Background: Premature beats (PBs) have been considered as artifacts producing a bias in the traditional analysis of heart rate (HR) variability. We assessed the effects and significance of PBs on fractal scaling exponents in healthy subjects and patients with a recent myocardial infarction (AMI).
Methods: Artificial PBs were first generated into a time series of pure sinus beats in 20 healthy subjects and 20 post-AMI patients. Thereafter, a case-control approach was used to compare the prognostic significance of edited and nonedited fractal scaling exponents in a random elderly population and in a post-AMI population. Detrended fluctuation analysis (DFA) was used to measure the short-term (alpha1) and long-term (alpha2) fractal scaling exponents.
Results: Artificial PBs caused a more pronounced reduction of alpha1 value among the post-AMI patients than the healthy subjects, for example, if > 0.25% of the beats were premature a > 25% decrease in the alpha1 was observed in post-AMI patients, but 4% of the premature beats were needed to cause a 25% reduction in alpha1 in healthy subjects. Both edited (1.01 +/- 0.31 vs 1.19 +/- 0.27, P < 0.01) and unedited alpha1 (0.71 +/- 0.33 vs 0.89 +/- 0.36, P < 0.05) differed between the patients who died (n = 42) and those who survived (n = 42) after an AMI. In the general population, only unedited alpha1 differed significantly between survivors and those who died (0.96 +/- 0.19 vs 0.83 +/- 0.27, P < 0.05).
Conclusions: Unedited premature beats result in an increase in the randomness of short-term R-R interval dynamics, particularly in post-AMI patients. Premature beats must not necessarily be edited when fractal analysis is used for risk stratification.