冠心病患者术后心律失常的风险因素分析及 Nomogram 风险模型的建立

Jie Gao, Zhiying He, Xiaoqing Luo
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摘要

背景:探讨冠心病(CHD)患者术后心律失常的风险因素,并建立预测冠心病患者术后心律失常风险的 Nomogram 模型。方法回顾性收集冠心病患者的医疗数据(2021 年 1 月至 2024 年 1 月,n = 390)。根据经皮冠状动脉介入手术后是否发生心律失常,将患者分为心律失常组(n = 130)和非心律失常组(n = 260)。通过多因素逻辑回归分析得出术后心律失常的风险因素。使用 R 语言建立了预测心脏病患者术后心律失常风险的 Nomogram 模型,并进行了验证。结果多因素逻辑回归分析结果显示,舒张压、心功能 III-IV 级、肌酐、C 反应蛋白(CRP)、N-端前脑钠尿肽(NT-ProBNP)峰值、总胆红素(TBIL)和红细胞分布宽度(RDW)是诱发冠心病患者术后心律失常的危险因素。根据这些风险因素,成功建立了一个 Nomogram 模型。验证结果显示,预测值与实际值基本一致,表明 Nomogram 模型具有良好的预测能力。曲线下面积(AUC)值为 0.974,表明 Nomogram 模型具有较高的预测效率。结论舒张压、心功能 III-IV 级、肌酐、CRP、NT-ProBNP 峰值、TBIL 和 RDW 是冠心病患者术后心律失常的危险因素。基于这些风险因素的提名图模型具有良好的预测效率和潜在的临床价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of Risk Factors of Postoperative Arrhythmia in Patients with Coronary Heart Disease and Establishment of Nomogram Risk Model
Background: To explore the risk factors of postoperative arrhythmia in patients with coronary heart disease (CHD) and to establish a Nomogram model for predicting the risk of postoperative arrhythmia in CHD patients. Methods: Retrospectively, the medical data of CHD patients (from January 2021 to January 2024, n = 390) were collected. According to whether arrhythmia occurred after percutaneous coronary intervention surgery, patients were divided into the arrhythmia group (n = 130) and non-arrhythmia group (n = 260). The risk factors of postoperative arrhythmia were obtained by multi-factor logistic regression analysis. A Nomogram model for predicting the risk of postoperative arrhythmia in CHD patients was established using R language and underwent verification. Results: The results of multi-factor logistic regression analysis showed that diastolic pressure, heart function grade at III–IV, creatinine, C-reactive protein (CRP), N-terminal pro-brain natriuretic peptide (NT-ProBNP) peak value, total bilirubin (TBIL) and red cell distribution width (RDW) were the risk factors inducing postoperative arrhythmia in CHD patients. Based on these risk factors, a Nomogram model was successfully established. The verification results revealed that the predicted values were basically consistent with the actual values, indicating that the Nomogram model had good prediction ability. The area under the curve (AUC) value was 0.974, suggesting the high prediction efficiency of Nomogram model. Conclusion: Diastolic pressure, heart function grade at III–IV, creatinine, CRP, NT-ProBNP peak value, TBIL and RDW are the risk factors of postoperative arrhythmia in CHD patients. Nomogram model based on these risk factors has good prediction efficiency and underlying clinical value.
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