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Identifying Contextual and Spatial Risk Factors for Post-Acute Sequelae of SARS-CoV-2 Infection: An EHR-based Cohort Study from the RECOVER Program
Yongkang Zhang; Hui Hu; Vasilios Fokaidis; Colby Lewis V; Jie Xu V; Chengxi Zang; Zhenxing Xu; Fei Wang; Michael Koropsak; Jiang Bian; Jaclyn Hall; Russell Rothman; Elizabeth Shenkman; Wei-Qi Wei; Mark G Weiner; Thomas W Carton; Rainu Kaushal.
Afiliação
  • Yongkang Zhang; Weill Cornell Medical College
  • Hui Hu; Brigham and Womens Hospital and Harvard Medical School
  • Vasilios Fokaidis; Weill Cornell Medical College
  • Colby Lewis V; Weill Cornell Medical College
  • Jie Xu V; University of Florida
  • Chengxi Zang; Weill Cornell Medical College
  • Zhenxing Xu; Weill Cornell Medical College
  • Fei Wang; Weill Cornell Medical College
  • Michael Koropsak; Weill Cornell Medical College
  • Jiang Bian; University of Florida
  • Jaclyn Hall; University of Florida
  • Russell Rothman; Vanderbilt University Medical Center
  • Elizabeth Shenkman; University of Florida
  • Wei-Qi Wei; University of Florida
  • Mark G Weiner; Weill Cornell Medical College
  • Thomas W Carton; Louisiana Public Health Institute
  • Rainu Kaushal; Weill Cornell Medical College
Preprint em Inglês | medRxiv | ID: ppmedrxiv-22281010
ABSTRACT
Post-acute sequelae of SARS-CoV-2 infection (PASC) affects a wide range of organ systems among a large proportion of patients with SARS-CoV-2 infection. Although studies have identified a broad set of patient-level risk factors for PASC, little is known about the contextual and spatial risk factors for PASC. Using electronic health data of patients with COVID-19 from two large clinical research networks in New York City and Florida, we identified contextual and spatial risk factors from nearly 200 environmental characteristics for 23 PASC symptoms and conditions of eight organ systems. We conducted a two-phase environment-wide association study. In Phase 1, we ran a mixed effects logistic regression with 5-digit ZIP Code tabulation area (ZCTA5) random intercepts for each PASC outcome and each contextual and spatial factor, adjusting for a comprehensive set of patient-level confounders. In Phase 2, we ran a mixed effects logistic regression for each PASC outcome including all significant (false positive discovery adjusted p-value < 0.05) contextual and spatial characteristics identified from Phase I and adjusting for confounders. We identified air toxicants (e.g., methyl methacrylate), criteria air pollutants (e.g., sulfur dioxide), particulate matter (PM2.5) compositions (e.g., ammonium), neighborhood deprivation, and built environment (e.g., food access) that were associated with increased risk of PASC conditions related to nervous, respiratory, blood, circulatory, endocrine, and other organ systems. Specific contextual and spatial risk factors for each PASC condition and symptom were different across New York City area and Florida. Future research is warranted to extend the analyses to other regions and examine more granular contextual and spatial characteristics to inform public health efforts to help patients recover from SARS-CoV-2 infection.
Licença
cc_by_nc_nd
Texto completo: Disponível Coleções: Preprints Base de dados: medRxiv Tipo de estudo: Cohort_studies / Estudo observacional / Estudo prognóstico / Rct Idioma: Inglês Ano de publicação: 2022 Tipo de documento: Preprint
Texto completo: Disponível Coleções: Preprints Base de dados: medRxiv Tipo de estudo: Cohort_studies / Estudo observacional / Estudo prognóstico / Rct Idioma: Inglês Ano de publicação: 2022 Tipo de documento: Preprint
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