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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
The Montreal Cognitive Assessment-Basic: A Screening Tool for Mild Cognitive Impairment in Illiterate and
Parunyou Julayanont1,2,3,4, Sookjaroen Tangwongchai5, Solaphat Hemrungrojn5
1Division of Neurology, Department of Internal Medicine, Chulalongkorn University, Bangkok, Thailand.
Objectives:
To assess the validity of a newly developed cognitive screening tool, the Montreal Cognitive Assessment-Basic (MoCA-B), in screening for mild cognitive impairment (MCI) in elderly adults with low education and varying literacy.
Design:
Cross-sectional.
Setting:
Community hospital in Bangkok, Thailand.
Participants:
Cognitively normal controls (n = 43) and individuals with MCI according to the National Institute on Aging-Alzheimer's Association work group criteria (n = 42) aged 55 to 80 with less than 5 years of education.
Measurements:
MoCA-B scores.
Results:
Mean MoCA-B scores were 26.3 ± 1.6 for illiterate controls and 21.3 ± 3.8 for illiterate participants with MCI (P < .001) and 26.6 ± 2.0 for literate controls and 23.0 ± 2.1 for literate participants with MCI (P < .001). MoCA-B scores did not differ significantly according to literacy, and multiple regression suggested no association with age or education. The optimal cutoff score of 24 out of 25 yielded 81% sensitivity and 86% specificity for MCI (area under the receiver operating characteristic curve = 0.90, P < .001). Test-retest reliability was 0.91 (P < .001), and internal consistency was 0.82. Administration time was 15 to 21 minutes.
Conclusion:
The MoCA-B appears to have excellent validity and addresses an unmet need by accurately screening for MCI in poorly educated older adults regardless of literacy.
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