  As for most of cardiac arrhythmias, atrial fibrillation (AF) is primarily
treated by catheter ablation (CA). However, the mid-term recurrence rate of
this procedure in persistent AF patients is still limited and the preoperative
prediction of its outcome is clinically interesting to select candidates who
could benefit the most from the intervention. This context encouraged the study
of C0 complexity as a novel predictor, because it estimates organization of the
power spectral distribution (PSD) of the fibrillatory waves (f-waves). For that
purpose, the PSD was divided into two divergent components using a threshold,
theta, which was considered by multiplying the mean value of the PSD by a
factor, alpha, ranging between 1.5 and 2.5. On a database of 74 patients, the
values of C0 complexity computed for all alpha factors reported statistically
significant differences between the patients who maintained sinus rhythm and
those who relapsed to AF after a follow-up of 9 months. They also showed higher
values of sensitivity (Se), specificity (Sp), and accuracy (Acc) than the well
known predictors of the dominant frequency (DF) and f-wave amplitude. Moreover,
the combination of the DF and the C0 complexity computed with alpha = 2, via a
decision tree, improved classification until values of Se, Sp and Acc of 75.33,
77.33 and 76.58%, respectively. These results manifests the relevance of the
f-wave PSD distribution to anticipate CA outcome in persistent AF patients.
