PT  - JOURNAL ARTICLE
AU  - Zara Steinmeyer
AU  - Antoine Piau
AU  - Joséphine Thomazeau
AU  - Samantha Huo Yung Kai
AU  - Fati Nourhashemi
TI  - Mortality in hospitalised older patients: the WHALES short-term predictive score
AID  - 10.1136/bmjspcare-2021-003258
DP  - 2021 Nov 24
TA  - BMJ Supportive & Palliative Care
PG  - bmjspcare-2021-003258
4099  - http://spcare.bmj.com/content/early/2021/11/24/bmjspcare-2021-003258.short
4100  - http://spcare.bmj.com/content/early/2021/11/24/bmjspcare-2021-003258.full
AB  - Objective To develop and validate the WHALES screening tool predicting short-term mortality (3 months) in older patients hospitalised in an acute geriatric unit.Methods Older patients transferred to an acute geriatric ward from June 2017 to December 2018 were included. The cohort was divided into two groups: derivation (n=664) and validation (n=332) cohorts. Cause for admission in emergency room, hospitalisation history within the previous year, ongoing medical conditions, cognitive impairment, frailty status, living conditions, presence of proteinuria on a urine strip or urine albumin-to-creatinine ratio and abnormalities on an ECG were collected at baseline. Multiple logistic regressions were performed to identify independent variables associated with mortality at 3 months in the derivation cohort. The prediction score was then validated in the validation cohort.Results Five independent variables available from medical history and clinical data were strongly predictive of short-term mortality in older adults including age, sex, living in a nursing home, unintentional weight loss and self-reported exhaustion. The screening tool was discriminative (C-statistic=0.74 (95% CI: 0.67 to 0.82)) and had a good fit (Hosmer-Lemeshow goodness-of-fit test (X2 (3)=0.55, p=0.908)). The area under the curve value for the final model was 0.74 (95% CI: 0.67 to 0.82).Conclusions and implications The WHALES screening tool is a short and rapid tool predicting 3-month mortality among hospitalised older patients. Early identification of end of life may help appropriate timing and implementation of palliative care.Data are available upon reasonable request.