■心率变异性(HRV)被认为具有疾病检测的潜力。然而,早期识别心脏病仍然具有挑战性,因为犬的HRV分析主要反映了疾病的晚期阶段。
■本研究的目的是将24小时HRV与睡眠HRV进行比较,以评估睡眠HRV分析的潜在实用性。
■本研究纳入了30只无超声心动图异常的健康犬,包括23名女性和7名男性,年龄从2个月到8岁不等(平均值[标准差],1.4[1.6])。
■这项研究采用了横断面研究。从48小时Holter记录中测量24小时HRV和睡眠HRV。两者都是线性分析,传统的心率变异性分析方法,和非线性分析,一种新颖的方法,进行了。此外,对昼夜节律参数进行评估。
■在线性分析的频率分析中,与平均24小时期间相比,睡眠期间副交感神经指数nHF明显更高(平均睡眠HRV[标准偏差]与平均24小时[标准偏差],95%置信区间,p值,r系列:0.24[0.057]vs.0.23[0.045],0.006-0.031,p=0.005,r=0.49)。关于时域分析,睡眠期间副交感神经指数SDNN和RMSSD也显著升高(SDNN:179.7[66.9]vs.156.6[53.2],14.5-31.7,p<0.001,r=0.71RMSSD:187.0[74.0]vs.165.4[62.2],13.2-30.0,p<0.001,r=0.70)。在非线性分析的几何方法中,副交感神经指数SD1和SD2在睡眠期间显示出较高的值(SD1:132.4[52.4]与117.1[44.0],9.3-21.1,p<0.001,r=0.70SD2:215.0[80.5]vs.185.9[62.0],17.6-40.6,p<0.001,r=0.69)。此外,副交感神经指数SDNN的昼夜节律项目,RMSSD,SD1和SD2在睡眠期间表现出正峰值。
■研究结果表明,在睡眠期间关注HRV可以更准确地表示副交感神经活动,因为它捕获了峰值昼夜节律项目。
UNASSIGNED: 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.
UNASSIGNED: The aim of this study is to compare 24-h HRV with sleep HRV to assess the potential utility of sleep HRV analysis.
UNASSIGNED: 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]).
UNASSIGNED: 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.
UNASSIGNED: 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, p value, r-family: 0.24 [0.057] vs. 0.23 [0.045], 0.006-0.031, p = 0.005, r = 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, p < 0.001, r = 0.71 RMSSD: 187.0 [74.0] vs. 165.4 [62.2], 13.2-30.0, p < 0.001, r = 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, p < 0.001, r = 0.70 SD2: 215.0 [80.5] vs. 185.9 [62.0], 17.6-40.6, p < 0.001, r = 0.69). Furthermore, the circadian rhythm items of the parasympathetic indices SDNN, RMSSD, SD1, and SD2 exhibited positive peaks during sleep.
UNASSIGNED: 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.