Otzenberger H, Gronfier C, Simon C, Charloux A, Ehrhart J, Piquard F, Brandenberger G
Laboratoire des Régulations Physiologiques et des Rythmes Biologiques chez l'Homme, Institut de Physiologie, 67085 Strasbourg Cedex, France.
Am J Physiol. 1998 Sep;275(3):H946-50. doi: 10.1152/ajpheart.1998.275.3.H946.
We have recently demonstrated that the overnight profiles of cardiac interbeat autocorrelation coefficient of R-R intervals (rRR) calculated at 1-min intervals are related to the changes in sleep electroencephalographic (EEG) mean frequency, which reflect depth of sleep. Other quantitative measures of the Poincaré plots, i.e., the standard deviation of normal R-R intervals (SDNN) and the root mean square difference among successive R-R normal intervals (RMSSD), are commonly used to evaluate heart rate variability. The present study was designed to compare the nocturnal profiles of rRR, SDNN, and RMSSD with the R-R spectral power components: high-frequency (HF) power, reflecting parasympathetic activity; low-frequency (LF) power, reflecting a predominance of sympathetic activity with a parasympathetic component; and the LF-to-HF ratio (LF/HF), regarded as an index of sympathovagal balance. rRR, SDNN, RMSSD, and the spectral power components were calculated every 5 min during sleep in 15 healthy subjects. The overnight profiles of rRR and LF/HF showed coordinate variations with highly significant correlation coefficients (P < 0.001 in all subjects). SDNN correlated with LF power (P < 0.001), and RMSSD correlated with HF power (P < 0.001). The overnight profiles of rRR and EEG mean frequency were found to be closely related with highly cross-correlated coefficients (P < 0. 001). SDNN and EEG mean frequency were also highly cross correlated (P < 0.001 in all subjects but 1). No systematic relationship was found between RMSSD and EEG mean frequency. In conclusion, rRR appears to be a new tool for evaluating the dynamic beat-to-beat interval behavior and the sympathovagal balance continuously during sleep. This nonlinear method may provide new insight into autonomic disorders.
我们最近证实，以1分钟为间隔计算的R-R间期心脏搏动自相关系数（rRR）的夜间变化曲线与睡眠脑电图（EEG）平均频率的变化相关，而EEG平均频率反映睡眠深度。庞加莱图的其他定量指标，即正常R-R间期的标准差（SDNN）和连续正常R-R间期之间的均方根差（RMSSD），常用于评估心率变异性。本研究旨在比较rRR、SDNN和RMSSD的夜间变化曲线与R-R频谱功率成分：高频（HF）功率，反映副交感神经活动；低频（LF）功率，反映交感神经活动占主导且伴有副交感神经成分；以及LF与HF比值（LF/HF），被视为交感-迷走神经平衡指数。在15名健康受试者睡眠期间，每5分钟计算一次rRR、SDNN、RMSSD和频谱功率成分。rRR和LF/HF的夜间变化曲线显示出协同变化，相关系数高度显著（所有受试者P<0.001）。SDNN与LF功率相关（P<0.001），RMSSD与HF功率相关（P<0.001）。发现rRR和EEG平均频率的夜间变化曲线密切相关，交叉相关系数很高（P<0.001）。SDNN和EEG平均频率也高度交叉相关（除1名受试者外所有受试者P<0.001）。未发现RMSSD与EEG平均频率之间存在系统关系。总之，rRR似乎是一种在睡眠期间连续评估动态逐搏间期行为和交感-迷走神经平衡的新工具。这种非线性方法可能为自主神经功能障碍提供新的见解。
