A short comprehensive assessment to predict outcome of elderly patients after hip fracture.
OBJECTIVE
Hip fractures result in significant functional impairment and a high rate of institutionalization. The aim of our study was to evaluate in patients with a recent hip fracture the contribution of a short (15-min) comprehensive assessment to predict the length of stay and the risk of discharge to a nursing home.


METHODS
Prospective clinical study conducted in a rehabilitation ward of the Geriatric Hospital. Functional assessment included basic activities of daily living (BADL), cognitive status (MMSE) and a 4-item geriatric depression scale (Mini-GDS). Information on demographic data, living situation, diagnosis and illness burden was also collected.


RESULTS
The mean age of the 86 patients (67W/19M) was 84.2 +/- 6.8 years. In a multiple regression analysis, the length of stay in a geriatric hospital was significantly associated with both marital status (living alone) (p = 0.035) and the intervention of a caregiver on a regular basis (p = 0.036), but not with Charlson's comorbidity score. In a logistic regression model, adjusted for age, gender, marital status, intervention of a caregiver on a regular basis, BADL, Mini-GDS and Charlson's comorbidity score, the only independent predictor of nursing home admission was a MMSE < 24, which increased by 10.7-fold (2.2-50.9) the risk of being admitted to a nursing home (p = 0.003).


CONCLUSIONS
A short comprehensive assessment completed a few days after a hip fracture is useful in predicting length of stay and risk of nursing home admission.
Pautex
Sophie
S
Geriatric Evaluation Unit, University Hospitals of Geneva, Switzerland. sophie.pautex@hcuge.ch
Jacques
Marie-Claire
MC
Sant
Aditya
A
Herrmann
François
F
Chevalley
Thierry
T
D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D015577:Geriatric Assessment; D006620:Hip Fractures / Q000523:psychology*; D006801:Humans; D007902:Length of Stay; D016015:Logistic Models; D008297:Male; D009735:Nursing Homes; D012044:Regression Analysis