4.6 Article

Task performance to discriminate among variants of primary progressive aphasia

期刊

CORTEX
卷 145, 期 -, 页码 201-211

出版社

ELSEVIER MASSON, CORP OFF
DOI: 10.1016/j.cortex.2021.09.015

关键词

Aphasia; Dementia; Language; Evaluation

资金

  1. National Institutes of Health/Na-tional Institute on Deafness and Other Communication Dis-orders (NIH/NIDCD) [R01 DC05375, P50 DC014664, R01 DC011317]

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This study retrospectively analyzed 435 evaluations of individuals with primary progressive aphasia, finding that a battery of cognitive and linguistic assessments had varying sensitivity and specificity in distinguishing different variants. Naming assessments were identified as the strongest basis for distinguishing all variants.
Primary progressive aphasia can be distinguished into one of three variants: semantic, non-fluent/agrammatic, and logopenic. While a considerable body of work exists charac-terizing each variant, few prior studies have addressed the problem of optimizing behav-ioral assessment in a typical outpatient evaluation setting. Our aim is to examine the sensitivity and specificity of a battery of cognitive and linguistic assessments and deter-mine optimal scores for distinguishing patients' subtype based on these instruments. This was a retrospective analysis of outpatient clinical testing of individuals with known or suspected primary progressive aphasia. Evaluations included the National Alz-heimer's Coordinating Center frontotemporal lobar degeneration module and additional measures of naming, semantic association, word verification, and picture description. Receiver operating characteristic analysis was used to examine the utility of each task in distinguishing each variant from the others. Logistic regressions were used to examine the combined utility of tasks for distinguishing a given subtype. We examined 435 evaluations of 222 patients retrospectively. The battery was most consistent in distinguishing semantic variant by low scores and non-fluent/agrammatic variant by high scores on a similar subset of tasks. Tasks best distinguishing semantic variant produced a model that correctly classified 86% of cases. Tasks best distinguishing non-fluent/agrammatic variant correctly classified 77% of cases. The battery of tasks was weakest in identifying logopenic variant; only the ratio of sentence reading to sentence repetition performance was identified as a reasonable predictor, and it had predictive ac-curacy of 67%. Naming assessments were the strongest basis for distinguishing all variants, particu-larly semantic variant from non-fluent/agrammatic variant. These data illustrate that a number of commonly used assessments perform at chance in distinguishing variant and preliminarily support an abbreviated battery that marginally favors tools not currently included in the frontotemporal lobar degeneration module. (c) 2021 Elsevier Ltd. All rights reserved.

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