A reduced short-term scaling exponent alpha(1) (<0.75) independently predicted all-cause mortality (RR 3.0; 95% CI 2.5 to 4.2; P<0.001) in survivors of acute MI with depressed LV function.
Cohort (n=446)
Does fractal analysis of short-term R-R interval dynamics predict mortality better than traditional heart rate variability measures in survivors of acute myocardial infarction with depressed left ventricular function?
Fractal analysis of short-term R-R interval dynamics provides powerful prognostic information for mortality in post-MI patients with depressed LV function, outperforming traditional heart rate variability measures.
Effect estimate: RR 3.0 (95% CI 2.5 to 4.2)
p-value: p=<0.001
BACKGROUND: Preliminary data suggest that the analysis of R-R interval variability by fractal analysis methods may provide clinically useful information on patients with heart failure. The purpose of this study was to compare the prognostic power of new fractal and traditional measures of R-R interval variability as predictors of death after acute myocardial infarction. METHODS AND RESULTS: Time and frequency domain heart rate (HR) variability measures, along with short- and long-term correlation (fractal) properties of R-R intervals (exponents alpha(1) and alpha(2)) and power-law scaling of the power spectra (exponent beta), were assessed from 24-hour Holter recordings in 446 survivors of acute myocardial infarction with a depressed left ventricular function (ejection fraction </=35%). During a mean+/-SD follow-up period of 685+/-360 days, 114 patients died (25.6%), with 75 deaths classified as arrhythmic (17.0%) and 28 as nonarrhythmic (6.3%) cardiac deaths. Several traditional and fractal measures of R-R interval variability were significant univariate predictors of all-cause mortality. Reduced short-term scaling exponent alpha(1) was the most powerful R-R interval variability measure as a predictor of all-cause mortality (alpha(1) <0.75, relative risk 3.0, 95% confidence interval 2.5 to 4.2, P<0.001). It remained an independent predictor of death (P<0.001) after adjustment for other postinfarction risk markers, such as age, ejection fraction, NYHA class, and medication. Reduced alpha(1) predicted both arrhythmic death (P<0.001) and nonarrhythmic cardiac death (P<0.001). CONCLUSIONS: Analysis of the fractal characteristics of short-term R-R interval dynamics yields more powerful prognostic information than the traditional measures of HR variability among patients with depressed left ventricular function after an acute myocardial infarction.
Huikuri et al. (Tue,) conducted a cohort in Acute myocardial infarction with depressed left ventricular function (n=446). Reduced short-term scaling exponent alpha(1) (<0.75) vs. Traditional measures of HR variability was evaluated on All-cause mortality (RR 3.0, 95% CI 2.5 to 4.2, p=<0.001). A reduced short-term scaling exponent alpha(1) (<0.75) independently predicted all-cause mortality (RR 3.0; 95% CI 2.5 to 4.2; P<0.001) in survivors of acute MI with depressed LV function.