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.     

自主神经系统在阵发性心房颤动发作前后心率变异性变化中的作用

目的分析阵发性心房颤动发作前后心率变异性的变化,探讨自主神经系统在阵发性心房颤动中的作用。方法采用动态心电图记录28例阵发性心房颤动患者24h心电信息,分析其发作前后5min及白天（6：00～22：00）和夜间（22：00～6：00）的心率变异性指标。结果心房颤动发作前5min平均正常R—R间期的标准差（SDNN）、高频成份（HF）较终止后5min显著升高（P〈0．01）,低频／高频比值（LF／HF）显著降低（P〈0．01）,LF无变化：LF、HF白天均高于夜间（P〈0．01）,白天与夜间SDNN、LF／HF无差异;阵发性心房颤动发作前5minSDNN与阵发性心房颤动发作频率呈正相关（r=0．545。P〈0．01）,LF／HF与阵发性心房颤动发作频率和持续时间呈负相关（r=-0532、-0．563,均P〈0．01）。结论阵发性心房颤动发作前心率变异性升高,迷走神经支配占优势,使心房颤动得以诱发和持续。     

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.     

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.     

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。     

Reliability of Ultra‐Short ECG Indices for Heart Rate Variability

Background: Heart rate variability (HRV) is an accepted and reliable means for assessing autonomic nervous system dysfunction. A 5‐minute measurement of HRV is considered methodologically adequate. Several studies have attempted to use shorter recordings of 1–2 minutes or 10 seconds. The aim of this study was to determine the reliability of HRV parameters calculated from ultra‐short electrocardiogram recordings. Methods: Seventy healthy volunteers were recruited for the study. HRV was evaluated for 5 minutes according to accepted procedures. Thereafter, HRV parameters were recalculated from randomly selected 1‐minute and 10‐second intervals. The standard and ultra‐short measurements were correlated using intraclass correlation coefficients. Results: Good correlations between the 5‐minute electrocardiograms (ECGs) and both the 1‐minute and 10‐second ECGs were noted for average RR interval, and root mean square of successive differences in RR intervals (RMSSD). No correlation was noted for standard deviation of the RR interval (SDNN) and several other HRV parameters. Conclusions: RMSSD, but not SDNN, seem a reliable parameter for assessing HRV from ultra‐short (1 minute or 10 seconds) resting electrocardiographic recordings. Power spectral analysis and evaluation of other HRV parameters require longer recording periods. Further research is required to evaluate the importance of ultra‐short RMSSD for cardiovascular risk stratification. Ann Noninvasive Electrocardiol 2011;16(2):117–122     

孤立性心房颤动患者心率变异与 P 波离散度的相关性研究

目的:探讨孤立性心房颤动患者心率变异性(HRV)与P波离散度(Pd)的关系.方法:在动态心电图上分析30例孤立性心房颤动患者(房颤组)的心率变异性指标,包括孤立性心房颤动发作前、后5分钟的时域、频域指标:RR间期的标准差、低频段功率、高频段功率以及低频段功率/高频段功率和24小时时域指标:全部RR间期的标准差、每5分钟平均RR间期的标准差、相邻RR间期差值的均方根和相邻RR间期差值大于50ms的心搏数占总心搏数的百分比,并计算P波最大宽度与P波离散度,再与30例正常对照组进行比较.结果:①对孤立性心房颤动患者发作前、后5分钟的时域、频域指标进行比较,可见孤立性心房颤动患者发作前5分钟RR间期的标准差、高频段功率较发作后5分钟增高(P＜0.05),而低频段功率/高频段功率降低(P＜0.05),差异有统计学意义,低频段功率无明显变化(P＞0.05).②24小时时域分析显示房颤组的全部RR间期的标准差、每5分钟平均RR间期的标准差、相邻RR间期差值的均方根和相邻RR间期差值大于50ms的心搏数占总心搏数的百分比高于正常对照组(P＜0.01),差异有统计学意义.③房颤组的P波最大宽度、P波离散度高于正常对照组(P＜0.01),差异有统计学意义.④房颤组的全部RR间期标准差、每5分钟平均RR间期的标准差、相邻RR间期差值的均方根和相邻RR间期差值大于50ms的心搏数占总心搏数的百分比与P波最大宽度、P波离散度呈正相关(P＜0.01),差异有统计学意义.结论:孤立性心房颤动患者迷走神经张力增高,特别在发作前迷走神经张力有明显增强,并且其P波最大宽度、P波离散度显著增高,两者之间有一定的相关性,可能是孤立性心房颤动的发病机制之一.     

