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静息态脑电图与临床指标相关联以预测亚急性中风患者上肢运动恢复情况。

Resting-state EEG associated with clinical measures to predict upper limb motor recovery of subacute stroke.

作者信息

Ding Ling, Tian Xiang, Ren Huiming, Chen Zihang, Shu Xiaokang, Chen Shugeng, Jia Jie

机构信息

The First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China.

Shanghai Fifth People's Hospital, Shanghai, China.

出版信息

Front Neurol. 2025 Aug 22;16:1577393. doi: 10.3389/fneur.2025.1577393. eCollection 2025.

Abstract

BACKGROUND

After stroke, upper limb dysfunction seriously affects patients' quality of life. The uncertain prognosis of patients poses a challenge for therapists in developing personalized rehabilitation programs. Electroencephalograph (EEG) power spectrum changes during rehabilitation training may have a predictive effect on the improvement of upper limb movement. Therefore, it is of great clinical significance to explore the EEG power spectrum related to the recovery of upper limb function after stroke.

METHOD

This study included 113 subacute stroke survivors who were treated with routine rehabilitation for 2 weeks. At week 0 (T0) and week 2 (T2), behavioral scales including Fugl-Meyer Assessment of Upper Limb (FMA-UL), action research arm test (ARAT), modified Barthel index (MBI), and National Institutes of Health Stroke Scale (NIHSS) was assessed to compare correlations and observe the relationship between behavioral indicators and function under conventional rehabilitation. Twenty-six of the 113 patients were selected to undergo resting state EEG detection at week 0 (T0), week 1 (T1) and week 2 (T2), respectively. Power spectrum (PSD) and BSI values were calculated by EEG spectral analysis. The relationships between beta PSD and the clinical scales, between BSI and the clinical scales were examined by correlation and regression analysis.

RESULTS

Behavioral scales at T0 and T2 were positively correlated in both cohorts ( = 113, = 26). Beta PSD correlated with FMA-UL (T1: = 0.469, = 0.016*; T2: = 0.391, = 0.048*) and ARAT (T0: = 0.412, = 0.037*; T1: = 0.453, = 0.021*; T2: = 0.487, = 0.012*). Beta BSI negatively correlated with Brunnstrom-UL (T2: = -0.498, = 0.01*), FMA-UL (T1: = -0.441, = 0.036*; T2: = -0.507, = 0.008*), and MBI (T2: = -0.457, = 0.019*). PSD-T0 predicted FMA-Hand ( = 0.997, = 0.014*); PSD-T1 predicted ARAT ( = 1.945, = 0.014*). BSI-T1 predicted Brunnstrom-Hand ( = -401.7, = 0.049*) and FMA-UL ( = -194.4, = 0.041*), demonstrating beta EEG's prognostic value.

CONCLUSION

Resting state EEG indicators, including beta PSD and BSI, may serve as prognostic biomarkers for upper limb motor function recovery of stroke survivors, providing valuable reference for further clinical decision-making.

摘要

背景

中风后,上肢功能障碍严重影响患者的生活质量。患者预后的不确定性给治疗师制定个性化康复计划带来了挑战。康复训练期间脑电图(EEG)功率谱变化可能对上肢运动的改善具有预测作用。因此,探索与中风后上肢功能恢复相关的EEG功率谱具有重要的临床意义。

方法

本研究纳入了113例接受常规康复治疗2周的亚急性中风幸存者。在第0周(T0)和第2周(T2),评估包括Fugl-Meyer上肢评估(FMA-UL)、动作研究臂测试(ARAT)、改良Barthel指数(MBI)和美国国立卫生研究院卒中量表(NIHSS)在内的行为量表,以比较相关性并观察常规康复下行为指标与功能之间的关系。113例患者中的26例分别在第0周(T0)、第1周(T1)和第2周(T2)接受静息态EEG检测。通过EEG频谱分析计算功率谱(PSD)和BSI值。通过相关性和回归分析检验β频段PSD与临床量表之间、BSI与临床量表之间的关系。

结果

两个队列中T0和T2时的行为量表均呈正相关(n = 113,n = 26)。β频段PSD与FMA-UL(T1:r = 0.469,P = 0.016*;T2:r = 0.391,P = 0.048*)和ARAT(T0:r = 0.412,P = 0.037*;T1:r = 0.453,P = 0.021*;T2:r = 0.487,P = 0.012*)相关。β频段BSI与Brunnstrom上肢量表(T2:r = -0.498,P = 0.01*)、FMA-UL(T1:r = -0.441,P = 0.0

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ceb1/12411749/4afb447a7c45/fneur-16-1577393-g001.jpg

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