中国卒中杂志 ›› 2020, Vol. 15 ›› Issue (08): 869-875.DOI: 10.3969/j.issn.1673-5765.2020.08.009

• 论著 • 上一篇    下一篇

急性大面积脑梗死脑电图δ/α功率比值与中线结构移位的相关性研究

张哲,刘大成,刘婧伊,田佳,濮月华,刘丽萍   

  1. 1100070 北京首都医科大学附属北京天坛医院神经病学中心神经重症医学科
    2河北医科大学第二医院神经内科
  • 收稿日期:2019-12-18 出版日期:2020-08-20 发布日期:2020-08-20
  • 通讯作者: 刘丽萍 lipingsister@gmail.com
  • 基金资助:

    “十三五”国家重点研发计划(2016YFC13077301-DR)

Association of δ/α Ratio of Different Brain Regions with Midline Shift in Patients with Acute Large HemisphericInfarction

  • Received:2019-12-18 Online:2020-08-20 Published:2020-08-20

摘要:

目的 评估急性大面积脑梗死患者定量脑电图(quantitative electroencephalography,qEEG)参数和脑 中线结构移位之间的相关性,探索反映脑中线结构移位最敏感的qEEG变化区域。 方法 纳入2017年9月-2019年5月于首都医科大学附属北京天坛医院神经重症医学科住院治疗,脑 梗死体积>患侧大脑中动脉流域的2/3,发病7 d内完成脑电图监测的脑梗死患者。使用快速傅里 叶变换分别计算梗死侧和健侧的前、中、后区域以及半球脑电图的δ/α功率比值(delta/alpha power ratio,DAR),并记录同期GCS评分、NIHSS评分。在脑电图监测前后4 h内完成头颅CT或MRI,测量透明 隔水平的大脑中线结构移位。统计不同区域的DAR与中线结构移位的相关性。根据中线结构移位 ≥5 mm和<5 mm,≥10 mm和<10 mm分组,比较组间不同部位DAR的差异。绘制ROC曲线,确定提示中 线结构移位≥5 mm和≥10 mm的DAR界值及其敏感性和特异性,并与NIHSS评分、GCS评分对中线结构 移位预测价值比较。 结果 共29例患者、38段脑电图记录纳入分析。健侧后头部DAR与中线结构移位正相关(ρ=0.5264, P =0.0007)。中线结构移位≥5 mm组相比<5 mm组、≥10 mm组相比<10 mm组,健侧后头部DAR均显 著升高(分别为6.48±5.70 vs 2.09±1.47,P =0.0043;10.59±6.60 vs 3.29±3.30,P =0.0008)。分别 以DAR≥2.326和≥2.569为界值,可以提示中线结构移位≥5 mm和≥10 mm(敏感度分别为72.73%和 100.00%,特异度分别为81.25%和64.52%),均优于NIHSS评分和GCS评分。 结论 健侧后头部DAR增加与大面积脑梗死中线结构移位呈正相关。qEEG可作为监测大面积脑梗 死中线结构移位的方法。

文章导读: 通过对急性大面积脑梗死患者EEG的回顾性分析发现健侧后头部qEEG指标DAR可以反映患者中线结构移位,该指标优于NIHSS评分和GCS评分。

关键词: 定量脑电图; 大面积脑梗死; 中线结构移位; δ 功率比值

Abstract:

Objective To determine the association between quantitative electroencephalography (qEEG) parameters and midline shift in patients with malignant middle cerebral artery (MCA) infarction. Methods This retrospective analysis enrolled the patients with unilateral ischemic changes that affected two-thirds or more of MCA territory and who underwent EEG monitoring within seven days after stroke onset from Neurocritical Care Unit of Beijing Tiantan Hospital between 2017 September and 2019 May. The δ/α ratios (delta/alpha power ratio, DAR) of anterior, middle and posterior hemispheric regions of infarct side and non-infarct side were calculated using fast Fourier transformation. The baseline GCS and NIHSS score and other clinical data were collected. The brain midline structure shift was measured based on CT or MRI that was performed within four hours before and/or after the EEG monitoring. The association between the DAR and midline shift was analyzed. The data were also stratified into midline shift ≥5 mm and <5 mm, ≥10 mm and <10 mm, to compare the DARs of different regions. The cut-off point of DAR of specified regions for midline shift ≥5 mm or ≥10 mm were identified using ROC curve analysis. Results A total of 38 EEG records from 29 patients were analyzed. The DAR of posterior hemisphere of non-infarct side was significantly associated with midline shift (ρ =0.5264, P =0.0007). The DAR of posterior hemisphere of non-infarct side was higher in the group of midline shift <5 mm compared to the group of ≥5 mm (6.48±5.70 vs 2.09±1.47, P =0.0043), and so was in the midline shift of 10 mm stratification groups (10.59±6.60 vs 3.29±3.30, P =0.0008). In posterior hemisphere of non-infarct side, DAR ≥2.326 and ≥2.569 could suggest the midline shift ≥5 mm and ≥10 mm, with a sensitivity of 72.73% and 100.00%, a specificity of 81.25% and 64.52%, respectively. Conclusions An increase in DAR of posterior hemisphere of non-infarct side was positively correlated with midline shift caused by malignant MCA infarction. DAR could serve as a better marker for monitoring the midline shift.

Key words: Quantitative electroencephalography; Large hemispheric infarction; Midline shift;δ/α power ratio