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Catheter ablation (CA) is a commonly used treatment for persistent atrialfibrillation (AF). Since its medium/long-term success rate remains limited,preoperative prediction of its outcome is gaining clinical interest tooptimally select candidates for the procedure. Among predictors based on thesurface electrocardiogram, the dominant frequency (DF) and harmonic exponentialdecay (g) of the fibrillatory waves ( f -waves) have reported promising butclinically insufficient results. Hence, the main goal of this work was toconduct a broader analysis of the f -wave harmonic spectral structure toimprove CA outcome prediction through several entropy-based measures computedon different frequency bands. On a database of 151 persistent AF patients underradio-frequency CA and a follow-up of 9 months, the newly introduced parametersdiscriminated between patients who relapsed to AF and those who maintained SRat about 70%, which was statistically superior to the DF and approximatelysimilar to g. They also provided complementary information to g throughdifferent combinations in multivariate models based on lineal discriminantanalysis and report classification performance improvement of about 5%. Theseresults suggest that the presence of larger harmonics and a proportionallysmaller DF peak is associated with a decreased probability of AF recurrenceafter CA.

journal of personalized medicine

Preoperative Prediction of Catheter Ablation Outcome in Persistent  Atrial Fibrillation Patients through Spectral Organization Analysis of the  Surface Fibrillatory Waves