No abstract

The goal of this study was to investigate the usefulness of nonlinear analysis in determining the success of low energy internal cardioversion (IC) in patients with atrial fibrillation (AF). Nonlinear analysis has previously been used for characterizing AF patterns, and spontaneous termination in its paroxysmal form. However, the relationship between the probability to restore sinus rhythm by IC and quantitative nonlinear analysis based electrocardiographic (ECG) markers has not been explored before. Thirty nine patients with AF, for elective DC cardioversion at the Royal Victoria Hospital in Belfast, were included in this study. One catheter was positioned in the right atrial appendage and another in the coronary sinus, to deliver a biphasic shock waveform. A voltage step-up protocol (50-300 V) was used for patient cardioversion. Residual atrial fibrillatory signal (RAFS) was derived from 60 seconds of surface ECG from defibrillator pads, prior to shock delivery, by bandpass filtering and ventricular activity (QRST) cancellation. QRST complexes were cancelled using a recursive least squared (RLS) adaptive filter. The maximal Lyapunov exponent (lambda), correlation dimension (course grained estimation, CDcg) and approximate entropy (ApEn) were extracted from the RAFS. These variables were calculated from 10 s of the RAFS before shock delivery. 26 patients were successfully cardioverted, employing a maximum energy of 11.84 joules. A lower lambda (0.037+/-0.006 vs. 0.044+/-0.008, P=0.01) and CDcg (5.552+/-2.075 vs. 6.592+/-1.130, P=0.049) were found in successfully cardioverted patients than in those non successful ones, with an energy