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Automated detection of cognitive impairment in clinical practice

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Abstract

Objective

Cognitive impairment is now recognized as an impending public health crisis. About one-third of adults are concerned about their cognition, and the prevalence of objective cognitive impairment is much higher among those with neurological disorders. Existing screening tools are narrowly focused on detecting dementia in older adults and must be clinician-administered and scored, making them impractical for many neurology practices. This study examined the utility of a brief, self-administered, computerized cognitive screening tool, the Brief Assessment of Cognitive Health (BACH), in identifying cognitive impairment in adults.

Methods

912 adults (ages 18–84) completed BACH and a neuropsychological battery. Multivariable models were developed to provide a BACH index score reflecting the probability of cognitive impairment for individual patients. Predictive accuracy was compared to that of the Montreal Cognitive Assessment (MoCA) in a subset of 160 older adults from a Memory Disorders clinic.

Results

The final multivariable model showed good accuracy in identifying cognitively impaired individuals (c = 0·77). Compared to MoCA, BACH had superior predictive accuracy in identifying older patients with cognitive impairment (c = 0·79 vs. 0·67) as well as differentiating those with MCI or dementia from those without cognitive impairment (c = 0·86 vs. c = 0·67).

Conclusions

Results suggest that cognitive impairment can be identified in adults using a brief, self-administered, automated cognitive screening tool, and BACH provides several advantages over existing screeners: self-administered; automatic scoring; immediate results in health record; easily interpretable score; utility in wide range of patients; and flags for treatable factors that may contribute to cognitive complaints (i.e., depression, sleep problems, and stress).
Title
Automated detection of cognitive impairment in clinical practice
Authors
Robyn M. Busch
Olivia Hogue
Abagail F. Postle
Darlene P. Floden
Publication date
04-06-2024
Publisher
Springer Berlin Heidelberg
Published in
Journal of Neurology / Issue 8/2024
Print ISSN: 0340-5354
Electronic ISSN: 1432-1459
DOI
https://doi.org/10.1007/s00415-024-12444-8
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Navigating neuroimaging in Alzheimer’s care: Practical applications and strategies for integration/© Springer Health+ IME