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. 1999 Mar 15;515(Pt 3):887–896. doi: 10.1111/j.1469-7793.1999.887ab.x

Assessment of cardiac sympathetic regulation by respiratory-related arterial pressure variability in the rat

Cheryl C H Yang *, Terry B J Kuo *
PMCID: PMC2269192  PMID: 10066913

Abstract

  1. Mechanical ventilation evokes a corresponding arterial pressure variability (APV) which is decreased by β-adrenoceptor antagonism. Therefore, in this study we set out to determine whether the respiratory-related APV can be used to assess cardiac sympathetic tone.

  2. Computer-generated broad-band mechanical ventilation (0–3 Hz) was applied to Sprague-Dawley rats that had been anaesthetized with ketamine and paralysed with pancuronium. APV and its relationship to lung volume variability (LVV–APV) was systematically quantified with auto- or cross-spectral frequency domain analysis.

  3. APV and LVV–APV transfer magnitudes between 0.5 and 1.5 Hz showed dose-dependent suppression by propranolol from 0.01 to 1 mg kg−1, while the static value of arterial pressure remained unchanged. Stroke volume variability, assessed by the use of a pulse contour method, exhibited a similar pattern of suppression by propranolol. In contrast, heart rate variability was not lowered with propranolol.

  4. The effect of propranolol on respiratory-related APV persisted even in the presence of combined α-adrenoceptor and muscarinic receptor blockade by phentolamine and atropine.

  5. The frequency range of 0.5–1.0 Hz was optimal for LVV–APV transfer magnitude to correlate with cardiac sympathetic tone.

  6. We conclude that respiratory-related APV may provide a valid assessment of cardiac sympathetic regulation which is independent of parasympathetic and vascular sympathetic influences in ketamine-anaesthetized and positive pressure-ventilated rats.

Neural regulation of the heart is maintained by the integration of sympathetic and parasympathetic outflow. Both autonomic divisions are essential in the maintenance of a normal cardiac function and under conditions related to various pathological states. Abnormal activation of cardiac sympathetic regulation and/or lack of presumably protective parasympathetic autonomic tone may result in lethal arrhythmia, which is a major cause of sudden death (Schwartz et al. 1992). Thus it is not surprising that numerous efforts have been made to develop adequate monitoring techniques for the autonomic nervous system. Among these techniques, frequency domain analysis of heart rate variability (HRV) has become the most useful in recent years and has many potential applications (Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology, 1996). Our laboratory has demonstrated the applicability of HRV to assist in the prognosis of critical illness (Yien et al. 1997) and to differentiate brain death from vegetative state (Kuo et al. 1997b). With the computer algorithm for Fourier transform or autoregression, HRV can be distinguished in two variants: the respiratory-related high frequency power (HF) and the vasomotor-related low frequency power (LF). Representation of vagal activity by HF has been widely accepted, but the quantitative estimate of cardiac sympathetic modulation by LF remains controversial. For example, LF of HRV is jointly modulated by vagal and sympathetic control (Berger et al. 1989) and has been shown to increase with β-adrenoceptor blockade (Niemela et al. 1994). Recently, Montano et al. (1994) reported that LF of HRV in normalized units (LF%) is well correlated with sympathetic activation induced by tilt. However, it is not clear whether LF% or LF to HF ratio represents absolute sympathetic modulation of the heart, or merely reflects the relative value of sympathovagal balance.

Given the present monitoring techniques for cardiac sympathetic regulation, it is difficult to find an ideal index which is both accessible and accurate. While the absolute value of heart rate (HR) is the most accessible index of sympathetic activation, it is nevertheless severely confounded by vagal activity. Plasma catecholamine concentration and recording of muscle sympathetic fibres (Pagani et al. 1997) are also widely applied as indices for sympathetic function; however, they require special instrumentation and do not specifically reflect the cardiac division of the sympathetic system.

