Cardiometabolic Index as a Predictor of Major Adverse Cardiovascular Events in Atrial Fibrillation: Insights from a Community-Based Cohort

Jingjing Sha¹Jiayue Cheng¹Xunhan Qiu²Mangmang Pan²Caihong Liu¹Long Shen²Zhichun Gu²Hao Huang¹Siliang Zeng^3*

• ¹Jinyang Community Health Service Center, Shanghai, China
• ²Shanghai Jiao Tong University School of Medicine Affiliated Renji Hospital, Shanghai, China
• ³Shanghai Normal University Tianhua College, Shanghai, China

Background：The cardiometabolic index, a composite indicator integrating central obesity and lipid abnormalities, has demonstrated predictive value in several cardiovascular diseases. However, its role in predicting major adverse cardiovascular events among patients with atrial fibrillation remains underexplored. Methods：This single-center retrospective cohort study enrolled 192 atrial fibrillation (AF) patients managed at the Jinyang Community Health Service Center (Shanghai) between January 2022 and January 2024. Patients were grouped into tertiles based on baseline cardiometabolic index. The primary endpoint was major adverse cardiovascular events (MACE), including cardiovascular death, nonfatal myocardial infarction, nonfatal stroke, heart failure hospitalization, and coronary revascularization.Cox proportional hazards models assessed the association between CMI and MACE. Kaplan–Meier curves with log-rank tests compared event rates across groups. Restricted cubic splines evaluated nonlinearity. An extreme gradient boosting (XGBoost) model was used for risk prediction, with SHapley Additive exPlanations (SHAP) identifying key predictors. Subgroup analyses explored the consistency of CMI’s predictive value across clinical subpopulations.The median follow-up was 664 days (IQR: 384–900), estimated via the reverse Kaplan–Meier method. Results：MACE incidence increased significantly with rising CMI levels. Compared to the low CMI group, the high CMI group had a significantly higher risk of MACE (HR = 5.56, 95% CI: 1.48 – 20.90, P = 0.011). Kaplan–Meier analysis showed significant differences in cumulative incidence among the three groups (Log-rank P < 0.001). restricted cubic spline (RCS) modeling revealed a nonlinear positive association, with a sharp increase in MACE risk above a CMI threshold of approximately 0.85 (P for nonlinearity < 0.001). The Extreme Gradient Boosting (XGBoost) model achieved a C-index of 0.737 in the test set, with SHapley Additive exPlanations (SHAP) analysis ranking CMI as the fourth most influential predictor, following age, left atrial diameter, and left ventricular ejection fraction. Subgroup analyses suggested that the predictive value of CMI was particularly evident in patients without chronic kidney disease and those without prior catheter ablation. Conclusion：Elevated CMI is independently associated with higher MACE risk in atrial fibrillation patients, showing a nonlinear dose–response pattern. As a simple and accessible marker, CMI may aid in cardiovascular risk stratification and personalized management, particularly in high-risk patients without evident metabolic disorders.