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Risk factors for severe COVID-19 differ by age for hospitalized adults.
Molani, Sevda; Hernandez, Patricia V; Roper, Ryan T; Duvvuri, Venkata R; Baumgartner, Andrew M; Goldman, Jason D; Ertekin-Taner, Nilüfer; Funk, Cory C; Price, Nathan D; Rappaport, Noa; Hadlock, Jennifer J.
Afiliación
  • Molani S; Institute for Systems Biology, 401 Terry Ave N, Seattle, WA, 98109, USA.
  • Hernandez PV; Institute for Systems Biology, 401 Terry Ave N, Seattle, WA, 98109, USA.
  • Roper RT; Washington University School of Medicine, St. Louis, MO, 63110, USA.
  • Duvvuri VR; Institute for Systems Biology, 401 Terry Ave N, Seattle, WA, 98109, USA.
  • Baumgartner AM; Institute for Systems Biology, 401 Terry Ave N, Seattle, WA, 98109, USA.
  • Goldman JD; Institute for Systems Biology, 401 Terry Ave N, Seattle, WA, 98109, USA.
  • Ertekin-Taner N; Swedish Center for Research and Innovation, Seattle, WA, 98109, USA.
  • Funk CC; Providence St. Joseph Health, Renton, WA, 98057, USA.
  • Price ND; Division of Allergy & Infectious Diseases, University of Washington, Seattle, WA, 98109, USA.
  • Rappaport N; Department of Neuroscience, Department of Neurology, Mayo Clinic Jacksonville, Jacksonville, FL, 32224, USA.
  • Hadlock JJ; Institute for Systems Biology, 401 Terry Ave N, Seattle, WA, 98109, USA.
Sci Rep ; 12(1): 6568, 2022 04 28.
Article en En | MEDLINE | ID: mdl-35484176
ABSTRACT
Risk stratification for hospitalized adults with COVID-19 is essential to inform decisions about individual patients and allocation of resources. So far, risk models for severe COVID outcomes have included age but have not been optimized to best serve the needs of either older or younger adults. Models also need to be updated to reflect improvements in COVID-19 treatments. This retrospective study analyzed data from 6906 hospitalized adults with COVID-19 from a community health system across five states in the western United States. Risk models were developed to predict mechanical ventilation illness or death across one to 56 days of hospitalization, using clinical data available within the first hour after either admission with COVID-19 or a first positive SARS-CoV-2 test. For the seven-day interval, models for age ≥ 18 and < 50 years reached AUROC 0.81 (95% CI 0.71-0.91) and models for age ≥ 50 years reached AUROC 0.82 (95% CI 0.77-0.86). Models revealed differences in the statistical significance and relative predictive value of risk factors between older and younger patients including age, BMI, vital signs, and laboratory results. In addition, for hospitalized patients, sex and chronic comorbidities had lower predictive value than vital signs and laboratory results.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: COVID-19 Tipo de estudio: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Adult / Humans / Middle aged País/Región como asunto: America do norte Idioma: En Revista: Sci Rep Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: COVID-19 Tipo de estudio: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Adult / Humans / Middle aged País/Región como asunto: America do norte Idioma: En Revista: Sci Rep Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos