Farseeing partners from the University of Bologna, Robert Bosch Gesellschaft fuer Medizinische Forschung and Azienda Sanitaria di Firenze publish in the Journal of Post Acute and Long Term Care Medicine on:
Predictive Performance of a Fall Risk Assessment Tool (FRAT-up) for
Community-Dwelling Older People in 4 European Cohorts.
Palumbo P, Klenk J, Cattelani L, Bandinelli S, Ferrucci L, Rapp K,
Chiari L, Rothenbacher D.J Am Med Dir Assoc. 2016 Sep 1. pii: S1525-8610(16)30293-6. doi:
10.1016/j.jamda.2016.07.015. [Epub ahead of print]
Background and objective
The fall risk assessment tool (FRAT-up) is a tool for predicting falls in community-dwelling older people based on a meta-analysis of fall risk factors. Based on the fall risk factor profile, this tool calculates the individual risk of falling over the next year. The objective of this study is to evaluate the performance of FRAT-up in predicting future falls in multiple cohorts.
Information about fall risk factors in 4 European cohorts of older people [Activity and Function in the Elderly (ActiFE), Germany; English Longitudinal Study of Aging (ELSA), England; Invecchiare nel Chianti (InCHIANTI), Italy; Irish Longitudinal Study on Aging (TILDA), Ireland] was used to calculate the FRAT-up risk score in individual participants. Information about falls that occurred after the assessment of the risk factors was collected from subsequent longitudinal follow-ups. We compared the performance of FRAT-up against those of other prediction models specifically fitted in each cohort by calculation of the area under the receiver operating characteristic curve (AUC).
The AUC attained by FRAT-up is 0.562 [95% confidence interval (CI) 0.530–0.594] for ActiFE, 0.699 (95% CI 0.680–0.718) for ELSA, 0.636 (95% CI 0.594–0.681) for InCHIANTI, and 0.685 (95% CI 0.660–0.709) for TILDA. Mean FRAT-up AUC as estimated from meta-analysis is 0.646 (95% CI 0.584–0.708), with substantial heterogeneity between studies. In each cohort, FRAT-up discriminant ability is surpassed, at most, by the cohort-specific risk model fitted on that same cohort.
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