Literature DB >> 27810646

The unbridged gap between clinical diagnosis and contemporary research on aphasia: A short discussion on the validity and clinical utility of taxonomic categories.

Dimitrios S Kasselimis1, Panagiotis G Simos2, Christos Peppas3, Ioannis Evdokimidis4, Constantin Potagas4.   

Abstract

Even if the traditional aphasia classification is continuously questioned by many scholars, it remains widely accepted among clinicians and included in textbooks as the gold standard. The present study aims to investigate the validity and clinical utility of this taxonomy. For this purpose, 65 left-hemisphere stroke patients were assessed and classified with respect to aphasia type based on performance on a Greek adaptation of the Boston Diagnostic Aphasia Examination. MRI and/or CT scans were obtained for each patient and lesions were identified and coded according to location. Results indicate that 26.5% of the aphasic profiles remained unclassified. More importantly, we failed to confirm the traditional lesion-to-syndrome correspondence for 63.5% of patients. Overall, our findings elucidate crucial vulnerabilities of the neo-associationist classification, and further support a deficit-rather than a syndrome-based approach. The issue of unclassifiable patients is also discussed.
Copyright © 2016 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Aphasia; Aphasia classification; Disconnection syndromes; Localization; Stroke

Mesh:

Year:  2016        PMID: 27810646     DOI: 10.1016/j.bandl.2016.10.005

Source DB:  PubMed          Journal:  Brain Lang        ISSN: 0093-934X            Impact factor:   2.381


  5 in total

1.  Exploring the Complexity of Aphasia With Network Analysis.

Authors:  Sameer Ashaie; Nichol Castro
Journal:  J Speech Lang Hear Res       Date:  2021-09-17       Impact factor: 2.674

2.  Diagnosing and managing post-stroke aphasia.

Authors:  Shannon M Sheppard; Rajani Sebastian
Journal:  Expert Rev Neurother       Date:  2020-12-10       Impact factor: 4.618

3.  Investigating the effect of changing parameters when building prediction models for post-stroke aphasia.

Authors:  Ajay D Halai; Anna M Woollams; Matthew A Lambon Ralph
Journal:  Nat Hum Behav       Date:  2020-04-20

4.  Individualized response to semantic versus phonological aphasia therapies in stroke.

Authors:  Sigfus Kristinsson; Alexandra Basilakos; Jordan Elm; Leigh Ann Spell; Leonardo Bonilha; Chris Rorden; Dirk B den Ouden; Christy Cassarly; Souvik Sen; Argye Hillis; Gregory Hickok; Julius Fridriksson
Journal:  Brain Commun       Date:  2021-08-05

5.  A data-driven approach to post-stroke aphasia classification and lesion-based prediction.

Authors:  Jon-Frederick Landrigan; Fengqing Zhang; Daniel Mirman
Journal:  Brain       Date:  2021-06-22       Impact factor: 15.255

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.