Local epicardial robotic-enhanced hybrid ablation efficacy predictors for persistent atrial fibrillation

摘要

Background: Hybrid ablation can manage persistent atrial fibrillation (PsAF) and long-standing persistent atrial fibrillation (LSPAF). Robotic-enhanced hybrid ablation (RE-HA) offers greater precision and stability. However, biophysical predictors of effective local epicardial radiofrequency ablation (ELRF) during epicardial ablation are unknown. Objective: The purpose of this study was to compare the time course of biophysical predictors of ELRF and no-ELRF during the first stage of RE-HA in patients with PsAF and LSPAF. Methods: We conducted a dual-center retrospective cohort study involving 92 consecutive patients with PsAF or LSPAF who underwent RE-HA between January 2021 and May 2024. Epicardial electrogram disappearance, defined as a reduction of bipolar voltages to <0.05 mV, baseline impedance (BI), and impedance drop (ID), were compared between ELRF and no-ELRF cases. Univariate and multivariate logistic regression models were used to identify predictive variables. Optimal cutoff values were determined using receiver operating characteristic curves. Results: Among 2474 radiofrequency (RF) applications, significant predictors of ELRF included BI and ID at 1 and 8 seconds, with optimal cutoff values of <107, 0-7, and 5-17 Ω. The composite predictive model had an area under the receiver operating characteristic of 0.775, with 94% sensitivity, 53% specificity, and 65% accuracy. Our predictive ELRF score ranged from 0-4, and the Youden J test identifying a cutoff value of 3 as optimal. Conclusion: BI and progressive ID were strong predictors of local epicardial RE-HA efficacy. The composite model was a reliable tool for early identification of ELRF, potentially reducing RF delivery and enhancing procedural efficiency. Larger prospective studies are needed to validate these findings.