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Updated: Aug 6, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Detecting mild cognitive impairment remotely with the modified memory impairment screen by telephone
Amanda L Stein1, Kathryn A Tolle1,2, Amanda N Stover1,3
1Department of Psychiatry & Behavioral Neuroscience, University of Cincinnati Academic Health Center, Cincinnati, OH, US.
Abstract:
The original Memory Impairment Screen by Telephone (MIST) was designed to identify individuals with dementia but was relatively ineffective for identification of less severe impairment observed in mild cognitive impairment (MCI). We expanded the original MIST to create a modified instrument (mMIST) with greater sensitivity to less severe memory impairment. Older men and women with subjective cognitive decline were assessed by phone with the mMIST and subsequently classified independently with MCI or non-pathological cognitive decline. Participants with MCI produced lower scores on the mMIST than did participants without MCI, 10.8 ± 2.7 vs 13.3 ± 1.3, t = 5.68, p < 0.001, and performance on the mMIST predicted performances on the California Verbal Learning Test (CVLT), Verbal Paired Associate Learning Test (VPAL), Montreal Cognitive Assessment (MoCA) total score, and MoCA memory index score, p < 0.001. Receiver operating characteristic (ROC) analyses identified the optimal cut score on the mMIST to distinguish participants with and without MCI with Sensitivity = 73.1%, Specificity = 79.1%, and AUC = 0.79. Predictive values for distinguishing the amnestic form of MCI (aMCI) from non-amnestic MCI were Sensitivity = 81.8%, Specificity = 30%, and AUC = 0.82. These findings indicate that the mMIST is a valid screening instrument for identifying MCI. It can be administered remotely at low cost and low participant burden. Also, the mMIST has potential utility for remote cross-sectional and longitudinal evaluation in research and clinical contexts. Further investigation is indicated to corroborate its utility for assessment of aging patients and research participants.
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