Although not as popular as HRV, arterial pressure variability (APV) also carries important information about the body (Pagani et al. 1986). The recent development of a non-invasive method for measuring arterial pressure has further extended the applicability of APV (Kuo et al. 1998). As in the case of HRV, APV can also be divided into respiratory and vasomotor components. It has been reported that vasomotor-related APV is correlated to vascular sympathetic function via α-adrenoceptors (Cerutti et al. 1991; Kuo et al. 1997a). In a recent study concerning the dynamic relationship between lung volume variability (LVV) and APV, we found that β-adrenoceptor blockade dramatically decreases respiratory-related APV in the anaesthetized, mechanically ventilated rat. Furthermore, this effect was found to be independent of vagal function (Kuo et al. 1996). In the present study, we were interested in determining whether respiratory-related APV can adequately express graded changes in cardiac sympathetic tone under various autonomic states. If such a relationship exists, it would be possible to assess cardiac sympathetic regulation from respiratory-related APV. Since frequency domain analysis of transfer function can be used to assess the relationship between two variabilities (Kuo et al. 1996), it is suitable for quantifying the APV in relation to unit LVV. We hypothesized that respiratory-related APV or LVV-APV transfer magnitude may provide a valid index for cardiac sympathetic regulation which is independent of vagal and vascular sympathetic function in the ketamine-anaesthetized and positive pressure-ventilated rat.

METHODS

Preparation of animals

Experiments were carried out on adult male Sprague-Dawley rats (260–300 g). Each experimental group consisted of eight animals. Animals were initially anaesthetized with ketamine (120 mg kg−1i.p.), under which preparatory surgery was performed. The surgery included intubation of the trachea to facilitate ventilation, and cannulation of both femoral veins for injection of drugs and infusion of anaesthetic and muscle relaxant.

As in our previous study (Kuo et al. 1996), rats were maintained under ketamine infusion of 50 mg kg−1 h−1i.v. The adequacy of anaesthesia was continuously assessed by on-line monitoring of the power spectrum of arterial pressure and heart rate signals (Kuo & Chan, 1993; Yang et al. 1996). As a further precaution, all surgical incision sites were topically treated with 0.25 % bupivacaine, a long-acting local anaesthetic agent. It was only after the satisfactory establishment of these conditions that animals were paralysed by infusion of pancuronium (2 mg kg−1 h−1i.v.) and mechanically ventilated at a stroke volume of 2.5 ml. Animals were killed at the end of the experiment by an overdose of intravenous pentobarbitone.

Control of mechanical ventilation

The rate control circuit of the ventilator (Harvard 683) was modified to receive control signals from a digital-to-analog converter (Advantech PCL1800) regulated by a computer (IBM PC compatible). Under the regular mode, the computer was programmed to maintain a constant ventilatory rate of 1.5 Hz. During the test period, the computer output was switched to an irregular mode, during which the ventilatory rate varied randomly from 0 to 3 Hz, with a mean rate of 1.5 Hz. The purpose of irregular ventilation was to generate a broad-band ventilatory spectrum as an input signal for transfer function analysis. Thus the power spectrum of the ventilatory drive chain was nearly flat without preferred peaks (Kuo et al. 1996). Each test period lasted for 180 s, and ventilation was returned to a regular mode between tests. For the purpose of reproducibility, our computer program reset the sequence of randomized signals to the ventilator after each test. Thus, essentially the same pattern of irregular ventilation was delivered to the animal during every test period.

