Demonstration of circadian rhythm in heart rate turbulence using novel application of correlator functions

• Published in: Heart rhythm Vol. 4; no. 3; p. 292
• Main Authors: Watanabe, Mari A, Alford, Mark, Schneider, Raphael, Bauer, Axel, Barthel, Petra, Stein, Phyllis K, Schmidt, Georg
• Format: Journal Article
• Language: English
• Published: United States 01.03.2007
• Subjects: Adrenergic beta-Antagonists - therapeutic use; Chi-Square Distribution; Circadian Rhythm - drug effects; Databases, Factual; Electrocardiography, Ambulatory; Female; Heart Conduction System - drug effects; Heart Conduction System - physiopathology; Heart Rate - drug effects; Humans; Male; Mathematical Computing; Middle Aged; Myocardial Infarction - drug therapy; Myocardial Infarction - physiopathology; Predictive Value of Tests; Signal Processing, Computer-Assisted; Ventricular Premature Complexes - physiopathology
• ISSN: 1547-5271
• DOI: 10.1016/j.hrthm.2006.11.016

Demonstration of a circadian rhythm in two parameters of heart rate turbulence--turbulence onset (TO) and turbulence slope (TS)--has been difficult. The aim of this study was to devise a new method for detecting circadian rhythm in noisy data and to apply it to selected Holter recordings from two postmyocardial infarction databases: Cardiac Arrhythmia Suppression Trial (CAST, n = 684) and Innovative Stratification of Arrhythmic Risk (ISAR, n = 327). For each patient, TS and TO were calculated for each hour with >4 ventricular premature contractions (VPCs). An autocorrelation function Corr(Deltat) = <TS(t) TS(t + Deltat)> then was calculated and averaged over all patients. Positive Corr(Deltat) indicates that TS at a given hour and Deltat hours later are similar. TO was treated likewise. Simulations and mathematical analysis showed that a circadian rhythm required Corr(Deltat) to have a U-shape consisting of positive values near Deltat = 0 and 23 and negative values for intermediate Deltat. Significant deviation of Corr(Deltat) from the correlator function of pure noise was evaluated as a Chi-square value. Circadian patterns were not apparent in hourly averages of TS and TO plotted against clock time, which had large error bars. However, their correlator functions produced Chi-square values of approximately 10 in CAST (both P <.0001) and approximately 3 in ISAR (both P <.0001), indicating the presence of circadian rhythmicity. Correlator functions may be a powerful tool for detecting the presence of circadian rhythms in noisy data, even with recordings limited to 24 hours.