Ablation index predicts outcomes of catheter ablation of focal atrial tachycardia: results of a multicenter study. (19th May 2022) - Compagnucci, P; Dello Russo, A; Bergonti, M; Anselmino, M; Zucchelli, G; Gasperetti, A; Cipolletta, L; Volpato, G; Ascione, C; Ferraris, F; Bongiorni, MG; Natale, A; et al.
Abstract: Funding Acknowledgements: Type of funding sources: None. Background: Ablation index (AI) is a radiofrequency energy lesion quality marker integrating power, contact force, and time, which was recently shown to be linked to successful catheter ablation (CA) of atrial fibrillation, atrial flutter, and premature ventricular complexes. The possible role of AI as a predictor of outcomes after CA of focal atrial tachycardia (AT) has not been explored so far. Purpose: To evaluate the role of AI as a predictor of arrhythmia-free survival after CA of focal AT. Methods: We retrospectively enrolled forty-five consecutive patients undergoing CA for focal AT in four referral Italian electrophysiology laboratories. Clinical and procedural information were collected. For each patient, maximum and mean (by averaging maximum AI values for each radiofrequency ablation lesion) values of AI were measured. Focal AT-free survival was the primary outcome, and was assessed with repeated Holter monitors or cardiac implantable electronic devices, when available. The Shapiro-Wilk's test was used to check continuous variables for normality; non-normal variables were expressed as median (1st-3rd quartile), whereas categorical variables were reported as counts and percentages. The primary outcome was assessed in a time-to-event fashion, with the Kaplan-Meier method, and the role of AI as a predictor of focal AT recurrence was tested with univariable Cox proportional hazard regression. Furthermore, differences in AI values between patients experiencing a primary outcome event and patients not experiencing a primary outcome event were analyzed with the Student t test. Discrimination ability of AI was measured with area under the receiver operating characteristic curve, and the optimal AI cutoff value was identified with Youden's index. An alpha level <0.05 was considered statistically significant, and the software RStudio (RStudio Inc., Boston, MA) was used for statistical analysis. Results: CA was acutely effective in every patient; however, 20% (n=9) of the study population had a focal AT recurrence over a median follow-up of 288 (160-560) days. Both maximum and mean AI values were significantly higher among patients without AT recurrences (maximum AI=568±91, mean AI=426±105) than in patients with AT relapses (maximum AI=447±142, mean AI=352±76, p=0.036 and p=0.028, respectively). All other procedural parameters were similar between the two groups. In a time-to-event analysis, only maximum AI was significantly associated with survival free from AT recurrence (p=0.001, Figure), whereas mean AI was not (p=0.08). By receiver operating characteristic (ROC) curve analysis, the optimal maximum AI cutoff for predicting effective CA according to Youden's index was 461 (sensitivity, 0.89; specificity, 0.56). Conclusion: We observed a strong association between maximum AI and outcomes, suggesting that maximum AI may be regarded as a quantitative marker of successful CA of focal AT.