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Risk-standardized sepsis mortality map of the United States.
Hu, Jiun-Ruey; Yo, Chia-Hung; Lee, Hsin-Ying; Su, Chin-Hua; Su, Ming-Yang; Huang, Amy Huaishiuan; Liu, Ye; Hsu, Wan-Ting; Lee, Matthew; Chen, Yee-Chun; Lee, Chien-Chang.
Afiliação
  • Hu JR; Department of Internal Medicine, Yale School of Medicine, USA.
  • Yo CH; Department of Emergency Medicine, Far Eastern Memorial Hospital, Taiwan.
  • Lee HY; Department of Medicine, College of Medicine, National Taiwan University, Taiwan.
  • Su CH; Department of Emergency Medicine, National Taiwan University Hospital, Taiwan.
  • Su MY; Department of Surgery, Chang Gung Memorial Hospital, Taiwan.
  • Huang AH; Department of Emergency Medicine, National Taiwan University Hospital, Taiwan.
  • Liu Y; Department of Internal Medicine, Taipei City Hospital, Renai Branch, Taiwan.
  • Hsu WT; Department of Health Care Organization and Policy, University of Alabama at Birmingham, School of Public Health, USA.
  • Lee M; Department of Epidemiology, Harvard T.H. Chan School of Public Health, USA.
  • Chen YC; Medical Wizdom, LLC, USA.
  • Lee CC; Department of Medicine, College of Medicine, National Taiwan University, Taiwan.
Digit Health ; 8: 20552076211072400, 2022.
Article em En | MEDLINE | ID: mdl-35096409
ABSTRACT

OBJECTIVE:

Sepsis is the leading cause of in-hospital mortality in the United States (US). Quality improvement initiatives for improving sepsis care depend on accurate estimates of sepsis mortality. While hospital 30-day risk-standardized mortality rates have been published for patients hospitalized with acute myocardial infarction, heart failure, and pneumonia, risk-standardized mortality rates for sepsis have not been well characterized. We aimed to construct a sepsis risk-standardized mortality rate map for the United States, to illustrate disparities in sepsis care across the country.

METHODS:

This cross-sectional study included adults from the US Nationwide Inpatient Sample who were hospitalized with sepsis between 1 January 2010 and 30 December 2011. Hospital-level risk-standardized mortality rates were calculated using hierarchical logistic modelling, and were risk-adjusted with predicted mortality derived from (1) the Sepsis Risk Prediction Score, a logistic regression model, and (2) gradient-boosted decision trees, a supervised machine learning (ML) algorithm.

RESULTS:

Among 1,739,033 adults hospitalized with sepsis, 50% were female, and the median age was 71 years (interquartile range 58-81). The national median risk-standardized mortality rate for sepsis was 18.4% (interquartile range 17.0, 21.0) by the boosted tree model, which had better discrimination than the Sepsis Risk Prediction Score model (C-statistic 0.87 and 0.78, respectively). The highest risk-standardized mortality rates were found in Wyoming, North Dakota, and Mississippi, while the lowest were found in Arizona, Colorado, and Michigan.

CONCLUSIONS:

Wide variation exists in sepsis risk-standardized mortality rates across states, representing opportunities for improvement in sepsis care. This represents the first map of state-level variation of risk-standardized mortality rates in sepsis.
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Texto completo: 1 Bases de dados: MEDLINE Tipo de estudo: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Digit Health Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Bases de dados: MEDLINE Tipo de estudo: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Digit Health Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos