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The effects of cardiac rehabilitation on heart rate variability in patients with coronary heart disease
Abstract and Figures
Introduction Structured exercise, as a therapeutic intervention, is central to cardiac rehabilitation (CR).1 Following myocardial infarction (Ml), cardiac autonomic activity becomes disordered, often resulting in loss ofvagal reflexes and increased sympathetic activity.2 Sympathetic hyperactivity predisposes towards ventricular fibrillation, while vagal reflexes are considered to have a cardio-protective effect.3 The activity of the autonomic nervous system (ANS) can be measured non-invasively by analysis of heart rate variability (HRV), which is a characteristic that can potentially be increased by physical activity.4 Coarse-graining spectral analysis (CGSA) of HRV is a sensitive, non-invasive technique commonly used to evaluate cardiac autonomic activity.5 HRV allows the examination of parasympathetic and sympathetic function via the analysis of the various components of the frequency domain. High frequency spectral power (HF, 0.15-0.40 Hz) is generally considered to be a measure of cardiac parasympathetic modulation, whereas low frequency power (LF, 0.04-0.15 Hz) reflects both parasympathetic and sympathetic control.6 The purpose of this study was to determine the effects of a predominantly exercise-based cardiac rehabilitation programme over a six-month period on cardiac autonomic modulation, using power spectral analysis of HRV.
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... Therapeutic interventions such as cardiac rehabilitation mainly include structured exercise [12]. Structured exercise training (ET) and physical activity are recommended for cardiac health in the HF guidelines of the European Society of Cardiology. ...
Background: Cardiac resynchronization therapy (CRT) results in improved
morbidity, mortality, symptoms, quality of life (QOL) and exercise capacity,
in appropriate chronic heart failure (CHF) patients. Moreover, combined ex-
ercise training (ET) and CRT maximize these improvements in these patients.
The study evaluated the effect of ET on these patients in terms of QOL, func-
tional class, exercise capacity and left ventricular ejection fraction (LVEF).
Results: There were significant improvements in the QOL, functional class,
exercise capacity, and LVEF compared with the Control Group. Comparison
of both groups confirmed the cumulative effects of ET with CRT. The QOL
improved by the end of training in the exercise group (p = 0.001), compared
to the Control Group (p = 0.850). NYHA functional class improved signifi-
cantly in the Exercise Group (p = 0.013). Percent-predicted peak oxygen
consumption (VO2 peak) had significantly improved in the trained (p <
0.001) versus the untrained CRT Group (p = 0.596). There was a mean per-
cent rise of the ejection fraction from 39.2 ± 12.86 to 44.40% ± 14.42% in the
Exercise Group compared to a non-significant change in the Control Group.
Conclusion: ET in resynchronized CHF patients is feasible and further en-
hances QOL and exercise tolerance in addition to the improvements seen af-
ter CRT. The study therefore recommends for the prescription of ET after
implantation in order to maximize the expected benefit.
Keywords
Chronic Heart Failure, Cardiac Resynchronization Therapy, Exercise
Training, Quality of Life
Objective:
The measurement of heart rate variability (HRV) is often applied as an index of autonomic nervous system (ANS) balance and, therefore, myocardial stability. Previous studies have suggested that relaxation or mind-body exercise can influence ANS balance positively as measured by HRV but may act via different mechanisms. No studies, to the authors' knowledge, have examined the acute response in HRV to interventions combining relaxation and mind-body exercise. The objective of this study was to compare the acute HRV responses to Yoga Nidra relaxation alone versus Yoga Nidra relaxation preceded by Hatha yoga.
Design:
This was a randomized counter-balanced trial.
Setting:
The trial was conducted in a university exercise physiology laboratory.
Subjects:
Subjects included 20 women and men (29.15±6.98 years of age, with a range of 18-47 years).
Interventions:
Participants completed a yoga plus relaxation (YR) session and a relaxation only (R) session.
Results:
The YR condition produced significant changes from baseline in heart rate (HR; beats per minute [bpm], p<0.001) and indices of HRV: R-R (ms, p<0.001), pNN50 (%, p=0.009), low frequency (LF; %, p=0.008) and high frequency (HF; %, p=0.035). The R condition produced significant changes from baseline in heart rate (bpm, p<0.001) as well as indices of HRV: R-R (ms, p<0.001), HF (ms(2), p=0.004), LF (%, p=0.005), HF (%, p=0.008) and LF:HF ratio (%, p=0.008). There were no significant differences between conditions at baseline nor for the changes from baseline for any of the variables.
Conclusions:
These changes demonstrate a favorable shift in autonomic balance to the parasympathetic branch of the ANS for both conditions, and that Yoga Nidra relaxation produces favorable changes in measures of HRV whether alone or preceded by a bout of Hatha yoga.
Exercise training and heart rate variability in older people. Med. Sci. Sports Exerc., Vol. 31, No. 6, pp. 816-821, 1999.
Purpose: Heart rate variability (HRV), a characteristic that is potentially increased by physical activity, has been associated with incidence of cardiac events and total mortality. Since the incidence of cardiac events among older people is high and their physical activity levels and HRV are generally low, it is important to investigate whether regular physical activity can modify HRV in this age group. The purpose of the study was to investigate the effect of regular physical activity on HRV in older men and women.
Methods: In a randomized controlled trial, the effect of six months' training on HRV was investigated in a group of 51 older men and women (67.0 ± 5.1 yr). The training group gathered three times per week for 45 min supervised training.
Results: At the end of the intervention period, HRV was higher primarily during the day. During daytime, the SD of all normal intervals (+6%) as well as the low frequency component (+15%) and the very low frequency component (+10%) of HRV were significantly increased (P < 0.05) as compared with the control group. Effects of training were most pronounced in subjects inactive in sports at baseline.
Conclusion: This study demonstrates that regular physical activity increases HRV (specifically in the very low and low frequency components) in older subjects. Hence, in older subjects, physical training may be an effective means to modify positively a factor that is associated with increased incidence of cardiac events.
A protective effect of exercise in preventing sudden cardiac death is supported by studies in healthy populations as well as in patients with cardiac disease. The mechanisms involved in this protective effect are unknown.
We hypothesized that exercise conditioning would beneficially alter autonomic nervous system tone, measured by heart rate variability.
We prospectively studied 20 cardiac patients enrolled in a Phase 2 12-week cardiac rehabilitation program following a recent cardiac event. The patients underwent 24 h Holter monitoring at program entry and 12 weeks later. Heart rate variability analysis was assessed for both time domain and spectral analysis.
The group demonstrated a modest mean conditioning effect, indicated by an average reduction in resting heart rate from 81 +/- 16 to 75 +/- 12 beats/min (p = 0.03), and an increase in training METS from 2.1 +/- 0.4 to 3.3 +/- 1.1 (p < 0.0001). Overall, 15 of 20 (75%) patients demonstrated increased total and high-frequency power, and mean high-frequency power was significantly increased (3.9 +/- 1.4 vs. 4.4 +/- 1.0 ln, p = 0.05). When stratified according to the magnitude of exercise conditioning, patients achieving an increase of > 1.5 training METS demonstrated significant increases in SDNN, SDANN index, SDNN index, pNN50, total power, and high-frequency power (all p < 0.05) (see text for explanation of abbreviations).
Exercise conditioning improves heart rate variability in cardiac patients, particularly in patients who achieve a threshold of > 1.5 training METS increase over a 12-week period. These study results are supportive of the concept that exercise training lowers the risk of sudden cardiac death via increased vagal tone, which likely beneficially alters ventricular fibrillatory and ischemic thresholds.
The aim was to examine the cardiac autonomic responses to orthostatic stress and recovery from steady state exercise in endurance trained athletes and sedentary subjects.
The power spectrum of heart rate variability was measured before and after exercise in 10 male long distance runners and 14 male sedentary control subjects. Both groups were comparable in sex, age, and body mass index. Continuous ECG recordings were obtained during the following physiological manoeuvres: 45 min supine rest state; 10 min standing; 15 min steady state exercise at 50% maximum workload, and 15 min while supine during post-exercise recovery. The resting heart rate of athletes was lower than controls, at 52(SD 4.9) v 67(8.7) beats.min-1, p < 0.001. Power spectrum analysis was performed using autoregressive modelling.
