Data-driven analysis to understand long COVID using electronic health records from the RECOVER initiative

Chengxi Zang, Yongkang Zhang, Jie Xu, Jiang Bian, Dmitry Morozyuk, Edward J. Schenck, Dhruv Khullar, Anna S. Nordvig, Elizabeth A. Shenkman, Russell L. Rothman, Jason P. Block, Kristin Lyman, Mark G. Weiner, Thomas W. Carton, Fei Wang () and Rainu Kaushal
Additional contact information
Chengxi Zang: Weill Cornell Medicine
Yongkang Zhang: Weill Cornell Medicine
Jie Xu: University of Florida
Jiang Bian: University of Florida
Dmitry Morozyuk: Weill Cornell Medicine
Edward J. Schenck: Division of Pulmonary and Critical Care Medicine, Weill Cornell Medicine
Dhruv Khullar: Weill Cornell Medicine
Anna S. Nordvig: Weill Cornell Medicine
Elizabeth A. Shenkman: University of Florida
Russell L. Rothman: Vanderbilt University Medical Center
Jason P. Block: Harvard Pilgrim Health Care Institute, Harvard Medical School
Kristin Lyman: Louisiana Public Health Institute
Mark G. Weiner: Weill Cornell Medicine
Thomas W. Carton: Louisiana Public Health Institute
Fei Wang: Weill Cornell Medicine
Rainu Kaushal: Weill Cornell Medicine

Nature Communications, 2023, vol. 14, issue 1, 1-14

Abstract: Abstract Recent studies have investigated post-acute sequelae of SARS-CoV-2 infection (PASC, or long COVID) using real-world patient data such as electronic health records (EHR). Prior studies have typically been conducted on patient cohorts with specific patient populations which makes their generalizability unclear. This study aims to characterize PASC using the EHR data warehouses from two large Patient-Centered Clinical Research Networks (PCORnet), INSIGHT and OneFlorida+, which include 11 million patients in New York City (NYC) area and 16.8 million patients in Florida respectively. With a high-throughput screening pipeline based on propensity score and inverse probability of treatment weighting, we identified a broad list of diagnoses and medications which exhibited significantly higher incidence risk for patients 30–180 days after the laboratory-confirmed SARS-CoV-2 infection compared to non-infected patients. We identified more PASC diagnoses in NYC than in Florida regarding our screening criteria, and conditions including dementia, hair loss, pressure ulcers, pulmonary fibrosis, dyspnea, pulmonary embolism, chest pain, abnormal heartbeat, malaise, and fatigue, were replicated across both cohorts. Our analyses highlight potentially heterogeneous risks of PASC in different populations.

Date: 2023
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DOI: 10.1038/s41467-023-37653-z

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