Prediction of malignant course in large middle cerebral artery infarction by electroencephalography
10.3760/cma.j.issn.1673-4165.2010.04.003
- VernacularTitle:脑电图预测大面积大脑中动脉供血区梗死的恶性过程
- Author:
Yafang REN
;
Yongming WU
;
Zhong JI
;
Yan YU
;
Jingxin WANG
;
Suyue PAN
- Publication Type:Journal Article
- Keywords:
Brain infarction;
Infarction,middle cerebral artery;
Electroencephalography;
Disease progression
- From:
International Journal of Cerebrovascular Diseases
2010;18(4):249-253
- CountryChina
- Language:Chinese
-
Abstract:
Objective To explore the predictive value of early electroenphalography (EEG) for a malignant course in patients with large middle cerebral artery infarction (LMCAI).Methods Thirty-seven patients (20 patients with a malignant and 17 with a benign course) with stroke of >50% of the middle cerebral artery territory in early CT/MRI scan were included;Glasgow-Pittsberg Coma Scale (24 ±1 vs. 30 ±4, P =0. 003) and National Institutes of Health Stroke Scale (23 ±3 vs. 16 ±4, P =0.000) in the group with a malign course were higher than those in the group with a benign course. Early EEG was recorded within 24 h after ischemic stroke. The correlation between the change characteristics of EEG and a malignant course in patients with LMCAI was analyzed. Results The contralateral occipital background frequencies < 8 Hz (17/20 vs. 3/20, P =0.000), β frequency within the focus ≤20 Hz (19/26 vs. 7/26, P= 0-001), EEG non-reaction to stimuli (11/12 vs. 1/12, P= 0.002),slowing affecting the whole hemisphere in the lesion (17/24 vs. 7/24, P = 0. 008) and focal slowing contralateral to the lesion (16/19 vs. 3/19, P =0. 000) were significantly related with a malignant course. Whereas the contralateral occipital background frequencies ≥8 Hz (14/17 vs. 3/17, P =0. 000),β frequency >20 Hz within the focus (10/11 vs. 1/11, P =0. 001) were related with a benign course. Conclusions Early EEG has a certain predictive value for a malignant course in patients with LMCAI, and it may be used as one of the bedside monitoring approaches of LMCAI.
