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Updated: Mar 25, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Both Financial and Cognitive Decline Predict Clinical Progression in MCI
Adam Gerstenecker1, Kristen L Triebel, Roy Martin
1Departments of *Neurology ‡Education †Alzheimer's Disease Center, University of Alabama at Birmingham, Birmingham, AL.
Abstract:
We investigated the roles of financial/functional and cognitive abilities in predicting clinical progression in patients with mild cognitive impairment (MCI). In a longitudinal sample of 51 patients with consensus conference diagnosed MCI likely due to Alzheimer disease (AD), two-year change scores were calculated for a performance measure of functional ability, cognitive variables, and 3 outcome measures used to track progression in neurological disorders. We examined patterns of financial and cognitive decline across the 2-year study period, and used these data and the 3 outcome variables to construct discrete predictor models of clinical progression in MCI. We found that both financial skills and cognitive abilities declined over the 2-year study period, were significantly associated with clinical progression, and contributed unique variance to all 3 predictor models. The resulting models accounted for 40% to 75% of variance in clinical progression across outcome variables. Taken together, our results indicate that changes in both cognitive abilities and higher order functional skills appear integral to understanding clinical progression in MCI likely due to AD. Specifically, declines in financial skills contribute unique variance to measures commonly used to track progression in neurological disorders associated with aging, and thus represent an important functional marker of clinical progression in prodromal AD.
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