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Updated: Nov 29, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
A Brief Digital Cognitive Assessment for Detection of Cognitive Impairment in Cuban Older Adults
Ana M Rodríguez-Salgado1,2, Jorge J Llibre-Guerra1,2,3, Elena Tsoy4
1Department of Neurology, National Institute of Neurology and Neurosurgery, La Havana, Cuba.
Background:
Rapid technological advances offer a possibility to develop cost-effective digital cognitive assessment tools. However, it is unclear whether these measures are suitable for application in populations from Low and middle-income countries (LMIC).
Objective:
To examine the accuracy and validity of the Brain Health Assessment (BHA) in detecting cognitive impairment in a Cuban population.
Methods:
In this cross-sectional study, 146 participants (cognitively healthy = 53, mild cognitive impairment (MCI) = 46, dementia = 47) were recruited at primary care and tertiary clinics. The main outcomes included: accuracy of the BHA and the Montreal Cognitive Assessment (MoCA) in discriminating between controls and cognitively impaired groups (MCI and dementia) and correlations between the BHA subtests of memory, executive functions, and visuospatial skills and criterion-standard paper-and-pencil tests in the same domains.
Results:
The BHA had an AUC of 0.95 (95% CI: 0.91-0.98) in discriminating between controls and cognitively impaired groups (MCI and dementia, combined) with 0.91 sensitivity at 0.85 specificity. In discriminating between control and MCI groups only, the BHA tests had an AUC of 0.94 (95% CI: 0.90-0.99) with 0.71 sensitivity at 0.85 specificity. Performance was superior to the MoCA across all diagnostic groups. Concurrent and discriminant validity analyses showed moderate to strong correlations between the BHA tests and standard paper-and-pencil measures in the same domain and weak correlations with standard measures in unrelated domains.
Conclusion:
The BHA has excellent performance characteristics in detecting cognitive impairment including dementia and MCI in a Hispanic population in Cuba and outperformed the MoCA. These results support potential application of digital cognitive assessment for older adults in LMIC.
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