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High-Frequency Modulation of Heart Rate Variability During Exercise in Patients With COPD^*

^* From the Human Performance Laboratory (Dr. Bartels), Department of Rehabilitation Medicine, Department of Medicine (Drs. Jelic, Ngai, and Basner), College of Physicians and Surgeons and Teachers College (Dr. DeMeersman), Columbia University, New York, NY.

Correspondence to: Matthew N. Bartels, MD, MPH, 630 West 168th St, Box 38, New York, NY 10032; e-mail: mnb4{at}columbia.edu

	Abstract

TOP Abstract Introduction Materials and Methods Results Discussion References

 
Study objectives: To evaluate cardiac autonomic modulation in patients with COPD during peak exercise.

Methods: Fifty-three patients with COPD (mean FEV₁, 35% predicted [SD, 11% predicted]; mean PaO₂, 68 mm Hg [SD, 11 mm Hg]; mean PaCO₂, 40 mm Hg [SD, 7 mm Hg]; mean age, 61 years [SD, 10 years]; 26 women and 27 men) and 14 healthy control subjects aged 60 years (SD, 8 years) [seven women and seven men] were studied at rest and during ramped bicycle ergometry to their volitional peak. Patients were not receiving autonomic medications other than inhaled ß-agonist agents and/or anticholinergic agents. Control subjects were not receiving any medications. Cardiac autonomic modulation was assessed via time-frequency analysis (Wigner-Ville) of ECG-derived heart rate variability as the power in the low-frequency (LF) band (ie, 0.04 to 0.15 Hz) and the high-frequency (HF) band (ie, > 0.15 to 0.4 Hz) averaged from > 3 min at rest and minutes 2 through 5 of their exercise period.

Results: Patients with COPD had a significantly increased mean, ln-transformed HF band from rest to peak exercise (9.9 ms² [SD, 1.4 ms²] vs 10.7 ms² [SD, 1.4 ms²], respectively; p < 0.01), while the HF band was unchanged for the control group (10.7 ms² [SD, 1.5 ms²] vs 10.4 ms² [1.3 ms²], respectively; difference not significant). The mean ln-transformed LF band was significantly increased from rest to peak exercise in patients with COPD (10.9 ms² [SD, 1.5 ms²] vs 11.5 ms² [SD, 1.4 ms²], respectively; p < 0.01) and in control subjects (10.9 ms² [SD, 1.5 ms²] vs 11.5 ms² [SD, 1.3 ms²], respectively; p < 0.01). The mean LF/HF ratio was significantly decreased from rest to peak exercise in patients with COPD (3.1 [SD, 1.5] vs 2.5 [SD, 1.0], respectively; p < 0.01) and was increased in control subjects (1.9 [SD, 0.8] vs 2.4 [1.0], respectively; p < 0.01). When expressed in normalized units ([absolute power of the components]/[total power - very low frequency power] x 100), the HF band was again significantly greater during peak exercise than at rest in the patients with COPD and was unchanged during peak exercise for the control group. Autonomic changes were not significantly correlated with age, gender, body mass index, spirometry, lung volumes, resting gas exchange, or oxygen saturation during exercise

Conclusion: These data suggest that, in contrast to control subjects, the balance of sympathetic to parasympathetic cardiac modulation decreases in patients with COPD during maximal volitional exercise.

Key Words: autonomic function • COPD • exercise • heart rate variability

	Introduction

TOP Abstract Introduction Materials and Methods Results Discussion References

 
Normoxemic as well as hypoxemic patients with COPD appear to have impaired cardiac autonomic modulation at rest, as reflected in reduced heart rate variability (HRV).^{1 2 3 4} Autonomic dysfunction at rest and during exercise is also present in patients with cardiovascular and metabolic disorders, and has been repeatedly shown to predict poor clinical outcomes in such patients.^{5 6 7} While exercise generally has been associated with the withdrawal of parasympathetic tone and the concomitant increase of sympathetic tone in healthy subjects,⁸ cardiac autonomic response to exercise has not been well-characterized in patients with COPD. Such response could have significant clinical importance in these patients.

Spectral analysis of HRV is a noninvasive method for assessing autonomic function that has been used extensively in the clinical setting.⁸ The majority of exercise studies in humans have utilized frequency domain analyses to delineate cardiac autonomic modulation. However, such analysis, using Fourier transforms, is most reliably performed on stationary data, which are not present during exercise in general, and during exercise in COPD patients in particular.

