Prediction of sudden cardiac death by fractal analysis of heart rate variability in elderly subjects

OBJECTIVES The aim of this study was to test the hypothesis that abnormal scaling characteristics of heart rate (HR) predict sudden cardiac death in a random population of elderly subjects. BACKGROUND An abnormality in the short-term fractal scaling properties of HR has been observed to be related to a risk of life-threatening arrhythmias among patients with advanced heart diseases. The predictive power of altered short-term scaling properties of HR in general populations is unknown. METHODS A random sample of 325 subjects, age 65 years or older, who had a comprehensive risk profiling from clinical evaluation, laboratory tests and 24-h Holter recordings were followed up for 10 years. Heart rate dynamics, including conventional and fractal scaling measures of HR variability, were analyzed. RESULTS At 10 years of follow-up, 164 subjects had died. Seventy-one subjects had died of a cardiac cause, and 29 deaths were defined as sudden cardiac deaths. By univariate analysis, a reduced short-term fractal scaling exponent predicted the occurrence of cardiac death (relative risk [RR] 2.5, 95% confidence interval [CI], 1.9 to 3.2, p < 0.001) and provided even stronger prediction of sudden cardiac death (RR 4.1, 95% CI, 2.5 to 6.6, p < 0.001). After adjusting for other predictive variables in a multivariate analysis, reduced exponent value remained as an independent predictor of sudden cardiac death (RR 4.3, 95% CI, 2.0 to 9.2, p < 0.001). CONCLUSIONS Altered short-term fractal scaling properties of HR indicate an increased risk for cardiac mortality, particularly sudden cardiac death, in the random population of elderly subjects.