A steep slope of the power-law regression line of heart rate variability (< -1.50) independently predicted all-cause mortality in elderly subjects (adjusted RR 1.74; 95% CI 1.42-2.13; P<.0001).
Cohort (n=347)
Does the power-law relationship of 24-hour heart rate variability predict mortality in elderly subjects?
Altered long-term behavior of heart rate variability, measured by a steep power-law regression slope, is a strong independent predictor of all-cause, cardiac, and cerebrovascular mortality in the elderly.
Effect estimate: adjusted RR 1.74 (95% CI 1.42 to 2.13)
p-value: p=<.0001
BACKGROUND: The prognostic role of heart rate (HR) variability analyzed from 24-hour ECG recordings in the general population is not well known. We studied whether analysis of 24-hour HR behavior is able to predict mortality in a random population of elderly subjects. METHODS AND RESULTS: A random sample of 347 subjects of > or =65 years of age (mean, 73+/-6 years) underwent a comprehensive clinical evaluation, laboratory tests, and 24-hour ECG recordings and were subsequently followed up for 10 years. Various spectral and nonspectral measures of HR variability were analyzed from the baseline 24-hour ECG recordings. Risk factors for all-cause, cardiac, cerebrovascular, cancer, and other causes of death were assessed. By the end of 10-year follow-up, 184 subjects (53%) had died and 163 (47%) were still alive. Seventy-four subjects (21%) had died of cardiac disease, 37 of cancer (11%), 25 of cerebrovascular disease (7%), and 48 (14%) of various other causes. Among all analyzed variables, a steep slope of the power-law regression line of HR variability (< -1.50) was the best univariate predictor of all-cause mortality (odds ratio, 7.9; 95% confidence interval CI, 3.7 to 17.0; P<.0001). After adjusting for age and sex and including all univariate predictors of mortality in the proportional hazards analysis, ie, measures of HR variability, history of heart disease, functional class, smoking, medication, and blood cholesterol and glucose concentrations, all-cause mortality was predicted only by the slope of HR variability (adjusted relative risk, 1.74; 95% CI, 1.42 to 2.13; P<.0001) and a history of congestive heart failure (adjusted relative risk, 1.70; P=.0002). The slope of HR variability predicted both cardiac (adjusted relative risk, 2.05; P=.0002) and cerebrovascular death (adjusted relative risk, 2.84; P=.0001) but not cancer or other causes of death. CONCLUSIONS: Power-law relationship of 24-hour HR variability is a more powerful predictor of death than the traditional risk markers in elderly subjects. Altered long-term behavior of HR implies an increased risk of vascular causes of death rather than being a marker of any disease or frailty leading to death.
Huikuri et al. (1998) conducted a cohort in General elderly population (n=347). Steep slope of the power-law regression line of HR variability (< -1.50) was evaluated on All-cause mortality (adjusted RR 1.74, 95% CI 1.42 to 2.13, p=<.0001). A steep slope of the power-law regression line of heart rate variability (< -1.50) independently predicted all-cause mortality in elderly subjects (adjusted RR 1.74; 95% CI 1.42-2.13; P<.0001).