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弥漫性脑胶质瘤患者脑电图表现特征及其影响因素

Characteristics and Influencing Factors of EEG in Patients with Diffuse Gliomatosis Cerebri
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摘要 目的:探讨弥漫性脑胶质瘤(GC)患者脑电图(EEG)表现特征及其影响因素。方法:选取2017年8月-2021年3月惠州市第三人民医院收治的65例弥漫性GC患者,均进行脑电图检查,记录患者脑电图特征异常情况,EEG检查轻度异常24例,中度异常24例,重度异常17例,将患者纳入正常组(24例)与异常组(41例);分析弥漫性GC患者脑电图异常的影响因素。结果:两组性别、年龄及体质量指数(BMI)对比,差异无统计学意义(P>0.05);正常组弥漫性GC临床分型明显优于异常组患者,差异有统计学意义(P<0.05);Logistic回归分析结果显示,临床分型是导致弥漫性GC患者脑电图特征异常的影响因素(OR>1,P<0.05)。结论:弥漫性GC患者脑电图特征表现异常可能与其临床分型有关,临床可考虑通过其临床分型以预测脑电图表现特征,对于临床工作具有积极意义。 Objective:To investigate the characteristics and influencing factors of electroencephalogram (EEG) in patients with diffuse gliomatosis cerebri (GC).Method:Sixty-five patients with diffuse GC admitted to Huizhou Third People’s Hospital from August 2017 to March 2021 were selected for EEG examination,and abnormal EEG characteristics of the patients were recorded,24 cases with mild,24 cases with moderate and 17 cases with severe abnormal EEG,and they were included in normal group (24 cases) and abnormal group (41 cases).Analyzed the influencing factors of abnormal EEG in patients with diffuse GC.Result:There were no significant differences in gender,age and body mass index (BMI) between the two groups (P>0.05).The clinical classification of diffuse GC in normal group was significantly better than that in abnormal group,and the difference was statistically significant (P<0.05).Logistic regression analysis showed that clinical classification was an influential factor leading to abnormal EEG characteristics in patients with diffuse GC (OR>1,P<0.05).Conclusion:Abnormal EEG characteristics in patients with diffuse GC may be related to their clinical classification,which can be considered to predict EEG characteristics by clinical classification,which has positive significance for clinical work.
作者 黄丽霞 赵芸 HUANG Lixia;ZHAO Yun(Huizhou Third People’s Hospital,Huizhou 516002,China;不详)
出处 《中外医学研究》 2022年第4期67-69,共3页 CHINESE AND FOREIGN MEDICAL RESEARCH
关键词 弥漫性脑胶质瘤 脑电图表现特征 临床分型 影响因素 Diffuse gliomatosis cerebris EEG characteristics Clinical classification Influence factor
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