Linear and non-linear 24 h heart rate variability in chronic heart failure

It has recently been demonstrated that SDNN of heart rate variability (HRV) is a useful independent prognostic tool in chronic heart failure (CHF). The purpose of the present study was to evaluate if spectral and non-linear analysis of 24-h HRV, considered markers of autonomic cardiac modulation, contain independent prognostic information in CHF patients. Twenty normal subjects and thirty consecutive outpatients with clinically stable CHF were studied for 2 years. Periods of 300 R–R intervals were analyzed from Holter recordings. The power spectral analysis, the slope of the linear relationship between log-power versus log-frequency (1/f), and the complexity content (using corrected conditional entropy; CCE) of the R–R series were calculated. The normalized power of the low frequency spectral component (LF) and the 1/f slope were significantly lower in patients compared to controls (respectively 30.1±3.0 vs. 48.6±3.4 and −1.27±0.04 vs.−1.08±0.05; P<0.05). Moreover, the patients who died during the study presented a reduced LF (20.9±4.1 vs. 35.5±3.5 nu; P<0.05) and a steeper 1/f slope (−1.40±0.09 vs. −1.21±0.04 nuts, P<0.05) compared to survivors. These results remained significant in a logistic model including heart rate and SDNN. The information content present in spectral and non-linear analysis of HRV in CHF patients has prognostic relevance independently from the time domain measures of HRV. In particular, the reduction of LF power seems the best indicator among those considered.