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Updated: Apr 23, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Everyday cognition scale items that best discriminate between and predict progression from clinically normal to mild
Gad A Marshall, Amy S Zoller, Kathleen E Kelly
1Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, 221 Longwood Avenue, BL-104H, Boston, MA 02115, USA. gamarshall@partners.org.
Background:
Impairment in instrumental activities of daily living (IADL) starts as individuals with amnestic mild cognitive impairment (MCI) transition to Alzheimer's disease (AD) dementia. However, most IADL scales have not shown IADL alterations in clinically normal (CN) elderly. The objective of this study was to determine which of the IADL-related Everyday Cognition (ECog) scale items are most sensitive for detection of early functional changes.
Methods:
We assessed 290 CN and 495 MCI participants from the Alzheimer's Disease Neuroimaging Initiative. We performed logistic regression analyses predicting the probability of CN vs. MCI diagnosis using only the 17 participant-based and 17 informant-based ECog items related to IADL. We then performed Cox regression analyses to predict progression from CN to MCI. All analyses were adjusted for demographic characteristics.
Results:
We found that worse performance on "remembering a few shopping items" (participant and informant-based p<0.0001), "remembering appointments" (participant and informant-based p<0.0001), "developing a schedule in advance of anticipated events" (participant-based p=0.007), "balancing checkbook" (participant-based p=0.02), and "keeping mail and papers organized" (informant-based p=0.002) best discriminated MCI from CN. We found that worse performance on "keeping mail and papers organized" (participant-based Hazard Ratio (HR)=2.27, p=0.07) marginally predicted greater hazard of progressing from CN to MCI.
Conclusions:
Our results indicate that a few simple questions targeting early functional changes, addressed either to the individual or informant, can effectively distinguish between CN elderly and individuals with MCI. Additionally, one of the above questions related to organization suggested which CN individuals are likely to progress to MCI.
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