Predicting Short-Term Mortality in Older Patients Discharged from Acute Hospitalizations Lasting Less Than 24 Hours.

Heltø, Amalia Lærke Kjær; Rosager, Emilie Vangsgaard; Aasbrenn, Martin; Maule, Cathrine Fox; Petersen, Janne; Nielsen, Finn Erland; Suetta, Charlotte; Gregersen, Rasmus

Heltø, Amalia Lærke Kjær; Rosager, Emilie Vangsgaard; Aasbrenn, Martin; Maule, Cathrine Fox; Petersen, Janne; Nielsen, Finn Erland; Suetta, Charlotte; Gregersen, Rasmus.

Afiliación

Heltø ALK; Department of Emergency Medicine, Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark.
Rosager EV; Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
Aasbrenn M; Department of Emergency Medicine, Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark.
Maule CF; Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
Petersen J; Department of Geriatrics and Palliative Medicine, Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark.
Nielsen FE; Center of Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark.
Suetta C; Center of Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark.
Gregersen R; Section of Biostatistics, Department of Public Health, University of Copenhagen, Copenhagen, Denmark.

Clin Epidemiol ; 15: 707-719, 2023.

Article en En | MEDLINE | ID: mdl-37324726

Palabras clave

early discharge; emergency medicine; geriatric; machine learning; prediction model; register-based

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Clin Epidemiol Año: 2023 Tipo del documento: Article País de afiliación: Dinamarca

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