Abstract

Long COVID, or complications arising from COVID-19 weeks after infection, has become a central concern for public health experts. The United States National Institutes of Health founded the RECOVER initiative to better understand long COVID. We used electronic health records available through the National COVID Cohort Collaborative to characterize the association between SARS-CoV-2 vaccination and long COVID diagnosis. Among patients with a COVID-19 infection between August 1, 2021 and January 31, 2022, we defined two cohorts using distinct definitions of long COVID—a clinical diagnosis (n = 47,404) or a previously described computational phenotype (n = 198,514)—to compare unvaccinated individuals to those with a complete vaccine series prior to infection. Evidence of long COVID was monitored through June or July of 2022, depending on patients’ data availability. We found that vaccination was consistently associated with lower odds and rates of long COVID clinical diagnosis and high-confidence computationally derived diagnosis after adjusting for sex, demographics, and medical history.

The extent to which COVID-19 vaccination protects against long COVID is not well understood. Here, the authors use electronic health record data from the United States and find that, for people who received their vaccination prior to infection, vaccination was associated with lower incidence of long COVID.

Details

Title
Long COVID risk and pre-COVID vaccination in an EHR-based cohort study from the RECOVER program
Author
Brannock, M. Daniel 1   VIAFID ORCID Logo  ; Chew, Robert F. 1   VIAFID ORCID Logo  ; Preiss, Alexander J. 1   VIAFID ORCID Logo  ; Hadley, Emily C. 1   VIAFID ORCID Logo  ; Redfield, Signe 2   VIAFID ORCID Logo  ; McMurry, Julie A. 3 ; Leese, Peter J. 4 ; Girvin, Andrew T. 5 ; Crosskey, Miles 6 ; Zhou, Andrea G. 7 ; Moffitt, Richard A. 8   VIAFID ORCID Logo  ; Funk, Michele Jonsson 4 ; Pfaff, Emily R. 4   VIAFID ORCID Logo  ; Haendel, Melissa A. 3   VIAFID ORCID Logo  ; Chute, Christopher G. 9   VIAFID ORCID Logo  ; Stürmer, Til 4 ; Loomba, Johanna J. 7 ; Koraishy, Farrukh M. 10 ; Divers, Jasmin 11 ; Thorpe, Lorna E. 12 ; Horwitz, Leora 12 ; Katz, Stuart 13 

 RTI International, Durham, USA (GRID:grid.62562.35) (ISNI:0000000100301493) 
 Patient-Led Research Collaborative, Pomfret, USA (GRID:grid.516329.a) 
 University of Colorado Anschutz Medical Campus, Denver, USA (GRID:grid.430503.1) (ISNI:0000 0001 0703 675X) 
 University of North Carolina at Chapel Hill, Chapel Hill, USA (GRID:grid.10698.36) (ISNI:0000000122483208) 
 Palantir Technologies, Denver, USA (GRID:grid.10698.36) 
 CoVar Applied Technologies, Durham, USA (GRID:grid.10698.36) 
 iTHRIV, University of Virginia, Charlottesville, USA (GRID:grid.27755.32) (ISNI:0000 0000 9136 933X) 
 Stony Brook University, Department of Biomedical Informatics, Stony Brook, USA (GRID:grid.36425.36) (ISNI:0000 0001 2216 9681); Emory University, Departments of Biomedical Informatics and Hematology and Medical Ontology, Atlanta, USA (GRID:grid.189967.8) (ISNI:0000 0001 0941 6502) 
 Johns Hopkins University, Schools of Medicine, Public Health, and Nursing, Baltimore, USA (GRID:grid.21107.35) (ISNI:0000 0001 2171 9311) 
10  Stony Brook Medicine, Stony Brook, USA (GRID:grid.459987.e) (ISNI:0000 0004 6008 5093) 
11  New York University Long Island School of Medicine, Department of Foundations of Medicine, Mineola, USA (GRID:grid.137628.9) (ISNI:0000 0004 1936 8753) 
12  New York University Grossman School of Medicine, Department of Population Health, New York, USA (GRID:grid.137628.9) (ISNI:0000 0004 1936 8753) 
13  New York University Grossman School of Medicine, Leon H. Charney Division of Cardiology, Department of Medicine, New York, USA (GRID:grid.137628.9) (ISNI:0000 0004 1936 8753) 
Pages
2914
Publication year
2023
Publication date
2023
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2817273990
Copyright
© The Author(s) 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.