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吴东宇,孙智千,柯 莎,袁 英,李广庆.脑电非线性分析用于意识障碍苏醒预测[J].中国康复医学杂志,2009,24(11):969~972
脑电非线性分析用于意识障碍苏醒预测    点此下载全文
吴东宇  孙智千  柯 莎  袁 英  李广庆
首都医科大学宣武医院康复医学科,北京,100053
基金项目:国家自然科学基金资助课题(30600186)
DOI:
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摘要:
      目的:利用脑电非线性分析方法评价意识障碍程度,研究其在意识障碍苏醒预测中的作用。 方法:本研究包括37例严重颅脑外伤或脑卒中的意识障碍患者,其中持续植物状态(PVS)21例,最小意识状态(MCS)16例,均经临床及神经电生理方法评估。依次采集所有患者安静闭眼、声音刺激和疼痛刺激三种状态下的脑电信号,并计算脑电信号的复杂度、近似熵和互近似熵非线性指数。入院后6个月用格拉斯哥结局量表(GOS)评定患者预后。 结果:三种状态下,PVS组非线性指数均低于MCS组。3例PVS和7例MCS患者入院6月后GOS达到3分。苏醒患者和未苏醒患者脑干听觉诱发电位、体感诱发电位和常规脑电图无明显差异。在疼痛刺激状态下,苏醒患者脑电非线性指数明显高于未苏醒患者。结论:脑电非线性分析能够定量评估PVS和MCS患者大脑皮质受抑制的程度。脑电非线性指数可能在PVS和MCS苏醒预测中存在价值,对疼痛刺激有良好反应可能意味着预后良好。
关键词:脑电描记术  非线性动力学  意识障碍  苏醒
Predicting awakening of unconscious patients with EEG nonlinear analysis    Download Fulltext
Xuanwu Hospital of Capital Medical University, Beijing, 100053
Fund Project:
Abstract:
      Objective: To quantify the severity of unconsciousness and investigate the effect in predicting prognosis of awakening unconscious patients with EEG nonlinear analysis. Method: Thirty-seven unconscious patients with severe brain trauma or stroke were involved in the study, including twenty-one patients in persistent vegetative state(PVS), sixteen in minimally conscious state(MCS). All of them were diagnosed as unconsciousness by clinical and electrophysiological assessment. EEG was recorded under 3 conditions: eyes closed, auditory stimulation and pain stimulation. EEG nonlinear indices such as Lempel-Ziv complexity(Cx), approximate entropy(ApEn) and cross-approximate entropy(cross-ApEn) were calculated for all subjects. Glasgow outcome scale(GOS) was used to assess the prognosis of the subjects during 6 months after admission. Result: EEG nonlinear indexes of PVS group were significantly lower than that of MCS group for all 3 conditions. Three cases of PVS group and seven cases of MCS group awoke and their GOS scores rose to 3 during 6 months after admission. There was no statistically significant difference between awaked and non-awaked patients in assessments of brainstem auditory evoked potential, somatosensory evoked potential and routine EEG. Under pain stimulation condition, nonlinear indices of awaked patients increased more significantly than that of non-awaked patients. Conclusion: With EEG nonlinear analysis, the severity of cerebral cortex suppression in PVS and MCS could be quantitatively measured. EEG nonlinear indices might have effect in predicting prognosis of awakening of PVS and MCS patients and for unconscious patients the better response to pain stimulation might mean the better prognosis.
Keywords:electroencephalography  nonlinear dynamics  unconsciousness  awake
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