基于Logistic回归模型的急性Stanford A型主动脉夹层和非ST段抬高型心肌梗死鉴别研究

目的 通过分析Stanford A型主动脉夹层(stanford type A aortic dissection,TAAD)和非ST段抬高型心肌梗死(Non-ST-segment elevation myocardial infarction,NSTEMI)患者的临床资料,寻找两者间快速、有效、廉价的鉴别诊断方法.方...

Differential study of acute Stanford Type A aortic dissection and non-ST segment elevation myocardial infarction based on Logistic regression model

Objective In this study,clinical data of patients undergoing Stanford type A aortic dissection(TAAD)and non-ST elevation myocardial infarction(NSTEMI)were analyzed in order to find a rapid,effective,and cost-effective differential diagnosis between them.Methods Retrospective analysis was performed on 104 patients with TAAD and 107 patients with NSTEMI who visited the First Affiliated Hospital of Zhengzhou University from January 2013 to September 2018.Univariate and multivariate Logistic regression analysis was used to screen the risk factors related to their differentiation and establish Logistic regression model based on regression coefficient.Results Logistic regression analysis showed that age,history of hypertension,and plasma D-dimer levels were risk factors for the differentiation of Stanford type A aortic dissection from non-ST-elevation myocardial infarction.The area under ROC curve of the Logistic regression model was 0.982(95%CI:0.962~0.994),indicating that the Logistic regression model had good identification ability.The decision curve analysis of the Logistic regression equation shows that when the threshold probability of the Logistic regression equation is 60%~90%,the net benefit of the equation is 70%~85%.Conclusion Age,history of hypertension,and D-dimer combination provide a rapid,effective,and inexpensive differential diagnosis between TAAD and NSTEMI.The differential diagnosis model constructed in this study improved the ability to identify TAAD and NSTEMI in the early stage of admission.