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Increased total heart rate variability and enhanced cardiac vagal autonomic activity in healthy humans with sinus bradycardia.

Sinus bradycardia can be defined as a sinus rhythm with a resting heart rate (HR) of 60 beats per minute (bpm) or less. However, few patients actually become symptomatic until their heart rate drops to <50 bpm (1). That is, even while resting HR tends to diminish with age (2), physiological regulatory mechanisms maintain normal cardiac output by increasing stroke output both at rest and during exercise (2).

Sinus bradycardia is not commonly included among relevant biomarkers precipitating overt cardiovascular disease (1); a low resting sinus rate even appears to be a protecting factor against heart failure, but a high sinus rate emerged as an independent predictor of mortality in prospective studies carried out in the general population (3) and in selected groups of patients with hypertension (4) or myocardial infarction (5).

Commonly, sinus bradycardia is an incidental finding in otherwise healthy individuals, particularly in adults or sleeping patients. However, it remains unknown whether the autonomic nervous system has a significant influence on the maintenance of sinus bradycardia. Although it is assumed that the vagal system is contributory toward sinus bradycardia (2), actual data relating to cardiac autonomic indices of asymptomatic patients with resting heart rates of <60 bpm are lacking. However, considerable effort has gone into describing resting HR being modulated by a balance between sympathetic and parasympathetic tone with a predominance of the latter (6, 7). On this basis, some reports state that an increased vagal tonus is the main mechanism for the bradycardia induced by aerobic and/or endurance physical training (8). However, several other studies have failed to demonstrate differences in vagal tone between trained and untrained subjects (9, 10). Thus, our aims were to study healthy asymptomatic subjects with sinus bradycardia, calculate their cardiac heart rate variability (HRV) indices, and contrast these results with those of a group of subjects with normal sinus HR.


To be included in this study, human subjects had to be at least 45 years old with no known diabetes or other cardiovascular health problems. Participants were excluded from the analysis if any cardiovascular anomaly was reported or identified on the electrocardiogram (ECG) trace (apart from sinus bradycardia) as well as if the ECG trace contained excessive noise. A standard three-lead ECG was obtained from 43 subjects (15 men and 28 women; mean age 54 [+ or -] 11 years SD) who had normal sinus rhythm and from 25 subjects (8 men and 17 women; mean age 57 [+ or -] 11 years SD) with sinus bradycardia. ECG data were acquired using a Maclab system (AD Instruments) and Chart (version 5). The ECG sampling rate was 400 samples per second with filters set to recommended levels to minimize baseline noise. A 20-minute ECG was recorded while the subject was in a resting supine position.

HRV was analyzed using the program Soft-ECG (copyright Herbert Jelinek). Before the Macintosh ECG recording was converted into Soft-ECG format, the digital ECG trace was manually edited to remove any movement artifacts and ectopic beats (11). Soft-ECG then converts the raw ECG trace into an R-R interval graph for analysis. R-R intervals are determined by using the criteria for detecting the fiducial point of the QRS wave (12). Once converted into an R-R graph, further intervals greater and smaller than 200 ms from the mean interval length were removed, as these were deemed to reflect ectopic beats or noise. The HRV parameters calculated include frequency domain analysis, time domain analysis, and nonlinear analysis measures (Table 1). The results were statistically analyzed using a t test or a Kruskal-Wallis test if the HRV data between sample comparisons were nonparametric. Results were considered significant if the P value was <0.05.


Statistically significant increases in time domain analysis HRV parameters (SDNN, RMSDD) were found in the sinus bradycardia group when compared with normal sinus rate subjects (P < 0.05) (Table 2). SDNN reflects both sympathetic and parasympathetic activity and therefore provides an index of total HRV (6). RMSSD estimates the short-term components of HRV and provides an estimate of vagal nerve activity (6). Thus, in sinus bradycardia, total HRV is increased, and there is likely an increase in vagal activity that is also likely responsible for slowing the HR. It is difficult to interpret if sympathetic drive is changed using time domain analysis, although nonlinear analysis measures of HRV revealed no significant sympathetic differences between subjects with sinus bradycardia and normal sinus rate. Additionally, the nonlinear measure of HRV DFA32 was significantly increased in bradycardia subjects compared with normal sinus subjects, reflecting the increased complexity of the ECG and hence increased total HRV in bradycardia.


This study reflects two important findings. First, bradycardia is associated with increased total power, as measured in the frequency domain. Thus, a reduced nonpathological HR is likely to confer cardiac protection. Indeed, it has been shown that decreased HRV is associated with advancing age, which carries an increased risk of cardiac-related events in clinically disease-free patients (13); however, this is not likely to be the case in aging populations with reduced HR. Also, studies have demonstrated that a decreased HRV provides a poor prognosis for postinfarction patients and heart failure patients (14).

Second, we can confirm that "normal" sinus bradycardia in our study population is due to an increase in vagal drive, as revealed by time domain measures of HRV, i.e., an increase in RMSDD. It is incorrect to assume that increased vagal drive must be responsible for all cases of sinus bradycardia. For example, enhanced cardiac vagal efferent activity does not explain sports endurance training--induced bradycardia compared with age-matched controls. Finally, it has been shown that there is a decline in total HRV with aging mainly, but not exclusively, due to a decline in parasympathetic tonus (15).

Thus, in an aging population, a slow heart rate is likely to confer cardioprotective benefits due to an associated increase in parasympathetic autonomic tone and also an associated increase in total HRV.

(1.) Alboni P, Brignole M, Menozzi C, Scarfa S. Is sinus bradycardia a factor facilitating overt heart failure? Eur Heart J 1999;20(4):252-255.

(2.) Agruss NS, Rosin EY, Adolph RJ, Fowler NO. Significance of chronic sinus bradycardia in elderly people. Circulation 1972;46(5):924-930.

(3.) Kannel WB, Kannel C, Paffenbarger RS Jr, Cupples LA. Heart rate and cardiovascular mortality: the Framingham Study. Am Heart J 1987;113(6):1489-1494.

(4.) Gillman MW, Kannel WB, Belanger A, D'Agostino RB. Influence of heart rate on mortality among persons with hypertension: the Framingham Study. Am Heart J 1993;125(4):1148-1154.

(5.) Dyer AR, Persky V, Stamler J, Paul O, Shekelle RB, Berkson DM, Lepper M, Schoenberger JA, Lindberg HA. Heart rate as a prognostic factor for coronary heart disease and mortality: findings in three Chicago epidemiologic studies. Am J Epidemiol 1980;112(6):736-749.

(6.) 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(5):1043-1065.

(7.) Akselrod S, Gordon D, Ubel FA, Shannon DC, Berger AC, Cohen RJ. Power spectrum analysis of heart rate fluctuation: a quantitative probe of beat-to-beat cardiovascular control. Science 1981;213(4504):220-222.

(8.) Catai AM, Chacon-Mikahil MP, Martinelli FS, Forti VA, Silva E, Golfetti R, Martins LE, Szrajer JS, Wanderley JS, Lima-Filho EC, Milan LA, Marin-Neto JA, Maciel BC, Gallo-Junior L. Effects of aerobic exercise training on heart rate variability during wakefulness and sleep and cardiorespiratory responses of young and middle-aged healthy men. Braz J Med Biol Res 2002;35(6):741-752.

(9.) Perrault H, Gagnon MC, Johnson D, Mokrane A, Nadeau RA. An enhanced vagal influence does not explain training-induced bradycardia. Physiologist 1996;39:A20.

(10.) Scott AS, Eberhard A, Ofir D, Benchetrit G, Dinh TP, Calabrese P, Lesiuk V, Perrault H. Enhanced cardiac vagal efferent activity does not explain training-induced bradycardia. Auton Neurosci 2004;112(1-2):60-68.

(11.) Touma F, Chew VS, Chua WC, Jelinek H, Wong PT, Spence I, McLachlan CS. Chronic high dose captopril decreases total heart rate variability and increases heart rate in C57BL/6J mice. Int J Cardiol 2009;136(2):211-213.

(12.) Tompkins WJ. Biomedical Digital Signal Processing: C-Language Examples and Laboratory Experiments for the IBM PC. Englewood Cliffs, NJ: Prentice Hall, 1993.

(13.) Tsuji H, Venditti FJ Jr, Manders ES, Evans JC, Larson MG, Feldman CL, Levy D. Determinants of heart rate variability. J Am Coll Cardiol 1996;28(6):1539-1546.

(14.) de Bruyne MC, Kors JA, Hoes AW, Klootwijk P, Dekker JM, Hofman A, van Bemmel JH, Grobbee DE. Both decreased and increased heart rate variability on the standard 10-second electrocardiogram predict cardiac mortality in the elderly: the Rotterdam Study. Am J Epidemiol 1999;150(12):1282-1288.

(15.) Shannon DC, Carley DW, Benson H. Aging of modulation of heart rate. Am J Physiol 1987;253(4 Pt 2):H874-H877.

Craig S. McLachlan, PhD, MPH, Ryan Ocsan, MSc, Ian Spence, PhD, Brett Hambly, MD, PhD, Slade Matthews, PhD, Lexin Wang, MD, PhD, and Herbert F. Jelinek, PhD

From the Department of Physiology, National University of Singapore, Singapore (McLachlan); the Kolling Institute, the Sydney Medical School, the University of Sydney, Australia (McLachlan); the Departments of Pharmacology (Spence, Matthews) and Pathology (Ocsan, Hambly), the University of Sydney, Sydney, Australia; the School of Biomedical Sciences, Charles Sturt University, Wagga Wagga, Australia (Wang); and the School of Community Health, Charles Sturt University, Albury, Australia (Jelinek).

