NSTEMI患者PCI术后再入院风险预测模型的建立及验证  

Establishment and validation of a readmission risk prediction model for patients with non-ST elevation myocardial infarction after primary percutaneous coronary intervention

作　　者：刘延旭 罗豪 文聪 崔扬扬 杜林芹 周阳 Ofe Eugene Kwaku 岳荣川[1] LIU Yan-xu;LUO Hao;WEN Cong;CUI Yang-yang;DU Lin-qin;ZHOU Yang;Ofe Eugene Kwaku;YUE Rong-chuan(Department of Cardiovascular Medicine,Affiliated Hospital of North Sichuan Medical College,Nanchong 637000,Sichuan,China)

机构地区：[1]川北医学院附属医院心血管内科,四川南充637000

出　　处：《川北医学院学报》2024年第5期598-602,共5页Journal of North Sichuan Medical College

基　　金：中央引导地方科技发展项目(2022ZYD0056);国家自然科学基金青年项目(81600232);四川省科技厅面上项目(2021YJ0210);南充市科技计划项目(23JCYJPT0059);川北医学院科研创新团队培育项目(CBY23-TD01)。

摘　　要：目的:探讨急性非ST段抬高型心肌梗死(NSTEMI)患者行直接PCI术后再入院的影响因素,并建立预测模型。方法:选取166例NSTEMI患者为研究对象,依据患者PCI术后1年内是否因心梗及心肌梗死并发症再入院分为再入院组(n=110)和未再入院组(n=56)。分析NSTEMI患者行直接PCI术后再入院的独立影响因素,并构建其风险预测模型列线图,绘制受试者工作特征(ROC)曲线来评估模型区分度,采用Hosmer-Lemeshow对模型进行拟合优度检验,绘制校准曲线评估模型准确度。结果:心率、有无肺炎病史、病变血管数、甘油三酯、B型利钠肽为NSTEMI患者经直接PCI术后再入院的独立预测因素(P<0.05)。构建预测模型列线图,ROC曲线显示,曲线下面积(AUC)为0.773,敏感度为70.9%,特异度为76.8%,Hosmer-Lemeshow拟合优度检验显示,差异无统计学意义(χ^(2)=8.329,P=0.351)。通过模型校准曲线提示列线图模型的实际曲线接近理想曲线。结论:心率、有无肺炎病史、病变血管数、甘油三酯、B型利钠肽为NSTEMI患者直接PCI术后再入院的独立预测因素,以此建立的预测模型列线图可直观、快捷的对该类患者再入院的风险进行评估。Objective:To investigate the factors influencing readmission after primary percutaneous coronary intervention(PCI)in patients with acute non-ST-segment elevation myocardial infarction(NSTEMI)and establish a predictive model.Methods:166 patients with NSTEMI were selected and divided into two groups according to whether the patients were readmitted to the hospital due to myocardial infarction and its complications within 1 year after PCI surgery:the readmission group(n=110)and the non-readmission group(n=56).The independent risk factors of readmission after primary PCI in patients with NSTEMI were analyzed.Construct a risk prediction model column chart,and draw receiver operating characteristic(ROC)curves to evaluate model discrimination.The Hosmer-Lemeshow was used to test the goodness of fit of the model,and a calibration curve was drawn to evaluate the accuracy of the model.Results:The heart rate,history of pneumonia,number of diseased vessels,triglyceride levels,and B-type natriuretic peptide levels were independent predictors of readmission after primary PCI in patients with NSTEMI(P<0.05).To construct a nomogram for the predictive model,we analyzed the ROC curve results.The area under the curve(AUC)was 0.773.The sensitivity was 70.9%,and the specificity was 76.8%.The Hosmer-Lemeshow goodness-of-fit test showed that the difference was not statistically significant(χ^(2)=8.329,P=0.351),and the model calibration curve analysis showed that the nomogram model predicted the actual readmission curve for patients with NSTEMI within 1 year after PCI,which was close to the ideal curve.Conclusion:The heart rate,history of pneumonia,number of diseased vessels,triglyceride levels,and B-type natriuretic peptide levels are found to be independent predictors of readmission after primary PCI in patients with NSTEMI,and this model can be used to directly and quickly evaluate the risk of readmission.

关 键 词：非ST抬高型心肌梗死 PCI 再入院 预测模型 

分 类 号：R542.22[医药卫生—心血管疾病]