摘要
背景急性心肌梗死具有病死率高、发病急的特点,虽然临床上其治疗方式已取得较快进展,但是病死率及再入院率依旧很高。因此,明确急性心肌梗死患者经皮冠状动脉介入术(PCI)后1年内再入院的危险因素对患者预后意义重大。目的构建急性心肌梗死患者PCI后1年内再入院风险预测列线图,并评估其区分度和有效性。方法选取2018年6月至2020年6月在淮安市第二人民医院接受PCI的急性心肌梗死患者247例为研究对象。根据患者1年内是否因冠心病再次入院治疗,将其分为再入院组(42例)和未再入院组(205例)。收集患者临床资料,采用多因素Logistic回归分析探讨急性心肌梗死患者PCI后1年内再入院的影响因素,构建急性心肌梗死患者PCI后1年内再入院风险预测列线图模型,采用ROC曲线、H-L拟合优度检验、校准曲线评估该列线图模型预测急性心肌梗死患者PCI后1年内再入院风险的区分度及有效性。结果多因素Logistic回归分析结果显示,年龄〔OR=2.918,95%CI(1.848,4.607)〕、糖尿病〔OR=2.289,95%CI(1.523,3.441)〕、总胆固醇〔OR=1.760,95%CI(1.301,2.380)〕、三酰甘油〔OR=2.305,95%CI(1.645,3.229)〕是急性心肌梗死患者PCI后1年内再入院的影响因素(P<0.05)。基于多因素Logistic回归分析结果,构建急性心肌梗死患者PCI后1年内再入院风险预测列线图模型。ROC曲线分析结果显示,列线图模型预测急性心肌梗死患者PCI后1年内再入院的曲线下面积为0.843。H-L拟合优度检验结果显示,χ^(2)=5.786,P=0.357。列线图模型预测急性心肌梗死患者PCI后1年内再入院的实际曲线接近理想曲线。结论年龄、糖尿病、总胆固醇、三酰甘油是急性心肌梗死患者PCI后1年内再入院的影响因素,且基于上述影响因素构建的急性心肌梗死患者PCI后1年内再入院风险预测列线图模型具有较好的区分度和有效性,能够作为临床早期预测急性心肌梗死
Background Acute myocardial infarction has the characteristics of high fatality rate and acute onset.Although the clinical treatment has made rapid progress,the fatality rate and readmission rate are still high.Therefore,identifying the risk factors of readmission within 1 year after percutaneous coronary intervention(PCI)in patients with acute myocardial infarction is of great significance for the prognosis of patients.Objective To construct a nomogram for predicting the risk of readmission within 1 year after PCI in patients with acute myocardial infarction,and to evaluate its discrimination and validity.Methods A total of 247 patients with acute myocardial infarction who received PCI in Huai'an Second People's Hospital from June 2018 to June 2020 were selected as the research subjects.According to whether the patients were readmitted for coronary heart disease within 1 year,they were divided into readmission group(42 cases)and non readmission group(205 cases).The clinical data of patients were collected,and multivariate Logistic regression analysis was used to explore the influencing factors of readmission within 1 year after PCI in patients with acute myocardial infarction.ROC curve,H-L goodness of fit test,and calibration curve were used to evaluate the discrimination and effectiveness of the nomogram model in predicting the risk of readmission within 1 year after PCI in patients with acute myocardial infarction.Results Multivariate Logistic regression analysis showed that age[OR=2.918,95%CI(1.848,4.607)],diabetes[OR=2.289,95%CI(1.523,3.441)],total cholesterol[OR=1.760,95%CI(1.301,2.380)],triacylglycerol[OR=2.305,95%CI(1.645,3.229)]were the influencing factors of readmission within 1 year after PCI in patients with acute myocardial infarction(P<0.05).Based on the results of multivariate Logistic regression analysis,the nomogram model for predicting the risk of readmission within 1 year after PCI in patients with acute myocardial infarction was constructed.The results of ROC curve analysis showed that the are
作者
张萌
许艳
郑红艳
ZHANG Meng;XU Yan;ZHENG Hongyan(Emergency Department,Huai'an Second People's Hospital,Huai'an 223002,China)
出处
《实用心脑肺血管病杂志》
2022年第3期17-21,共5页
Practical Journal of Cardiac Cerebral Pneumal and Vascular Disease
关键词
心肌梗死
经皮冠状动脉介入治疗
病人再入院
预测
列线图模型
Myocardial infarction
Percutaneous coronary intervention
Patient readmission
Forecasting
Nomogram model
