Authors:
Elisa Salvi
1
;
Irma Sterpi
2
;
Antonio Caronni
2
;
Peppino Tropea
2
;
Michela Picardi
2
;
Massimo Corbo
2
;
Giordano Lanzola
1
;
Silvana Quaglini
1
and
Lucia Sacchi
1
Affiliations:
1
Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy
;
2
Department of Neurorehabilitation Sciences, Casa di Cura Privata del Policlinico, Milan, Italy
Keyword(s):
Fall Risk, Predictive Models, Model Comparison, Aging in Place.
Abstract:
Within the NONCADO project, which aims at preventing falls in the elderly living alone at home, we performed a literature search for models that provide an estimate of the subject’s risk of falling. Our goal is to combine the scores produced by multiple models to derive an overall risk score. In this work we described nine predictive models and we tested their concordance in assessing the risk of falling of two patient populations, namely a simulated patient population and an Italian real-world patient population. Using the real-world population, we also measured the performance of a subset of these models, by comparing their predictions with the outcome (in terms of occurred falls) collected in a 9-months follow-up study. Our experiments showed poor model concordance and dependence of the results on the population. Furthermore, the predictive performance measured the Italian population were limited. Therefore, attempts to combine the risk predictions of multiple models should be cau
tious.
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