Recording of respiratory airflow, arterial pressure and electrocardiogram

Respiratory airflow was detected by a pneumotachometer (Gould 369500–45001 and Fleisch no. 0000) that was inserted along the trachea tube. The pneumotachometer was connected to a differential pressure transducer (Validyne P300D) coupled to a universal amplifier (Gould G-20-4615-58). A calibrated syringe was used for calibration of the pneumotachometer-transducer system. The left femoral artery was cannulated with a 20 cm PE-50 catheter filled with heparinized saline (200 u ml−1). The arterial catheter was connected to a pressure transducer (Statham P23ID) and, in turn, to a universal amplifier (Gould G-20-4615-58). The catheter-transducer system had a damped natural frequency of 40 Hz and showed a flat amplitude response with no phase shift to 20 Hz. Both airflow and arterial pressure signals were amplified and filtered (frequency range, 0–100 Hz), and were acquired by a 12-bit analog-to-digital converter (Advantech PCL 1800) at a sampling rate of 256 Hz, which satisfied the requirement of the Nyquist theorem (Nyquist, 1928). Lead II electrocardiogram was also amplified and filtered (3–300 Hz) by a universal amplifier (Gould G-20-4615-58), and was synchronously acquired with the flow and pressure signals at a sampling rate of 2048 Hz. The computer was a general-purpose personal computer (IBM PC compatible). The acquired data were analysed on-line but were simultaneously stored on an optical disk system (Fujitsu M2512A) for subsequent off-line verification.

Average periodogram and transfer function analysis of lung volume, arterial pressure, stroke volume and HR signals

Instantaneous lung volume signals were obtained by digital integration of the bi-directional airflow signals. The raw arterial pressure signals were first normalized to their mean value and were expressed by percentage variation from the mean arterial pressure (unit). This normalization procedure made the subsequent spectral and transfer function analysis independent of an absolute mean value. Original lung volume and normalized arterial pressure signals were subjected to off-line spectral analysis by the construction of an average periodogram (Kuo et al. 1996; Yang et al. 1996; Kuo et al. 1998). For this purpose, the signals to be analysed were first subjected to an 8-point average algorithm which essentially reduced the sampling rate to 32 Hz. These were subsequently truncated into 16 s (512 point) epochs with 50 % overlap. For each epoch, the linear trend was removed to avoid its contribution to the power of lower frequencies. A Hamming window in the time domain was used to attenuate the leakage effect. Power spectral analysis of lung volume or arterial pressure signals was accomplished by fast Fourier transform, and an average periodogram of lung volume or arterial pressure signals was generated by averaging the autospectra from 16 epochs.

Cross-spectral analysis was carried out on the same 16 epochs of lung volume and arterial pressure signals used in average periodogram analysis, which led to the estimation of transfer function:

graphic file with name tjp0515-0887-m1.jpg (1)

where f is any given frequency, SBR(f) is the cross-spectrum and SRR(f) is the auto-spectrum of the lung volume signal. The magnitude of H(f) is defined as:

graphic file with name tjp0515-0887-m2.jpg (2)

where HR(f) and HI(f) are the real and imaginary parts of the complex transfer function, respectively, and H(f) is expressed in units per millilitre.

Beat-to-beat measurement of the left ventricular stroke volume was obtained by the pulse contour method (Jardin et al. 1983) according to the following formula (Kouchoukos et al. 1970):

graphic file with name tjp0515-0887-m3.jpg (3)

where SV is stroke volume index in millilitres per square metre, K is an arbitrary constant, Psa is the area under the systolic portion of the pressure curve above a horizontal line drawn from the diastolic pressure and bounded by a vertical line through the lowest point in the incisura, Ts is the duration of systole, and Td is the duration of diastole. Beat-to-beat measurement of HR was obtained from the digitized electrocardiogram. Our computer algorithm first detected the R point of each QRS complex, from which HR was calculated, from the reciprocal of the R-R interval. The stroke volume and HR signals were re-sampled and interpolated at a rate of 32 Hz to accomplish the continuity in time domain. As in the case for arterial pressure signals, the stroke volume and HR signals were also normalized to their mean values and were expressed by percentage variation from the mean value (unit). They were subjected to the same procedure described above for the construction of the average periodogram and subsequent transfer function analysis of the relationship with LVV.

