ritonavir Prescribing Patterns During the COVID-19 Pandemic”. medRxiv [Preprint]. 2022 Dec 26:2022.12.23.22283868.
DOI: 10.1101/2022.12.23.22283868
Update in: Hosp Pediatr. 2024 Aug 1;14(8):e341-e348.
DOI: 10.1542/hpeds.2023-007132
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