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Early prediction of hospital admission for emergency department patients: a comparison between patients younger or older than 70 years.
Lucke, Jacinta A; de Gelder, Jelle; Clarijs, Fleur; Heringhaus, Christian; de Craen, Anton J M; Fogteloo, Anne J; Blauw, Gerard J; Groot, Bas de; Mooijaart, Simon P.
Afiliación
  • Lucke JA; Department of Emergency Medicine, Leiden University Medical Center, Leiden, The Netherlands.
  • de Gelder J; Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands.
  • Clarijs F; Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands.
  • Heringhaus C; Department of Emergency Medicine, Leiden University Medical Center, Leiden, The Netherlands.
  • de Craen AJM; Department of Emergency Medicine, Leiden University Medical Center, Leiden, The Netherlands.
  • Fogteloo AJ; Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands.
  • Blauw GJ; Department of Internal Medicine, Leiden University Medical Center, Leiden, The Netherlands.
  • Groot B; Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands.
  • Mooijaart SP; Department of Internal Medicine and Geriatrics, Medical Center Haaglanden-Bronovo, The Hague, The Netherlands.
Emerg Med J ; 35(1): 18-27, 2018 Jan.
Article en En | MEDLINE | ID: mdl-28814479
OBJECTIVE: The aim of this study was to develop models that predict hospital admission to ED of patients younger and older than 70 and compare their performance. METHODS: Prediction models were derived in a retrospective observational study of all patients≥18 years old visiting the ED of a university hospital during the first 6 months of 2012. Patients were stratified into two age groups (<70 years old and ≥70 years old). Multivariable logistic regression analysis was used to identify predictors of hospital admission among factors available immediately after patient arrival to the ED. Validation of the prediction models was performed on patients presenting to the ED during the second half of the year 2012. RESULTS: 10 807 patients were included in the derivation and 10 480 in the validation cohorts. The strongest independent predictors of hospital admission among the 8728 patients <70 years old were age, sex, triage category, mode of arrival, performance of blood tests, chief complaint, ED revisit, type of specialist, phlebotomised blood sample and all vital signs. The area under the curve (AUC) of the validation cohort for those <70 years old was 0.86 (95% CI 0.85 to 0.87). Among the 2079 patients ≥70 years, the same factors were predictive, except for gender, type of specialist and heart rate; the AUC was 0.77 (95% CI 0.75 to 0.79). The prediction models could identify a group of 10% of patients with the highest risk in whom hospital admission was predicted at ED triage, with a positive predictive value (PPV) of 71% (95% CI 68% to 74%) in younger patients and PPV of 87% (95% CI 81% to 92%) in older patients. CONCLUSION: Demographic and clinical factors readily available early in the ED visit can be useful in identifying patients who are likely to be admitted to the hospital. While the model for the younger patients had a higher AUC, the model for older patients had a higher PPV in identifying the patients at highest risk for admission. Of note, heart rate was not a useful predictor in the older patients.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Triaje / Predicción / Hospitalización Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Adult / Aged / Female / Humans / Male / Middle aged País/Región como asunto: Asia / Europa Idioma: En Revista: Emerg Med J Asunto de la revista: MEDICINA DE EMERGENCIA Año: 2018 Tipo del documento: Article País de afiliación: Países Bajos Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Triaje / Predicción / Hospitalización Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Adult / Aged / Female / Humans / Male / Middle aged País/Región como asunto: Asia / Europa Idioma: En Revista: Emerg Med J Asunto de la revista: MEDICINA DE EMERGENCIA Año: 2018 Tipo del documento: Article País de afiliación: Países Bajos Pais de publicación: Reino Unido