Squara Fabien, Scarlatti Didier, Bun Sok-Sithikun, Moceri Pamela, Ferrari Emile, Meste Olivier, Zarzoso Vicente
Cardiology Department, Pasteur Hospital, Université Côte d'Azur, Nice, France.
I3S Laboratory, Université Côte d'Azur, CNRS, Sophia Antipolis, France.
Front Cardiovasc Med. 2023 Aug 17;10:1145894. doi: 10.3389/fcvm.2023.1145894. eCollection 2023.
Persistent Atrial Fibrillation (PersAF) electrogram-based ablation is complex, and appropriate identification of atrial substrate is critical. Little is known regarding the value of the Average Complex Interval (ACI) feature for PersAF ablation.
Using the evolution of AF complexity by sequentially computing AF dominant frequency (DF) along the ablation procedure, we sought to evaluate the value of ACI for discriminating active drivers (AD) from bystander zones (BZ), for predicting AF termination during ablation, and for predicting AF recurrence during follow-up.
We included PersAF patients undergoing radiofrequency catheter ablation by pulmonary vein isolation and ablation of atrial substrate identified by Spatiotemporal Dispersion or Complex Fractionated Atrial Electrograms (>70% of recording). Operators were blinded to ACI measurement which was sought for each documented atrial substrate area. AF DF was measured by Independent Component Analysis on 1-minute 12-lead ECGs at baseline and after ablation of each atrial zone. AD were differentiated from BZ either by a significant decrease in DF (>10%), or by AF termination. Arrhythmia recurrence was monitored during follow-up.
We analyzed 159 atrial areas (129 treated by radiofrequency during AF) in 29 patients. ACI was shorter in AD than BZ (76.4 ± 13.6 vs. 86.6 ± 20.3 ms; = 0.0055), and mean ACI of all substrate zones was shorter in patients for whom radiofrequency failed to terminate AF [71.3 (67.5-77.8) vs. 82.4 (74.4-98.5) ms; = 0.0126]. ACI predicted AD [AUC 0.728 (0.629-0.826)]. An ACI < 70 ms was specific for predicting AD (Sp 0.831, Se 0.526), whereas areas with an ACI > 100 ms had almost no chances of being active in AF maintenance. AF recurrence was associated with more ACI zones with identical shortest value [3.5 (3-4) vs. 1 (0-1) zones; = 0.021]. In multivariate analysis, ACI < 70 ms predicted AD [OR = 4.02 (1.49-10.84), = 0.006] and mean ACI > 75 ms predicted AF termination [OR = 9.94 (1.14-86.7), = 0.038].
ACI helps in identifying AF drivers, and is correlated with AF termination and AF recurrence during follow-up. It can help in establishing an ablation plan, by prioritizing ablation from the shortest to the longest ACI zone.
基于心电图的持续性心房颤动(PersAF)消融术较为复杂,准确识别心房基质至关重要。关于平均复合间期(ACI)特征在PersAF消融中的价值,目前知之甚少。
通过在消融过程中顺序计算房颤主导频率(DF)来评估房颤复杂性的演变,我们试图评估ACI在区分活跃驱动灶(AD)和旁观者区域(BZ)、预测消融期间房颤终止以及预测随访期间房颤复发方面的价值。
我们纳入了接受肺静脉隔离及通过时空离散或复杂碎裂心房电图识别的心房基质消融(>70%记录)的射频导管消融的PersAF患者。操作者对ACI测量结果不知情,对每个记录的心房基质区域进行ACI测量。在基线及每个心房区域消融后,通过独立成分分析在1分钟12导联心电图上测量房颤DF。AD通过DF显著降低(>10%)或房颤终止与BZ区分开来。随访期间监测心律失常复发情况。
我们分析了29例患者的159个心房区域(129个在房颤期间接受射频治疗)。AD的ACI比BZ短(76.4±13.6 vs. 86.6±20.3毫秒;P = 0.0055),对于射频未能终止房颤的患者,所有基质区域的平均ACI更短[71.3(67.5 - 77.8)vs. 82.4(74.4 - 98.5)毫秒;P = 0.0126]。ACI可预测AD [曲线下面积0.728(0.629 - 0.826)]。ACI < 70毫秒对预测AD具有特异性(特异性0.831,敏感性0.526),而ACI > 100毫秒的区域几乎没有维持房颤活动的可能性。房颤复发与更多具有相同最短值的ACI区域相关[3.5(3 - 4)vs. 1(0 - 1)个区域;P = 0.021]。在多变量分析中,ACI < 70毫秒预测AD [比值比 = 4.02(1.49 - 10.84),P = 0.006],平均ACI > 75毫秒预测房颤终止[比值比 = 9.94(1.14 - 86.7),P = 0.038]。
ACI有助于识别房颤驱动灶,并且与随访期间的房颤终止和房颤复发相关。它可以通过从最短到最长ACI区域优先进行消融来帮助制定消融计划。