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Prospective evaluation of data-driven models to predict daily risk of Clostridioides difficile infection at 2 large academic health centers.
Kamineni, Meghana; Ötles, Erkin; Oh, Jeeheh; Rao, Krishna; Young, Vincent B; Li, Benjamin Y; West, Lauren R; Hooper, David C; Shenoy, Erica S; Guttag, John G; Wiens, Jenna; Makar, Maggie.
Afiliación
  • Kamineni M; Electrical Engineering and Computer Science Department, Massachusetts Institute of Technology, Cambridge, Massachusetts.
  • Ötles E; Medical Scientist Training Program, University of Michigan Medical School, Ann Arbor, Michigan.
  • Oh J; Department of Industrial and Operations Engineering, University of Michigan College of Engineering, Ann Arbor, Michigan.
  • Rao K; Division of Computer Science and Engineering, University of Michigan College of Engineering, Ann Arbor, Michigan.
  • Young VB; Department of Internal Medicine, Division of Infectious Diseases, University of Michigan Medical School, Ann Arbor, Michigan.
  • Li BY; Department of Internal Medicine, Division of Infectious Diseases, University of Michigan Medical School, Ann Arbor, Michigan.
  • West LR; Medical Scientist Training Program, University of Michigan Medical School, Ann Arbor, Michigan.
  • Hooper DC; Division of Computer Science and Engineering, University of Michigan College of Engineering, Ann Arbor, Michigan.
  • Shenoy ES; Infection Control Unit, Massachusetts General Hospital, Boston, Massachusetts.
  • Guttag JG; Infection Control Unit, Massachusetts General Hospital, Boston, Massachusetts.
  • Wiens J; Division of Infectious Diseases, Massachusetts General Hospital, Boston, Massachusetts.
  • Makar M; Harvard Medical School, Boston, Massachusetts.
Infect Control Hosp Epidemiol ; 44(7): 1163-1166, 2023 Jul.
Article en En | MEDLINE | ID: mdl-36120815
ABSTRACT
Many data-driven patient risk stratification models have not been evaluated prospectively. We performed and compared the prospective and retrospective evaluations of 2 Clostridioides difficile infection (CDI) risk-prediction models at 2 large academic health centers, and we discuss the models' robustness to data-set shifts.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Infecciones por Clostridium Tipo de estudio: Etiology_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Infect Control Hosp Epidemiol Asunto de la revista: DOENCAS TRANSMISSIVEIS / ENFERMAGEM / EPIDEMIOLOGIA / HOSPITAIS Año: 2023 Tipo del documento: Article
Texto completo
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PubMed Links
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Infecciones por Clostridium Tipo de estudio: Etiology_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Infect Control Hosp Epidemiol Asunto de la revista: DOENCAS TRANSMISSIVEIS / ENFERMAGEM / EPIDEMIOLOGIA / HOSPITAIS Año: 2023 Tipo del documento: Article