Experimental protocols

The effects of graded β-adrenoceptor blockade on respiratory-related APV were evaluated in the first series of experiments. A control test with irregular ventilation was delivered initially. This was followed by an intravenous injection of saline and incremental doses of propranolol (0.01, 0.1 and 1 mg kg−1) to produce vehicle control and graded β-adrenoceptor blockade. Tests with irregular ventilation were performed 5 min after each administration. By excluding the participation of the α-adrenergic and cholinergic systems with phentolamine (2.5 mg kg−1) and atropine (0.3 mg kg−1) (Kuo et al. 1996), our second series of experiments delineated the dominant contribution of the β-adrenergic system to respiratory-related APV. A control test with irregular ventilation was delivered first. This was followed by intravenous injection of combined phentolamine and atropine, followed by incremental doses of propranolol (0.01, 0.1 and 1 mg kg−1). Tests with irregular ventilation were performed 5 min after each administration. The third series of experiments demonstrated the effect of propranolol on respiratory-related stroke volume variability. The time schedule of drug administration or analysis was the same as that for the first experiment.

Statistical analysis

The power of LVV, APV or stroke volume variability was quantified by integration of the average periodogram between 0.0 and 0.5, 0.5 and 1.0, and 1.0 and 1.5 Hz. The frequency ranges were determined from our previous observation that respiratory-related APV below 2.0 Hz is more pronounced, which is useful in demonstrating the suppressive effect of propranolol. The relationship between two variabilities was assessed by the corresponding transfer magnitude in each frequency range. Values are expressed as means ±s.e.m. Data between groups were compared by Student's t test or a repeated measures analysis of variance followed by Duncan's multiple range tests for a posteriori comparison of individual means. Differences were considered statistically significant at P < 0.05.

RESULTS

The ventilatory rate was varied within a wide range during testing. Since the mean values for ventilatory rate and tidal volume were not changed, the minute ventilation before or during the test period was the same. Figure 1 provides an example of the effect of programmed irregular ventilation on the static value and variability of arterial pressure, stroke volume and HR before, during and after testing. During the test period, arterial pressure and stroke volume variability were noticeably evoked. However, their static value essentially remained unchanged (Table 1), indicating that possible respiratory distress on the cardiovascular function due to short term irregular ventilation was insignificant.

Figure 1. Irregular mechanical ventilation technique.

Figure 1

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The ventilatory rate was fixed at 1.5 Hz before and after each test period. During the test period, the ventilatory rate varied randomly from 0 to 3 Hz, with a mean value of 1.5 Hz, and the lung volume (LV) was essentially unchanged. Note the irregular fluctuations in arterial pressure (AP) and stroke volume (SV) signals during the test period, and their return to baseline status after the test period. In contrast, the fluctuation in heart rate (HR) was minimal (bpm, beats min−1).

Table 1.

Static value of arterial pressure (mmHg) under each of the conditions of the study

Propranolol (mg kg−1 I.V.)
Ventilation Control Pretreatment 0.01 0.1 1
Saline pretreatment Regular 112 ± 5 107 ± 8 111 ± 7 109 ± 6 108 ± 6
Irregular 117 ± 5 104 ± 9 113 ± 8 107 ± 4 111 ± 6
Phentolamine(2.5 mg kg−1 I.V.) and tropine (0.3 mg kg−1 I.V.) pretreatment Regular 115 ± 5 62 ± 3* 69 ± 3 74 ± 4 72 ± 3
Irregular 118 ± 6 65 ± 4* 73 ± 5 76 ± 5 76 ± 4
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Values are expressed as means ± S.E.M., n =8.

*

P < 0.05vs. corresponding value of the preceding treatment by Duncan's multiple range test. No significant difference was detected between regular and irregular ventilation by Student's t test.

Effect of propranolol on the static value of arterial pressure and respiratory-related APV

Pretreatment with saline caused no discernible effects on the static (Table 1) and dynamic (Fig. 2B, APV) components of arterial pressure. Intravenous administration of propranolol significantly suppressed respiratory-related APV (Fig. 2A); however, the static value of arterial pressure remained unaffected (Table 1). The dose-response dependency between propranolol and respiratory-related APV was particularly evident within the frequency ranges of 0.5 to 1.5 Hz but was less notable below 0.5 Hz. Propranolol also suppressed LVV-APV transfer magnitude (Fig. 2B) in a dose-dependent manner between frequency ranges of 0.5 and 1.5 Hz.

Figure 2. Effect of propranolol on respiratory-related APV.

Figure 2

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A, time domain illustration of lung volume (LV) and arterial pressure (AP) signals before (a) and 5 min after (b) i.v. administration of propranolol (1 mg kg−1). B, frequency domain analysis of the effect of propranolol (Pro; 0.01–1 mg kg−1i.v.) on LVV, APV and LVV-APV transfer magnitude following pretreatment with saline. Values are presented as means ±s.e.m., n = 8 rats. *P < 0.05 vs. corresponding value of the preceding treatment by Duncan's multiple range test.

Effect of propranolol on the static value of arterial pressure and respiratory-related APV following systemic α-adrenoceptor and muscarinic receptor blockade

Pretreatment with phentolamine (2.5 mg kg−1i.v.) and atropine (0.3 mg kg−1i.v.) achieved a combined α-adrenoceptor and muscarinic receptor blockade (Kuo et al. 1996) and elicited profound hypotension (Table 1). However, such pretreatment caused an increase in respiratory-related APV and LVV-APV transfer magnitude in the frequency ranges between 0.5 and 1.5 Hz (Fig. 3). Following the pretreatment, all the above parameters still showed a dose-dependent response to propranolol.

Figure 3. Effect of propranolol on respiratory-related APV following systemic α-adrenoceptor and muscarinic receptor blockade.

Figure 3

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Frequency domain analysis of the effect of propranolol (Pro; 0.01–1 mg kg−1i.v.) on LVV, APV and LVV-APV transfer magnitude following combined pretreatment with phentolamine (Phe; 2.5 mg kg−1i.v.) and atropine (Atr; 0.3 mg kg−1i.v.). Values are presented as means ±s.e.m., n = 8. *P < 0.05 vs. corresponding value with the preceding treatment by Duncan's multiple range test.

Correlation between HR and LVV-APV transfer magnitude

Since HR under systemic α-adrenoceptor and muscarinic receptor blockade is determined largely by cardiac sympathetic tone, we performed linear regression analysis between HR and LVV-APV transfer magnitude in each frequency range to demonstrate the optimal frequency range in which respiratory-related APV best correlated with cardiac sympathetic tone (Table 2). Following pretreatment with phentolamine and atropine, we found that LVV-APV transfer magnitude in the frequency range of 0.5–1.0 Hz best correlated with HR in all frequency ranges. This was also true in the case of saline pretreatment. The relationship between HR and LVV-APV transfer magnitude in the frequency range of 0.5–1.0 Hz is shown in Fig. 4. Despite the graded suppression of HR and LVV-APV transfer magnitude by propranolol following pretreatment with saline or combined phentolamine and atropine, the static value of arterial pressure remained essentially unchanged (Table 1).

Table 2.

Correlation coefficient between heart rate and LVV–APV transfer magnitude at different frequency ranges

0.0–0.5(Hz) 0.5–1.0(Hz) 1.0–1.5(Hz)
Saline pretreatment 0.83 ± 0.02 0.93 ± 0.01* 0.89 ± 0.02
Phentolamine(2.5 mg kg−1 I.V.) and atropine (0.3 mg kg−1 I.V.) pretreatment 0.76 ± 0.03 0.93 ± 0.02* 0.87 ± 0.02
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Frequency range values are expressed as means ± s.e.m., n = 8.

*

P < 0.05vs. other frequency ranges by Duncan's multiple range test.

Figure 4. Correlation between heart rate and transfer magnitude of LVV and APV.

Figure 4

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Relationship between the static value of HR and the transfer magnitude of LVV and APV as measured within the frequency range of 0.5–1.0 Hz in response to incremental doses of propranolol (0.01, 0.1, 1 mg kg−1i.v.) following pretreatment with saline or combined phentolamine (Phe; 2.5 mg kg−1i.v.) and atropine (Atr; 0.3 mg kg−1i.v.). Values are presented as means ±s.e.m., n = 8.

Effect of propranolol on respiratory-related stroke volume and HR variability

To assess the possible involvement of variability in stroke volume and HR in the suppressive effect of propranolol under conditions of respiratory-related APV, we evaluated the response of stroke volume and HR variability to graded β-adrenoceptor blockade (Fig. 5). It was noted that the suppressive effect of propranolol on stroke volume variability or transfer magnitude of LVV and stroke volume variability had a pattern very similar the effect of propranolol on APV or LVV-APV transfer magnitude. In contrast, HRV had a much smaller magnitude, which was not affected by propranolol.

Figure 5. Effect of propranolol on respiratory-related stroke volume and HR variability.

Figure 5

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A, time domain illustration of lung volume (LV), stroke volume (SV) and HR signals before (a) and 5 min after (b) i.v. administration of propranolol (1 mg kg−1). B, frequency domain analysis of the effect of propranolol (Pro; 0.01–1 mg kg−1i.v.) on the transfer magnitude of LVV and stroke volume variability, and the transfer magnitude of LVV and HRV following pretreatment with saline. Values are presented as means ±s.e.m., n = 8. *P < 0.05vs. corresponding value of the preceding treatment by Duncan's multiple range test.

Correlation between APV and stroke volume variability

Since the stroke volume determination was not made directly, but rather was derived from the arterial pressure record, we tested the independence of stroke volume and arterial pressure in response to incremental doses of propranolol during irregular ventilation. The correlation coefficients between their static values and variabilities at 0.0–0.5, 0.5–1.0 and 1.0–1.5 Hz were −0.02 ± 0.42, 0.09 ± 0.36, 0.85 ± 0.05 and 0.86 ± 0.07, respectively. It was noted that although their static values or variabilities in the lower frequency range (< 0.5 Hz) were poorly correlated, their variabilities in the higher frequency ranges (≥ 0.5 Hz) were well correlated. This disparity indicates that the stroke volume index evaluated by the pulse contour method is not a simple reflection of the arterial pressure.

DISCUSSION

The present study demonstrates that respiratory-related APV and LVV-APV transfer magnitude are suppressed in a dose-dependent manner by β-adrenoceptor antagonism in the rat under general anaesthesia and positive-pressure ventilation. The suppressive effect of the β-adrenoceptor blocker persisted in the presence of systemic α-adrenoceptor and muscarinic receptor blockade. The frequency range of 0.5–1.0 Hz was optimal for LVV-APV transfer magnitude to correlate with cardiac sympathetic tone. Respiratory-related stroke volume variability estimated by the pulse contour method also exhibited a dose-dependent depression by propranolol. Thus it is concluded that under the conditions of general anaesthesia and positive-pressure ventilation, respiratory-related APV may be used as an index for cardiac sympathetic tone in the rat. Furthermore, this phenomenon can be quantified by adequate numeric analysis including power spectral or transfer function analysis.

