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Updated: Jun 14, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Cognitive decline in incident Alzheimer disease in a community population
R S Wilson1, N T Aggarwal, L L Barnes
1Rush AD Center, Rush University Medical Center, 600 South Paulina Avenue, Suite 1038, Chicago, IL 60612, USA. rwilson@rush.edu
Objective:
To measure the cognitive consequences of incident Alzheimer disease (AD) in older African American and white subjects.
Methods:
Data are from the Chicago Health and Aging Project, a longitudinal cohort study of older white and black persons residing in a geographically defined community. At 3-year intervals, the entire study population completed 4 brief cognitive tests, from which a previously established composite measure of global cognition was derived, and a subset underwent detailed clinical evaluation that supported clinical classification of mild cognitive impairment, dementia, and AD. We used mixed-effects models to examine change in cognitive function following the diagnostic evaluation.
Results:
On clinical evaluation, 614 persons were found to have no cognitive impairment, 395 had mild cognitive impairment, and 149 had AD (88.5% mild); 10 persons with other dementias were excluded from analyses. During up to 11 years of observation following the clinical evaluation (mean = 5.5, SD = 2.5), the composite measure of global cognition declined a mean of 0.042 unit per year (SE = 0.008, p < 0.001) in those with no cognitive impairment. In comparison to the no cognitive impairment group, the annual rate of decline was increased more than twofold in mild cognitive impairment (estimate = 0.086, SE = 0.011, p < 0.001) and more than fourfold in AD (estimate = 0.173, SE = 0.020, p < 0.001). Results did not reliably vary by race, sex, or age.
Conclusions:
Alzheimer disease has a devastating impact on cognition, even in its prodromal stages, with comparable effects in African American and white persons.
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