The aim of the present study was to noninvasively evaluate cardiac autonomic modulation in patients with COPD during their maximal volitional exercise using time-frequency domain analysis, which does not require stationary data for the accurate assessment of autonomic modulations. We hypothesized that patients with COPD would demonstrate impaired cardiac autonomic regulation compared with healthy subjects during exercise.

	Materials and Methods

TOP Abstract Introduction Materials and Methods Results Discussion References

 
Subjects
Participants were prospectively recruited from a group of patients with COPD who had been referred for cardiopulmonary exercise testing at the New York Presbyterian Hospital (Columbia-Presbyterian campus) as a part of the routine evaluation for possible lung volume reduction surgery or transplantation. All patients had stopped smoking at least 6 months prior to enrollment in the study. All COPD patients who had been referred for clinical evaluation between November 1999 and January 2001 were screened for this study. Control subjects of similar age and gender to the study population were recruited from among patients who had been referred to the exercise laboratory with a diagnosis of dyspnea. Control subjects were included in the analysis if they had normal findings on pulmonary function testing and exercise testing, had not received a diagnosis of a major illness during the prior 6 months, and had no history of diagnosed pulmonary disease, cardiac disease, or malignancy. All participants gave their informed consent to participate in the study, which was approved by the New York Presbyterian Hospital (Columbia-Presbyterian campus) Institutional Review Board. No participants were financially compensated for participating in this research. All participants underwent a medical history and physical examination by a physician investigator prior to being accepted for the study, as well as pulmonary function testing. Patients with COPD also underwent arterial blood gas analysis. None of the study patients were receiving autonomically active medications other than inhaled ß-agonist and/or anticholinergic agents. None of the control subjects were receiving any medications of any type. The testing was performed in the Human Performance Laboratory of the Columbia Presbyterian Medical Center.

Protocol and Measurements
Subjects were postprandial for at least 4 h and had refrained from alcoholic and caffeinated beverages for at least 12 h prior to the data collection. All patients with COPD received two puffs of albuterol via a metered-dose inhaler 30 min prior to the resting measurements being made, as per the clinical cardiopulmonary exercise testing laboratory protocol. None of the control subjects received such treatment. Resting and exercise data were collected while patients were breathing supplemental oxygen (fraction of inspired oxygen, 0.3) through a mouthpiece that was attached to a mass flow sensor with a nose clip. Control subjects were studied while breathing room air. During rest, subjects sat on a bicycle ergometer maintaining their normal breathing patterns. Resting data were collected for 5 min. Exercise stress testing then was performed on the bicycle ergometer (Vmax 229 series workstation; SensorMedics; Yorba Linda, CA). Subjects were familiarized with the cycling protocol prior to performing the exercise test. The exercise testing used a ramp protocol with 5-min baseline resting data collection, followed by a 3-min warm up at no load, and then a maximum exercise test at either 5 W per minute (in patients with maximal voluntary ventilation [MVV] of < 40 L/min) or 10 W per minute (in patients with MVV of 40 L/min) ramp until their maximal volitional exercise capacity was reached. Criteria for terminating the exercise study were volitional leg fatigue (as assessed by a modified Borg scale score) or intolerable dyspnea.⁹ No patient was able to achieve his/her predicted maximal oxygen consumption (O₂), while all control subjects achieved their predicted maximal O₂.

During rest and exercise testing, an ECG was recorded using lead II and lead V5 with an ECG machine (Marquette Max-1; Marquette Medical Systems; Milwaukee, WI). Oxygen saturation was monitored noninvasively by finger pulse oximetry (Sat-Trak Pulse Oxymeter 767589–103; SensorMedics). The autonomic biopotentials were obtained through an interface board (BNC 2080; National Instruments Co; Austin, TX) and were fed into a 12-bit analog-to-digital converter (DAQ Card-700; National Instruments Co) and then into a Pentium computer (Vision Book Plus; Hitachi; San Jose, CA). The data were sampled at 200 Hz.⁸

Postacquisition Data Analysis
Patients with technically inadequate ECG tracings or cardiac arrhythmia were excluded from the data analysis. The current investigation used time-frequency, or the Wigner-Ville distribution, to decompose the HRV. This analysis is preferred over the traditional frequency spectral analysis due to the nonstationarity of respiration in COPD patients. Specifically, the Wigner-Ville distribution decomposes a signal expressed as a function of time into a signal expressed as a function of both time and frequency. The time-frequency method uses a modified Fourier transform applied to overlapping sections of the time signal to develop a joint density function that is dependent on both time and frequency.^{10 11} In this approach, the signal is divided into a series of short windows, and the Fourier transform then is calculated for each section. It has been shown to provide a reliable estimate of spectral powers without generating undesirable cross-terms.^{10 11} The power (ie, the density of the beat-to-beat oscillation in the R-R interval) of HRV in the high-frequency (HF) band has been shown to be influenced primarily by parasympathetic nervous system activity,¹² while both parasympathetic and sympathetic activity contribute to the low-frequency (LF) band.^{12 13} It has been suggested that the ratio of LF to HF reflects the sympathovagal balance.^{12 13} Power in the LF band (ie, 0.04 to 0.15 Hz), the HF band (ie, > 0.15 to 0.4 Hz), and the very LF (VLF) band (ie, 0.00 to < 0.04 Hz) were averaged over the last 3 min of resting data acquisition and during minutes 2 through 5 of exercise. Spectral components were expressed both as absolute values in milliseconds^{2 14 15} and as normalized units (nu), which were calculated as follows: (absolute power of the components)/(total power - VLF power) x 100.^{16 17}

Statistical Analysis
Assuming differences of 30% in baseline measurements, 48 patients with COPD provide 80% statistical power to detect a 30% difference in HRV measurements at rest and during exercise, with a type 1 error of 0.05. We recruited 64 patients, anticipating a 30% dropout rate, to satisfy these conditions. Based on our preliminary data in non-COPD subjects, assuming differences of 30% in baseline measurements, 12 control subjects provide 80% power to detect a 30% difference in HRV measurements at rest and during exercise, with a type 1 error of 0.05. We enrolled 14 control subjects to satisfy these conditions. Logarithmic transformation was used to stabilize the skewness of the raw data.¹⁸ Five physiologic parameters (ie, lnHF, lnLF, nuHF, nuLF, and LF/HF ratio) were compared from rest to exercise by analysis of covariance, which was used to make comparisons across groups, and were based on final values with baseline as the covariate.¹⁹ Correlations between HRV changes and demographic continuous variables (ie, age and body mass index) and physiologic continuous variables (ie, FVC, FEV1, total lung capacity, residual volume, MVV, PaO₂, PaCO₂, and exercise arterial oxygen saturation), which may have influenced these HRV changes, were performed using the Spearman-Row test. Associations between HRV changes and gender were performed using the Wilcoxon rank sum test.

	Results

TOP Abstract Introduction Materials and Methods Results Discussion References

 
Sixty-four consecutive eligible patients with COPD were recruited between November 1999 and January 2001. Eleven patients were excluded after the exercise study because of ECG artifacts or cardiac arrhythmia that developed during the study, thus precluding reliable spectral analysis. Thus, 53 patients of the original 64 had technically adequate data and were included in the data analysis. We did not use imputational methods for the analysis, as data from patients excluded because of technically inadequate data could not have been analyzed. The clinical characteristics of the subjects in the COPD and control groups are shown in Table 1 . There were no significant differences between the 53 COPD patients included in the data analysis and the 11 patients excluded because of ECG artifacts or arrhythmia in regard to age, gender, FEV₁, FVC, FVC FEV1, PaO₂, and PaCO₂. See Table 2 for a comparison of the included and excluded subjects.

A comparison of the control group and the COPD group at both stages was performed and is presented in Table 4 for completeness. There is a difference in subjects with COPD compared to the healthy control subjects at rest in terms of resting heart rate (87 beats/min [SD, 14 beats/min] vs 77 beats/min [SD, 12 beats/min], respectively; p < 0.05), and in the autonomic indexes of the normalized LF band (0.24 [SD, 0.06] vs 0.16 [SD, 0.04], respectively; p < 0.01) and the LF/HF ratio (3.1 [SD, 1.5] vs 1.9 [SD, 0.8], respectively; p < 0.01). At maximum exercise, the differences seen are predominantly in the areas of peak O₂ (18 mL/kg/min [SD, 4 mL/kg/min] vs 31 mL/kg/min [SD, 5 mL/kg/min], respectively; p < 0.01) oxygenation (94% [SD, 1.6%] vs 99% [1.4%], respectively; p < 0.05), lower maximum heart rate (110 beats/min [SD, 16 beats/min] vs 156 beats/min [SD, 15 beats/min], respectively; p < 0.01), and lower respiratory rate (27 breaths/min [SD, 5 breaths/min] vs 35 breaths/min [SD, 6 breaths/min], respectively; p < 0.05) at maximum exercise. The autonomic indexes are more comparable at peak exercise in the COPD group and the healthy control group, with no significant difference in any of the indexes, including the LF/HF ratio and the overall normalized LF values.

	Discussion

TOP Abstract Introduction Materials and Methods Results Discussion References

Since the known association between spectral components of the HRV and cardiac sympathetic and parasympathetic activity is based on studies conducted at rest,^{13 23 24} an extrapolation to exercise is more difficult to interpret.^{22 25} We sought to actually evaluate sympathetic and parasympathetic activity in exercise by direct measurement, and, in contrast to most previous investigations of HRV in humans during exercise, we spectrally decomposed our data using time-frequency analysis rather than frequency analysis since exercise data do not meet the requirements for stationary data for frequency domain analysis.^{11 26} Since HF modulation is reflective of parasympathetic cardiac modulation, we demonstrated an increase in parasympathetic activity during exercise in COPD that was consistently present whether analyzed as absolute power or normalized for total power.^{22 25} This is in clear contrast to the lack of change in parasympathetic activity seen in our control group and reported in other studies of healthy subjects.^{14 15 17 20 21 22} Additionally, there is a lack of alteration of the sympathetic tone in the COPD group, and, in combination with the alterations of parasympathetic tone, these lead to the observed changes.

The physiologic effects seen at maximum exercise with a greater increase in heart and respiratory rates, and a decrease in oxygen saturation are consistent with the expected physiology of COPD. The dyspnea at maximum exercise and the oxygen desaturation would be expected to increase sympathetic tone and to decrease parasympathetic tone, but the opposite was seen. The maximum heart rate achieved was lower, and this may have contributed in part to the changes that were seen. However, the lower maximum heart rate could possibly be due to the increased HF band that was seen and is also related to the lack of respiratory reserve, as evidenced by the mild decrease in oxygen saturation and the limited respiratory rate.

The physiologic basis by which parasympathetic cardiac modulation may increase during exercise in patients with COPD is unclear and was not investigated in the current study. However, several possible mechanisms may be postulated. Large intrathoracic pressure swings that occur in patients with obstructive airway disease can cause abnormal cardiac autonomic modulation and an increase in parasympathetic activity at rest.^{27 28} Such an effect could be potentiated during dynamic hyperinflation and increased end-expiratory lung volumes, which invariably attend even minimal exercise in patients with COPD.²⁹ The mechanism may in part reflect a degree of input from hypercapnia, which has been seen to cause an increase in parasympathetic tone in animal models.^{30 31}

Another possible mechanism of the increased HF component of HRV found in the COPD patients during exercise may be an effect of increased respiratory frequency with exercise, causing a shift in power out of the LF range and into the HF range.^{22 25 32} Similarly, respiratory sinus arrhythmia during exercise also may be influenced by nonneural mechanisms, such as atrial stretch.^{16 33 34} The presence of inhaled ß-agonist and anticholinergic agents in the subject population could be thought to have effects on HF modulation and LF/HF ratios. However, although inhaled ß-agonist agents can increase sympathetic activity as measured by HRV analysis in healthy subjects,^{35 36} these agents do not change the parasympathetic (HF) cardiac modulation.^{35 36} Likewise, inhaled anticholinergic agents and ipratropium bromide do not alter HRV in human subjects.³⁷ Therefore, it is unlikely that the inhaled medications used by the COPD subjects influenced our findings of increased HF modulation of HRV during exercise. Finally, even if there had been an effect, the expected trend would have been opposite to our findings, with a decrease in HF modulation and an increase in the LF/HF ratio.

In summary, the novel finding in our data is that during exercise there is a significant increase in HF modulation with a decrease in the LF/HF ratio in COPD patients, while HF modulation of HRV is stable with an increased LF/HF ratio in control subjects. Considered together, the significant increase in the HF component of the HRV with decreased LF/HF ratio during peak exercise in patients with COPD suggests increased parasympathetic cardiac modulation due to this condition. This is in direct contrast to the HRV response seen in non-COPD control subjects during peak exercise. While decreased HRV at rest, as represented by decreased HF and increased LF/HF ratio, has been associated with poorer cardiovascular prognosis in patients with cardiovascular disease,^{5 6 7 8} the physiologic and prognostic significance of increased parasympathetic cardiac modulation during exercise in COPD patients remains to be investigated. Additionally, the increased parasympathetic tone seen with exercise in this study may have a significant bearing on the ability to perform exercise and on the response to a conditioning program. Further investigations into the alterations of these parameters with training will possibly shed light on techniques to help normalize the sympathetic to parasympathetic balance in individuals with COPD.

