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Updated: Mar 31, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Staging cognitive impairment and incidence of dementia
J Santabárbara1, R Lopez-Anton2, P Gracia-García2
1Department of Preventive Medicine and Public Health,Universidad de Zaragoza,Zaragoza,Spain.
Aims:
In a background of interest in staging models in psychiatry, we tested the validity of a simple staging model of cognitive impairment to predict incident dementia.
Method:
A large community sample of adults aged ≥55 years (N = 4803) was assessed in the baseline of a longitudinal, four-wave epidemiological enquiry. A two-phase assessment was implemented in each wave, and the instruments used included the Mini-Mental Status Examination (MMSE); the History and Aetiology Schedule and the Geriatric Mental State-AGECAT. For the standardised degree of cognitive impairment Perneczky et al's MMSE criteria were applied. A panel of psychiatrists diagnosed cases of dementia according to DSM-IV criteria, and cases and sub-cases of dementia were excluded for the follow-up waves. Competing risk regression models, adjusted by potential confounders, were used to test the hypothesised association between MMSE levels and dementia risk.
Results:
Out of the 4057 participants followed up, 607 (14.9%) were classified as 'normal' (no cognitive impairment), 2672 (65.8%) as 'questionable' cognitive impairment, 732 (18.0%) had 'mild' cognitive impairment, 38 (0.9%) had 'moderate' cognitive impairment and eight (0.2%) had 'severe' impairment. Cognitive impairment was associated with risk of dementia, the risk increasing in parallel with the level of impairment (hazard ratio: 2.72, 4.78 and 8.38 in the 'questionable', 'mild' and 'moderate' level of cognitive impairment, respectively).
Conclusions:
The documented gradient of increased risk of dementia associated with the severity level of cognitive impairment supports the validity of the simple staging model based on the MMSE assessment.
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