Measures of heart period variability as predictors of mortality in hospitalized patients with decompensated congestive heart failure.

Depressed heart rate variability (HRV) is a powerful independent predictor of a poor outcome in patients with chronic and stable congestive heart failure (CHF). However, the prognostic value of HRV analysis in patients hospitalized for decompensated CHF is not known. The aim of this study was to investigate whether HRV parameters obtained during admission for decompensated CHF could predict survival after hospital discharge. We studied 199 patients (131 men, aged 60 +/- 14 years) with a previous diagnosis of New York Heart Association class III or IV CHF who were admitted to the hospital for decompensated CHF. Twenty-four-hour Holter recordings were obtained on admission, and measures of HRV were calculated in the time and frequency domain. During a mean follow-up of 312 +/- 150 days, 40 patients (21.1%) died. Kaplan-Meier analysis indicated that patients with SD of the RR intervals over a 24-hour period (p = 0.027), SD of all 5-minute mean RR intervals (p = 0.043), total power (p = 0.022), and ultra-low-frequency power (p = 0.008) in the lower tertile were at a higher risk of death. In a multivariate Cox regression model, the same indexes in the lower tertile were independent predictors of mortality: SD of the RR intervals over a 24-hour period (risk ratio [RR] 2.2, 95% confidence interval [CI] 1.05 to 4.3, p = 0.036), SD of all 5-minute mean RR intervals (RR 2.1, 95% CI 1.05 to 4.2, p = 0.04), total power (RR 2.2, 95% CI 1.08 to 4.2, p = 0.03), and ultra-low-frequency power (RR 2.6, 95% CI 1.3 to 5.3, p = 0.007). Therefore, the severity of autonomic perturbations during hospital admission for CHF decompensation, as reflected by measures of overall HRV, can predict survival after hospital discharge. Together with previous studies, our findings suggest that indexes of overall HRV provide useful prognostic information in the full spectrum of CHF severity.