	Footnotes

 
Abbreviations: HF = high frequency; HRV = heart rate variability; LF = low frequency; MVV = maximal voluntary ventilation; nu = normalized units; VLF = very low frequency; O₂ = oxygen uptake

This work was sponsored in part by the Rehabilitation Medicine Scientist Development Program Fellowship (grant NIH-1-K12-HD01097-01A1), the Langeloth Foundation, and the VIDDA Foundation.

Received for publication July 12, 2001. Accepted for publication January 9, 2003.

	References

TOP Abstract Introduction Materials and Methods Results Discussion References

 

1. Stewart, AG, Waterhouse, JC, Howard, P (1991) Cardiovascular autonomic nerve function in patients with hypoxaemic chronic obstructive pulmonary disease. Eur Respir J 4,1207-1214[Abstract]
2. Volterrani, M, Scalvini, S, Mazzuero, G, et al Decreased heart rate variability in patients with chronic obstructive pulmonary disease. Chest 1994;106,1432-1437[Abstract/Free Full Text]
3. Stein, PK, Nelson, P, Rottman, JN, et al Heart rate variability reflects severity of COPD in PiZ 1-antitrypsin deficiency. Chest 1998;113,327-333[Abstract/Free Full Text]
4. Scalvini, S, Porta, R, Zanelli, E, et al Effects of oxygen on autonomic nervous system dysfunction in patients with chronic obstructive pulmonary disease. Eur Respir J 1999;13,119-124[Abstract]
5. Kleiger, RE, Miller, JP, Bigger, JT, et al Decreased heart rate variability and its association with increased mortality after acute myocardial infarction. Am J Cardiol 1987;59,256-262[CrossRef][ISI][Medline]
6. Pagani, M, Malfatto, G, Pierini, S, et al Spectral analysis of HRV in the assessment of autonomic diabetic neuropathy. J Auton Nerv Syst 1988;23,143-153[CrossRef][ISI][Medline]
7. Kleiger, RE, Miller, JP, Krone, RJ, et al The independence of cycle length variability and exercise testing on predicting mortality of patients surviving acute myocardial infarction: the Multicenter Postinfarction Research Group. Am J Cardiol 1990;65,408-411[CrossRef][ISI][Medline]
8. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology.. Heart rate variability: standards of measurement, physiological interpretation, and clinical use. Circulation 1996;93,1043-1065[Free Full Text]
9. Borg, GA Psychophysical bases of perceived exertion. Med Sci Sports Exerc 1982;14,377-381[ISI][Medline]
10. Novak, P Time/frequency mapping of the heart rate, blood pressure and respiratory signals. Med Biol Eng Comput 1993;31,103-110[CrossRef][ISI][Medline]
11. Novak, V Slow cardiovascular rhythms at tilt and syncope. J Clin Neurophysiol 1995;12,64-71[ISI][Medline]
12. Pagani, M, Somers, V, Furlan, R, et al Changes in autonomic regulation induced by physical training in mild hypertension. Hypertension 1988;12,600-610[Abstract/Free Full Text]
13. Pagani, M, Montano, N, Porta, A, et al Relationship between spectral components of cardiovascular variabilities and direct measures of muscle sympathetic nerve activity in humans. Circulation 1997;95,1441-1448[Abstract/Free Full Text]
14. Arai, Y, Saul, JP, Albrecht, P, et al Modulation of cardiac autonomic activity during and immediately after exercise. Am J Physiol 1989;256,H132-H141
15. Yamamoto, Y, Hughson, RL, Peterson, JC Autonomic control of heart rate during exercise studied by heart rate variability spectral analysis. J Appl Physiol 1991;71,1136-1142[Abstract/Free Full Text]
16. Bernardi, L, Salvucci, F, Suardi, R, et al Evidence for an intrinsic mechanism regulating heart rate variability in the transplanted and the intact heart during submaximal dynamic exercise? Cardiovasc Res 1990;24,969-981[Free Full Text]
17. Rimoldi, O, Furlan, R, Pagani, M, et al Analysis of neural mechanisms accompanying different intensities of dynamic exercise. Chest 1992;101 (suppl),226S-230S[Abstract/Free Full Text]