While arterial pressure has long been known to fluctuate spontaneously about a mean value (which also known as APV), APV has only in recent years been extensively explored and found to be closely related to the function of the autonomic nervous system (ANS). Time and frequency domain analyses of APV have revealed that APV is regulated by at least two different mechanisms: respiration and vasomotion. The vasomotor component of APV is now generally considered to be a good index of sympathetic tone or baroreceptor activity (DeBoer et al. 1987; Japundzic et al. 1990; Rimoldi et al. 1990; Cerutti et al. 1991). In terms of the respiratory component, the relationship between respiration and arterial pressure must be considered. However, such a relationship in living subjects is not static, but dynamic, and is found to be frequency dependent (Dornhorst et al. 1952; Scharf et al. 1980). In this regard, the broad-band ventilation model coupled with transfer function analysis provides an efficient method to evaluate the magnitude and phase relationship between respiration and circulation in human subjects (Saul et al. 1991) and animals (Kuo et al. 1996). In a previous study (Kuo et al. 1996), we noted that although respiratory-related APV is basically generated by the respiratory pumping mechanism, the lower-frequency end of this mechanical influence is subjected to additional amplification by the ANS, in which the β-adrenergic system plays a major role via its influence on the heart. In the present study, we have further demonstrated the dose-response relationship of this phenomenon in the presence or absence of α-adrenergic and vagal functions. The graded decreases of HR in response to incremental doses of propranolol following pretreatment with phentolamine and atropine indicates that HR under such conditions may reflect cardiac sympathetic modulation. Therefore, the high correlation coefficient between HR and LVV-APV transfer magnitude further supports the validity of the use of respiratory-related APV as an index of cardiac sympathetic tone.

It is of interest to note that respiratory-related APV or LVV-APV transfer magnitude is highly correlated with cardiac sympathetic function. The static value of arterial pressure is determined by stroke volume, HR and total peripheral resistance (TPR). Although the mechanism underlying the dynamic variability of arterial pressure is still uncertain, it is reasonable to suppose that such variability may be contributed by the variability in stroke volume, HR and TPR. We have previously reported that the frequency response of neurogenic variability in TPR is limited below 0.8 Hz in the rat (Kuo et al. 1997a). Thus it is not likely that the respiratory-related APV is chiefly contributed by variability in TPR. When the respiration-induced APV, stroke volume variability and HRV were compared, it was noted that both arterial pressure and stroke volume had significant variability upon ventilation. In contrast, dynamic changes in lung volume resulted in only small magnitude HRV, which was not lowered with propranolol. Thus HRV is unlikely to be the cause of APV. All the above data support the idea that the respiratory-related APV is chiefly determined by the corresponding stroke volume variability in our experimental conditions. In addition, we were particularly interested in the role of stroke volume variability in the suppressive effect of propranolol on respiratory-related APV. As expected, the respiratory-related stroke volume variability and LVV- stroke volume variability transfer magnitude were decreased in a dose-dependent way by the β-adrenoceptor antagonist. Therefore, the change in respiratory-related APV in response to altered sympathetic tone may be explained, at least in part, by the change in stroke volume variability. However, the detailed mechanisms of neural regulation underlying stroke volume variability essentially remain uncharacterized at the present time.

The mechanism of respiratory-related APV has been reported to be a combination of stroke volume variability and direct pressure transmission (Scharf et al. 1980; Toska & Eriksen, 1993). The latter mechanism is the more straightforward: variations of intrathoracic pressure induced by ventilation transmit directly to systemic arterial pressure. Such a mechanism becomes dominant when the heart beat is stopped, and the APV still significantly coheres to LVV although with a much smaller magnitude and near-zero phase shift (Kuo et al. 1996). On the other hand, the contribution of stroke volume variability is significant under normal physiological conditions when the heart is beating (Toska & Eriksen, 1993). Such a mechanism is characterized by a smaller magnitude in a higher frequency range (Kuo et al. 1996). Therefore, when the respiratory frequency is sufficiently high, the impact of stroke volume mechanism on respiratory-related APV is eventually replaced by that of direct pressure transmission from the lungs. Accordingly, the β-adrenoceptor antagonist has little or no effect on respiratory-related APV at frequencies higher than 2.0 Hz (Kuo et al. 1996). In contrast, however, if the respiratory frequency is sufficiently low to reach the frequency range of the vasomotor activity (around 0.8 Hz) (Kuo et al. 1997a), the APV induced by ventilation may be contaminated by that induced by the vasomotor mechanism. In the present study, the optimal frequency for the coupling of cardiac sympathetic tone and respiratory-related APV was found to be in the range of 0.5–1.0 Hz (Table 2). This frequency range may also represent the optimal frequency range for the stroke volume mechanism of respiratory-related APV.

