Pathophysiology of Exercise Heart Rate Recovery: A Comprehensive Analysis

Expanded use of exercise heart rate recovery (HRR) has renewed interest in the pathophysiology of heart rate control. This study uses basic physiologic principles to construct a unique model capable of describing the full time course of sympathetic and parasympathetic activity during HRR. The model is tested in a new study of 22 diverse subjects undergoing both maximal and submaximal treadmill exercise. Based on this analysis, prolongation of HRR involves changes within the sinus node, changes in sympathetic function, in parasympathetic function, and in the central mechanisms regulating autonomic balance. The methods may provide unique insight into alterations in autonomic control in health and disease.     

Interaction between Heart Rate and Heart Rate Variability

Heart rate variability (HRV) is significantly associated with average heart rate (HR), therefore, HRV actually provides information on two quantities, that is, on HR and its variability. It is difficult to conclude which of these two plays a principal role in the HRV clinical value, or in other words, what is the HR contribution to the clinical significance of HRV. Moreover, the association between HRV and HR is both a physiological phenomenon and a mathematical one. The physiological HRV dependence on HR is determined by the autonomic nervous system activity, but the mathematical one is caused by the nonlinear relationship between RR interval and HR. By employing modification methods of the HRV and HR relationship, it is possible to investigate the HR contribution to the HRV clinical value. Recent studies have shown that the removal of the HR impact on HRV makes HRV more predictive for noncardiac death, however, the enhancement of this impact causes HRV to be a better predictor of cardiovascular mortality. Thus, HR seems to constitute a cardiovascular factor of the HRV predictive ability. HR also influences the reproducibility of HRV, therefore, HR changes should be considered when one compares HRV measurements in a given patient. This review summarizes methodological aspects of investigations of the HRV and HR interaction as well as latest observations concerning its clinical utility. The issues discussed in this article should also refer to any other heart rate dynamics analysis which indices are significantly associated with HR.     

Endurance Exercise Training Improves Heart Rate Recovery in Patients with COPD

Background: Abnormalities of autonomic function have been reported in patients with chronic obstructive pulmonary disease. The effect of the exercise training in heart rate recovery (HRR) has not been established in patients with COPD. Objective: To assess the effects of 8-weeks’ endurance training program on parasympathetic nervous system response measured as heart rate recovery in a sample of moderate-to-severe COPD patients. Methods: We recruited a consecutive sample of patients with COPD candidates to participate in a pulmonary rehabilitation program from respiratory outpatient clinics of a tertiary hospital. HRR was calculated, before and after training, as the difference in heart rate between end-exercise and one minute thereafter (HRR₁) in a constant-work rate protocol. Results: A total of 73 COPD patients were included: mean (SD) age 66 (8) years, median (P₂₅-P₇₅) post-bronchodilator FEV₁ 39 (29–53)%. The prevalence of slow HRR₁ (≤12 beats) at baseline was 63%, and was associated with spirometric severity (mean FEV₁ 35% in slow HRR₁ vs 53 in normal HRR₁, p < 0.001). After 8-weeks training, HRR₁ improved from mean (SD) 10 (7) to 12 (7) beats (p = 0.0127). Multivariate linear regression models showed that the only variable related to post-training HRR₁ was pre-training HRR₁ (p < 0.001). Conclusions: These results suggest that training enhances HRR in patients with moderate-to-severe COPD. HRR is an easy tool to evaluate ANS such that it may be a useful clinical marker of parasympathetic nervous system response in patients with COPD.     

