Contributing factors concerning inconsistencies in persistent atrial fibrillation ablation outcomes

In the present work, we investigated current methods for complex fractionated atrial electrogram (CFAE) classification during persistent atrial fibrillation (persAF). Potential contributing factors concerning the low reproducibility of CFAE-guided ablation outcomes in persAF therapy have been explored, such as inconsistencies in automated CFAE classification performed by different systems, the co-existence of different types of atrial electrograms (AEGs), and insufficient AEG duration for CFAE detection. First, we show that CFAE classification may vary for the same individual, depending on the system being used and settings being applied. Revised thresholds are suggested for the indices calculated by each system to minimize the differences in CFAE detection performed independently by them. Second, our results show that some AEGs are affected by stepwise persAF ablation, while others remain unaffected by it. Different types of AEGs might correlate with distinct underlying persAF mechanisms. Single descriptors measured from the AEGs, such as sample entropy and dominant frequency, were not able to discriminate the different types of AEGs individually, but multivariate analysis using multiple descriptors measured from the AEGs can effectively discriminate the different types of AEGs. Finally, we show that AEG duration of 2.5 s — as currently used by some systems — might not be sufficient to measure CFAEs consistently.