Temporal Patterns of Atrial Arrhythmia Recurrences in Patients with Implantable Defibrillators: Implications for Assessing Antiarrhythmic Therapies

Temporal Patterns of Atrial Arrhythmias. 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.

[1]  K. Lee,et al.  Life-table methods for evaluating antiarrhythmic drug efficacy in patients with paroxysmal atrial tachycardia. , 1983, The American journal of cardiology.

[2]  Larry S. Liebovitch,et al.  Ion channel kinetics: a model based on fractal scaling rather than multistate Markov processes , 1987 .

[3]  L S Liebovitch,et al.  Fractal analysis of a voltage-dependent potassium channel from cultured mouse hippocampal neurons. , 1987, Biophysical journal.

[4]  E L Pritchett,et al.  Random and nonrandom behavior of symptomatic paroxysmal atrial fibrillation. , 1989, The American journal of cardiology.

[5]  P. Kligfield,et al.  Fractal clustering of ventricular ectopy and sudden death in mitral regurgitation. , 1992, Journal of electrocardiology.

[6]  R. Page,et al.  Asymptomatic arrhythmias in patients with symptomatic paroxysmal atrial fibrillation and paroxysmal supraventricular tachycardia. , 1994, Circulation.

[7]  B B Lerman,et al.  Fractal clustering of ventricular ectopy correlates with sympathetic tone preceding ectopic beats. , 1995, Circulation.

[8]  K. Ellenbogen,et al.  Long-term temporal patterns of ventricular tachyarrhythmias. , 1995, Circulation.

[9]  K M Stein,et al.  Predictive value for future arrhythmic events of fractal dimension, a measure of time clustering of ventricular premature complexes, after myocardial infarction. CAST Investigators. Cardia Arrhythmia Suppression Trial. , 1997, Journal of the American College of Cardiology.

[10]  Larry S. Liebovitch,et al.  NONLINEAR PROPERTIES OF CARDIAC RHYTHM ABNORMALITIES , 1999 .

[11]  C. Peng,et al.  Fractal analysis of heart rate dynamics as a predictor of mortality in patients with depressed left ventricular function after acute myocardial infarction. TRACE Investigators. TRAndolapril Cardiac Evaluation. , 1999, The American journal of cardiology.

[12]  A. Gillis,et al.  Evaluation of the bias in using the time to the first event when the inter-event intervals have a Weibull distribution. , 1999, Statistics in medicine.

[13]  A. Gillis,et al.  Temporal patterns of paroxysmal atrial fibrillation following DDDR pacemaker implantation. , 2000, The American journal of cardiology.

[14]  A. Brett.  Amiodarone to Prevent Recurrence of Atrial Fibrillation , 2000 .

[15]  S. Connolly,et al.  Antiarrhythmic effects of azimilide in atrial fibrillation: efficacy and dose-response. Azimilide Supraventricular Arrhythmia Program 3 (SVA-3) Investigators. , 2000, Journal of the American College of Cardiology.

[16]  S. Connolly.  Appropriate outcome measures in trials evaluating treatment of atrial fibrillation. , 2000, American heart journal.

[17]  H V Huikuri,et al.  Prediction of sudden cardiac death by fractal analysis of heart rate variability in elderly subjects. , 2001, Journal of the American College of Cardiology.

[18]  K. Stein,et al.  Worldwide Clinical Experience with a New Dual‐Chamber Implantable Cardioverter Defibrillator System , 2001, Journal of cardiovascular electrophysiology.

[19]  W. Kaemmerer,et al.  Distribution of Patients′ Paroxysmal Atrial Tachyarrhythmia Episodes: Implications for Detection of Treatment Efficacy , 2001, Journal of cardiovascular electrophysiology.