JEPonline
Journal of 
Exercise Physiologyonline

ISSN 1097-9751

An International Electronic
Journal for Exercise Physiologists

Vol 1 No 3 October 1998


Systems Physiology: Cardiopulmonary
Heart rate variability and baroreceptor responsiveness to evaluate autonomic cardiovascular adaptations to exercise

WILLIAM H. COOKE

Department of Internal Medicine, Division of Cardiology, Medical College of Virginia at Virginia Commonwealth University, Richmond, Virginia



WILLIAM H. COOKE. Heart rate variability and baroreceptor responsiveness to evaluate autonomic cardiovascular adaptations to exercise. JEPonline Vol. 1 No. 3 1998. Exercise physiologists routinely evaluate adaptations to exercise such as aerobic capacity, muscular strength and flexibility, and body composition, but often overlook the effects of exercise training on autonomic regulation of cardiovascular function. A preponderance of cross-sectional studies report significant resting sinus bradycardia and high heart rate variability in active subjects, and suggest that exercise training induces adaptations in autonomic cardiovascular control. Alternatively, data from cross-sectional studies leave open the possibility that individuals with a genetic predisposition for lower heart rates or greater heart rate variability are also endowed with greater aerobic capacity. Conflicting results from a limited number of exercise training studies fail to conclusively demonstrate a direct effect of exercise training on the autonomic nervous system. In this report I suggest that simple measures of heart rate variability during controlled frequency breathing, and arterial baroreceptor responsiveness to Valsalva's maneuver provide unique insights into autonomic regulation of cardiovascular function. I propose that systemic-wide integration of exercise training effects might be better characterized if exercise physiologists would perform tests of autonomic function in conjunction with standard exercise tests during routine laboratory evaluations.

Key Words: CARDIAC CONTROL, CONTROLLED BREATHING, VALSALVA MANEUVER 


Introduction
Chronic aerobic exercise elicits important cardio-protective adaptations that have been linked to decreased all-cause mortality (1). Effects such as increased aerobic capacity (consequent to decreased peripheral vascular resistance and increased cardiac output and arteriovenous oxygen difference) are well documented (2,3), and characterize the physiological adaptation to endurance training. Surprisingly, despite important implications for cardiovascular health, the effects of aerobic exercise on autonomic cardiovascular regulation (4,5) receive comparatively less attention. Effects such as significant resting sinus bradycardia and increased heart rate variability [the latter being inversely related to mortality after myocardial infarction (6)], are thought to be mediated through adaptations in autonomic cardiovascular control (7).

Analyses of heart rate variability and baroreceptor responsiveness provide important information on exercise training effects. High heart rate variability is associated with increased parasympathetic cardiac control, and low heart rate variability is associated with decreased parasympathetic cardiac control and coronary heart disease (8). Heart rate variability was shown to be significantly higher in physically active, compared to non-physically active healthy humans (4,7). Conversely, decreased vagal outflow after myocardial infarction results in both decreased heart rate variability and baroreceptor responsiveness (9,10). Although not consistently found (11), some have reported increased arterial baroreceptor sensitivity in active, compared to sedentary humans (12,13). Taken together, these data suggest that the autonomic nervous system adapts to chronic demands imposed by exercise or inactivity.

Many applied exercise physiology laboratories evaluate the effects of exercise on functional rather than autonomic adaptations despite being equipped to do both. Autonomic function tests, performed in conjunction with standard exercise tests, would more completely inform mechanisms of systemic-wide adaptations to exercise, and contribute importantly to the evaluation of physical fitness and cardiovascular health. In this report, I provide rationale for the exercise physiologist to consider tests of heart rate variability and baroreceptor responsiveness, and briefly describe simple procedures that may easily be performed as an adjunct to standard exercise tests during routine evaluations.