Corresponding author: Craig S. McLachlan, PhD, MPH, The George Institute for Global Health, PO Box M201, Missenden Road, NSW 2050 Australia (e-mail:
Table 1. HRV definitions

Parameter Units Description

Frequency domain

Total power [ms.sup.2] Variance of normal-to-normal (NN)
 intervals (i.e., from one QRS
 point of the ECG to the next) over
 the temporal segment. Used as a
 global index/measure of total HRV.
 (Frequency range: ~<0.4 Hz)

HF (high frequency) [ms.sup.2] Power in high-frequency range.
 High power in this domain is
 associated with increased
 parasympathetic function/drive.
 (Frequency range: 0.15-0.04 Hz)

LF (low frequency) [ms.sup.2] Power in low-frequency range.
 Usually consists of a
 parasympathetic and sympathetic
 component. High power in this
 domain is associated with
 increased sympathetic tone.
 (Frequency range: 0.04-0.15 Hz)

HF ln HF power in logarithmic form. Can
 be used if distribution is skewed.

LF ln LF power in logarithmic form. Can
 be used if distribution is skewed.

HF norm nu HF power in normalized units--to
 reduce the effects of
 noise/artifacts and to minimize
 the effects of changes in total
 power on LF and HF components.

LF norm nu LF power in normalized
 units--useful when evaluating
 subjects with varying differences
 in total power.

LF/HF Ratio of low- to high-frequency
 power. An increase in the ratio
 suggests an increase in
 sympathetic modulation, a decrease
 in parasympathetic modulation, or

Time domain analysis: The heart rate at any point in time or the
intervals between successive normal complexes. In a continuous ECG
record, each QRS complex is detected, as well as the so-called
normal-to-normal (NN) intervals (that is, all intervals between
adjacent QRS complexes resulting from sinus node depolarizations).

SDNN (standard ms Standard deviation of all NN
deviation of NN intervals, reflecting all the
intervals) cyclic components responsible for
 variability. A global marker of
 HRV, encompassing parasympathetic
 and sympathetic influences.

RMSSD (square root ms The square root of the mean of the
of the mean squared sum of the squares of differences
differences of between adjacent NN intervals. It
successive NN evaluates components that have a
intervals) short-term effect on HRV,
 corresponding to parasympathetic

Nonlinear analysis

DFA (detrended Reveals distinct fractal features
fluctuation of HRV. Scale invariance has been
analysis) [alpha]1 commonly observed with a
and [alpha]2 characteristic break at segment
 sizes of 16 heartbeats.
 Consequently, two scaling
 exponents, termed a1 and a2, are
 computed in the ranges of 4 to 16
 and 16 to 64 heart beats,

DFA32 Fluctuation seen within one time
 domain at 32 beats.

ApEN (approximate An estimation of the overall
entropy) regularity and complexity of time
 series data. A low ApEn value
 indicates more regular and less

 complex data, whereas a high value
 indicates a more irregular data
 set with high complexity.

ECG indicates electrocardiogram; HRV, heart rate variability.

Table 2. Summary statistics for frequency domain, time domain,
and nonlinear heart rate variability across the two heart rate

 Mean value [+ or -] standard deviation

 Normal HR Bradycardia HR
Parameter (n = 43) (n = 25)

Frequency domain analysis

Total power 1817 [+ or -] 1460 2411 [+ or -] 1724
HF 367 [+ or -] 530 401 [+ or -] 290
LF 448 [+ or -] 404 621 [+ or -] 572
HF ln 5.27 [+ or -] 1.09 5.720 [+ or -] 0.827
LF ln 5.695 [+ or -] 0.960 6.086 [+ or -] 0.831
HF norm 47.7 [+ or -] 65.0 40.7 [+ or -] 12.6
LF norm 56.3 [+ or -] 19.0 56.8 [+ or -] 12.8
LF/HF 2.24 [+ or -] 2.10 1.75 [+ or -] 1.36

Time domain analysis

SDNN 40.5 [+ or -] 15.4 48.7 [+ or -] 15.1
RMSSD 26.2 [+ or -] 14.5 33.6 [+ or -] 13.0

Nonlinear analysis

DFA [alpha]1 1.013 [+ or -] 0.296 1.057 [+ or -] 0.247
DFA [alpha]2 0.938 [+ or -] 0.178 0.923 [+ or -] 0.132
DFA32 91.4 [+ or -] 42.2 129.0 [+ or -] 72.1
ApEN 1.112 [+ or -] 0.236 1.181 [+ or -] 0.199

 P value
 Kruskal- P value
Parameter Wallis test f test

Frequency domain analysis

Total power 0.113 0.155
HF 0.038 * 0.34
LF 0.135 0.19
HF ln 0.038 * 0.06
LF ln 0.135 0.082
HF norm 0.488 0.498
LF norm 0.975 0.898
LF/HF 0.661 0.249

Time domain analysis

SDNN 0.038 * 0.038 *
RMSSD 0.007 * 0.034 *

Nonlinear analysis

DFA [alpha]1 0.537 0.513
DFA [alpha]2 0.642 0.688
DFA32 0.01 * 0.023 *
ApEN 0.242 0.203

* Significant at P < 0.05.

HR indicates heart rate; for other abbreviations, see Table 1.
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Article Details
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Author:McLachlan, Craig S.; Ocsan, Ryan; Spence, Ian; Hambly, Brett; Matthews, Slade; Wang, Lexin; Jelinek,
Publication:Baylor University Medical Center Proceedings
Article Type:Clinical report
Geographic Code:8AUST
Date:Oct 1, 2010
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