Browse by author
Lookup NU author(s): Dr Giacomo BergamiORCiD
Full text for this publication is not currently held within this repository. Alternative links are provided below where available.
Smart cities face the challenge of combining sustainable national welfare with high living standards. In the last decades, life expectancy increased globally, leading to various age-related issues in almost all developed countries. Frailty affects elderly who are experiencing daily life limitations due to cognitive and functional impairments and represents a remarkable burden for national health systems. In this paper, we proposed two different predictive models for frailty by exploiting 12 socioclinical databases. Emergency hospitalization or all-cause mortality within a year were used as surrogates of frailty. The first model was able to assign a frailty risk score to each subject older than 65 years old, identifying five different classes for tailor made interventions. The second prediction model assigned a worsening risk score to each subject in the first nonfrail class, namely the probability to move in a higher frailty class within the year. We conducted a retrospective cohort study based on the whole elderly population of the Municipality of Bologna, Italy. We created a baseline cohort of 95 368 subjects for the frailty risk model and a baseline cohort of 58 789 subjects for the worsening risk model, respectively. To evaluate the predictive ability of our models through calibration and discrimination estimates, we used, respectively, a six-year and a four-year observation period. Good discriminatory power and calibration were obtained, demonstrating a good predictive ability of the models.
Author(s): Bertini F, Bergami G, Montesi D, Veronese G, Marchesini G, Pandolfi P
Publication type: Article
Publication status: Published
Journal: Proceedings of the IEEE
Year: 2018
Volume: 106
Issue: 4
Pages: 723-737
Print publication date: 01/04/2018
Online publication date: 05/02/2018
Acceptance date: 05/02/2018
ISSN (print): 0018-9219
ISSN (electronic): 1558-2256
Publisher: IEEE
URL: https://doi.org/10.1109/JPROC.2018.2791463
DOI: 10.1109/JPROC.2018.2791463
Altmetrics provided by Altmetric
