Determining levels of linguistic deficit by applying cluster analysis to the aphasia quotient of Western Aphasia Battery in post-stroke aphasia

Abstract The aphasia quotient of Western Aphasia Battery (WAB-AQ) has been used as an inclusion criterion and as an outcome measure in clinical, research, or community settings. The WAB-AQ is also commonly used to measure recovery. This study aimed to quantitatively determine levels of the linguisti...

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Main Authors: Zhijie Yan, Dongshuai Wei, Shuo Xu, Jingna Zhang, Chunsheng Yang, Xinyuan He, Chong Li, Yongli Zhang, Mengye Chen, Xiaofang Li, Jia Jie
Format: Article
Language:English
Published: Nature Portfolio 2022-09-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-022-17997-0
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author Zhijie Yan
Dongshuai Wei
Shuo Xu
Jingna Zhang
Chunsheng Yang
Xinyuan He
Chong Li
Yongli Zhang
Mengye Chen
Xiaofang Li
Jia Jie
author_facet Zhijie Yan
Dongshuai Wei
Shuo Xu
Jingna Zhang
Chunsheng Yang
Xinyuan He
Chong Li
Yongli Zhang
Mengye Chen
Xiaofang Li
Jia Jie
author_sort Zhijie Yan
collection DOAJ
description Abstract The aphasia quotient of Western Aphasia Battery (WAB-AQ) has been used as an inclusion criterion and as an outcome measure in clinical, research, or community settings. The WAB-AQ is also commonly used to measure recovery. This study aimed to quantitatively determine levels of the linguistic deficit by using a cluster analysis of the WAB-AQ in post-stroke aphasia (PSA). 308 patients were extracted from the database. Cutoff scores are defined by mean overlap WAB-AQ scores of clusters by systematic cluster analysis, the method of which is the farthest neighbor element, and the metrics are square Euclidean distance and Pearson correlation, performed on the full sample of WAB-AQ individual subitem scores. A 1-way analysis of variance, with post hoc comparisons conducted, was used to determine whether clusters had significant differences. Three clusters were identified. The scores for severe, moderate, and mild linguistic deficit levels ranged from 0 to 30, 30.1 to 50.3, and 50.4 to 93.7, respectively. For PSA, the cluster analysis of WAB-AQ supports a 3-impairment level classification scheme.
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spelling doaj.art-90805bfb97264b0499d0ca9c00a712252022-12-22T04:24:52ZengNature PortfolioScientific Reports2045-23222022-09-011211510.1038/s41598-022-17997-0Determining levels of linguistic deficit by applying cluster analysis to the aphasia quotient of Western Aphasia Battery in post-stroke aphasiaZhijie Yan0Dongshuai Wei1Shuo Xu2Jingna Zhang3Chunsheng Yang4Xinyuan He5Chong Li6Yongli Zhang7Mengye Chen8Xiaofang Li9Jia Jie10Department of Rehabilitation Medicine, The Third Affiliated Hospital of Xinxiang Medical UniversityDepartment of Rehabilitation Medicine, The Third Affiliated Hospital of Xinxiang Medical UniversityDepartment of Rehabilitation Medicine, Huashan Hospital, Fudan UniversityDepartment of Rehabilitation Medicine, The Third Affiliated Hospital of Xinxiang Medical UniversityDepartment of Rehabilitation Medicine, The Third Affiliated Hospital of Xinxiang Medical UniversityDepartment of Rehabilitation Medicine, The Third Affiliated Hospital of Xinxiang Medical UniversityDepartment of Rehabilitation Medicine, Huashan Hospital, Fudan UniversityDepartment of Rehabilitation Medicine, Huashan Hospital, Fudan UniversityDepartment of Rehabilitation Medicine, Huashan Hospital, Fudan UniversityDepartment of Rehabilitation Medicine, The Third Affiliated Hospital of Xinxiang Medical UniversityDepartment of Rehabilitation Medicine, Huashan Hospital, Fudan UniversityAbstract The aphasia quotient of Western Aphasia Battery (WAB-AQ) has been used as an inclusion criterion and as an outcome measure in clinical, research, or community settings. The WAB-AQ is also commonly used to measure recovery. This study aimed to quantitatively determine levels of the linguistic deficit by using a cluster analysis of the WAB-AQ in post-stroke aphasia (PSA). 308 patients were extracted from the database. Cutoff scores are defined by mean overlap WAB-AQ scores of clusters by systematic cluster analysis, the method of which is the farthest neighbor element, and the metrics are square Euclidean distance and Pearson correlation, performed on the full sample of WAB-AQ individual subitem scores. A 1-way analysis of variance, with post hoc comparisons conducted, was used to determine whether clusters had significant differences. Three clusters were identified. The scores for severe, moderate, and mild linguistic deficit levels ranged from 0 to 30, 30.1 to 50.3, and 50.4 to 93.7, respectively. For PSA, the cluster analysis of WAB-AQ supports a 3-impairment level classification scheme.https://doi.org/10.1038/s41598-022-17997-0
spellingShingle Zhijie Yan
Dongshuai Wei
Shuo Xu
Jingna Zhang
Chunsheng Yang
Xinyuan He
Chong Li
Yongli Zhang
Mengye Chen
Xiaofang Li
Jia Jie
Determining levels of linguistic deficit by applying cluster analysis to the aphasia quotient of Western Aphasia Battery in post-stroke aphasia
Scientific Reports
title Determining levels of linguistic deficit by applying cluster analysis to the aphasia quotient of Western Aphasia Battery in post-stroke aphasia
title_full Determining levels of linguistic deficit by applying cluster analysis to the aphasia quotient of Western Aphasia Battery in post-stroke aphasia
title_fullStr Determining levels of linguistic deficit by applying cluster analysis to the aphasia quotient of Western Aphasia Battery in post-stroke aphasia
title_full_unstemmed Determining levels of linguistic deficit by applying cluster analysis to the aphasia quotient of Western Aphasia Battery in post-stroke aphasia
title_short Determining levels of linguistic deficit by applying cluster analysis to the aphasia quotient of Western Aphasia Battery in post-stroke aphasia
title_sort determining levels of linguistic deficit by applying cluster analysis to the aphasia quotient of western aphasia battery in post stroke aphasia
url https://doi.org/10.1038/s41598-022-17997-0
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