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

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.