Neuropsychological predictors of conversion to probable Alzheimer disease in elderly with mild cognitive impairment
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Updated: Apr 15, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Sara García-Herranz1, M Carmen Díaz-Mardomingo1, Herminia Peraita1
1Department of Psychology Basic I, National University of Distance Education (UNED), Madrid, Spain.
Abstract:
In the field of neuropsychology, it is essential to determine which neuropsychological tests predict Alzheimer's disease (AD) in people with mild cognitive impairment (MCI) and which cut-off points should be used to identify people at greater risk for converting to dementia. The aim of the present study was to analyse the predictive value of the cognitive tests included in a neuropsychological battery for conversion to AD among MCI participants and to analyse the influence of some sociodemographic variables - sex, age, schooling - and others, such as follow-up time and emotional state. A total of 105 participants were assessed with a neuropsychological battery at baseline and during a 3-year follow-up period. For the present study, the data were analysed at baseline. During the follow-up period, 24 participants (22.85%) converted to dementia (2.79 ± 1.14 years) and 81 (77.14%) remained as MCI. The logistic regression analysis determined that the long delay cued recall and the performance time of the Rey figure test were the best predictive tests of conversion to dementia after an MCI diagnosis. Concerning the sociodemographic factors, sex had the highest predictive power. The results reveal the relevance of the neuropsychological data obtained in the first assessment. Specifically, the data obtained in the episodic verbal memory tests and tests that assess visuospatial and executive components may help to identify people with MCI who may develop AD in an interval not longer than 4 years, with the masculine gender being an added risk factor.
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