Development of a Nomogram That Predicts the Risk of Atrial Fibrillation in Patients with Coronary Heart Disease

IF 2.7 4区医学 Q2 HEALTH CARE SCIENCES & SERVICES Risk Management and Healthcare Policy Pub Date : 2024-07-09 DOI:10.2147/rmhp.s466205

Xinfu Cao, Yi Sun, Yuqiao Chen, Chao Tang, Hongwen Yu, Xiaolong Li, Zhenhua Gu

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Abstract

Objective: To explore the risk factors of atrial fibrillation (AF) in patients with coronary heart disease (CHD), and to construct a risk prediction model.
Methods: The participants in this case-control study were from the cardiovascular Department of Changzhou Affiliated Hospital of Nanjing University of Chinese Medicine from June 2016 to June 2023, and they were divided into AF group and non-AF group according to whether AF occurred during hospitalization. The clinical data of the two groups were compared by retrospective analysis. Multivariate Logistic regression analysis was used to investigate the risk factors of AF occurrence in CHD patients. The nomogram model was constructed with R 4.2.6 language “rms” package, and the model’s differentiation, calibration and effectiveness were evaluated by drawing ROC curve, calibration curve and decision curve.
Results: A total of 1258 patients with CHD were included, and they were divided into AF group (n=92) and non-AF group (n=1166) according to whether AF was complicated. Logistic regression analysis showed that age, coronary multiple branch lesion, history of heart failure, history of drinking, pulmonary hypertension, left atrial diameter, left ventricular end-diastolic diameter and diabetes mellitus were independent risk factors for the occurrence of AF in CHD patients (P < 0.05). The ROC curve showed that the AUC of this model was 0.956 (95% CI (0.916, 0.995)) and the consistency index was 0.966. The calibration curve of the model is close to the ideal curve. The analysis of decision curve shows that the prediction value of the model is better when the probability threshold of the model is 0.042~0.963.
Conclusion: The nomogram model established in this study for predicting the risk of AF in patients with CHD has better predictive performance and has certain reference value for clinical identification of high-risk groups prone to AF in patients with CHD.

keywords: coronary heart disease, atrial fibrillation, risk factors, logistic regression analysis, nomogram model

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开发可预测冠心病患者心房颤动风险的提名图

目的：探讨冠心病患者心房颤动（AF）的风险因素，并构建风险预测模型：探讨冠心病患者心房颤动（房颤）的危险因素，并构建风险预测模型：本病例对照研究的参与者来自南京中医药大学常州附属医院心血管内科，时间为2016年6月至2023年6月，根据住院期间是否发生房颤分为房颤组和非房颤组。通过回顾性分析比较两组患者的临床数据。采用多变量逻辑回归分析法研究冠心病患者发生房颤的风险因素。使用 R 4.2.6 语言 "rms "软件包构建了提名图模型，并通过绘制 ROC 曲线、校准曲线和决策曲线对模型的区分度、校准度和有效性进行了评估：共纳入 1258 例冠心病患者，根据是否合并房颤分为房颤组（92 例）和非房颤组（1166 例）。逻辑回归分析显示，年龄、冠状动脉多支病变、心力衰竭史、饮酒史、肺动脉高压、左心房直径、左心室舒张末期直径和糖尿病是冠心病患者发生房颤的独立危险因素（P <0.05）。ROC 曲线显示，该模型的 AUC 为 0.956（95% CI (0.916, 0.995)），一致性指数为 0.966。该模型的校准曲线接近理想曲线。决策曲线分析表明，当模型的概率阈值为 0.042~0.963 时，模型的预测值较好：本研究建立的预测冠心病患者房颤风险的提名图模型具有较好的预测性能，对临床识别冠心病患者中易发生房颤的高危人群具有一定的参考价值。关键词：冠心病；房颤；危险因素；逻辑回归分析；提名图模型

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来源期刊

Risk Management and Healthcare Policy Medicine-Public Health, Environmental and Occupational Health

CiteScore

6.20

自引率

2.90%

发文量

242

审稿时长

16 weeks

期刊介绍： Risk Management and Healthcare Policy is an international, peer-reviewed, open access journal focusing on all aspects of public health, policy and preventative measures to promote good health and improve morbidity and mortality in the population. Specific topics covered in the journal include: Public and community health Policy and law Preventative and predictive healthcare Risk and hazard management Epidemiology, detection and screening Lifestyle and diet modification Vaccination and disease transmission/modification programs Health and safety and occupational health Healthcare services provision Health literacy and education Advertising and promotion of health issues Health economic evaluations and resource management Risk Management and Healthcare Policy focuses on human interventional and observational research. The journal welcomes submitted papers covering original research, clinical and epidemiological studies, reviews and evaluations, guidelines, expert opinion and commentary, and extended reports. Case reports will only be considered if they make a valuable and original contribution to the literature. The journal does not accept study protocols, animal-based or cell line-based studies.