急性冠脉综合征患者PCI术后1年发生不良心血管事件风险预测模型的构建及评价

Establishment and Evaluation of Risk Prediction Model of Major Adverse Cardiac Events in Patients with Acute Coronary Syndrome One Year after Percutaneous Coronary Intervention

目的探讨急性冠脉综合征患者PCI术后1年发生不良心血管事件的独立危险因素,并构建风险预测模型。方法回顾性收集潍坊市某三级甲等医院心内科诊断为急性冠脉综合征PCI术后1年随访的271例患者,按照随访时间的先后顺序将模型组和验证组按照7∶3的比例分组,模型组190例,验证组81例,模型组依据随访结局分为发生不良心血管事件组(61例)与未发生不良心血管事件组(129例),比较2组危险因素并建立风险预测模型,应用ROC曲线下面积检验模型预测效果,并选取81例验证组患者对模型的预测效果进行验证。结果经单因素及多因素分析发现左主干病变、高血压、吸烟史、支架植入个数、低密度脂蛋白、中性粒细胞和血红蛋白是发生不良心血管事件的独立危险因素。预测模型为P=ex/(1+e^x),X=-7.476+2.352×左主干病变的赋值+2.061×高血压的赋值+1.479×吸烟史的赋值+1.036×支架植入个数的赋值+3.526×低密度脂蛋白的赋值+1.096×中性粒细胞的赋值-0.487×血红蛋白的赋值。本模型的ROC曲线下面积为0.718[95%CI(0.629~0.807),P<0.001],灵敏度为62.3%,特异度为79.7%,约登指数为0.420。模型验证结果:ROC曲线下面积为0.756[95%CI(0.682~0.830),P<0.001],灵敏度为89.5%,特异度为85.0%,准确率为81.4%。结论本研究构建的预测模型效果良好,可判别急性冠脉综合征患者PCI术后1年的发生不良心血管事件的危险因素,为临床医护人员进行风险管理提供参考依据。

Objective To investigate the independent risk factors of major adverse cardiac events(MACEs)in patients with acute coronary syndrome(ACS)1 year after percutaneous coronary intervention(PCI),and to establish a risk prediction model.Methods A retrospective study was conducted.A total of 271 ACS patients diagnosed in one tertiary gradeA hospital in Weifang receiving 1-year postoperative follow-up were divided into model group(n=190)and validation group(n=81)and the model group was sub-divided into MACE group(n=61)and non-MACE group(n=129).The risk factors in MACE group and non-MACE group were compared and the risk prediction model was established.The prediction effect was assessed using the area under the ROC curve,and 81 patients in validation group were selected to validate the prediction effect of the model.Results Univariate and multivariate analysis showed that left main artery disease,hypertension,smoking history,number of stents implanted,low density lipoprotein,neutrophils and hemoglobin were independent risk factors for MACEs.The predictive model was P=ex/(1+e^x),X=-7.476+2.352×left main disease+2.061×hypertension+1.479×smoking history+1.036×number of stent implantation+3.526×low-density lipoprotein+1.096×neutrophil-0.487×hemoglobin.The area under ROC curve of this model was 0.718[95%CI(0.629~0.807),P<0.001];the sensitivity 62.3%;the specificity 79.7%;and the Jorden index 0.420.The area under ROC curve was 0.756[95%CI(0.682~0.830),P<0.001]and the sensitivity,specificity and accuracy were 89.5%,85.0%and 81.4%respectively.Conclusion The prediction model constructed in this study has a good effect,which can identify the risk factors of MACEs in patients with ACS 1 year after PCI,and provide reference for clinical medical staff to carry out risk management.