Estimating cardiac autonomic activity during sleep: impedance cardiography, spectral analysis, and Poincaré plots
Introduction
Estimating cardiac autonomic activity during sleep has emerged as a new focus of interest, due to the clinical importance of assessing the impact of sleep on cardiovascular activity. Cardiac autonomic activity in humans is necessarily assessed with noninvasive techniques. A number of sleep studies have used a measure derived from Poincaré plots of consecutive R-R intervals, the autocorrelation coefficient rRR, to examine ‘sympathovagal’ balance (Schechtman et al., 1992, Otzenberger et al., 1997, Otzenberger et al., 1998, Spiegel et al., 1999, Ehrhart et al., 2000). These studies have consistently shown that rRR oscillates in synchrony with NREM-REM sleep cycles (Schechtman et al., 1992, Otzenberger et al., 1997, Otzenberger et al., 1998, Ehrhart et al., 2000). The physiological significance of the rRR index remains, however, unclear as this index has not been carefully validated by pharmacological blockades. In other studies (e.g. Trinder et al., 2001), cardiac autonomic activity during sleep was estimated using extensively validated measures; i.e. high frequency power from the spectral analysis of R-R intervals and pre-ejection period from impedance cardiography, that are purported to specifically reflect cardiac parasympathetic (vagal) and cardiac sympathetic activity, respectively. We performed a direct comparison of these measures in order to explore the potential physiological significance of changes in rRR during sleep, and to present a general overview of these measures.
While many measures of autonomic activity can be derived from the electrocardiograph (ECG), the most commonly used are the high frequency (HF) and low frequency (LF) measures. These measures are derived from the spectral analysis of R-R intervals that are typically selected from a 2–5 min period of stable ECG activity (see reviews Ori et al., 1992, Kamath and Fallen, 1993). Briefly, the spectral analysis produces a power spectrum ranging from 0 to ∼0.40 Hz (Fig. 1, bottom left). The HF measure is usually calculated as the area under the curve within the range of 0.15–0.40 Hz, and the LF measure is often calculated as the area under the curve within the range of 0.04–0.15 Hz (see review by Berntson et al., 1997). As the power in these bands can vary widely within and between individuals, the absolute power of LF and HF can be ‘normalized’ by dividing the power in each band by the total power minus DC noise (0.04–0.40 Hz). Thus the resulting ‘LFn.u.’ and ‘HFn.u.’ (n.u.=normalized units) can theoretically vary between 0 and 1 and HFn.u.+LFn.u.=1.
HF is a well-accepted noninvasive measure of cardiac parasympathetic activity in humans. HF is believed to largely reflect the degree of respiratory sinus arrhythmia in the ECG; R-R intervals increase during expiration and decrease during inspiration. Detailed studies have shown that only parasympathetic fibers contribute to the generation of respiratory sinus arrhythmia (see Berntson et al., 1993, Berntson et al., 1997). Indeed, pharmacological blockade studies have shown that HF specifically reflects cardiac parasympathetic activity (e.g. Akselrod et al., 1981, Pomeranz et al., 1985, Cacioppo et al., 1994). Others have suggested that HFn.u. is also a relatively pure measure of cardiac parasympathetic activity (Malliani et al., 1991, Malliani et al., 1994), although as part of its derivation, HFn.u. will include power in the LF band, which as described below, may mean that HFn.u. reflects both sympathetic and parasympathetic activity. Much of the early work that explored sleep and circadian influences on cardiac parasympathetic activity only reported HFn.u. (e.g. Burgess et al., 1996, Burgess et al., 1997).
Pharmacological blockade studies have also revealed that contrary to some reports (Malliani et al., 1991, Malliani et al., 1994), LF is not a specific measure of cardiac sympathetic activity (e.g. Akselrod et al., 1981, Pomeranz et al., 1985). Instead, the general consensus is that LF and LFn.u. most likely reflect a mix of both parasympathetic and sympathetic influences (see review by Berntson et al., 1997). Despite this, the ease of calculating LF (particularly if HF is also being calculated) has led to its continued use by some as a marker of cardiac sympathetic activity. The LF/HF ratio is often calculated as a marker of ‘sympathovagal balance’ (Malliani et al., 1991, Malliani et al., 1994).