Heart Rate Variability Assessment of the Effect of Physical Training on Autonomic Cardiac Control

Background: The effect of exercise interventions on autonomic nervous system (ANS) control of the heart by heart rate variability (HRV) is often investigated in just one position. It was hypothesized that results of exercise‐induced changes on ANS are dependent on body position and that it is possible to distinguish between exercise induced changes in vagal and sympathetic influence by taking measurements in different body positions. Methods: One hundred eighty‐three (male = 100, female = 83) healthy volunteers, between 18 and 22 years, participated in a prospective twelve week medium to high intensity exercise intervention study with a self‐control design. The influence of the exercise intervention was investigated on supine, rising, and standing as well as on the orthostatic response. Time domain, frequency domain and nonlinear (Poincaré) HRV analysis were performed. Results: The exercise intervention lead to a significant increase (P < 0.05) in vagal influence during supine, rising, and standing. Sympathetic control in the supine position was decreased and increased during rising and standing. In the initial orthostatic response to rising from the supine position, the exercise intervention lead to increased (P < 0.05) vagal withdrawal as well as increased sympathetic control. The orthostatic response measured as the difference between standing and supine indicated only an exercise induced increase in sympathetic control. Conclusions: Exercise‐induced changes in sympathetic and parasympathetic ANS control differ, depending on posture and period of measurement. Exercise induced changes in parasympathetic and sympathetic outflow, respectively, can be extracted from measurements from supine, through the orthostatic response, to standing, thereby detecting changes in ANS that are otherwise obscured.     

Heart Rate and Heart Rate Variability in Normal Young Adults

Heart Rate and Heart Rate Variability. Introduction: The relationships between heart rate (HR) and HR variability (HRV) are not simple. Because both depend on the autonomic nervous system (ANS), they are not independent variables. Technically, the quantification of HRV is influenced by the duration of the cardiac cycles. The complexity of these relationships does not justify ignoring HK when studying HRV, as frequently occurs. Methods and Results: Using spectral and nonspectral methods, the HR and various normalized and non-normalized indices of HRV were studied in 24-hour recordings of a homogeneous cohort of seventeen 20-year-old healthy males. The HR-HRV relationships were appraised by analyzing the same data in two different ways. The 24 mean hourly values provide consistent information on the circadian behavior of the indices, while the average 24-hour individual data show a wide spectrum of normality. Combined approaches allow assessment of the direct impact of RR interval on HRV evaluation. The correlations between HR and normalized indices of HRV arc weaker in 24-hour individual data than in pooled hourly data of the same individuals. These correlations are close to 1 in the latter case, which does not mean that measuring HRV is simply another method of evaluating HR, but that normal physiology supposes a harmonious behavior of the various indices. When considered individually without normalization, the specific indices of vagal modulation (high-frequency band of the spectrum, short-term HR oscillations of the nonspectral analysis) consistently increase at night and diminish during the day. However, the low-frequency power, which supposedly reflects sympathetic influences, also increases at night, whereas more logically the longer HR oscillations would predominate during the day. Moreover, the selective analysis of HR oscillations during HR acceleration or decrease indicates that their behavior differs accordingly. Conclusion: We recommend that closer attention be paid to the complex relationships between HR and HRV. The strong correlations found in healthy subjects may reflect either the physiological harmony of ANS functions or simple redundancy. Their tendency to deteriorate in diseased hearts suggests that redundancy is not the cause and that abnormalities of ANS functions are not demonstrated by HRV analysis alone.     

Physiological Background Underlying Short-Term Heart Rate Variability

A large number of papers has been published on heart rate variability (HRV) based on the assumption that the specific components of HRV provide specific information about cardiac parasympathetic or sympathetic efferent nerve activity. However, neural control of the cardiorespiratory system is very complex, and the physiological phenomenon underlying HRV in different conditions are far from being fully understood. This review summarizes, in the light of current literature, a series of studies focused on the mechanisms by which fluctuations in neural outflows are transferred into HRV. In the interpretation of HRV analyses, it should be taken into account that: (1) HRV seems to be strongly influenced by the parasympathetic nervous system at all the frequency components; (2) due to sympathovagal interactions, sympathetic outflow is able to reduce the variations generated by vagal modulation also in the high frequency band; and (3) the variations in heart rate reflect fluctuations in the neural activity rather than the mean level of sympathetic or parasympathetic neural activity. Thus, we should be cautious in interpreting a specific component of HRV as a specific marker of sympathetic or parasympathetic cardiac control. Furthermore, due to the complexity of the cardiorespiratory control system, the analysis of short-term HRV should be performed in well-controlled conditions, in which the behavior of the autonomic nervous system is well documented.     

心率变异性的研究及应用进展

心率变异性是评价自主神经功能最常用的无创方法,随着计算技术的发展越来越多测量心率变异性的新方法进入到实践之中。自主神经系统在不同系统疾病中的影响和作用,正由于这种无创评估方法的实用化而被逐渐认识。现仅就心率变异性方法学和应用领域方面的进展进行简要概述。     

The Correlation Dimension of Heart Rate Variability Reflects Cardiac Autonomic Activity

Background: Linear methods of time series analysis such as summary statistics and frequency-domain parameters have been used to measure heart rate variability (HRV). More recently, nonlinear methods including the correlation dimension (CDim) have been used to evaluate HRV. The aim of this study was to examine the effect of autonomic perturbations on the CDim. Methods: The CDim was calculated from 2000 data points (RR intervals) collected over a relatively short period of time (20–40 min) in 12 healthy subjects aged between 20 and 40 years (mean 30 ± 2 years) during: (a) supine rest; (b) head up tilt (sympathetic activation, parasympathetic nervous system activity withdrawal); (c) intravenous infusion of atropine (parasympathetic nervous system activity withdrawal); and (d) following overnight administration of low dose transdermal scopolamine (parasympathetic nervous system augmentation. Results: The CDim was determined at rest (7.8 ± 0.3) and found to be significantly reduced during tilt (5.9 ± 0.4, P < 0.01) and atropine administration (4.2 ± 0.4, P < 0.01) and possibly increased by scopolamine (8.3 ± 0.5, NS). Conclusions: The changes following these interventions suggest that CDim can accurately measure cardiac autonomic nervous system activity.     

Relationship between Autonomic Nervous System Activity and Lower Urinary Tract Symptoms: An Analysis of Heart Rate Variability in Men with Lower Urinary Tract Symptoms

Objectives: Lower urinary tract symptoms (LUTS) are common, but their etiology and mechanism remain unclear. We believe that changes in autonomic nervous system (ANS) activity may be contributory because the lower urinary tract is regulated through the sympathetic and parasympathetic nervous systems. Heart rate variability (HRV) is a tool by which autonomic nervous function can be measured; therefore, we measured and compared parameters of heart rate variability between men with LUTS and asymptomatic subjects. Methods: We studied 35 men with LUTS (mean age 50.5 ± 14.9 years) and 110 asymptomatic male volunteers who had requested a health check up (mean age 49.5 ± 5.19 years) from July 2006 to June 2008. HRV is known to be a useful tool for evaluating ANS activity, and we measured and compared HRV in the resting state. Results: The standard deviation of the N‐N interval (SDNN) and total power (TP) for patients with LUTS revealed no significant differences from those in the control group. On frequency domain analysis, there was evidence of decreased high frequency (HF) in patients with LUTS (P < 0.05), but there were no significant differences in other parameters, such as heart rate, square root of the mean squared differences of successive N‐N intervals (RMSSD), very low frequency (VLF), low frequency (LF), or LF/HF ratio. Conclusion: Patients with LUTS exhibited different HRV parameters compared with asymptomatic controls. Their decreased HF indicated that they may have had an imbalance in the autonomic nervous system.     

