Identifying Clinical Predictors for Permanent Pacemaker Implantation: A Single-Center Risk Score Development

Abstract

Background: Permanent pacemaker implantation carries considerable risks, yet tools for identifying high-risk individuals for primary prevention are lacking. We aimed to identify predictors and develop a clinical risk score to predict the need for permanent pacemaker implantation. Methods: We conducted a retrospective case-control study of 800 participants (550 cases with pacemakers, 250 controls). Data on demographics, comorbidities, and ECG findings were extracted. Logistic regression was used to identify independent predictors and create a point-based risk score, whose performance was assessed using ROC analysis. Results: Seven independent predictors were identified: chronic kidney disease (CKD), NYHA class III-IV heart failure, atrial fibrillation (AF), diabetes mellitus (DM), age >75, complete heart block (CHB), and temporary pacemaker use. A 9-point risk score successfully stratified patients into low, intermediate, and high-risk groups, demonstrating excellent discrimination (AUC 0.87). Conclusion: This simple, point-based score is a practical tool for identifying patients at high risk for pacemaker implantation, potentially guiding closer monitoring and preventative strategies. q