Frailty prevalence in chronic kidney disease (CKD) patients has been reported to be greater than general adult population and is independently associated with negative outcome in all stages of CKD. However, frailty is currently assessed using clinical criteria without adequately considering socio-health factors, therefore, the generalization of indicators and indices remains dicult. In this study we aimed at exploring the possibility of elaborating a frailty index based on the Apulian population aected by CKD, using administrative data available from central and peripheral administrative institutions, for the early identication of people at high risk of health and functional status deterioration.
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|Titolo:||OPLON Project: Developing a frailty score using large administrative data and machine learning algorithms|
|Data di pubblicazione:||2019|
|Appare nelle tipologie:||4.2 Abstract in Atti di convegno|