The resting high frequency (HF) vagal component was higher in athletes than controls, at 62 (10.7) v 44(22.4) beats.min-1.Hz-1, p < 0.05. The resting low frequency (LF) peak power was significantly reduced in athletes, at 54(9.9) v 70(19.5) in control, p < 0.05. Although no group differences were observed during upright posture or exercise, the LF:HF area ratio had already returned to pre-exercise levels within 5 min of recovery in athletes. Conversely, it required up to 15 min of recovery before a noticeable decrease in the LF:HF area ratio was seen in controls.
These data support the hypothesis that endurance training modifies heart rate control in whole or in part through neurocardiac mechanisms.
Experience with frequency domain analysis over the past two decades strongly suggests that it represents a unique, noninvasive tool for achieving a more precise assessment of autonomic function in both the experimental and clinical settings. Available studies indicate that the significance of the HF component is far better understood than that of the lower frequency components. In general, it is considered to reflect vagal activity, and because it is readily manipulated pharmacologically, is used as an index of that activity. However, some caution is required because this parameter also is strongly influenced by the degree of coupling between respiration and heart rate, which, in turn, reflects the intensity of the respiratory effort as well as of parasympathetic activity. Respiratory pattern also can significantly influence HF power. The use of controlled breathing minimizes these problems, improves reproducibility of test findings, and also facilitates quantitative comparisons. The situation with respect to LF power is more complicated because it is modulated by both sympathetic and parasympathetic outflows (see previous discussion) as well as by other factors, including baroreceptor activity. Therefore, LF analysis per se cannot afford a precise delineation of the state of sympathetic activation. Determinations of the LF/HF ratio, an index of sympathovagal balance both under control conditions and in conjunction with interventions that maximize sympathetic and parasympathetic activity, provide additional insights, as do correlations between spectral activity and direct nerve recordings, plasma norepinephrine concentrations, and radionuclide imaging of adrenergic nerves.
Seven hundred fifteen participants from a multicenter natural history study of acute myocardial infarction were studied (1) to determine the correlations among time and frequency domain measures of heart period variability, (2) to determine the correlations between the measures of heart period variability and previously established post-infarction risk predictors, and (3) to determine the predictive value of time domain measures of heart period variability for death during follow-up after acute myocardial infarction. Twenty-four hour electrocardiographic recordings obtained 11 +/- 3 days after acute myocardial infarction were analyzed and 11 measures of heart period variability were computed. Each of 4 bands in the heart period power spectrum had 1 or 2 corresponding variables in the time domain that correlated with it so strongly (r greater than or equal to 0.90) that the variables were essentially equivalent: ultra low frequency power with SDNN* and SDANN index,* very low frequency power and low-frequency power with SDNN index,* and high-frequency power with r-MSSD* and pNN50.* As expected from theoretical considerations, SDNN and the square root of total power were almost perfectly correlated. Correlations between the time and frequency domain measures of heart period variability and previously identified postinfarction risk predictors, e.g., left ventricular ejection fraction and ventricular arrhythmias, are remarkably weak. Time domain measures of heart period variability, especially those that measure ultra low or low-frequency power, are strongly and independently associated with death during follow-up. * Defined in Table II.
Many secondary abnormalities in chronic heart failure (CHF) may reflect physical deconditioning. There has been no prospective, controlled study of the effects of physical training on hemodynamics and autonomic function in CHF.