Recovery of Heart Rate Variability and Ventricular Repolarization Indices Following Exercise

Background: There is a heightened risk of sudden cardiac death related to exercise and the postexercise recovery period, but the precise mechanism is unknown. We have demonstrated that sympathoexcitation persists for ≥45 minutes after exercise in normals and subjects with coronary artery disease (CAD). The purpose of this study is to determine whether this persistent sympathoexcitation is associated with persistent heart rate variability (HRV) and ventricular repolarization changes in the postexercise recovery period. Methods and Results: Twenty control subjects (age 50.7 ± 1.4 years), 68 subjects (age 58.2 ± 1.5 years) with CAD and preserved left ventricular ejection fraction (LVEF), and 18 subjects (age 57.6 ± 2.4 years) with CAD and depressed LVEF underwent a 16‐minute submaximal bicycle exercise protocol with continuous ECG monitoring. QT and RR intervals were measured in recovery to calculate the time dependent corrected QT intervals (QTc), the QT–RR relationship, and HRV. QTc was dependent on the choice of rate correction formula. There were no differences in QT–RR slopes among the three groups in early recovery. HRV recovered quickly in controls, more slowly in those with CAD‐preserved LVEF, and to a lesser extent in those with CAD‐depressed LVEF. Conclusion: Despite persistent sympathoexcitation for the 45‐minute recovery period, ventricular repolarization changes do not persist for that long and HRV changes differ by group. Additional understanding of the dynamic changes in cardiac parameters after exercise is needed to explore the mechanism of increased sudden cardiac death risk at this time.     

Influence of the Maximum Heart Rate Attained during Exercise Testing on Subsequent Heart Rate Recovery

Background: Abnormal heart rate recovery (HRR) following exercise testing has been shown to be a predictor for adverse cardiovascular events. The actual maximum heart rate (MHR) attained during the exercise test does not however have a distinct significance in traditional HRR assessment. The objective of this study was to investigate the role of MHR in HRR. Methods: This prospective study consisted of 164 patients (62% male, mean age 53.7 ± 11.7 years) who were referred for a symptom‐limited standard Bruce Protocol treadmill exercise test, based on clinical indications. The patients were seated immediately at test completion and the heart rate (HR) recorded at one and two minutes postexercise. A normal HRR was defined as a HR drop of 18 beats per minute or more at the end of the first minute of recovery. The HRR profile of patients who reached ≥85% of their maximum predicted heart rate (MPHR) during peak exercise were then compared to HRR profile of those who could not. Results: One hundred twelve patients (Group A) achieved a MHR ≥ 85% of MPHR during peak exercise whereas 52 patients (Group B) did not. Chi‐square analysis showed a higher incidence of normal HRR in Group A compared to Group B (p = 0.029). Analysis of variance with repeated measures showed that group A had a greater HRR at the first minute F_1,162= 6.98, p = <0.01) but not the second minute (F_1,162=1.83, p = .18) postexercise. Conclusion: There is a relation between the peak heart rate attained during exercise and the subsequent HRR. A low peak heart rate increases the likelihood of a less than normal HRR. Assessment of the entire heart‐rate response seems warranted for more thorough risk‐stratification. Ann Noninvasive Electrocardiol 2010;15(1):43–48     

Heart Rate Variability as a Predictor of Autonomic Dysfunction in Patients Awaiting Liver Transplantation

Chronic liver disease, both alcoholic and nonalcoholic, has been shown to be associated with autonomic neuropathy, as well as other hemodynamic and circulatory disturbances. In a longitudinal study, the presence of autonomic neuropathy and the severity of liver disease were independent risk factors for mortality. The aim of this study was to determine whether the severity of liver disease correlated with measures of heart rate variability. We studied 21 patients being evaluated for liver transplantation to determine if severity of disease correlated with heart rate variability and compared them to seven healthy controls. Heart rate variability was determined for a series of 500 consecutive R-R intervals during quiet breathing. Standard deviation, pNN50, a marker of parasympathetic function, and approximate entropy (ApEn), a recently described measure of regularity, were calculated. Four standard tests of autonomic function were also performed. pNN50 was significantly reduced in all liver disease patients compared to controls (P < 0.05). Both standard deviation and ApEn were significantly reduced in Childs class C patients suggesting a generalized dysfunction in cardiovascular homeostasis. ApEn was significantly lower in the nonsurvivors during follow-up than the survivors (P < 0.05). In conclusion, increasing severity of liver failure is associated with a reduction in total heart rate variability and regularity. Measurement of heart rate variability offers a simple, noninvasive means of assessing the cardiovascular and autonomic effects of liver disease, particularly in those awaiting liver transplantation.     

