Establishment and Verification of a Nomogram for Predicting the Probability of New-Onset Atrial Fibrillation After Dual-Chamber Pacemaker Implantation.

Abstract

Background: This study aims to establish and validate a nomogram as a predictive model in patients with new-onset atrial fibrillation (AF) after dual-chamber cardiac implantable electronic device (pacemaker) implantation.

Methods: A total of 1120 Chinese patients with new-onset AF after pacemaker implantation were included in this retrospective study. Patients had AF of at least 180/minute lasting 5 minutes or longer, detected by atrial lead and recorded at least 3 months after implantation. Patients with previous atrial tachyarrhythmias before device implantation were excluded. A total of 276 patients were ultimately enrolled, with 51 patients in the AF group and 225 patients in the non-AF group. Least absolute shrinkage and selection operator (LASSO) method was used to determine the best predictors. Through multivariate logistic regression analysis, a nomogram was drawn as a predictive model. Concordance index, calibration plot, and decision curve analyses were applied to evaluate model discrimination, calibration, and clinical applicability. Internal verification was performed using a bootstrap method.

Results: The LASSO method regression analysis found that variables including peripheral arterial disease, atrial pacing-ventricular pacing of at least 50%, atrial sense-ventricular sense of at least 50%, increased left atrium diameter, and age were important predictors of developing AF. In multivariate logistic regression, peripheral arterial disease, atrial pacing-ventricular pacing of at least 50%, and age were found to be independent predictors of new-onset AF.

Conclusion: This nomogram may help physicians identify patients at high risk of new-onset AF after pacemaker implantation at an early stage in a Chinese population.