It appears you don't have support to open PDFs in this web browser. To view this file, Open with your PDF reader
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.
You have requested "on-the-fly" machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Show full disclaimer
Neither ProQuest nor its licensors make any representations or warranties with respect to the translations. The translations are automatically generated "AS IS" and "AS AVAILABLE" and are not retained in our systems. PROQUEST AND ITS LICENSORS SPECIFICALLY DISCLAIM ANY AND ALL EXPRESS OR IMPLIED WARRANTIES, INCLUDING WITHOUT LIMITATION, ANY WARRANTIES FOR AVAILABILITY, ACCURACY, TIMELINESS, COMPLETENESS, NON-INFRINGMENT, MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. Your use of the translations is subject to all use restrictions contained in your Electronic Products License Agreement and by using the translation functionality you agree to forgo any and all claims against ProQuest or its licensors for your use of the translation functionality and any output derived there from. Hide full disclaimer
Details









1 RTI International, Durham, USA (GRID:grid.62562.35) (ISNI:0000000100301493)
2 Patient-Led Research Collaborative, Pomfret, USA (GRID:grid.516329.a)
3 University of Colorado Anschutz Medical Campus, Denver, USA (GRID:grid.430503.1) (ISNI:0000 0001 0703 675X)
4 University of North Carolina at Chapel Hill, Chapel Hill, USA (GRID:grid.10698.36) (ISNI:0000000122483208)
5 Palantir Technologies, Denver, USA (GRID:grid.10698.36)
6 CoVar Applied Technologies, Durham, USA (GRID:grid.10698.36)
7 iTHRIV, University of Virginia, Charlottesville, USA (GRID:grid.27755.32) (ISNI:0000 0000 9136 933X)
8 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)
9 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)