Automatic Filtering of R‐R Intervals for Heart Rate Variability Analysis

Background: In R‐R analysis for heart rate variability, rhythm modificatipns other than those related to autonomic nervous system activity must be avoided. We describe an algorithm that performs a correction based on the comparison of each interval with a normal standard. Methods: Starting with a given R‐R list, a parameter R between 0 and 1 is chosen, the normal R‐R range is defined as: (1‐R, 1+R]. The first interval then is divided by the mode of the entire R‐R list. If the resulting value lies within the normal range, then it could be accepted as normal. Subsequent intervals are divided by the last accepted one and the mean value of the accepted intervals. If either of these results is inside.the normal range, then the considered interval is accepted. The abnormal intervals are evaluated to find out if they are in the expected range, which is [T‐1, T+11, where T is a new parameter smaller than R. Not expected intervals are handled differently to be corrected and in a few cases are eliminated. Results: Two types of tests were carried out. One uses real recordings containing artifacts. The other test was carried out by means of a computer program that generates corrupted data. R value was set in 0.2 and T in 0.05. Comparisons between our filter and other automatic algorithms were done. Conclusions: Our filter is fast and strong enough to perform an accurate automatic correction.     

Effects of Menstrual Cycle on Cardiac Autonomic Innervation As Assessed By Heart Rate Variability

Objective: The aim of the study was to investigate the effects of menstrual cycle on cardiac autonomic function parameters in young healthy women by means of heart rate variability (HRV). Methods: Forty‐three nonobese regularly cycling women (age 29 ± 6, range 20–38) were enrolled. Recordings for HRV analysis were obtained during the two phases of the menstrual cycle when the estrogen and progesterone levels peaked (follicular phase 11 ± 1 days and luteal phase 21 ± 1 days from the start of bleeding). Power spectral analysis of HRV was performed to calculate the low frequency peak (LF, 0.04–0.15 Hz), high frequency peak (HF, 0.15–0.40 Hz), LF in normalized unit (LF nU), HF in normalized unit (HF nU), and LF/HF ratio during the two phases of menstrual cycle. Results: The heart rates, LF and HF, were similar in both phases (P > 0.05). A significant increase was noted in the LF NU in the luteal phase compared to follicular phase of the menstrual cycle (P = 0.014), whereas a tendency for increased HF NU was observed in the follicular phase (P = 0.053). Furthermore, LF/HF ratio was significantly higher in the luteal phase compared to follicular phase (2.1 ± 1.5 vs 1.6 ± 0.9, P = 0.002), suggesting increased sympathetic activity in the luteal phase. Conclusion: We concluded that regulation of autonomic tone is modified during menstrual cycle. The alteration in the balance of ovarian hormones might be responsible for these changes in the cardiac autonomic innervation. A.N.E. 2002;7(1):60–63     

Heart Rate Variability to Assess Changes in Cardiac Vagal Modulation Prior to the Onset of Paroxysmal Atrial Fibrillation in Patients With and Without Structural Heart Disease

