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皮层网络拓变化是缺血性中风急性阶段临床演变的基础

Chiara Iacovelli¹, Giuseppe Reale², Giulia Baldazzi³

¹Department of Emergency, Anaesthesiology and Intensive Care Medicine, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy.

Neurorehabilitation and neural repair

|August 20, 2025

概括

通过脑电图 (EEG) 测量的脑网络效率可以预测中风的严重程度. 在中风24小时内,较高的三角波网络效率与较差的临床结果相关.

科学领域:

神经科学
临床神经学
生物物理

背景情况:

脑中风会破坏大脑网络的组织,其特点是局部连接 (集群系数,Cw) 和全球互连 (路径长度,Lw).
这些连接的平衡,称为小世界性 (Sw),反映了网络效率.

研究的目的:

确定脑电图 (EEG) 网络属性,以预测中风患者的临床演变.
使用多中心方法研究大脑网络特征与中风严重程度之间的关系.

主要方法:

招募87名前部循环缺血性中风患者进行横截面研究.
使用31个电极在24小时内 (T0) 和放电时 (T1) 获取静止状态EEG数据.
使用EEGLAB和eLORETA分析了EEG数据,以计算delta,theta和alpha网络的滞后线性一致性,Cw,Lw和Sw.

主要成果:

在T0 (β=0. 232, P=0. 04) 时发现alpha1 Sw与NIHSS之间存在负相关性,这表明较低的alpha效率预测了较高的中风严重程度.
在T1观察到delta Sw和NIHSS之间的正相关性 (β = 0. 423,P < 0. 001),这表明较高的delta效率预测出院时的中风严重程度更高.
较高的 delta Sw 在 T0 与较高的 NIHSS 在 T1 (β = 0. 259, P = 0. 02) 相关,这意味着早期的 delta 网络变化预测了以后的临床严重性.

结论:

在中风后24小时内增加的delta Sw与10天内NIHSS得分的增加有关.
超急性阶段的三角大脑网络变化可以作为中风预后的神经生理标志物.
将三角形网络效率整合到多式预后模型中可以提高中风结果的预测.

关键词:

美国电力大脑网络皮层连接性预后情况恢复情况一次中风

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