Reliability of heart rate variability during stable and disrupted polysomnographic sleep

Abstract

Heart rate variability (HRV) is commonly used within sleep and cardiovascular research, yet HRV reliability across various sleep stages remains equivocal. The present study examined the reliability of frequency- and time-domain HRV within stage II (N2), slow wave (SWS), and rapid eye movement (REM) sleep during both stable and disrupted sleep. We hypothesized that high-frequency (HF) HRV would be reliable in all three sleep stages, low-frequency (LF) HRV would be reliable during N2 and SWS, and that disrupted sleep via spontaneous cortical arousals would decrease HRV reliability. Twenty-seven participants (11 male, 16 female, 26±1 years) were equipped with laboratory polysomnography for one night. Both frequency- and time-domain HRV were analyzed in two 5-10 minute blocks during multiple stable and disrupted sleep cycles across N2, SWS and REM sleep. HF HRV was highly correlated across stable N2 (r=0.839, p<0.001), SWS (r=0.765, p<0.001) and REM (r=0.881, p<0.001). LF HRV was moderate-to-highly correlated during stable cycles of N2 sleep (r=0.694, p < 0.001), SWS, (r=0.765, p < 0.001), and REM (r=0.699, p<0.001) sleep. When stable sleep was compared with disrupted sleep, both time- and frequency-domain HRV were reliable (α>0.90, p<0.05) in N2, SWS, and REM, with the exception of LF HRV during SWS (α=0.62, p=0.089). In conclusion, time- and frequency-domain HRV demonstrated reliability across stable N2, SWS and REM sleep, and remained reliable during disrupted sleep. These findings support the use of HRV during sleep as a tool for assessing cardiovascular health and risk stratification.

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“…However, the use of RMSSD is recommended for studies in natural field settings, as this parameter is less affected by breathing than other parasympathetic activity indicators (Laborde et al, 2017). Resting levels of RMSSD have high reliability (Guijt et al, 2007; Herzig et al, 2018; Kerkering et al, 2022) and stability, especially when using aggregated values across at least two measurement times (Bertsch et al, 2012). However, RMSSD can be changed by interventions (Lin et al, 2015; Zhu et al, 2017).…”

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“…Furthermore, averaging HRV over the whole night is advisable as it decreases the variance in HRV in different sleep stages (Herzig et al., 2018). In addition, resting levels of HRV have high reliability (Alida et al., 2007; Herzig et al., 2018; Kerkering et al., 2022) and stability (Bertsch et al., 2012), when aggregated values across at least two measurement times are used (Bertsch et al., 2012).…”

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“…The data were analyzed using analysis of variance (ANOVA). Statistical significance was indicated by α = 0.05 and β = 0.2 with an effect size = 0.3 [45]. F tests and repeated-measures ANOVA were used to examine within-between interactions.…”