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Design and Analysis of Outcomes following SARS-CoV-2 Infection in Veterans
Valerie A. Smith; Theodore S.Z. Berkowitz; Paul Hebert; Edwin S. Wong; Meike Niederhausen; John A. Pura; Kristin Berry; Pamela Green; Anna Korpak; Alexandra Fox; Aaron Baraff; Alexandra Hickok; Troy A. Shahoumian; Amy S.B. Bohnert; Denise Hynes; Edward J. Boyko; George N. Ioannou; Theodore J. Iwashyna; C. Barrett Bowling; Ann M. O'Hare; Matthew L. Maciejewski.
Afiliação
  • Valerie A. Smith; Center of Innovation to Accelerate Discovery and Practice Transformation, Durham VA Medical Center, Durham, NC; Department of Population Health Sciences, Duke U
  • Theodore S.Z. Berkowitz; Center of Innovation to Accelerate Discovery and Practice Transformation, Durham VA Medical Center, Durham, NC
  • Paul Hebert; Health Services Research & Development Center of Innovation for Veteran-Centered and Value-Driven Care, and Gastroenterology section, Veterans Affairs Puget Sou
  • Edwin S. Wong; Health Services Research & Development Center of Innovation for Veteran-Centered and Value-Driven Care, and Gastroenterology section, Veterans Affairs Puget Sou
  • Meike Niederhausen; Center to Improve Veteran Involvement in Care, VA Portland Health Care System, Portland, OR; Oregon Health & Science University (OHSU), Portland, OR ; Portland
  • John A. Pura; Center of Innovation to Accelerate Discovery and Practice Transformation, Durham VA Medical Center, Durham, NC
  • Kristin Berry; Health Services Research & Development Center of Innovation for Veteran-Centered and Value-Driven Care, and Gastroenterology section, Veterans Affairs Puget Sou
  • Pamela Green; Health Services Research & Development Center of Innovation for Veteran-Centered and Value-Driven Care, and Gastroenterology section, Veterans Affairs Puget Sou
  • Anna Korpak; Seattle Epidemiologic Research and Information Center, VA Puget Sound, Seattle, WA
  • Alexandra Fox; Seattle Epidemiologic Research and Information Center, VA Puget Sound, Seattle, WA
  • Aaron Baraff; Seattle Epidemiologic Research and Information Center, VA Puget Sound, Seattle, WA
  • Alexandra Hickok; Center to Improve Veteran Involvement in Care, VA Portland Health Care System, Portland, OR
  • Troy A. Shahoumian; Population Health: Health Solutions, Veterans Health Administration, Washington, DC
  • Amy S.B. Bohnert; VA Center for Clinical Management Research, Ann Arbor VA, Ann Arbor, MI; Departments of Anesthesiology and Psychiatry, University of Michigan Medical School, An
  • Denise Hynes; Center to Improve Veteran Involvement in Care, VA Portland Health Care System, Portland, OR; College of Public Health and Human Sciences and Center for Quantita
  • Edward J. Boyko; Seattle Epidemiologic Research and Information Center, VA Puget Sound, Seattle, WA
  • George N. Ioannou; Health Services Research & Development Center of Innovation for Veteran-Centered and Value-Driven Care, and Gastroenterology section, Veterans Affairs Puget Sou
  • Theodore J. Iwashyna; VA Center for Clinical Management Research, Ann Arbor VA, Ann Arbor, MI; National Clinical Scholars Program, University of Michigan Medical School, Ann Arbor, M
  • C. Barrett Bowling; Center of Innovation to Accelerate Discovery and Practice Transformation, Durham VA Medical Center, Durham, NC; Geriatric Research Education and Clinical Center
  • Ann M. O'Hare; ; Division of Nephrology, University of Washington, Seattle, WA
  • Matthew L. Maciejewski; Center of Innovation to Accelerate Discovery and Practice Transformation, Durham VA Medical Center, Durham, NC; Department of Population Health Sciences, Duke U
Preprint em Inglês | medRxiv | ID: ppmedrxiv-22279120
ABSTRACT
AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSBackgroundC_ST_ABSUnderstanding how SARS-CoV-2 infection impacts long-term patient outcomes requires identification of comparable persons with and without infection. We report the design and implementation of a matching strategy employed by the Department of Veterans Affairs (VA) COVID-19 Observational Research Collaboratory (CORC) to develop comparable cohorts of SARS-CoV-2 infected and uninfected persons for the purpose of inferring potential causative long-term adverse effects of SARS-CoV-2 infection in the Veteran population. MethodsIn a retrospective cohort study, we identified VA health care system patients who were and were not infected with SARS-CoV-2 on a rolling monthly basis. We generated matched cohorts utilizing a combination of exact and time-varying propensity score matching based on electronic health record (EHR)-derived covariates that can be confounders or risk factors across a range of outcomes. ResultsFrom an initial pool of 126,689,864 person-months of observation, we generated final matched cohorts of 208,536 Veterans infected between March 2020-April 2021 and 3,014,091 uninfected Veterans. Matched cohorts were well-balanced on all 38 covariates used in matching after excluding patients for no VA health care utilization; implausible age, weight, or height; living outside of the 50 states or Washington, D.C.; prior SARS-CoV-2 diagnosis per Medicare claims; or lack of a suitable match. Most Veterans in the matched cohort were male (88.3%), non-Hispanic (87.1%), white (67.2%), and living in urban areas (71.5%), with a mean age of 60.6, BMI of 31.3, Gagne comorbidity score of 1.4 and a mean of 2.3 CDC high-risk conditions. The most common diagnoses were hypertension (61.4%), diabetes (34.3%), major depression (32.2%), coronary heart disease (28.5%), PTSD (25.5%), anxiety (22.5%), and chronic kidney disease (22.5%). ConclusionsThis successful creation of matched SARS-CoV-2 infected and uninfected patient cohorts from the largest integrated health system in the United States will support cohort studies of outcomes derived from EHRs and sample selection for qualitative interviews and patient surveys. These studies will increase our understanding of the long-term outcomes of Veterans who were infected with SARS-CoV-2.
Licença
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Texto completo: Disponível Coleções: Preprints Base de dados: medRxiv Tipo de estudo: Cohort_studies / Estudo observacional / Estudo prognóstico / Pesquisa qualitativa 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 / Pesquisa qualitativa Idioma: Inglês Ano de publicação: 2022 Tipo de documento: Preprint
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