预测急性ST段抬高型心肌梗死患者经皮冠状动脉介入术后发生心律失常的列线图模型构建

张海洋.预测急性ST段抬高型心肌梗死患者经皮冠状动脉介入术后发生心律失常的列线图模型构建[J].内科急危重症杂志,2025,31(3):260-265

DOI：10.11768/nkjwzzzz20250314

中文关键词: 单核细胞/高密度脂蛋白比值急性ST段抬高型心肌梗死经皮冠状动脉介入术心律失常

英文关键词:

基金项目:

作者	单位	E-mail
张海洋	安徽省濉溪县医院心血管内科	306239495@qq.com

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中文摘要:

摘要目的：探讨急性ST段抬高型心肌梗死（STEMI）患者经皮冠状动脉介入(PCI)术后发生心律失常的影响因素并构建列线图模型。方法：选择行PCI术的216例急性STEMI患者为研究对象，根据术后是否新发心律失常将患者分为心律失常组（43例）和非心律失常组（173例），比较组间临床资料差异；通过Logistic回归分析判断单核细胞/高密度脂蛋白比值(MHR）能否作为急性STEMI患者术后心律失常发生的独立危险因素；以卡方趋势检验分析各MHR水平组患者心律失常发生的趋势；通过受试者工作特征（ROC）曲线评估列线图对急性STEMI患者术后发生心律失常的预测效果；建立预测发生心律失常风险的列线图模型，并对其进行验证。结果：单因素Logistic回归分析显示，年龄、静息心率、肌钙蛋白T、白细胞计数、中性粒细胞计数、淋巴细胞计数、单核细胞计数、MHR、NLR、PLR及尿酸是心律失常发生的危险因素，多因素Logistic回归分析显示，MHR是急性STEMI患者术后发生心律失常的独立危险因素（OR=0.217，95%CI：0.080~0.591）；与非心律失常组比较，心律失常组MHR水平显著升高（P＜0.05）；ROC曲线分析显示，MHR预测心律失常发生的最佳截断值为0.834，敏感度为65.3%，特异性为82.1%，AUC为0.726（95%CI：0.695~0.757），提示MHR对急性STEMI患者PCI术后发生心律失常具有良好的预测价值；构建列线图模型，其一致性指数为0.745（95%CI：0.702~0.788），AUC为0.726（95%CI：0.695~0.757）。Calibration曲线和模型校准曲线提示列线图模型预测概率与实际发生概率具有较高的一致性，准确性较好。结论：可通过MHR水平和列线图评估急性STEMI患者早发心律失常风险。

英文摘要:

Abstract Objective: To explore the influencing factors of arrhythmia after percutaneous coronary intervention (PCI) in patients with acute ST-segment elevation myocardial infarction (STEMI), and construct a nomogram model. Methods: A total of 216 STEMI patients who underwent PCI at our hospital were divided into arrhythmia group (43 patients) and non arrhythmia group (173 patients) according to whether they developed arrhythmia after operation, and the differences of clinical data between groups were compared. Whether monocyte/high-density lipoprotein ratio (MHR) can be used an independent risk factor for the occurrence of postoperative arrhythmias in patients with STEMI was determined by logistic regression analysis. Trends in the occurrence of arrhythmias among patients in each MHR level group were analyzed with the Chi square trend test. The predictive effect of MHR on the occurrence of postoperative arrhythmias in STEMI patients was evaluated by ROC curve analysis. A nomogram model to predict the arrhythmia risk was developed and validated based on the independent risk factors for the patients' postoperative arrhythmia risk. Results: Univariate Logistic regression analysis showed that age, resting heart rate, troponin T, white blood cell count, neutrophil count, lymphocyte count, monocyte count, MHR, NLR, PLR and uric acid were risk factors for arrhythmia. Multivariate Logistic regression analysis showed that MHR was an independent risk factor for postoperative arrhythmia in patients with acute STEMI (OR=0.217，95%CI: 0.080-0.591). Compared with non-arrhythmia group, the level of MHR in arrhythmia group was significantly higher (P< 0.05). ROC curve analysis shows that the best cutoff value of MHR for predicting arrhythmia was 0.834, with sensitivity of 65.3%, specificity of 82.1% and AUC of 0.726 (95% CI: 0.695-0.757), which indicates that MHR has a good predictive value for arrhythmia in patients with acute STEMI after PCI. The nomogram model was constructed, and its consistency index was 0.745 (95% CI: 0.702-0.788) and AUC was 0.726 (95% CI: 0.695-0.757). Calibration curve and model calibration curve suggest that the predicted probability of nomogram model had high consistency with the actual occurrence probability, and the accuracy was good. Conclusion: MHR level and nomogram can be used to evaluate the risk of premature arrhythmia in patients with acute STEMI.