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A novel dataset of predictors of mortality for older Veterans living with type II diabetes.
Vaidya, Avi U; Benavidez, Gabriel A; Prentice, Julia C; Mohr, David C; Conlin, Paul R; Griffith, Kevin N.
Afiliação
  • Vaidya AU; Department of Health Policy, Vanderbilt University Medical Center, Nashville, TN, USA.
  • Benavidez GA; Department of Epidemiology and Biostatistics, University of South Carolina, Columbia, SC, USA.
  • Prentice JC; Department of Psychiatry, Boston University School of Medicine, Boston, MA, USA.
  • Mohr DC; Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System, Boston, MA, USA.
  • Conlin PR; Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System, Boston, MA, USA.
  • Griffith KN; Department of Health Law, Policy and Management, Boston University School of Public Health, Boston, MA, USA.
Data Brief ; 41: 108005, 2022 Apr.
Article em En | MEDLINE | ID: mdl-35282179
The dataset summarized in this article includes a nationwide prevalence sample of U.S. military Veterans who were aged 65 years or older, dually enrolled in the Veterans Health Administration and traditional Medicare and had a previous diagnosis of diabetes (diabetes mellitus) as of December 2005 (N = 275,190) [1]. Our data were originally used to develop and validate prognostic indices of 5- and 10-year mortality among older Veterans with diabetes. We include various potential predictors including demographics (e.g., sex, age, marital status, and VA priority group), healthcare utilization (e.g., # of outpatient visits, # days of inpatient stays), medication history, and major comorbidities. This novel dataset provides researchers with an opportunity to study the associations between a large variety of individual-level risk factors and longevity for patients living with diabetes.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Data Brief Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Data Brief Ano de publicação: 2022 Tipo de documento: Article