In a controlled crossover trial of 8 weeks of exercise training, 17 men with stable moderate to severe CHF (age, 61.8 +/- 1.5 years; left ventricular ejection fraction, 19.6 +/- 2.3%), increased exercise tolerance (13.9 +/- 1.0 to 16.5 +/- 1.0 minutes, p less than 0.001), and peak oxygen uptake (13.2 +/- 0.9 to 15.6 +/- 1.0 ml/kg/min, p less than 0.01) significantly compared with controls. Training increased cardiac output at submaximal (5.9-6.7 l/min, p less than 0.05) and peak exercise (6.3-7.1 l/min, p less than 0.05), with a significant reduction in systemic vascular resistance. Training reduced minute ventilation and the slope relating minute ventilation to carbon dioxide production (-10.5%, p less than 0.05). Sympathovagal balance was altered by physical training when assessed by three methods: 1) RR variability (+19.2%, p less than 0.05); 2) autoregressive power spectral analysis of the resting ECG divided into low-frequency (-21.2%, p less than 0.01) and high-frequency (+51.3%, p less than 0.05) components; and 3) whole-body radiolabeled norepinephrine spillover (-16%, p less than 0.05). These measurements all showed a significant shift away from sympathetic toward enhanced vagal activity after training.
Carefully selected patients with moderate to severe CHF can achieve significant, worthwhile improvements with exercise training. Physical deconditioning may be partly responsible for some of the associated abnormalities and exercise limitation of CHF, including abnormalities in autonomic balance.
After acute myocardial infarction (AMI), several abnormalities of the autonomic control to the heart have been described. Heart rate (HR) variability has been used to explore the neural control to the heart. A low HR variability count measured 7-13 days after AMI is significantly related to a poor outcome. Little information is available on HR variability early after AMI and its relation to clinical and hemodynamic data.
We studied 54 consecutive patients (42 men and 12 women; mean age, 60.4 +/- 11 years) with evidence of AMI by collecting the 24-hour HR SD from Holter tapes recorded on day 2 or 3. We also measured HR variability in 15 patients with unstable angina and in 35 age-matched normal subjects. HR variability was lower in AMI than in unstable angina patients (57.6 +/- 21.3 versus 92 +/- 19 msec; p less than 0.001) and controls (105 +/- 12 msec; p less than 0.001). Also, HR variability was greater in non-Q-wave than in Q-wave AMI (p less than 0.0001) and in recombinant tissue-type plasminogen activator-treated patients with respect to the rest of the group (p less than 0.02). No difference was found for infarct site. HR variability was significantly related to mean 24-hour HR, peak creatine kinase-MB, and left ventricular ejection fraction (all p less than 0.0001). Patients belonging to Killip class greater than I or who required the use of diuretics or digitalis had lower counts (p less than 0.004, p less than 0.001, and p less than 0.024, respectively). Six patients died within 20 days after admission to the hospital. In these patients, HR variability was lower than in survivors (31.2 +/- 12 versus 60.9 +/- 20 msec; p less than 0.001), and a value less than 50 msec was significantly associated with mortality (p less than 0.025).
HR variability during the early phase of AMI is decreased and is significantly related to clinical and hemodynamic indexes of severity. The causes for the observed changes in HR variability during AMI may be reduced vagal and/or increased sympathetic outflow to the heart. It is suggested that early measurements of HR variability during AMI may offer important clinical information and contribute to the early risk stratification of patients.
Heart rate variability (HRV) spectra are typically analyzed for the components related to low- (less than 0.15 Hz) and high- (greater than 0.15 Hz) frequency variations. However, there are very-low-frequency components with periods up to hours in HRV signals, which might smear short-term spectra. We developed a method of spectral analysis suitable for selectively extracting very-low-frequency components, leaving intact the low- and high-frequency components of interest in HRV spectral analysis. Computer simulations showed that those low-frequency components were well characterized by fractional Brownian motions (FBMs). If the scale invariant, or self-similar, property of FBMs is considered a new time series (x') was constructed by sampling only every other point (course graining) of the original time series (x). Evaluation of the cross-power spectra between these two (Sxx') showed that the power of the FBM components was preserved, whereas that of the harmonic components vanished. Subtraction of magnitude of Sxx from the autopower spectra of the original sequence emphasized only the harmonic components. Application of this method to HRV spectral analyses indicated that it might enable one to observe more clearly the low- and high-frequency components characteristic of autonomic control of heart rate.