急性心肌梗死患者新发心房颤动的危险因素及列线图风险预测模型构建（Risk factors and nomogram prediction model for new-onset atrial fi brillation in patients with acute myocardial infarction）

Objective To analyze the risk factors associated with newly developed atrial fi brillation (AF) during hospitalization in patients with acute myocardial infarction (AMI), and to construct a nomogram-based risk prediction model to provide reference for early screening of high-risk patients in primary healthcare settings. Methods A retrospective case-control study was conducted, including 268 AMI patients admitted to our hospital from January 2024 to December 2025. Patients were divided into an AF group (n=42) and a non-AF group (n=226) based on whether they developed AF during hospitalization. Demographic data, echocardio graphic fi ndings, laboratory test results, and coronary angiography outcomes were collected. Univariate analysis was fi rst performed to identify variables with statistically signifi cant diff erences between groups, followed by multivariable binary logistic regression to determine independent risk factors. A nomogram prediction model was then constructed and validated using bootstrap resampling. Results Univariate analysis showed that the proportions of patients aged ≥65 years, those with comorbid hypertension or diabetes, increased left atrial diameter, left ventricular ejection fraction <50%, elevated NT-proBNP, elevated hs-CRP, and Gensini score ≥ 40 were signifi cantly higher in the AF group than in the non-AF group (P<0.05). Multivariate logistic regression revealed that age ≥ 65 years, increased left atrial diameter, elevated NT-proBNP, elevated hs-CRP, and Gensini score ≥ 40 were independent predictors of newly developed AF during hospitalization in AMI patients (all P<0.05). Based on these fi ve indicators, a nomogram model was de veloped. Internal validation demonstrated a concordance index (C-index) of 0.823, with calibration curves closely aligned to the ide al prediction line and a Hosmer-Lemeshow test P-value of 0.723, indicating good predictive accuracy. Conclusion Age, left atrial diameter, NT-proBNP, hs-CRP, and severity of coronary artery disease are closely related to the development of new-onset AF after AMI. The nomogram model based on these indicators eff ectively predicts the risk of AF during hospitalization, is simple to use, and is suitable for clinical application at primary care levels.