Predicting a long hospital stay after admission to a geriatric assessment unit: Results from an observational retrospective cohort study.
Détails
ID Serval
serval:BIB_92DAF4C7B73B
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
Predicting a long hospital stay after admission to a geriatric assessment unit: Results from an observational retrospective cohort study.
Périodique
Maturitas
ISSN
1873-4111 (Electronic)
ISSN-L
0378-5122
Statut éditorial
Publié
Date de publication
09/2018
Peer-reviewed
Oui
Volume
115
Pages
110-114
Langue
anglais
Notes
Publication types: Journal Article ; Observational Study
Publication Status: ppublish
Publication Status: ppublish
Résumé
Morbidities and related disabilities often lead to older inpatients having a long hospital stay. The aim of this study was to examine whether the 6-item brief geriatric assessment (BGA), developed and validated in France to determine a priori levels of risk of a long hospital stay (i.e.; low, moderate, high), could be successfully used with patients admitted to a geriatric assessment unit (GAU) in Quebec.
Observational retrospective cohort design.
A GAU of a McGill University affiliated hospital (Montreal, Quebec, Canada).
499 inpatients (84.7 ± 7.2 years; 73.3% female) recruited upon their admission.
The BGA comprises 6 items: age > 85 years, male gender, ≥ 5 drugs per day, use of home-help support, history of falls and temporal disorientation. It was administered at baseline and a priori levels of risk of a long hospital stay (i.e., low, moderate, high) were determined. Length of hospital stay (LHS, in days) was calculated using the hospital registry. The association between a priori levels of risk from the BGA and LSH was examined using regression models and Kaplan-Meier curves.
The LHS increased with the 6-item BGA a priori level of risk (P = 0.010). High-risk (Hazard ratio (HR) = 1.68 with P < 0.001) and moderate-risk (HR = 1.24 with P = 0.039) of a long hospital stay successfully predicted a long stay. Kaplan-Meier distributions of time to discharge showed that inpatients classified as having high and moderate risk levels for a long hospital stay were discharged later than those with a low risk level (P < 0.001 and P = 0.013).
The 6-item BGA a priori levels of risk for a long hospital stay successfully predicted a long stay among patients admitted to a GAU in Quebec.
Observational retrospective cohort design.
A GAU of a McGill University affiliated hospital (Montreal, Quebec, Canada).
499 inpatients (84.7 ± 7.2 years; 73.3% female) recruited upon their admission.
The BGA comprises 6 items: age > 85 years, male gender, ≥ 5 drugs per day, use of home-help support, history of falls and temporal disorientation. It was administered at baseline and a priori levels of risk of a long hospital stay (i.e., low, moderate, high) were determined. Length of hospital stay (LHS, in days) was calculated using the hospital registry. The association between a priori levels of risk from the BGA and LSH was examined using regression models and Kaplan-Meier curves.
The LHS increased with the 6-item BGA a priori level of risk (P = 0.010). High-risk (Hazard ratio (HR) = 1.68 with P < 0.001) and moderate-risk (HR = 1.24 with P = 0.039) of a long hospital stay successfully predicted a long stay. Kaplan-Meier distributions of time to discharge showed that inpatients classified as having high and moderate risk levels for a long hospital stay were discharged later than those with a low risk level (P < 0.001 and P = 0.013).
The 6-item BGA a priori levels of risk for a long hospital stay successfully predicted a long stay among patients admitted to a GAU in Quebec.
Mots-clé
Accidental Falls, Aged, Aged, 80 and over, Female, Geriatric Assessment, Hospitals, University, Humans, Inpatients, Length of Stay, Male, Patient Discharge, Proportional Hazards Models, Quebec, Retrospective Studies, Epidemiology, Frailty, Older inpatients, Screening
Pubmed
Web of science
Création de la notice
31/07/2018 10:43
Dernière modification de la notice
20/08/2019 14:55