AUTHOR=Hasegawa Mizuki , Sasaki Mayuko , Umemoto Yui , Hayashi Rio , Hatanaka Akari , Hosoki Marino , Farag Ahmed , Matsuura Katsuhiro , Yoshida Tomohiko , Shimada Kazumi , Hamabe Lina , Takahashi Ken , Tanaka Ryou 

TITLE=Exploring sleep heart rate variability: linear, nonlinear, and circadian rhythm perspectives

JOURNAL=Frontiers in Veterinary Science

VOLUME=11

YEAR=2024

URL=https://www.frontiersin.org/journals/veterinary-science/articles/10.3389/fvets.2024.1386425

DOI=10.3389/fvets.2024.1386425

ISSN=2297-1769

ABSTRACT=<sec id="sec1"><title>Background</title><p>Heart rate variability (HRV) is believed to possess the potential for disease detection. However, early identification of heart disease remains challenging, as HRV analysis in dogs primarily reflects the advanced stages of the disease.</p></sec><sec id="sec2"><title>Hypothesis/objective</title><p>The aim of this study is to compare 24-h HRV with sleep HRV to assess the potential utility of sleep HRV analysis.</p></sec><sec id="sec3"><title>Animals</title><p>Thirty healthy dogs with no echocardiographic abnormalities were included in the study, comprising 23 females and 7 males ranging in age from 2 months to 8 years (mean [standard deviation], 1.4 [1.6]).</p></sec><sec id="sec4"><title>Methods</title><p>This study employed a cross-sectional study. 24-h HRV and sleep HRV were measured from 48-h Holter recordings. Both linear analysis, a traditional method of heart rate variability analysis, and nonlinear analysis, a novel approach, were conducted. Additionally, circadian rhythm parameters were assessed.</p></sec><sec id="sec5"><title>Results</title><p>In frequency analysis of linear analysis, the parasympathetic index nHF was significantly higher during sleep compared to the mean 24-h period (mean sleep HRV [standard deviation] vs. mean 24 h [standard deviation], 95% confidence interval, <italic>p</italic> value, r-family: 0.24 [0.057] vs. 0.23 [0.045], 0.006–0.031, <italic>p</italic> = 0.005, <italic>r</italic> = 0.49). Regarding time domain analysis, the parasympathetic indices SDNN and RMSSD were also significantly higher during sleep (SDNN: 179.7 [66.9] vs. 156.6 [53.2], 14.5–31.7, <italic>p</italic> &lt; 0.001, <italic>r</italic> = 0.71 RMSSD: 187.0 [74.0] vs. 165.4 [62.2], 13.2–30.0, <italic>p</italic> &lt; 0.001, <italic>r</italic> = 0.70). In a geometric method of nonlinear analysis, the parasympathetic indices SD1 and SD2 showed significantly higher values during sleep (SD1: 132.4 [52.4] vs. 117.1 [44.0], 9.3–21.1, <italic>p</italic> &lt; 0.001, <italic>r</italic> = 0.70 SD2: 215.0 [80.5] vs. 185.9 [62.0], 17.6–40.6, <italic>p</italic> &lt; 0.001, <italic>r</italic> = 0.69). Furthermore, the circadian rhythm items of the parasympathetic indices SDNN, RMSSD, SD1, and SD2 exhibited positive peaks during sleep.</p></sec><sec id="sec6"><title>Conclusion</title><p>The findings suggest that focusing on HRV during sleep can provide a more accurate representation of parasympathetic activity, as it captures the peak circadian rhythm items.</p></sec>