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

Abstract

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.