Noninvasive Predictors of Atrial Fibrillation Early Recurrence After Electrical Cardioversion and their Link to Atrial Remodeling

Several clinical factors have been studied to predict atrial fibrillation (AF) recurrence after electrical cardioversion (ECV) with limited predictive value. In this work, several time-frequency parameters from the fibrillatory (f) waves characterization were studied to improve ECV outcome prediction at mid follow-up. By analyzing ECV outcome one month after the procedure of 63 persistent AF patients, f waves power (fWP) presented the highest predictive accuracy of 82.5%, whereas f waves organization, computed by sample entropy (SampEn), provided a 79.4%. Other analyzed features revealed accuracies lower than 70%. A stepwise discriminant analysis provided a model based on fWP and SampEn with 90.5% of accuracy. Moreover, a thorough analysis of the results allowed the outline of possible associations between these two features and the concomitant status of atrial remodeling. As a consequence, the information provided by advanced signal processing methodologies could be more effective in the prediction of long-standing AF early recurrences than previously analyzed clinical parameters.