  Surgical ablation (SA) is the most effective procedure to terminate atrial
fibrillation (AF) in patients requiring concomitant open heart surgery.
However, considering the great stress provoked in the patients heart, along
with the benefits of anticipating antiarrhythmic therapeutical decisions,
preoperative prediction of long term failure of the procedure is an interesting
clinical challenge. Hence, the present work introduces a novel algorithm to
anticipate SA outcome after one year of follow up by just analyzing the surface
ECG. The method firstly extracts fibrillatory waves reflected on standard lead
V1 using an adaptive QRST cancellation approach. The resulting signal is then
segmented into 1 s length intervals and wavelet energy is computed for all of
them. Finally, the coefficient of variation of the time series obtained for the
7th scale is computed. Analyzing 20 second length preoperative ECG excerpts
from 53 persistent AF patients undergoing concomitant openheart surgery, only
the proposed method reported statistically significant differences between the
patients who relapsed to AF and those who maintained sinus rhythm during the
follow up. The algorithm also provided values of sensitivity, specificity, and
accuracy between 10 and 20% better than the well established dominant atrial
frequency and fibrillatory waves amplitude, thus suggesting to be a promising
predictor of AF recurrence after SA.
