Non-Linear Dynamics In Patients With Stable Angina Pectoris

Dynamic analysis techniques may quantify abnormalities in heart rate behaviour based on non-linear and fractal analysis.The applicability of these new methods for detecting complex heart rate dynamics in coronary heart disease is not well established. To investigate the clinical and prognostic significance of fractal dimension and detrended fluctuation analysis, two different groups were studied, group of patients with stable angina pectoris without previous myocardial infarction, and age-matched healthy controls. The fractal dimension of the RR series was determined using the rescaled range (R/S) analysis technique. To quantify fractal longe-range-correlation properties of heart rate variability, the detrended fluctuation analysis (DFA) technique was used. The heart rate variability was characterized by a scaling exponent α, separately for short-term (< 11 beats) and for long-term (> 11 beats) time scales. The results of data sets show the existence of crossover phenomena between short-time scales. In patients with stable angina pectoris the short-term fractal scaling exponent (α1) was significantly lower (0.95 ± 0.05 vs. 1.08 ± 0.06; p < 0.05), while there were no differences in the long-term fractal scaling exponent (α2)(1.37 ± 0.26 vs. 1.39 ± 0.04; p<0.05). The patients with stable angina pectoris also had higher fractal dimension than a healthy control group (p < 0.05). The short-time scaling exponent and fractal dimension are better than other heart rate variability parametars in differentiating patients with stable angina pectoris from healthy subjects. Dynamic analysis may thus complement traditional analysis in detecting altered heart rate behaviour. Presented at Computers in Cardiology, September 23-26, 2001 Rotterdam, The Netherlands