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Updated: Nov 8, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
[Mini Mental State Examination (MMSE): Normative data for the Rosario Metropolitan Area, Argentina]
Pablo Luis Martino1, Mauricio Alejandro Cervigni, Leonardo Infante
1Centro de Investigación en Neurociencias de Rosario (CINR), Facultad de Psicología, Universidad Nacional de Rosario (UNR); Laboratorio de Cognición y Emoción (LABce), Facultad de Psicología, Universidad Nacional de Rosario (UNR).
Introduction:
It is estimated that population aging will continue to rise over the next few years, increasing cases of cognitive impairment. This requires having short, reliable and low-cost tests aimed at the early detection of cognitive disorders. The Mini Mental State Examination (MMSE) is a widely used test that allows an initial screening of cognitive disorders. Regarding this test, there is no normative data for the Rosario Metropolitan Area, Argentina, in elderly subjects.
Objective:
Obtain normative values for the MMSE test (language Spanish rioplatense version) in inhabitants of the Rosario Metropolitan Area, with ages 50 years and older.
Materials And Methods:
The MMSE was administered to 1126 subjects in the context of a campaign to prevent cognitive impairment. When applying the exclusion criteria, the sample was reduced to 824 subjects.
Results:
Schooling and age influence the performance of the test, while gender had no incidence. The means and standard deviations are reported according to levels of schooling and age ranges.
Conclusions:
These norms indicate an unprecedented local frame of reference for the purpose of researching cognitive disorders in subjects 50 years of age and older.
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