The Risk Prediction Tool for Pacing‐Induced Cardiomyopathy in Right Ventricular Pacing Patients

ABSTRACT Background Pacing‐induced cardiomyopathy (PICM) is a serious complication associated with right ventricular pacing. This study aims to identify patients at a high risk for PICM and mitigate its incidence by guiding the selection of left bundle branch pacing over right ventricular pacing. Methods Consecutive patients who underwent permanent right ventricular pacing at two centers from January 2013 to December 2022 were retrospectively evaluated. They were used as the derivation set and the validation set, respectively. Clinical, echocardiographic, and electrocardiographic data were collected at baseline and during follow‐up. Two models were developed using selected variables obtained through two different methods, and the superior model was chosen based on its simplicity and performance. Based on the selected model, a nomogram was constructed, evaluated, and externally validated using the validation set. Results The derivation set comprised 374 patients, with 74 (19.8%) diagnosed with PICM. The final Cox model incorporated ejection fraction, left ventricular end‐systolic diameter, baseline QRS duration, and atrial fibrillation status (present/absent). The nomogram based on this model demonstrated moderate discrimination, achieving a C statistic of 0.75 (95% confidence interval: 0.70–0.81). The calibration curve showed accurate risk predictions for PICM. Its performance was consistent during internal validation via bootstrapping and was maintained in the validation set. The model effectively stratified risk, distinguishing between high‐risk and low‐risk populations. Conclusion A user‐friendly tool effectively predicts 3‐, 5‐, and 8‐year risk of PICM in patients with right ventricular pacing and normal ejection fraction. It may help identify patients most likely to benefit from left bundle branch pacing versus right ventricular pacing, guiding initial pacing strategy selection.