摘要
目的探究CT平扫血肿的形态、密度分级方式联合多个危险因素对自发性脑出血(SICH)早期血肿增大的预测作用。方法纳入2015年1月至2019年12月广州医科大学附属第六医院脑血管病区收治的采用保守治疗的脑出血患者150例,全部病例在起病3 h内完成首次CT扫描。以24 h内复查CT平扫结果是否出现血肿相对体积增大33%或绝对体积增大6 ml为标准,分为血肿增大组(65例)和非血肿增大组(85例)。采用Logistics回归模型分析患者一般情况、既往服药史、实验室检查指标、Barras等学者提出的血肿CT平扫分级方式等各项指标对脑出血患者早期血肿增大的影响并建立回归模型。绘制受试者操作特征(ROC)曲线分析CT平扫血肿形态、密度分级方式联合多个危险因素的预测模型的预测效能。结果最终纳入149例(血肿增大组64例、非血肿增大组85例)的研究数据。Logistics回归分析显示:既往使用抗凝药物(OR=4.855,95%CI:1.102~21.38,P=0.037)、既往抗血小板聚集药物(OR=3.831,95%CI:1.089~13.472,P=0.036)、格拉斯哥昏迷评分(OR=0.797,95%CI:0.671~0.947,P=0.01)、高密度脂蛋白(OR=0.116,95%CI:0.025~0.534,P=0.006)、血肿CT扫描Barras血肿形态(OR=2.481,95%CI:1.429~4.308,P=0.001)和密度分级结果(OR=2.28,95%CI:1.312~3.963,P=0.003)均为早期血肿增大的独立预测因素。ROC曲线分析提示Barras血肿形态和密度分级联合多个危险因素构建的回归方程[曲线下面积(AUC)=0.907,特异度80.0%,敏感度89.1%]有更好的预测效能,单独应用Barras形态分级方式(AUC=0.746,特异度55.3%,敏感度82.8%)或密度分级方式(AUC=0.694,特异度55.3%,敏感度76.6%)或二者联合(AUC=0.799,特异度81.3%,敏感度62.4%)的预测效能均差于回归方程。结论既往使用抗凝药物、抗血小板聚集药物,格拉斯哥昏迷评分,血清高密度脂蛋白浓度,Barras等学者提出的血肿CT扫描分级评分,均为SICH患者出现早期血肿增大的独立预测�
Objective To explore the prediction effect of hematoma enlargement in the early stage of spontaneous intracerebral hemorrhage(SICH)by combining the morphology and density classification method of CT plain scan with multiple risk factors proposed by Barras et al.MethodsA total of 150 patients with cerebral hemorrhage treated conservatively from January 2015 to December 2019 in the cerebrovascular ward were retrospectively included,and all patients completed their first CT scan within 3 hours of the onset of disease,in the Sixth Affiliated Hospital of Guangzhou Medical University.According to whether the relative volume of hematoma increased by 33%or absolute volume increased by 6 ml on CT plain scan within 24 hours,the patients were divided into the increased hematoma group(65 cases)and the non-increased hematoma group(85 cases).Logistics regression was used to analyze the value of various indicators,including the general situation of patients,medication history,laboratory indicators,unenhanced CT plain scan,examination results,and other indicators,as well as the hematoma grading proposed by Barras et al,for the prediction of early hematoma enlargement in patients with spontaneous intracerebral hemorrhage.By drawing receiver operating characteristic(ROC)curve,the prediction efficiency of CT plain scan hematoma morphology and density classification combined with multiple risk factors was analyzed.ResultsTotally,149 cases were included(64 in the hematoma enlargement group and 85 in the non-hematoma enlargement group).Logistic regression analysis showed that previous use of anticoagulants(OR=4.855,95%CI:1.102-21.38,P=0.037),previous anti-platelet aggregation(OR=3.831,95%CI:1.089-13.472,P=0.036),Glasgow coma scale(OR=0.797,95%CI:0.671-0.947,P=0.01),high-density lipoprotein(OR0.116,95%CI:0.025-0.534,P=0.006),non-enhanced CT scan results of hematoma showed high-grade Barras hematoma morphology(OR=2.481,95%CI:1.429-4.308,P=0.001),and density grading results(OR=2.28,95%CI:1.312-3.963,P=0.003)were independent risk factors
作者
庄坚炜
陈向林
侯文仲
胡杨真
毛振敏
黄俊士
Zhuang Jianwei;Chen Xianglin;Hou Wenzhong;Hu Yangzhen;Mao Zhenmin;Huang Junshi(Department of Cerebrovascular Disease of the Sixth Affiliated Hospital of Guangzhou Medical University,Guangzhou 511518,China)
出处
《中华脑血管病杂志（电子版）》
2022年第2期92-99,共8页
Chinese Journal of Cerebrovascular Diseases(Electronic Edition)
基金
2022广东省医学科研基金(A2022224)
关键词
自发性脑出血
血肿增大
X线计算机体层扫描
Spontaneous cerebral hemorrhage
Hematoma enlargement
X-ray computed tomograph
