冠心病患者冠脉介入治疗术后预后不良的列线图预测模型构建

Construction of a nomogram prediction model to predict a poor prognosis after percutaneous coronary intervention in patients with coronary heart disease

目的分析冠心病患者经冠脉介入术治疗预后不良的相关因素,构建列线图预测模型并评价其性能。方法纳入2020年9月至2022年8月滕州市中医医院收治的冠心病患者300例作为研究对象,所有患者行冠脉介入术治疗,根据术后1年随访是否发生心血管不良事件分为观察组(n=61)和对照组(n=239)。对两组的临床资料进行统计分析,通过受试者工作特征(ROC)曲线分析有统计学意义的连续性变量;采用多元Logistic回归分析冠心病患者冠脉介入治疗术后预后不良的独立危险因素;R软件构建预测冠心病患者术后预后不良的列线图模型;校正曲线对预测模型进行内部验证;决策曲线评估预测模型的临床净收益。结果观察组糖尿病比例、吸烟比例、植入支架数>2比例、D-二聚体和白介素-6水平高于对照组(均P<0.05),D-二聚体(>1.23 mg/L)、白介素-6(>50.01 ng/L)、年龄(>66岁)、合并糖尿病和吸烟是冠心病患者冠脉介入治疗术后预后不良的独立危险因素(P<0.05)。内部验证结果显示,列线图预测模型的C-index为0.786(95%CI:0.397,0.896),观测值与预测值之间保持较好一致性。决策曲线显示当风险阈值>0.16时,此预测模型可以提供额外的临床净收益。结论本研究构建了冠心病患者冠脉介入治疗术后预后不良危险因素的列线图预测模型,有助于医护人员认识冠心病患者术后预后不良的相关因素,尽早制定个性化对策以改善预后,提升患者生活质量。

Objective To analyze risk factors for the poor prognosis in patients with coronary heart disease after percutaneous coronary intervention(PCI),and to construct a nomogram prediction model and evaluate its performance.Methods A total of 300 patients with coronary heart disease admitted to Tengzhou Traditional Chinese Medicine Hospital from September 2020 to August 2022 were enrolled as the research objects.All patients underwent PCI,and they were divided into observation group(n=61)and control group(n=239)according to the occurrence of adverse cardiovascular events during the 1-year follow-up.The clinical data of the two groups were compared.The continuous variables with significant differences between groups were analyzed by receiver operating characteristic(ROC)curve.A logistic regression model was used to analyze the independent risk factors for the poor prognosis after PCI in patients with coronary heart disease.R software was used to build a nomogram to predict the poor prognosis after PCI in patients with coronary heart disease.The internal validation and net clinical benefit of the nomogram were assessed by the calibration curve and decision curve analysis,respectively.Results The proportion of diabetes patients and smokers,number of implanted stents>2,D-dimer(D-D)and interleukin-6(IL-6)levels in the observation group were significantly higher than those of the control group(all P<0.05).D-D(>1.23 mg/L),IL-6(>50.01 ng/L),age(>66 years),diabetes and smoking were independent risk factors for poor prognosis in patients with coronary heart disease after PCI(all P<0.05).Internal validation Results showed that the C-index of the nomogram prediction model was 0.786(95%CI:0.397,0.896),presenting a good consistency between observed value and predictive value.The decision curve showed that the prediction model could provide additional net clinical benefits when the risk threshold was>0.16.Conclusion This study constructs a nomogram prediction model to predict risk factors for the poor prognosis in patients with coronary heart disease after PCI,which helps medical staff to recognize risk factors and provide individualized interventions to improve the prognosis and quality of life.