Background: This study evaluates a novel method for postinfarction risk stratification based on frequency-domain characteristics of heart rate variability (HRV) in 24-hour Holter recordings.
Methods and results: A new risk predictor, prevalent low-frequency oscillation (PLF), was determined in the placebo population of the European Myocardial Infarction Amiodarone Trial (EMIAT). Frequencies of peaks detected in 5-minute low-frequency HRV spectra were averaged to obtain the PLF index. PLF >or=0.1 Hz was the strongest univariate predictor of all-cause mortality associated with relative risk of 6.4 (95% CI, 3.9 to 10.6; P<10(-12)). In a multivariate Cox's regression model including clinical risk factors, mean RR interval, HRV index, low- and high-frequency HRV spectral power, and heart rate turbulence, PLF was the most powerful mortality predictor, with a relative risk of 4.6 (95% CI, 2.2 to 9.3; P=0.00003). Predictive power of PLF was blindly validated in the population of the Autonomic Tone and Reflexes After Myocardial Infarction (ATRAMI) trial. PLF >or=0.1 Hz was associated with univariate relative risk of 6.1 (95% CI, 2.9 to 12.9; P<10(-5)) for cardiac mortality or resuscitated cardiac arrest. In multivariate Cox's regression model including age, left ventricular ejection fraction, baroreflex sensitivity, mean RR interval, standard deviation of normal RR intervals, low- and high-frequency HRV spectral power, and heart rate turbulence, only left ventricular ejection fraction and PLF were significant predictors, with relative risks of 4.2 (95% CI, 1.5 to 11.7; P=0.007) and 3.6 (95% CI, 1.3 to 10.5; P=0.02), respectively.
Conclusions: An innovative analysis of frequency-domain HRV, which characterizes the distribution of spectral power within the low-frequency band, is a potent and independent risk stratifier in postinfarction patients.