文章摘要
脑梗死静脉溶栓后出血转化的危险因素分析及预测模型建立
Risk factor analysis and establishment of predictive model of hemorrhage transformation after intravenous thrombolysis in cerebral infarction
投稿时间:2021-02-06  
DOI:10.3969/j.issn.1000-0399.2021.09.008
中文关键词: 静脉溶栓  出血转化  危险因素  预测模型
英文关键词: Thrombolysis  Hemorrhagic transformation  Risk factors  Predictive model
基金项目:
作者单位E-mail
卞静 241001 安徽芜湖 皖南医学院弋矶山医院神经内科  
黄婷婷 241001 安徽芜湖 皖南医学院弋矶山医院神经内科  
李自保 241001 安徽芜湖 皖南医学院弋矶山医院神经内科  
徐阳 241001 安徽芜湖 皖南医学院弋矶山医院神经内科  
赵守财 241001 安徽芜湖 皖南医学院弋矶山医院神经内科  
储照虎 241001 安徽芜湖 皖南医学院弋矶山医院神经内科 chuzhaohu878@163.com 
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中文摘要:
      目的 观察脑梗死患者静脉溶栓后出血转化的危险因素并建立风险预测模型。方法 回顾性分析2018年1月至2020年11月入住皖南医学院弋矶山医院行静脉溶栓的179例急性脑梗死患者,根据是否发生溶栓后出血转化,分为出血转化组(n=33)与非出血转化组(n=146)。对可能影响出血转化的因素行二分类logistic回归分析,建立静脉溶栓后出血转化的风险预测模型,并对模型的区分度和拟合度进行验证。结果 多因素分析结果显示,心房颤动(OR=2.800,P=0.036)、基线美国国立卫生研究院卒中量表(NIHSS)(OR=1.206,P<0.001)、中重度脑白质疏松(OR=2.897,P=0.034)是溶栓后出血转化的独立危险因素,建立的风险预测模型为Logit(P)=-7.789+1.030×心房颤动+0.187×基线NIHSS+1.064×中重度脑白质疏松症,其区分度(受试者工作特征曲线下面积为0.861,95% CI:0.781~0.941)和拟合度(χ2=9.641,P=0.291)较好。结论 伴有神经功能缺损严重、心房颤动、中重度脑白质疏松的急性脑梗死患者更容易发生溶栓后出血转化,值得临床工作者重视。
英文摘要:
      Objective To investigate the risk factors and establish a risk predictive model for the hemorrhagic transformation following intravenous thrombolysis in acute cerebral infarction. Methods The clinical data of patients with ischemic stroke thrombolysis who admitted to Yijishan Hospital of Wannan Medical College from January 2018 to November 2020 were reviewed and analyzed retrospectively. According to the presence of hemorrhagic transformation, they were divided into hemorrhagic transformation group(n=33) and non-hemorrhagic transformation group(n=146).The factors associated with the hemorrhagic transformation were analyzed by logistic regression analysis. The risk predictive model of hemorrhage transformation was established and then the discrimination and calibration of the model were verified. Results The logistic analysis showed that atrial fibrillation(OR=2.800,P=0.036),baseline NIHSS score(OR=1.206,P<0.001), moderate to severe leukoaraiosis(OR=2.897,P=0.034) were independent risk factors for hemorrhage transformation after thrombolysis. The established risk prediction model is Logit(P)=-7.789+1.030×atrial fibrillation+0.187×baseline NIHSS score +1.064×moderate to severe leukoaraiosis, and its discrimination (under the receiver operating characteristic curve area)=0.861,95%CI:0.781~0.941) and goodness of fit(χ2=9.641, P=0.291). Conclusions The patients with severe neurological deficit, atrial fibrillation, moderate to severe leukoaraiosis are prone to hemorrhagic transformation after thrombolysis, which should be carefully taken into account.
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