VEEG在重症脑损伤患儿早期预后判断中的价值

发布时间：2018-06-22 06:45

本文选题：重症脑损伤 + 脑电监测　；参考：《复旦大学》2012年硕士论文

【摘要】：目的对重症脑损伤患儿VEEG脑电监测特征和入院时GCS评分与近期预后进行分析,探讨重症脑损伤患儿VEEG脑电活动特征与预后的相关性,及利用Young's脑电分级在重症脑损伤患儿预后判断中的价值。方法选取儿童重症监护室(PICU)中重症脑损伤患儿,在入住PICU时进行GCS评分,并在入院期间患儿出现意识障碍发生后72h内进行长程视频脑电监测；针对刺激后脑电背景活动变化、生理睡眠结构的存在、是否有癫痫波发放、是否存在运动性发作、是否有癫痫持续状态发生,是否存在爆发-抑制波形、脑电活动是否表现为电压低平及Young's脑电分级等脑电特征分类记录；以患儿出院时情况为近期预后终点,运用小儿大脑与总体表现分类评分(PCOPCS)作为近期预后评定标准分为：预后良好组(PCOPCS:1-2分)、预后不良(PCOPCS:3-4分)、严重预后不良组(PCOPCS:5-6分)；并与其GCS评分和各项脑电特征进行单因素分析(χ2检验)及多因素分析(logistic逐步回归),分析影响预后的危险因素。结果共计纳入病例103例,其中男性74例,女性29例,平均年龄：3.28±3.46岁(0.12～14岁),其中预后良好组n=36,预后不良组n=30,严重预后不良组n=37,将近期预后分组与各项脑电特征进行单因素分析得：入院时GCS、刺激后脑电背景活动变化、生理睡眠结构的消失、电活动表现为电压低平及Young's脑电分级在预后分组中具有统计学差异(P0.01)。与是否有癫痫波发放、是否存在癫痫性运动性发作、是否存在爆发-抑制波形与预后分组无明显统计学差异(P0.05)。 Logistic逐步回归分析得出：与预后相关的因素有：Young's分级(OR=1.66,95%CI1.2769-2.1623; p0.0005)与GCS评分(PR=0.809,95%CI0.7141-0.9169; p=0.001)。结论应用长程VEEG可作为重症脑损伤患儿判断预后方法,对刺激后无脑电背景活动变化(-)、生理睡眠结构的消失、电活动表现为电压低平及Young's脑电分级越高为提示预后不良的危险因素,GCS评分及Young's脑电分级在对早期预后评估具有重要价值。Young's分级标准在儿童脑损伤昏迷患儿的应用仍有需要调整或修改之必要。
[Abstract]:Objective to investigate the correlation between VEEG EEG activity and prognosis in children with severe brain injury by analyzing the characteristics of VEEG EEG monitoring, GCS score on admission and short-term prognosis. To evaluate the prognosis of children with severe brain injury by using YoungsEEG grade. Methods Children with severe brain injury in the Children's intensive Care Unit (PICU) were selected for GCS score when they were admitted to PICU, and long-term video EEG monitoring was carried out within 72 hours after the onset of disturbance of consciousness during admission. The presence of physiological sleep structures, whether there are epileptic waves, whether there are motor seizures, whether epileptic status occurs, whether there are explosion-suppression waveforms, Whether the EEG activity is classified as low voltage level and YoungsEEG grade, and taking the discharge of the child as the short-term prognosis end point, According to PCOPCS, children were divided into good prognosis group (PCOPCS: 1-2), poor prognosis (PCOPCS: 3-4) and severe poor prognosis (PCOPCS: 5-6). Univariate analysis (蠂 2 test) and multivariate analysis (logistic stepwise regression) were performed with GCS scores and EEG features to analyze the prognostic risk factors. Results A total of 103 cases were included, including 74 males and 29 females. The average age was 3. 28 卤3. 46 (0. 1214 years old). Among them, good prognosis group nong36, poor prognosis group nong30, severe poor prognosis group nong37. By univariate analysis of the short-term prognosis group and various EEG features, the changes of EEG background activity after GCSs stimulation were obtained. The disappearance of physiological sleep structure and electrical activity showed that there were statistical differences in the prognosis group between the low voltage level and YoungsEEG grade (P0.01). There was no significant difference between Epilepsy wave release, epileptic motor seizure, EPS and prognosis (P0.05). Logistic stepwise regression analysis showed that the prognostic factors were: 1: Youngsclassification (OR 1.2769-2.1623; p0.0005) and GCS score (PRT 0.809 ~ 95CI0.7141-0.9169; pP0.001). Conclusion Long-range VEEG can be used as a prognostic method in children with severe brain injury. The low voltage level and the higher the grade of YoungsEEG are the risk factors of poor prognosis. GCS score and YoungsEEG grade have important value in early prognostic evaluation. Youngsof grade standard should be used in children with brain injury coma. Use is still necessary to be adjusted or modified.
【学位授予单位】：复旦大学
【学位级别】：硕士
【学位授予年份】：2012
【分类号】：R726.5

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