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期刊目录

2022 年3 期 第30 卷

专题研究 查看全文 PDF下载

急性心肌梗死患者经皮冠状动脉介入术后1年内再入院风险预测列线图模型构建与评估

Construction and Evaluation of Nomogram Model for Predicting Readmission Risk within One Year after PercutaneousCoronary Intervention in Patients with Acute Myocardial Infarction

作者:张萌,许艳,郑红艳

单位:
223002江苏省淮安市第二人民医院急诊科 通信作者:张萌,E-mail:2522429096@qq.com
单位(英文):
Emergency Department, Huai’an Second People’s Hospital, Huai’an 223002, China Corresponding author: ZHANG Meng, E-mail: 2522429096@qq.com
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;
关键词(英文):
Myocardial infarction; Percutaneous coronary intervention; Patient readmission; Forecasting;Nomogram model
中图分类号:
DOI:
10.12114/j.issn.1008-5971.2022.00.058
基金项目:

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,χ2=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患者PCI后1年内再入院风险的有效工具。

英文摘要:

【Abstract】 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, identifyingthe risk factors of readmission within 1 year after percutaneous coronary intervention (PCI) in patients with acute myocardialinfarction is of great significance for the prognosis of patients. Objective To construct a nomogram for predicting the risk ofreadmission within 1 year after PCI in patients with acute myocardial infarction, and to evaluate its discrimination and validity.MethodsA total of 247 patients with acute myocardial infarction who received PCI in Huai'an Second People's Hospital fromJune 2018 to June 2020 were selected as the research subjects. According to whether the patients were readmitted for coronaryheart disease within 1 year, they were divided into readmission group (42 cases) and non readmission group (205 cases) . Theclinical data of patients were collected, and multivariate Logistic regression analysis was used to explore the influencing factorsof readmission within 1 year after PCI in patients with acute myocardial infarction. ROC curve, H-L goodness of fit test, andcalibration curve were used to evaluate the discrimination and effectiveness of the nomogram model in predicting the risk ofreadmission within 1 year after PCI in patients with acute myocardial infarction. Results Multivariate Logistic regressionanalysis 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 ofreadmission within 1 year after PCI in patients with acute myocardial infarction (P < 0.05) . Based on the results of multivariateLogistic regression analysis, the nomogram model for predicting the risk of readmission within 1 year after PCI in patients withacute myocardial infarction was constructed. The results of ROC curve analysis showed that the area under curve of the nomogrammodel for predicting readmission within 1 year after PCI in patients with acute myocardial infarction was 0.843. The results of H-Lgoodness of fit test showed thatχ2 =5.786, P=0.357. The actual curve of the nomogram model for predicting the risk of readmissionwithin 1 year after PCI in patients with acute myocardial infarction is close to the ideal curve. Conclusion Age, diabetes, totalcholesterol and triglyceride are the influencing factors of readmission within 1 year after PCI in patients with acute myocardialinfarction, and the nomogram model for predicting the risk of readmission within 1 year after PCI in patients with acute myocardialinfarction constructed based on the above influencing factors has good discrimination and validity, and can be used as an effectivetool for early clinical prediction of the risk of readmission within 1 year after PCI in patients with acute myocardial infarction.

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