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The Brain Health Assessment for Detecting and Diagnosing Neurocognitive Disorders - PubMed

The Brain Health Assessment for Detecting and Diagnosing Neurocognitive Disorders

Katherine L Possin et al. J Am Geriatr Soc. 2018 Jan.

Abstract

Background/objectives: Brief cognitive screens lack the sensitivity to detect mild cognitive impairment (MCI) or support differential diagnoses. The objective of this study was to validate the 10-minute, tablet-based University of California, San Francisco (UCSF) Brain Health Assessment (BHA) to overcome these limitations.

Design: Cross-sectional.

Setting: UCSF Memory and Aging Center.

Participants: Older adults (N = 347) (neurologically healthy controls (n = 185), and individuals diagnosed with MCI (n = 99), dementia (n = 42), and as normal with concerns (n = 21)).

Measurements: The BHA includes subtests of memory, executive function and speed, visuospatial skills, and language and an optional informant survey. Participants completed the Montreal Cognitive Assessment (MoCA) and criterion-standard neuropsychological tests. Standardized structural 3T brain magnetic resonance imaging was performed in 145 participants.

Results: At a fixed 85% specificity rate, the BHA had 100% sensitivity to dementia and 84% to MCI; the MoCA had 75% sensitivity to dementia and 25% to MCI. The BHA had 83% sensitivity to MCI likely due to AD and 88% to MCI unlikely due to AD, and the MoCA had 58% sensitivity to MCI likely AD and 24% to MCI unlikely AD. The BHA subtests demonstrated moderate to high correlations with the criterion-standard tests from their respective cognitive domains. Memory test performance correlated with medial temporal lobe volumes; executive and speed with frontal, parietal, and basal ganglia volumes; and visuospatial with right parietal volumes.

Conclusion: The BHA had excellent combined sensitivity and specificity to detect dementia and MCI, including MCI due to diverse etiologies. The subtests provide efficient, valid measures of neurocognition that are critical in making a differential diagnosis.

Keywords: cognitive screening; mild cognitive impairment; primary care.

© 2018, Copyright the Authors Journal compilation © 2018, The American Geriatrics Society.

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Conflict of interest statement

Conflicts of Interest

The remaining authors declare that they have no conflicts to disclose.

Figures

Figure 1
Figure 1

BHA subtest descriptions and sample screenshots from A. Favorites, B. Match, and C. Line Orientation

Figure 2
Figure 2

Receiver Operating Characteristic Curves of the Brain Health Assessment and the Montreal Cognitive Assessment in separating patients diagnosed with dementia or mild cognitive impairment from neurologically healthy controls aSensitivity is provided at two levels of specificity: 85%, 75%. bBHA: Complete was comprised of the subtests (operationalized by mean and lowest age-corrected z-score) and the BHS informant survey (the ECog-12 and the additional 9 questions). Abbreviations: Sensitivity (SN), mild cognitive impairment (MCI), Brain Health Assessment (BHA), Montreal Cognitive Assessment (MoCA)

Figure 3
Figure 3

Regional gray matter volume correlates of performance on the Brain Health Assessment Favorites, Match, and Lines subtests FWE-corrected t-maps depicting regional brain volumes that correlated with (A) Favorites, (B) Match, and (C) Line Orientation performance, controlling for age, sex, and total intracranial volume (N = 145). In (A), scores on the Favorites subtest correlated positively with gray matter volumes in bilateral temporal regions. In (B), scores on the Match subtest correlated positively with gray matter volumes in bilateral frontal-subcortical regions. In (C), scores on the Line Orientation subtest correlated with gray matter volumes in right parietal regions. Results are overlaid on a DARTEL-derived template. X, Y, and Z coordinates in the MNI space for each section are shown below the image. “L” denotes the left-right orientation of the images. All results depicted were significant at a corrected level (pFWE<0.05).

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