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Updated: Aug 6, 2026
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
[Mini-Mental State Examination: psychometric characteristics in elderly outpatients]
Roberto A Lourenço1, Renato P Veras
1Departamento de Medicina Interna, Faculdade de Ciências Médicas, Universidade do Estado do Rio de Janeiro, Rio de Janeiro, Brasil.
Objective:
To assess the psychometric characteristics of the Mini-Mental State Examination in elderly outpatients who seek primary health care.
Methods:
A total of 303 subjects (>65 years) underwent comprehensive geriatric assessment with functional tools, including Mini-Mental State Examination. Sensitivity, specificity, positive predictive value, negative predictive value, and ROC curve were calculated.
Results:
Sensitivity, specificity, positive and negative predictive values, and area under ROC curve were 80.8%, 65.3%, 44.7%, 90.7% and 0.807 respectively (cutoff point =23/24). The best cutoff point for illiterate was 18/19 (sensitivity =73.5%; specificity =73.9%); and for literate was 24/25 (sensitivity =75%; specificity =69.7%).
Conclusions:
While screening elderly outpatients for dementia, schooling must be considered in the choice of the best cutoff point in the Mini-Mental State Examination.
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