Heart Rate Variability
During supine rest, inspiration causes an increase, and expiration a decrease in heart rate. These spontaneous fluctuations in sinus node rate, known collectively as heart rate variability, are under dual neural control from both parasympathetic and sympathetic sources (14). At normal respiratory frequencies and tidal volumes, variations in beat-to-beat heart period (R-R interval) are proportional to, and predominantly controlled by parasympathetic activity. Thus, analysis of R-R interval oscillations at or around the respiratory frequency directly reflects parasympathetic cardiac control (15).

Time Domain Analysis: Time domain analytical methods are easy to apply to fluctuations in heart rate. Simple analysis of heart rate or R-R interval, or the difference between the longest and shortest R-R interval may be calculated from continuous QRS complexes. A recent Task Force report (16) summarized various time-domain methods lending insights into analysis of short- and long-term heat rate variability. One of the most widely used methods involves calculating the standard deviation from the mean R-R intervals of all cardiac cycles occurring during a given time period (usually ~ 5 min). Assuming normal respiratory frequencies, a simple standard deviation of R-R intervals calculated before and after an exercise program would provide the exercise physiologist with general information about the effects of the program on parasympathetic cardiovascular control. Although quantitative values for heart rate variability vary widely between groups of matched subjects [highlighting the need to standardize autonomic function tests], Figure 1 presents a generalized continuum of values for R-R interval standard deviations among groups of diseased, healthy, and active subjects. Time domain analytical methods are valuable, but for a more complete understanding of mechanisms underlying autonomic regulation of cardiovascular function, frequency domain analyses may be employed.

Frequency Domain Analysis: Akselrod et al. (17) demonstrated the usefulness of applying power spectral analysis (the distribution of variance as a function of frequency) to beat-by-beat fluctuations in heart rate. Fast Fourier transform-based spectral analyses are commonly used, and widely available as a component of many data analysis software packages. It should be mentioned that significant data transformation is required before data may be submitted to power spectral analysis. Briefly, to calculate R-R interval spectral power, it is recommended that the continuous electrocardiogram be initially sampled at rates between 250 to 500 Hz. The digitized signal must be checked for artifacts, and any such artifacts (such as extrasystoles, movement, muscular contraction) should be removed and replaced with markers calculated from preceding R-R interval means. Data must be equidistant, therefore resampling of the data (either via linear or polynomial interpolation) is required. There are a number of power spectral analyses that may be employed. Excellent reviews on this topic are available (16,18,19). As an example, in our laboratory we recently calculated R-R interval power spectra as follows: The non-equidistant R-R interval time series was spline interpolated (cubic), resampled at 4 Hz, and passed through a finite low-pass impulse response filter with a cut-off frequency of 0.5 Hz. Data sets comprising 64 s (256 samples), sliding every 10 s, were trend eliminated (linear regression), windowed (Hanning method), and fast Fourier transformed. We used the periodogram method to estimate power distribution. Power was expressed as the area under the spectrum over the frequency range of interest (20). In short term recordings, one typically sees three peaks of spectral power: very low frequency (less than ~ .04 Hz), low frequency (.04 to .15 Hz), and high frequency (.15 to .4 Hz) (16). The physiological significance of very low frequency oscillations is unclear; these oscillations are not usually considered when analyzing the periodicity of short term cardiovascular fluctuations. Fluctuations within the low- and high-frequency ranges, however, provide insight into autonomic efferent neural outflow.

Parasympathetic and sympathetic neural discharges are modulated by central and peripheral regulatory mechanisms which constantly interact to 'fine tune' beat-to-beat cardiac control. Interactions between parasympathetic and sympathetic outflow result in relatively short- and long-term heart rate fluctuations that are interpretable with power spectral analysis. High frequency oscillations are mediated by parasympathetic, whereas low frequency oscillations are mediated by both parasympathetic and sympathetic contributions (17). For the exercise physiologist, increased high frequency spectral power after training is indicative of increased parasympathetic cardiac control. Liao et al. (21) recently showed that heart rate variability is significantly different among groups differing in age, race, and sex. Group-matching of subjects should be considered.

Controlled Frequency Breathing:A recent study by our laboratory showed that various controlled breathing protocols yield similar information regarding cardiovascular rhythms (20). However, it is incorrect to suggest that respiratory input is unimportant to the assessment of heart rate variability. Variability in tidal volume and respiratory frequency is high when subjects breathe spontaneously (without respiratory frequency control) (22); when breathing is variable, the interpretation of autonomic cardiac control may be confounded. Brown et al. (22) showed that R-R interval spectral power is influenced profoundly by respiratory input, and concluded that respiration must be taken into account to properly assess heart rate variability. When the breathing rate is controlled at frequencies lower than normal respiratory frequencies (below ~ 12 breaths/min), low frequency and high frequency R-R interval oscillations tend to merge (20), making it impossible to evaluate parasympathetic neural outflow without pharmacological blockade. For these reasons, the effects of an exercise training program on parasympathetic cardiac control should be evaluated using strict control of respiratory rate [at or around normal respiratory frequencies (~ 12 to 15 breaths/min)]. Respiratory and R-R interval spectral power derived from uncontrolled and controlled breathing protocols are displayed for comparison in Figure 2 .

Suggested Methods and Procedures: At the minimum, to perform a controlled breathing protocol it is necessary to record beat-to-beat ECG. Respiratory rate must be strictly controlled. The subject should be allowed a period of supine rest followed by a period of controlled frequency breathing for at least 5 minutes. Respiratory rate should be constant, and set between 12 and 15 breaths per minute (0.2 - 0.25 Hz) using a metronome, pre-recorded audio tape, or in-house computer software.

Baroreceptor Responsiveness
Arterial baroreceptors are arterial pressure sensors, located on the walls of the carotid sinuses and aortic arch. Baroreceptors send afferent signals to the cardiovascular control center to modulate autonomic activity as a function of arterial pressure. Through the integrated activities of the baroreceptors and autonomic efferent outflow, the inverse relationship between arterial pressure and heart rate is regulated on a second-by-second basis. Although there are a number of techniques available to assess baroreflex function, not all are possible within the realm of the common applied exercise physiology laboratory. One technique that is possible, and highly informative, is Valsalva's maneuver.

Valsalva's Maneuver: The act of exhaling forcefully against a closed glottis, or 'Valsalva's maneuver' [named for Antonio Maria Valsalva (1666-1723)], evokes hemodynamic responses by way of immediate increases in intra-abdominal and intra-thoracic pressures. Consequent to straining, venous return to the heart is impeded, resulting in predictable increases and decreases in arterial pressure and autonomic neural activity. Either heart rate alone, or reciprocal relations between arterial pressure and heart rate are used to assess baroreceptor sensitivity (23).

Valsalva standardization procedures have not been documented, and tests may vary according to the depth of inspiration before straining, the straining pressure at the mouth, the duration of straining, and the position of the subject during straining. All of these variables could potentially influence arterial pressure responses to varying degrees. However, in spite of different testing protocols, the response to Valsalva's maneuver in normal subjects can generally be described in four phases: 1) an increase in arterial pressure and decrease in heart rate upon straining; 2) a fall, then recovery of arterial pressure accompanied by an increase in heart rate; 3) a brief reduction of arterial pressure and increase in heart rate at the release of straining; and 4) a sustained elevation of arterial pressure and slowing of heart rate [see Eckberg and Sleight (23) for a thorough description]. Patients with certain forms of heart disease exhibit 'square wave' responses characterized by a lack of decrease in arterial pressure during straining, and subsequent lack of sympathetic activation (24). Representative arterial pressure responses to Valsalva's maneuver in one healthy subject are shown with R-R interval, muscle sympathetic nerve activity (peroneal nerve microneurography), and respiration in Figure 3.

In Figure 3 it is interesting to observe reciprocal relations between arterial pressure and muscle sympathetic nerve activity. The dramatic increase in arterial pressure apparent during phase four is accompanied by inhibition of sympathetic activity and dramatic slowing of the heart rate (increased R-R interval).

Because the use of arterial catheters is highly invasive, beat-to-beat measures of arterial pressure are not always possible unless the laboratory is equipped with a finger photoplethysmograph device (such as a Finapres, Ohmeda, Englewood, CO). Assuming that no such device is available, baroreceptor responsiveness may still be evaluated from changes in heart rate. Levin (24) described the Valsalva ratio, which was simply the ratio of the maximal to the minimal R-R interval measured during the maneuver. The reproducibility of this analysis was good; average differences were about 5% when a second trial was performed one week after the first. Average Valsalva ratios for normal, healthy subjects ranged from 1.3 to 2.9, with greater than 50% of the 30 subjects studied showing values above 1.9 (24). The Valsalva ratio could easily be obtained during a fitness evaluation and compared to values recorded after a period of exercise training. Admittedly, the Valsalva ratio is largely a 'rough estimate' of baroreflex responsiveness. Greater sensitivity and accuracy is achieved if the laboratory is equipped to measure beat-by-beat arterial pressure.

Excellent insight into baroreceptor responsiveness may be obtained by analyzing heart rate and arterial pressure responses to phase four of Valsalva's maneuver. In this analysis, the slope of the linear regression between systolic pressure and R-R interval is calculated, and baroreflex sensitivity is defined as changes in R-R interval as a function of changes in systolic pressure. Kautzner et al. (25) described this procedure in detail, and also calculated baroreflex sensitivity as the simple ratio of maximal and minimal R-R interval to maximal and minimal systolic pressure; baroreflex sensitivity was not significantly different when calculated by the linear regression (13.7 ± 8.4 ms/mmHg) vs. the ratio (15.3 ± 8.8 ms/mmHg) method. Either procedure would be appropriate to assess baroreflex sensitivity in the exercise physiology laboratory.

Suggested Methods and Procedures:At the minimum, the subject should be instrumented for ECG, fitted with a noseclip, and then to a mouthpiece device connected via a short plastic tube to a mercury manometer or Statham pressure transducer. Mercury manometers provide direct visual feedback so the subject may maintain the required expiratory pressure. Visual feedback from a calibrated Statham pressure transducer can be achieved by routing the analog output signal through an oscilloscope (and then to a digital converter). To insure that expiratory pressure is not simply maintained by closing the glottis, a small leak should be incorporated into the system. If available, beat-to-beat arterial pressure should be measured. Responses to Valsalva's maneuver are directly proportional to expiratory effort, and 30 mmHg for 15 seconds in the supine position seems to produce maximal responses (25,26). To perform a Valsalva, subjects should breathe at a controlled rate (12 to 15 breaths/min) for at least 30 seconds followed by a 15-second strain initiated at the same time in the breathing cycle (i.e. at the end of a normal inspiration). Recovery durations should be long enough for arterial pressure and heart rate to stabilize (~ 2 min), during which time the subject should maintain the control of breathing.

Summary
In this brief report, I suggest that thorough evaluations of exercise training responses should include basic tests of autonomic regulation. Autonomic function tests explore cardio-protective adaptations such as increased parasympathetic cardiac control, are useful in identifying pathophysiological conditions (square wave Valsalva response), and add importantly to our understanding of systemic-wide integration of exercise training effects. Simple measures of heart rate variability during controlled frequency breathing, and arterial baroreceptor responsiveness to Valsalva's maneuver could easily be incorporated into standard exercise evaluations as a means to quantify autonomic adaptability. 



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Please note new address for correspondence:
William H. Cooke, PhD, Assistant Professor of Applied Physiology, Michigan Technological University, Center for Biomedical Engineering,1400 Townsend Drive, Chem. Sci. 312, Houghton, Michigan 49931
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