The best validated measure of cardiac sympathetic activity is pre-ejection period (PEP). PEP (Fig. 1, middle right) is derived from impedance cardiography (Sherwood et al., 1990). In brief, a small harmless externally generated electrical signal is passed across the chest and the change in impedance across time (dZ/dt) is measured. PEP is the time interval between the Q wave on the ECG signal and the ‘B point’ on the dZ/dt signal. Physiologically, PEP represents the time interval in which the left ventricle, that is largely innervated by β-adrenergic sympathetic fibers, contracts while both the aortic and mitral valves are closed. Systematic pharmacological blockade studies have supported the use of PEP as a specific measure of cardiac sympathetic activity (e.g. Cacioppo et al., 1994, Schachinger et al., 2001). As sympathetic activity increases, PEP shortens.
Poincaré plots (Fig. 1, bottom right) are calculated by plotting each R-R interval, against the following R-R interval (R-Rn vs. R-Rn+1). From these data points, the correlation coefficient rRR can be calculated. This coefficient can theoretically vary between 0 and 1. To date, only two studies have examined Poincaré plots during pharmacological blockades (Zemaityte et al., 1984, Kamen et al., 1996). While Kamen et al. suggested that measures derived from the plots are relatively pure measures of cardiac parasympathetic activity, neither study specifically assessed rRR. Thus the validity of rRR as a specific measure of cardiac parasympathetic activity remains uncertain. If rRR is a specific measure of cardiac parasympathetic activity then we expect it to correlate highly with HF but not with PEP. Previous reports found a weak correlation between rRR and HF during sleep (mean r=−0.19, Otzenberger et al., 1998), but no study has yet examined the relationship between rRR and PEP.
Thus the current study had two aims. The first was to examine the relationship between rRR and specific measures of cardiac autonomic activity, HF and PEP, in order to assess the potential physiological significance of rRR. The second broader aim was to examine the relationships between HFn.u., LFn.u., LF/HF, PEP, and rRR during night-time sleep episodes and in doing so, to present for the first time, a general overview of the advantages and disadvantages of these separate measures, which are often used to evaluate changes in cardiac autonomic control during sleep.
Section snippets
Subjects
Nine young males (mean±SE; age 23.3±5.5 years, body mass index 21.6±2.6 kg/m2) participated. All subjects were healthy with no clinically significant neurological, psychiatric and sleep disorders. They also had no chronic medical conditions requiring active treatment. All subjects reported drinking less than 10 standard alcoholic drinks per week, were not night workers and had not traveled across time zones in the previous month. The study protocol was approved by the University of Chicago's
Results
All subjects slept well with mean sleep efficiency of 94.4±4.2% (SE) and normal sleep stage distribution (see Table 1). Fig. 2 shows the pattern of change in HR, PEP, HFn.u., rRR, SBP and DBP across time, during the sleep period of an individual subject. Fig. 3 shows the changes in total spectral power, HF, LF, HFn.u., LFn.u. and LF/HF during the same sleep period. We did not calculate mean profiles for the group, as this would have obscured the NREM to REM sleep transitions. The profiles of HR
Discussion
Our results suggest that rRR can track sympathovagal changes during sleep but is not a specific measure of either cardiac parasympathetic or sympathetic activity. We found a weak relationship between rRR and HF (r=0.13), of similar magnitude as the correlation reported in the single other study that correlated the two measures (average r=−0.19, Otzenberger et al., 1998). It is possible that this low correlation is due to the generally elevated cardiac parasympathetic tone during sleep, and this
Acknowledgements
We thank Drs. Kathyrn Reid and John Trinder for their comments on the manuscript. This work was supported by the following grants: NIH grants DK-41814 and AG-11412 and The University of Chicago Clinical Research Center grant RR00055.
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