There is evidence that the vascular sympathetic system may contribute to respiratory-related APV, possibly interacting with the effect of the cardiac sympathetic system. For example, sympathetic nerve activity has been shown to synchronize with phrenic nerve activity (Connelly & Wurster, 1985; Boczek-Funcke et al. 1992). Ashton & Cassidy (1985) demonstrated that inflation of the isolated left lung led to a decrease in vascular resistance, which is mediated by α-adrenoceptors. However, as described above, the contribution of the vascular sympathetic system cannot theoretically extend to the respiratory frequency because of the frequency characteristic of TPR. In our preparation, α-adrenoceptor blockade alone did not cause a discernible effect on the LVV-APV transfer magnitude, as expected (Kuo et al. 1996). In the present study, despite the hypotensive effects of combined α-adrenoceptor and muscarinic receptor blockade, such pretreatment increased the respiratory-related APV, which was expressed as percentage variation from the mean. Therefore, we interpret that changes in respiratory-related APV are chiefly contributed by cardiac sympathetic function, and that the direct contribution of the vascular sympathetic system may be insignificant due its response frequency. Thus α-adrenoceptor blockade did not decrease the respiratory-related APV and LVV-APV transfer magnitude, but rather increased it, possibly via a baroreflex effect.

Ketamine is a widely used dissociative anaesthetic (Reich & Silvay, 1989). Although most anaesthetics exhibit a suppressive effect on sympathetic outflow, ketamine avoids cardiovascular depression via central and peripheral sympathomimetic actions (Dowdy & Kaya, 1968), and remains one of the primary agents used to induce anaesthesia in patients with hypovolemia. In our experimental model, we applied a continuous intravenous infusion to deliver this anaesthetic in order to maintain a stable cardiac sympathetic tone. A reduction in HR and respiratory-related APV induced by propranolol suggested that the capacity for cardiac sympathetic regulation persists under this anaesthetic management. Thus, under this condition, the correlation between cardiac sympathetic tone and respiratory-related APV can be successfully analysed. While this study does not imply that ketamine anaesthetic is a suitable platform for the study of the sympathetic function in vivo, it does make clear that the relationship between respiratory-related APV and cardiac sympathetic tone persists in rats under ketamine anaesthesia (Kuo et al. 1996).

In this study, we extrapolated back to cardiac sympathetic tone from the correlation between HR and LVV-APV transfer magnitude. The interpretation requires that there is a relatively linear relationship between cardiac sympathetic tone and HR. It has been noted that the relationship between cardiac sympathetic stimulation and HR response is more likely to be exponential especially when the stimulus intensity is high (Rosenblueth & Simeone, 1934; Furnival et al. 1973; Cowan et al. 1975). It has also been noted, however, that if the increase in HR is less than 50 %, the relationship between the two is linear. Since the maximal HR change in this study was smaller than 50 %, our data may demonstrate this linearity between respiratory-related APV and change in cardiac sympathetic tone. Nevertheless, there is still a requirement for a more specific experimental design to test its usefulness for detecting the absolute level of basal sympathetic tone for an individual animal. Moreover, it is well known that the effects of spontaneous breathing and controlled positive-pressure ventilation on haemodynamics are very different. Although it has been reported that the respiratory-related APV may also decrease in response to propranolol in spontaneously breathing rats (Yang et al. 1996), extrapolation of the findings in this paper to the normal, awake condition is still to be evaluated.

Frequency domain analysis of cardiovascular variability has gained popularity for broader application within recent years. Since it is easily accessible, increasing numbers of clinical and basic investigators are using the technique to monitor ANS function of humans or experimental animals. Our findings indicate that this technique may offer an additional index of cardiac sympathetic tone from mere arterial pressure signals. The applicability to other animals or humans and the detailed underlying mechanism are worth exploring.

Acknowledgments

This study was supported in part by National Council Research Grant NSC 87–2314-B320–012 and a research grant (TCMRC 85–02) from the Tzu Chi Charity Foundation.

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