重症吉兰-巴雷综合征电生理特征以及预后不良相关因素分析

Analysis of the electrophysiological characteristics and adverse prognosis of severe Gilanbare syndrome

目的分析重症吉兰-巴雷综合征(GBS)患者的电生理特征和引起患者预后不良的相关因素,并评价神经电生理对预后不良的预测价值。方法选取2020年3月-2022年5月收治于我院的78例GBS患者的临床资料,根据病情严重程度分为轻症组(n=52)和重症组(n=26),另根据预后情况分为良好组(n=45)和不良组(n=33);分别对比不同组别的临床资料,比较不同病情程度患者神经电生理特征,对引起预后不良的相关因素进行多因素分析,构建列线图预测模型并进行验证;通过对患者病变特征(ROC)曲线分析电生理特征对预后不良的预测价值。结果比较病情严重程度不同的两组患者的临床资料发现,重症组患者面瘫、胸闷、腹泻、机械通气、自主神经功能障碍、合并其他自身免疫性疾病的发生率显著高于轻症组患者(P<0.05);通过比较两组患者电生理特征发现,重症组的腓总神经传导速率和胫神经运动传导速率显著低于轻症组,而F波异常率和远端复合肌肉动作电位波幅(dCMAP)波幅异常率则显著高于轻症组(P<0.05);单因素以及多因素结果说明,入院前病程>2周、脑脊液蛋白升高、入院时医学研究委员会肌力评分(MRC-Score)≤30、机械通气、合并其他自身免疫性疾病、腓总神经传导速率减慢、胫神经运动传导速率减慢、F波异常率增加、dCMAP波幅异常率增加以及轴索型损伤均为影响预后不良的危险因素(OR值均大于1,P<0.05);列线图预测模型总分613分,对应预后不良概率为74.56%,具有良好的区分度、准确度和有效性;ROC曲线获得腓总神经传导速率、胫神经运动传导速率、F波异常率、dCMAP波幅异常率四者联合预测的ROC曲线下面积、阳/阴性预测值、灵敏度、特异度均明显高于单独预测,具有更优的预测效能。结论分析重症GBS患者的电生理特征有利于对患者病情严重程度进行更清楚的了解,对预后不良具有十分重要的预测价值,值得在临床上推广应用。

Objective To analyze the electrophysiological characteristics of patients with severe Guillain-Barrésyndrome and the related factors causing poor prognosis,and evaluate the value of neuroelectrophysiology in predicting poor prognosis.Methods The clinical data of 78 GBS patients admitted to our hospital from March 2020 to May 2022 were selected,divided into mild(n=52)and severe(n=26)according to the severity of the disease,and the good group(n=45)and bad group(n=33)according to the prognosis;Compare the clinical data of different groups,compare the neuroelectrophysiological characteristics of patients in different disease groups,analyze the relevant factors causing poor prognosis,build a line chart prediction model and verify it;analyze the value of electrophysiological characteristics for poor prognosis through the subject's working characteristics(ROC)curve.Results A comparison of the clinical data of two groups of patients with different severity found that the incidence of facial paralysis,chest tightness,diarrhea,mechanical ventilation,autonomic nervous dysfunction and other autoimmune diseases in the severe group was significantly higher than that of patients in the mild group(P<0.05).By comparing the electrophysiological characteristics of the two groups,it was found that the total peroneal nerve conduction rate and tibia motor conduction rate of the severe severe group were significantly lower than that of the mild group,while the F-wave abnormality rate and dCMAP wave amplitude abnormality rate were significantly higher than that of the mild group(P<0.05);single-factor and multi-factor results showed that the pre-hospital course of hospitalization was>2 weeks,elevated cerebrospinal fluid protein,and MRC score≤30 at hospital,mechanical ventilation,combined with other autoimmune diseases,slowing of the total peroneal nerve conduction rate,slowing down the tibial motion conduction rate,increased F-wave abnormality rate,increased amplitude abnormality of dCMAP and axial cord injury are all risk factors affecting poor prognosis(OR values are greater than 1,P<0.05);the total score of the line chart prediction model is 613 points,and the corresponding adverse prognosis probability is 74.56%,which has good distinction,accuracy and effectiveness;the ROC curve obtains the total peroneal nerve conduction rate,tibial nerve motion conduction rate,F-wave abnormality,dCMAP wave amplitude abnormality four the area,positive/negative prediction value,sensitivity and specificity under the ROC curve of the joint prediction are significantly higher than that of individual predictions,with better prediction performance.Conclusion Analyzing the electrophysiological characteristics of severe GBS patients is conducive to a clearer understanding of the severity of patients'condition.It has a very important predictive value for poor prognosis,and is worth popularizing and applying in clinic.