Data-driven classification of patients with primary progressive aphasia
Data-driven classification of patients with primary progressive aphasia
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DOI：
10.1016/j.bandl.2017.08.001
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发表时间：
2017-11-01
影响因子：
2.5
通讯作者：
Nestor, Peter J.
中科院分区：
文献类型：
--
作者：
Hoffman, Paul;Sajjadi, Seyed Ahmad;Nestor, Peter J.
目前的诊断标准将原发性进行性失语分为语义型（sv）、非流利型（nfv）和逻辑缺失型（lv）三种类型的PPA，尽管这一方案的适用性还存在争议。本研究采用了数据驱动的方法，将k-means聚类应用于43名PPA患者的数据。该算法根据语言、语义和非语言认知评分的相似性对患者进行分组。最优解由三组组成。一组，几乎完全是那些被诊断为svPPA的人，表现出选择性的语义障碍。第二个duster，言语产生，重复和句法处理受损，包含大多数nfvPPA患者，但也有一些lvPPA患者。最后一组表现出更严重的缺陷，语音，重复和句法以及语义和其他认知缺陷。这些结果表明，在非语义PPA的情况下，分化主要反映了语言/认知障碍的整体程度。所观察到的模式几乎没有影响纳入/排除非语言认知分数。
Current diagnostic criteria classify primary progressive aphasia into three variants semantic (sv), nonfluent (nfv) and logopenic (lv) PPA-though the adequacy of this scheme is debated. This study took a data-driven approach, applying k-means clustering to data from 43 PPA patients. The algorithm grouped patients based on similarities in language, semantic and non-linguistic cognitive scores. The optimum solution consisted of three groups. One group, almost exclusively those diagnosed as svPPA, displayed a selective semantic impairment. A second duster, with impairments to speech production, repetition and syntactic processing, contained a majority of patients with nfvPPA but also some lvPPA patients. The final group exhibited more severe deficits to speech, repetition and syntax as well as semantic and other cognitive deficits. These results suggest that, amongst cases of non-semantic PPA, differentiation mainly reflects overall degree of language/cognitive impairment. The observed patterns were scarcely affected by inclusion/exclusion of non-linguistic cognitive scores.