A Longitudinal Study of CogEvo’s Prediction of Cognitive Decline in Older Adults

TL;DR

This study shows that CogEvo, a computer-based screening tool, can predict cognitive decline in older adults with high specificity, though it may miss some cases.

Contribution

The study longitudinally validates CogEvo's ability to predict cognitive decline in older adults with minimal professional involvement.

Findings

Participants with CogEvo grade 4 had significantly higher rates of cognitive decline compared to those with grade ≤3.

CogEvo grade 4 showed 50% sensitivity and 93.6% specificity in predicting cognitive decline.

The predictive relationship remained significant after adjusting for baseline MMSE scores and other confounders.

Abstract

The predictive abilities of computer-based screening devices for early cognitive decline (CD) in older adults have rarely been longitudinally examined. Therefore, this study examined the ability of CogEvo, a short-duration, computer-based cognitive screening device requiring little professional involvement, to predict CD among community-dwelling older adults. We determined whether 119 individuals aged ≥ 65 years living in Japanese rural communities who scored ≥ 24 on the Mini-Mental State Examination (MMSE) at baseline developed CD by annually administering the MMSE to them. CD was defined as an MMSE score of ≤23. At baseline, the overall CogEvo judgment grade, with lower grades indicating better cognitive function, was calculated from the results of various cognitive tasks. Over 2 years, 10 participants developed CD. Participants with grades of 4 had a higher percentage of CD cases than those with grades of ≤3 (p < 0.01). This relationship remained significant after controlling for possible confounders, including the MMSE score at baseline. The sensitivity and specificity of the CogEvo grade cutoff of 4 were 50.0% and 93.6%, respectively. In conclusion, CogEvo may be an efficient tool for identifying individuals at a high risk for dementia. The possibility of missing CD cases should be considered when using CogEvo for screening.

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