Introduction: The statistical measures commonly used to assess therapies for recurrent atrial arrhythmias (such as time to first recurrence) often assume a uniformly random pattern of arrhythmic events over time. However, the true temporal pattern of atrial arrhythmia recurrences is unknown. The aim of this study was to use linear and nonlinear analyses to characterize the temporal pattern of atrial arrhythmia recurrences in patients with implantable cardioverter defibrillators.
Methods and results: The time and date of atrial tachyarrhythmias recorded in 65 patients with combined atrial and ventricular defibrillators were used to construct a probability density function (PDF) and a model of a Poisson distribution of arrhythmic events for each patient. Average patient age was 66 +/- 10 years and follow-up was 7.8 +/- 4.8 months. A total of 10,759 episodes of atrial tachyarrhythmias were analyzed (range 43 to 618 episodes per patient). The PDF fit a power law distribution for all 65 patients, with an average r2 = 0.89 +/- 0.08. The PDF distribution differed significantly from the model Poisson distribution in 47 of 65 patients (P = 0.0002). Differences from the Poisson distribution were noted for patients both taking (30/43 patients; P < or = 0.015) and not taking (17/22 patients; P < or = 0.017) antiarrhythmic drugs. Median time between atrial arrhythmia detections for all 65 patients was 10.8 minutes.
Conclusion: In implantable cardioverter defibrillator patients, the temporal pattern of frequent recurrences of atrial tachyarrhythmias usually is characterized by a power law distribution. The unique statistical properties of this type of distribution should be considered in designing outcome measures for treatment of atrial tachyarrhythmias.