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Updated: Sep 23, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Comparing Detection of Alzheimer's and Vascular Disease-Related Cognitive Impairment With Brief Cognitive Screens
Robert J Kanser1, Alicia B VandenBussche Jantz1, Patrick M Logan1
1Department of Mental Health & Behavioral Sciences, James A. Haley Veterans' Hospital, Tampa, Florida.
Abstract:
Objectives: The study compared the accuracy of the Mini-Mental State Examination (MMSE) with its modified version (3MS) in distinguishing healthy older adults from adults with cognitive impairment due to suspected Alzheimer’s disease (AD) or vascular disease (VaD). Method: Participants were 98 veterans who underwent comprehensive neuropsychological evaluation due to concern for cognitive decline. Participants were selected via retrospective chart review on the basis of diagnosis. They had diagnoses of mild or major neurocognitive disorder due to suspected AD (N=20), mild or major neurocognitive disorder due to suspected VaD (N=44), or no neurocognitive diagnosis (i.e., healthy adult comparisons; HC, N=34). Results: The 3MS demonstrated superior detection of cognitive impairment. The extent of this enhanced detection was influenced by the suspected etiology of cognitive impairment. The 3MS and MMSE had comparable discrimination of AD and HC. With respect to VaD, the 3MS showed superior discriminability compared to the MMSE. Conclusions: Overall, results support the adoption of the 3MS over that of the MMSE. The 3MS is a superior (and free) tool for detecting cognitive impairment in geriatric populations. Its use is recommended for first-line screening of cognitive symptoms in older adult populations, especially those with concern for VaD.
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