Frailty Index and Incident Mortality, Hospitalization, and Institutionalization in Alzheimer's Disease: Data From the...

The identification of an objective evaluation of frailty capable of predicting adverse outcomes in Alzheimer's disease is increasingly discussed. The purpose of this study was to investigate whether the Frailty Index (FI) predicts hospitalization, institutionalization, and mortality in Alzheimer's disease patients.

A prospective multicenter cohort study (follow-up = 2 years) that included 1,191 participants with Alzheimer's disease was carried out. The outcomes of interest were incident hospitalization, institutionalization, and mortality. The FI was calculated as the ratio of actual to thirty potential deficits, that is, deficits presented by the participant divided by 30. Severity of dementia was assessed using the Clinical Dementia Rating score. Cox proportional hazard models were performed.

Mean age of the study sample was 76.2 (SD = 7.6) years. A quadratic relationship of the FI with age was reported at baseline (R (2) = .045, p < .001). The FI showed a statistically significant association with mortality (age- and gender-adjusted hazard ratio [HR] = 1.019, 95% confidence interval [CI] = 1.002-1.037, p = .031) and hospitalization (age- and gender-adjusted HR = 1.017, 95% CI = 1.006-1.029, p = .004) and a borderline significance with institutionalization. When the Clinical Dementia Rating score was simultaneously included in the age- and gender-adjusted models, the FI confirmed its predictive capacity for hospitalization (HR = 1.019, 95% CI = 1.006-1.032, p = .004), whereas the Clinical Dementia Rating score was the strongest predictor for mortality (HR = 1.922, 95% CI = 1.256-2.941, p = .003) and institutionalization (HR = 1.955, 95%CI = 1.427-2.679, p < .001).

The FI is a robust predictor of adverse outcomes even after the stage of the underlying dementia is considered. Future work should evaluate the clinical implementation of the FI in the assessment of demented individuals in order to improve the personalization of care.