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Updated: Mar 19, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Improving screening in the WHO ICOPE strategy: lessons from risk profiles for major adverse health outcomes
Karine Pérès1, Ivane Koumetio Jiatsa1, Antoine Gbessemehlan1
1University of Bordeaux-Inserm, Bordeaux Population Health Research Center, U1219, Bordeaux, 33076, France.
Background:
This study aimed to estimate the risk of four adverse outcomes [disability in instrumental activities of daily living (IADL), institutionalisation, dementia and death] associated with Intrinsic Capacity (IC) impairment at baseline, and to test different combinations of IC impairments to better identify high-risk profiles.
Methods:
The sample was drawn from two population-based cohorts (Three-City and AMI), in which the six IC domains were assessed: cognition, nutrition, psychology, hearing, vision and mobility. Participants were categorised into three groups: no impairment (IC0), single impairment (IC1) and two impairments or more (IC2+). Cox models were used to estimate the risk of adverse outcomes associated with IC1 and IC2+ compared to IC0. Conditional inference tree analyses, followed by Cox models, were then conducted to identify the most predictive domains and combinations defining the highest-risk profiles.
Results:
Among the 2964 participants ≥65 included, 24.9% had one IC impairment and 62.3% had two or more. Being in the IC2+ group was associated with a significantly increased risk of all outcomes [adjusted hazard ratios (aHRs) ranging from 2.0 to 3.0], whereas IC1 was not, except for IADL-disability (aHR = 1.46; 95%CI = 1.14-1.87). Mobility, cognitive and visual impairments were constitutive of the highest-risk profiles.
Conclusions:
This study supports the relevance of the ICOPE-targeted IC domains in predicting adverse outcomes. Given the high proportion of individuals screened positive, refining the screening threshold by considering the number and combination of impairments may better identify those who should benefit from the subsequent steps for more advanced assessment or intervention as a priority.
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