CHEST. 2003;123(3) 

In This Article

What Is "Heart Rate Variability" and Is It Blunted by Tumor Necrosis Factor?

In the 18th century, Albrecht von Haller[1] made the initial observation that the beat of a healthy heart is not absolutely regular. Heart rate and rhythm are governed by the intrinsic automaticity of the sinoatrial node and the modulating influence of the autonomic nervous system. Vagal tone dominates under resting conditions,[2] and rhythmic variations in heart rate are largely dependent on vagal modulation.[3] The vagal and sympathetic nervous system constantly interact. The stimulation of the vagal afferent fibers leads to the reflex excitation of vagal efferent activity and the inhibition of sympathetic efferent activity.[4] The opposite reflex events are mediated by the stimulation of sympathetic afferent activity.[5] Central oscillators (ie, vaso-motor and respiratory centers) and peripheral oscillators (ie, oscillation in arterial pressure and respiratory movements) can further modulate the efferent sympathetic and vagal activities that are directed to the sinus node.[6] These oscillators generate rhythmic fluctuations in efferent neural discharge that are manifested as short-term and long-term oscillation in beat-to-beat intervals and periodic heart rates.[6] Heart rate variability (HRV) is a conventionally accepted term that is used to characterize these heart rate fluctuations. The analysis of HRV permits inferences to be made about the state and function of the central oscillators, autonomic efferent activity, humoral factors, and the sinus node.

In most clinical applications, HRV is analyzed by time and/or frequency domain methods.[7] Time-domain analysis refers to statistics that are derived directly from the measurement of the normal-to-normal (N-N) intervals (ie, intervals between consecutive QRS complexes resulting from sinoatrial dis-charge) and statistics calculated from the differences between successive N-N intervals.[7] Premature ectopic beats are ignored in these analyses. N-N interval-based measures are influenced both by short-term factors (eg, respiratory) and long-term factors (eg, circadian).[8] The simplest variable to calculate is the SD of the N-N intervals (SDNN). SDNN reflects all the cyclic components (ie, short-term and long-term) that are responsible for variability in the period of recording. The SD of the averages of N-N intervals determined for each 5-min period during a 24-h recording (SDANN) is a measure that nullifies short-term variability within 5-min cycles and, therefore, is used to assess intermediate-term and long-term components of HRV.[7] Short-term HRV can be evaluated using the mean of the SDNNs derived for each 5-min period for > 24 h.[7] Alternatively, time domain variables that are based on comparisons of the lengths of adjacent cycles (eg, the square root of the mean squared differences of successive N-N intervals) can be used to evaluate short-term variation.[7]

HRV analysis in the frequency domain is mathematically even more complex. Power spectral density analysis provides the basic information of how power (variance) distributes as a function of frequency. The following three main spectral components are distinguished in a spectrum calculated from short-term recordings of 2 to 5 min: high frequency (HF); low frequency (LF); and very low frequency (VLF).[7] An ultralow-frequency band (ULF) also can be found on 24-h recordings. Autonomic maneuvers such as electrical vagal stimulation, muscarinic receptor blockade, and vagotomy influence the HF spectrum component, confirming efferent vagal activity as a major contributor.6,9,10 The interpretation of the LF component is more controversial. An increased LF expressed in normalized units (ie, LF/LF 1 HF) is observed during maneuvers that increase sympathetic tone such as a 90° tilt, standing, mental stress, and moderate exercise in healthy subjects.[6] Yet, direct cardiac sympathetic blockade via epidural anesthesia, which theoretically should abolish LF power, has no effect.[11] In addition, atropine, which blocks the vagal component of HRV, reduces LF power, indicating that vagal tone contributes to LF.[9] Thus, LF power appears to represent a complex mixture of sympathetic and parasympathetic modulation of heart rate, which can reflect, under certain circumstances, sympathetic tone. While VLF and ULF components account for 95% of the total power in long-term recordings, less is known about their physiologic correlates. The VLF band may represent the influence of the peripheral vasomotor and reninangiotensin systems,[9] and perhaps the enhancement of hypoxic chemosensitivity.[12] Finally, the ULF band is thought to reflect primarily circadian variations with a periodicity of > 5 min.[13]

Chronic heart failure (CHF) is a complex clinical syndrome in which the sympathetic nervous system is chronically activated and the parasympathetic nervous system is blunted. Reduced HRV has been observed in patients with CHF.[14] The decrease in N-N variance has been attributed to impaired parasympathetic modulation of the heart rate.[15] Time domain indexes of HRV, such as SDNN, decline with increasing left ventricular dysfunction[16] and can independently predict mortality.[17] With regard to frequency domain measures, VLF components are common in patients with advanced CHF, perhaps related to severely impaired autonomic regulation, the suppression of baroreceptor function, the enhancement of hypoxic chemosensitivity, and/or distorted oscillatory breathing patterns.12,18 The LF spectral component of HRV is decreased or absent in CHF patients with advanced disease despite the presence of enhanced sympathetic activity.[14] Possible explanations for the decline in the LF component include the following: (1) impaired ß-adrenergic receptor responsiveness[19]; (2) central autonomic regulatory impairment[14]; and (3) increased chemoreceptor sensitivity.[12] The HF spectral component is detectable in most CHF patients and sometimes persists in the presence of a heavily reduced HRV, reflecting, perhaps, the effect of respiratory activity per se rather than vagal modulation. The reported decreased responsiveness of the HF component to controlled respiration in CHF emphasizes the blunted dynamics of oscillatory components in these patients compared to healthy people.[14]

In the current issue of CHEST (see page 716), Malave and colleagues present evidence that tumor necrosis factor (TNF) is involved in the suppression of HRV in patients with heart failure. Patients with mild-to-moderate heart failure and age-matched control subjects underwent 24-h ambulatory ECG recordings for the purpose of assessing time domain indexes (ie, SDNN and SDANN) and frequency domain indexes (ie, LF and HF) of HRV in the context of circulating levels of TNF, TNF receptors, and norepinephrine. The authors have made two significant observations in this study. First, they have shown that there is an inverse relationship between increased levels of circulating TNF and the depressed time and frequency domain indexes of HRV. Less robust relationships were observed with the soluble TNF receptors. Second, the circulating level of TNF was a stronger independent predictor of depressed HRV than was plasma norepinephrine. Based on previous work in isolated myocytes and in transgenic mice overexpressing TNF, the authors have speculated that "increased expression of TNF may be one of several different mechanisms that contribute to the blunting of ß-adrenergic responsiveness of the failing heart to sympathoadrenergic drive during the progression of heart failure."

As is often the case, this clinical study raises more questions than it is capable of answering. The underlying biochemical and neurophysiologic mechanisms that are responsible for alterations in HRV remain poorly understood. The complex interplay between the parasympathetic and the sympathetic nervous systems as well as between TNF and the sympathetic nervous system compound the difficulty in attributing precise explanations for the findings in this study.20,21 TNF also may have either direct or indirect influences on vagal tone and/or responsiveness. Not only were elevated TNF levels inversely correlated with the LF component of spectral power (a putative but not confirmed index of sympathetic activity/responsiveness),[6,9,11] they also were found to be inversely correlated with the HF band, a component generally thought to reflect parasympathetic activity/responsiveness.[7] Conceivably, the findings in this study represent an epiphenomenon. TNF levels are known to be low in healthy subjects and high in CHF patients, proportional to the degree of functional impairment.[22] Similarly, time and frequency domain indexes of HRV are high in healthy subjects and decline proportionally with the severity of heart failure. Any parameter that is normal in control subjects and is abnormal in CHF patients, proportional to the magnitude of disease, will likely correlate with any other parameter with the same characteristics. To test whether a direct cause-and-effect relationship exists between TNF level and depressed HRV, subjects would need to be reevaluated after treatment with an agent that either neutralizes the biological activity of TNF (eg, etanercept) or prevents the production of TNF (eg, pentoxifylline). Unfortunately, these studies could not be conducted. Clinical trials with TNF antagonists in patients with heart failure, including etanercept, have been stopped due to a lack of efficacy. Pentoxifylline increases cyclic adenosine monophosphate levels and might therefore alter HRV independently of its TNF lowering effects. The assessment of whether TNF directly influences parameters of HRV awaits the availability of an agent that can retard the synthesis and/or biological activity of this cytokine.

Despite these limitations, the finding that TNF is a stronger independent predictor of depressed HRV than was norepinephrine is encouraging for the possible existence of a direct relationship, as opposed to an epiphenomenon. The importance of norepinephrine as a mediator of diminished HRV in advanced heart failure is well-accepted and is supported by recent data[23] showing that carvedilol, a nonselective ß-blocker with a 1-blocking properties, improves time and frequency domain indexes of HRV in these patients. Adding to previous work[24] in which TNF has been shown to alter cardiac structure and function, this current study by Malave and colleagues provides further support for the belief that TNF is a maladaptive mediator in patients with CHF. Clearly, further study is needed to define the mechanisms of depressed HRV and the role of TNF in this devastating disease.

David R. Murray, MD, San Antonio, TX

Dr. Murray is Associate Professor of Medicine, University of Texas Health Science Center at San Antonio.

Reproduction of this article is prohibited without written permission from the American College of Chest Physicians (e-mail: permissions@chestnet.org).

Correspondence to: David R. Murray, MD, Medicine/Cardiology, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Dr, San Antonio, TX 78229-3900; E-mail: MurrayD@uthscsa.edu.

  1. von Haller A. Elements physiologica. Lausanne, Switzerland: T. II Lit. V, 1760; 330

  2. Levy MN. Sympathetic-parasympathetic interactions in the heart. Circ Res 1971; 29:437-445

  3. Chess GF, Tam RMK, Calaresu FR. Influence of cardiac neural inputs on rhythmic variations of heart period in the cat. Am J Physiol 1975; 228:775-780

  4. Schwartz PJ, Pagani M, Lombardi F, et al. A cardiogenic sympathovagal reflex in the cat. Circ Res 1973; 32:215-220

  5. Malliani A. Cardiovascular sympathetic afferent fibers. Rev Physiol Biochem Pharmacol 1982; 94:11-74

  6. Malliani A, Pagani M, Lombardi F, et al. Cardiovascular neural regulation explored in the frequency domain. Circulation 1991; 84:1482-1492

  7. 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

  8. Kleiger RE, Stein PK, Bosner MS, et al. Time domain measurements of heart rate variability. Cardiol Clin 1992; 10:487-498

  9. Akselrod S, Gordon D, Ubel FA, et al. Power spectrum analysis of heart rate fluctuation: a quantitative probe of beat to beat cardiovascular control. Science 1981; 213:220-222

  10. Pomeranz M, Macaulay RJB, Caudill MA, et al. Assessment of autonomic function in humans by heart rate spectral analysis. Am J Physiol 1985; 248:H151-H153

  11. Hopf H-B, Skyschally A, Heusch G, et al. Low-frequency spectral power of heart rate variability is not a specific marker of cardiac sympathetic modulation. Anesthesiology 1995; 82:609-619

  12. Ponikowski P, Chua TP, Amadi AA, et al. Detection and significance of a discrete very low frequency rhythm in RR interval variability in chronic congestive heart failure. Am J Cardiol 1996; 77:1320-1326

  13. Stein PK, Kleiger RE. Insights from the study of heart rate variability. Ann Rev Med 1999; 50:249-261

  14. Guzzetti S, Magatelli R, Borroni E, et al. Heart rate variability in chronic heart failure. Auton Neurosci 2001; 90:102-105

  15. Flores JS. Clinical aspects of sympathetic activation and parasympathetic withdrawal in heart failure. J Am Coll Cardiol 1993; 22:72A- 84A

  16. Casolo GC, Stroder P, Sulla A, et al. Heart rate variability and functional severity of congestive heart failure secondary to coronary artery disease. Eur Heart J 1995; 16:360-367

  17. Nolan J, Batin PD, Andrews R, et al. Prospective study of heart rate variability and mortality in chronic heart failure. Circulation 1998; 98:1510-1516

  18. Mortara A, Sleight P, Pinna GD, et al. Abnormal awake respiratory patterns are common in chronic heart failure and may prevent evaluation of autonomic tone by measures of heart rate variability. Circulation 1997; 96:246-252

  19. Bristow MR, Ginsberg R, Minobe W, et al. Decreased catecholamine sensitivity and ß-adrenergic receptor density in failing human hearts. N Engl J Med 1982; 307:205-211

  20. Murray DR, Freeman GL. Tumor necrosis factor-a induces a biphasic effect on myocardial contractility in conscious dogs. Circ Res 1996; 78:154-160

  21. Murray DR, Prabhu SD, Chandrasekar B. Chronic b adrenergic stimulation induces myocardial proinflammatory cytokine expression. Circulation 2000; 101:2338-2341

  22. Torre-Amione G, Kapadia S, Benedict C, et al. Proinflammatory cytokine levels in patients with depressed left ventricular ejection fraction: a report from the studies of left ventricular dysfunction (SOLVD). J Am Coll Cardiol 1996; 27:1201-1206

  23. Ridha M, Makikallio TH, Lopera G, et al. Effects of carve-dilol on heart rate dynamics in patients with congestive heart failure. Ann Noninvasive Electrocardiol 2002; 7:133-138

  24. Mann DL. Stress activated cytokines and the heart. Growth Factor Cytokine Rev 1996; 7:341-354