Abstract : Background. Catheter ablation (CA) of persistent atrial fibrillation (AF) is challenging and reported results are perfectible. Improving patient selection for the procedure could enhance its success rate while avoiding the risks associated with ablation for patients with low odds of success. CA outcome can be predicted noninvasively by atrial fibrillatory wave (f-wave) amplitude, but previous works have mostly focused on manual measures in single ECG leads only.
Aims. The present work aims at assessing the long-term prediction ability of f-wave amplitude when computed in multiple ECG leads.
Methods and Results. Sixty-two persistent AF patients (52 males, 61.5±10.4 years) referred to CA were enrolled in this study. During an average follow-up of 14±8 months, 47 patients had no AF recurrence after ablation. A standard one-minute 12-lead ECG was acquired before the ablation procedure for each patient. F-wave amplitudes in different ECG leads were computed by a noninvasive signal processing algorithm and combined into a multivariate prediction model based on logistic regression. A lead selection approach relying on the Wald index pointed to I, V1, V2 and V5 as the most relevant ECG leads to predict jointly CA outcome using f-wave amplitudes, reaching an AUC of 0.854 and improving on single-lead amplitude-based predictors.
Conclusion. Analyzing the f-wave amplitude simultaneously in several ECG leads can significantly improve CA long-term outcome prediction in persistent AF over predictors based on single-lead measures.