Non-linear Indices of Heart Rate Variability in Heart Failure Patients during Sleep

Abstract

In recent times researchers have manifested an interest towards non-linear analysis of the HRV signal, which might provide more significant diagnostic and prognostic information than the traditionally used approaches in pathological conditions characterized by reduced variability (such as, among others, Heart Failure, HF). The aim of the present study was to investigate if non-linear HRV derived parameters have clinical relevance in HF, specifically during the night.

The study was conducted on ten normal subjects and ten HF patients. For each subject HRV signal portions corresponding to daytime and nighttime were selected and a set of non-linear parameters were calculated.

Changes were observed between the parameters extracted from the signals acquired during the day and during the night and between the two populations. Significant differences were found between the two populations for some of the parameters evaluated from night recordings. Parameters which were able to discriminate between the two groups during sleep included Detrended Fluctuation Analysis index DFA1 (p-value = 0.0037), Fractal Slope (p-value = 0.0040), Sample Entropy (p-value = 0.0445) and Poincaré indices P1 (p-value = 0.0083) and P2 (p-value = 0.0061). Interestingly, the same parameters were not able to discriminate between the two groups during wakefulness. Our results confirm the possibility of using non-linear parameters derived from HRV signals recorded during sleep to discriminate between normal and pathological subjects.