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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Utility of the RBANS in detecting cognitive impairment associated with Alzheimer's disease: sensitivity, specificity,
Kevin Duff1, Joy D Humphreys Clark, Sid E O'Bryant
1Roy J. and Lucille A. Carver College of Medicine, Department of Psychiatry, University of Iowa, 1-308 MEB, Iowa City, IA 52242-1000, USA. kevin-duff@uiowa.edu
Abstract:
Although initially developed as a brief dementia battery, the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) has not yet demonstrated its sensitivity, specificity, and positive and negative predictive powers in detecting cognitive impairment in patients with Alzheimer's disease (AD). Therefore, the current study examined the clinical utility of the RBANS by comparing two age-, education-, and gender-matched groups: patients with AD (n=69) and comparators (n=69). Significant differences (p<0.001) were observed on the RBANS Total score, all 5 Indexes, and all 12 subtests, with patients performing worse than the comparison participants. An optimal balance between sensitivity and specificity on RBANS scores was obtained when cutoffs of one and one and a half standard deviations below the mean of the comparison sample were implemented. Areas under the Receiver Operating Characteristic curves for all RBANS Indexes were impressive though Immediate and Delayed Memory Indexes were excellent (0.96 and 0.98, respectively). Results suggest that RBANS scores yield excellent estimates of diagnostic accuracy and that the RBANS is a useful screening tool in detection of cognitive deficits associated with AD.
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