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; Rainu Kaushal

doi:10.1038/s41467-023-37653-z

Nature Communications (Apr 2023)

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,
Rainu Kaushal

Affiliations

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

DOI: https://doi.org/10.1038/s41467-023-37653-z
Journal volume & issue: Vol. 14, no. 1
pp. 1 – 14

Abstract

Read online

In this study, the authors characterise post-acute sequelae of SARS-CoV-2 (PASC) in two large cohorts based on electronic health records from the USA. They identify a broad range of PASC-related conditions which were only partially replicated across the two cohorts, indicating possible heterogeneity between populations.

Published in Nature Communications

ISSN: 2041-1723 (Online)
Publisher: Nature Portfolio
Country of publisher: United Kingdom
LCC subjects: Science
Website: https://www.nature.com/ncomms/

About the journal