慢性主观性头晕患者静息状态脑电图微态异常特征分析

Pan Tang, Pei-Ning Shao, Rong-Rong Qin, Cai-Xia Yin, Qi-Fei Qu, Zi-Xuan Ying, Ti-Fei Yuan, Rong-Rong Song
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摘要

背景头晕是神经内科临床最常见的临床症状之一。然而,头晕的神经机制,特别是脑电图微观状态的表征,仍然不完全阐明。目的探讨慢性主观性头晕(CSD)患者脑电微状态的潜在特征及眩晕障碍与脑电微状态参数的关系。方法招募29例CSD患者和31例年龄匹配的健康成人。对所有被试闭眼静息状态下的128通道脑电图进行记录。头晕障碍量表(DHI)用于评估患者的头晕相关障碍。脑电微观状态分为A、B、C和D四类,并确定其参数进行逻辑分析。结果与HC组相比,CSD组在BAI、BDI-13、Microstate B的时间覆盖和发生等方面得分较高。微状态B的时间覆盖和发生也与CSD患者的头晕障碍显著相关。Logistic回归分析显示,B类微观状态的发生(OR = 0.058, 95%CI: 0.005 ~ 0.744)是区分CSD组与HC组的显著指标。结论CSD患者脑电图微态的时间动态变化以及眩晕障碍与微态B的关系可能反映了其视觉网络的异常。脑电图微态的这些神经生理特征对头晕的辅助诊断有重要意义。
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Characterizing abnormalities in resting-state EEG microstates in patients with chronic subjective dizziness
Abstract Background Dizziness is one of the most prevalent clinical symptoms in neurology clinics. Nevertheless, the neural mechanisms of dizziness, especially the characterization of EEG microstates, remain incompletely elucidated. Objectives This study aimed to explore the potential characteristics of EEG microstate in patients with Chronic Subjective Dizziness (CSD) and the relationship between dizziness handicaps and EEG microstate parameters. Methods We recruited 29 patients with CSD and 31 age-matched healthy adults. The 128-channel EEG recording of all participants at resting state with eyes closed was performed. Dizziness handicap Inventory (DHI) was used to evaluate patients’ dizziness related handicaps. The EEG microstates was clustered into four classes (A, B, C, and D) and we identified their parameters for logistic analysis. Results The CSD group scored higher on BAI, BDI-13, and the time coverage and occurrence of Microstate B compared to the HC group. And the time coverage and occurrence of Microstate B were also significantly associated with dizziness handicaps in CSD patients. Logistic regression analysis showed that the occurrence of class B microstates (OR = 0.058, 95%CI: 0.005 ~ 0.744) was a significant indicator for distinguishing the CSD group from the HC group. Conclusion The temporal dynamic alternations of EEG microstates and the relationship between dizziness handicaps and Microstate B in patients with CSD may reflect anomalies in their visual network. These neurophysiological characteristics of EEG microstates could be significant for auxiliary diagnosis of dizziness.
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