18. Goldberger, JJ Sympathovagal balance: how should we measure it? Am J Physiol 1999;4,H1273-H1280
19. Zar, JH Biostatistical analysis. 1974 Prentice Hall. Englewood Cliffs, N J:
20. Perini, R, Orizio, C, Baselli, G, et al The influence of exercise intensity on the power spectrum of heart rate variability. Eur J Appl Physiol 1990;61,143-148
21. Casadei, B, Cochrane, S, Johnston, J, et al Pitfalls in the interpretation of spectral analysis of the heart rate variability during exercise in humans. Acta Physiol Scand 1995;153,125-131[ISI][Medline]
22. Nakamura, Y, Yamamoto, Y, Muraoka, I Autonomic control of heart rate during physical exercise and fractal dimension of heart rate variability. J Appl Physiol 1993;74,875-881[Abstract/Free Full Text]
23. Pomeranz, B, Macaulay, RJB, Caudill, MA, et al Assessment of autonomic function in humans by heart rate spectral analysis. Am J Physiol 1985;248,H151-H153
24. Pagani, M, Lombardi, F, Guzzetti, S, et al Power spectral analysis of heart rate and blood pressure variabilities as a marker of sympatho-vagal interaction in man and conscious dog. Circ Res 1986;59,178-193[Abstract/Free Full Text]
25. Casadei, B, Moon, J, Caiazza, A Respiratory sinus arrhythmia does not reflect cardiac vagal tone during exercise in man [abstract]. J Physiol 1993;473,66P
26. Kitney, RI Techniques for studying short-term changes in cardiorespiratory data. di Rienzo, M eds. Computer analysis of cardiovascular signals 1995,41-52 IOSA. Washington, DC:
27. Buda, AJ, Pinsky, MR, Ingels, NB, et al The effect of intrathoracic pressure on left ventricular performance. N Engl J Med 1979;301,453-459[Abstract]
28. Kallenbach, JM, Webster, T, Dowdeswell, R, et al Reflex heart rate control in asthma: evidence of parasympathetic overactivity. Chest 1985;87,644-648[Abstract/Free Full Text]
29. Marin, JM, Carrizo, SJ, Gascon, M, et al Inspiratory capacity, dynamic hyperinflation, breathlessness, and exercise performance during the 6-minute walk test in chronic obstructive pulmonary disease. Am J Respir Crit Care Med 2001;163,1395-1399[Abstract/Free Full Text]
30. Yasuma, F, Hayano, J Augmentation of respiratory sinus arrhythmia in response to progressive hypercapnia in conscious dogs. Am J Physiol 2001;280,H2336-H2341
31. Hayano, J, Yasuma, F, Okada, A, et al Respiratory sinus arrhythmia: a phenomenon improving pulmonary gas exchange and circulatory efficiency. Circulation 1996;94,842-847[Abstract/Free Full Text]
32. Brown, TE, Beightol, LA, Koh, J, et al Important influence of respiration on human R-R interval power spectra is largely ignored. J Appl Physiol 1993;75,2310-2317[Abstract/Free Full Text]
33. Blinks, JR Positive chronotropic effect of increasing right atrial pressure in the isolated mammalian heart. Am J Physiol 1956;186,299-303[Abstract/Free Full Text]
34. Kohl, P, Kamkin, AG, Kiseleva, IS, et al Mechanosensitive cells in the atrium of frog heart. Exp Physiol 1992;77,213-216[Abstract]
35. Silke, B, Hanratty, CG, Riddell, JG Heart-rate variability effects of beta-adrenoceptor agonists (xamoterol, prenalterol, and salbutamol) assessed nonlinearly with scatterplots and sequence methods. J Cardiovasc Pharmacol 1999;33,859-867[CrossRef][ISI][Medline]
36. Hanratty, CG, Silke, B, Riddell, JG Evaluation of the effect on heart rate variability of a beta2-adrenoceptor agonist and antagonist using non-linear scatterplot and sequence methods. Br J Clin Pharmacol 1999;47,157-166[CrossRef][ISI][Medline]
37. Dragone, AJ, Parlow, JL Effects of inhaled albuterol and ipratropium bromide on autonomic control of the cardiovascular system. Chest 1997;111,1514-1518[Abstract/Free Full Text]

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