Background and Objectives: In patients with paroxysmal lone AF, clinical data indicate a predominance of vagal modulation preceding attacks of the arryhthmia. Systematic data derived from time-domain analysis of HRV evaluating changes in autonomic modulation prior to AF onset are sparse, both in patients without and with evidence for structural heart disease. This study evaluated changes in autonomic modulation prior to the onset of AF in patients with and without structural heart disease. Methods and Results: In 26 consecutive patients with at least one episode of paroxysmal AF preceded by a period of sinus rhythm of at least 8 hours duration documented on Holter monitoring, the time-domain parameters SDNN, rMSSD, and pNN5O were analyzed at different time points between 8 hours and 10 minutes prior to the onset of AF. Fourteen patients had AF associated with structural heart disease, whereas 12 patients had paroxysmal lone AF. Analysis of HRV changes before onset of AF revealed significant differences between the two patient groups: In patients without heart disease, pNN5O and rMSSD increased from 10 ± 3 to 15 ± 4% (P=0.003) and from 38 ± 7 to 53 ± 9 ms (P=0.035). No significant change in HRV was observed in patients with structural heart disease (pNN5O 5 ± 3 vs. 6 ± 2 % and rMSSD 25 ± 4 vs. 28 ± 6 ms). Conclusions: In patients with lone AF, there is a significant shift of autonomic modulation towards a vagal predominance prior to the onset of paroxysmal AF as compared to patients with structural heart disease. Analysis of HRV prior to attacks of AF is useful in determining these triggering mechanisms.     

Circadian Variation of Heart Rate Variability in Postinfarction Patients With and Without Life-Threatening Ventricular Tachyarrhythmias

Circadian Variation of HRV. Introduction: Determination of heart rate variability (HRV) is widely used for noninvasive assessment of cardiac autonomic tone. A decreased HRV is associated with an increased mortality in patients surviving an acute myocardial infarction. There are, however, only sparse data about the circadian variation of different components of HRV that may be linked to the well-known circadian fluctuations in the occurrence of sudden death. In addition, the potential prognostic impact of circadian variations of HRV has not been examined. Methods and Results: The present study compared the circadian variation of HRV from 14 postinfarction patients who had survived at least one episode of out-of-hospital cardiac arrest (cardiac arrest group) with that of 14 age- and sex-matched patients without a history of malignant arrhythmias after their index infarct (control group). Several time- and frequency-domain measures of HRV were assessed from 24-hour Holter recordings. Circadian variations of high- (HF), low- (LF), and total-frequency (TF) components were determined by calculating for each parameter the hourly difference from the day's mean. The average of these differences was calculated for every hour as well as for predefined day and night periods. There was no significant difference between the two groups with regard to HRV indices that predominantly reflect vagal tone, such as SDNN (78 ± 25 vs 96 ± 24 msec), pNN50 (2.7%± 4.6% vs 4.9%± 4.2%), or HF (6.3 ± 3.0 vs 7.8 ± 3.2 msec; cardiac arrest vs control group). There was also no significant difference in the circadian variation of LF or TF between the two groups during daytime and nighttime. However, a significant difference in circadian variation of HF was found during daytime (0.02 ± 0.5 vs -0.6 ± 0.5 msec; P = 0.006) and nighttime (0.19 ± 0.64 vs 1.5 ± 0.75 msec; P = 0.0002). In cardiac arrest survivors, there was no difference in the mean deviation of HF between the day-and the nighttime periods. Conclusions: These results show an almost complete abolition in circadian variation of parasympathetic tone in postinfarction patients surviving an episode of out-of-hospital cardiac arrest, whereas circadian variation of sympathetic tone is comparable to that of postinfarction patients without arrhythmic episodes. These findings indicate that determination of diurnal variation of HRV may add to the prognostic value of HRV with respect to identifying patients at high risk of sudden death.     

Heart Rate Variability: Measurement and Clinical Utility

Electrocardiographic RR intervals fluctuate cyclically, modulated by ventilation, baroreflexes, and other genetic and environmental factors that are mediated through the autonomic nervous system. Short term electrocardiographic recordings (5 to 15 minutes), made under controlled conditions, e.g., lying supine or standing or tilted upright can elucidate physiologic, pharmacologic, or pathologic changes in autonomic nervous system function. Long‐term, usually 24‐hour recordings, can be used to assess autonomic nervous responses during normal daily activities in health, disease, and in response to therapeutic interventions, e.g., exercise or drugs. RR interval variability is useful for assessing risk of cardiovascular death or arrhythmic events, especially when combined with other tests, e.g., left ventricular ejection fraction or ventricular arrhythmias.