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Updated: Jun 26, 2026
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Combining functional scales and cognitive tests in screening for mild cognitive impairment at a university-based
Izabella Dutra de Abreu1, Paula Villela Nunes, Breno Satler Diniz
1Laboratory of Neuroscience (LIM 27), Department of Psychiatry, School of Medicine, Universidade de São Paulo, São Paulo, SP, Brazil.
Objective:
To determine the diagnostic accuracy of the Mini-Mental State Examination combined to the Informant Questionnaire on Cognitive Decline in the Elderly for the identification of mild cognitive impairment.
Method:
191 elderly subjects were assessed with the Mini-Mental State Examination, and their informants were assessed with the Informant Questionnaire on Cognitive Decline in the Elderly. Subjects were divided into three groups according to their cognitive state (controls: n = 67, mild cognitive impairment: n = 65 and dementia: n = 59), which was ascertained by clinical and neuropsychological evaluation. The diagnostic accuracy of each test in the discrimination of diagnostic groups (mild cognitive impairment vs. controls, mild cognitive impairment vs. dementia and dementia vs. controls) was examined with the aid of ROC curves. We additionally verified if the combination of both tests would increase diagnostic accuracy for mild cognitive impairment and control identification.
Results:
The combination of the Mini-Mental State Examination and the Informant Questionnaire on Cognitive Decline in the Elderly scores did not increase the Mini-Mental State Examination diagnostic accuracy in the identification of patients with mild cognitive impairment.
Conclusions:
The present data do not warrant the combination of the Mini-Mental State Examination and the Informant Questionnaire on Cognitive Decline in the Elderly as a sufficient diagnostic tool in the diagnostic screening for mild cognitive impairment.
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