Subtype identification of clinical and thrombus imaging features in acute ischemic stroke: using clustering analysis and principal component analysis

急性缺血性卒中临床和血栓影像学特征的亚型识别:基于聚类分析和主成分分析

阅读:1

Abstract

Acute ischemic stroke (AIS) presents significant heterogeneity in clinical and thrombus imaging characteristics, which can profoundly impact therapeutic decisions and outcomes. This study analyzed 520 AIS patients who underwent endovascular thrombectomy, integrating clinical variables and thrombus imaging features to identify potential subtypes through unsupervised clustering and principal component analysis. Three distinct subtypes emerged: Cluster 1, characterized by middle cerebral artery occlusion, shorter thrombus lengths, and favorable outcomes; Cluster 2, comprising predominantly male smokers and drinkers with no significant outcome differences; and Cluster 3, consisting of older patients with higher stroke severity, internal carotid artery occlusion, longer thrombus lengths, and poor outcomes. Key features driving subtype differentiation included atrial fibrillation, thrombus perviousness, and clot burden scores. Significant variations in recanalization and hemorrhagic transformation rates were also observed among clusters. These findings underscore the potential of integrating thrombus imaging characteristics into personalized treatment strategies, offering a more precise approach to prognosis and management for AIS patients.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。