Differences in Heart Rate Dynamics Before the Spontaneous Onset of Long and Short Episodes of Paroxysmal Atrial Fibrillation

Background: Altered heart rate (HR) dynamics precede the spontaneous onset of atrial fibrillation (AF), but the factors related to the perpetuation and duration of paroxysmal AF episodes are not well established. This study was designed to test the hypothesis that HR dynamics preceding the onset of (AF) may influence the duration of AF. Methods: Traditional time and frequency domain HR variability indices, along with a short‐term fractal scaling exponent (α₁) and approximate entropy (ApEn), were analyzed in 20‐minute intervals before 92 episodes of spontaneous paroxysmal AF in 22 patients without structural heart disease. AF episodes were divided into two groups according to the duration of the arrhythmia episodes. Results: The high‐frequency (HF) spectral component in normalized units (nu) of heart rate variability was higher and low‐frequency (LF) component lower before long (> 200 s, n = 41) compared to short (< 200 s, n = 51) AF episodes (HF nu; 40.1 ± 14.8 vs 31.5 ± 16.4, P < 0.0001 and LF nu; 59.9 ± 14.8 vs 68.5 ± 16.4, P < 0.0001). Short‐term scaling exponent values also were lower before long compared to short AF episodes (e.g., α₁; 1.12 ± 0.21 vs 1.24 ± 0.23, P < 0.0001). Women had a larger number of long AF episodes than men, but the duration of AF was not related to any other clinical or demographic features or antiarrhythmic medication. Conclusion: Increased HF oscillations and decreased short‐term correlation properties of R‐R intervals, reflecting altered sympathovagal balance before the onset of AF, predispose to perpetuation of spontaneous arrhythmia episodes in patients with vulnerability to paroxysmal AF and without structural heart disease. A.N.E. 2001;6(2):134–142     

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.     

Heart Rate Variability After Coronary Artery Bypass Graft Surgery: A Prospective 3‐Year Follow‐Up Study

Background: Autonomic heart rate control is impaired after CABG. The aim of this study was to establish the temporal pattern of change in the decrease of HRV observed after CABG. Methods and Results: Twelve patients with coronary artery disease were assessed with 24‐hour Holter recordings 2 days before CABG and 1 week, 3 months, 6 months, 1 year, and 3 years after CABG. All the time‐domain and frequency‐domain HRV parameters decreased precipitately after CABG and were mostly recovered 3 months after CABG except mean NN, rMSSD, and pNN50. The ratio of LF to HF showed a slight decrease after surgery, recovered to preoperative values after 3 months, surpassed, and continued to increase 6 months after surgery. At 3 years of follow‐up the recovery was complete. The rate of change of time‐domain and frequency‐domain parameters were calculated and their correlation with aortic cross‐clamping time, number of vessels bypassed, the amount of cardioplegic used were sought and no statistically significant correlation was found. Conclusion: The recovery of HRV regardless to the preoperative state of the patients and their postoperative course implies that the early drop of HRV after CABG was related to the acute effects of surgery. Late complete recovery of HRV may be due to resolution of ischemia or use of angiotensin‐converting enzyme inhibitor. A.N.E. 2002;7(3):247–250     

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.     

Is Baseline Autonomic Tone Associated with New Onset Atrial Fibrillation?: Insights from the Framingham Heart Study

Background: Recent reports have indicated that autonomic tone fluctuations measured by heart rate variability (HRV) precede episodes of paroxysmal atrial fibrillation (AF). Little is known about the impact of baseline autonomic tone and the development of new onset AF in a population‐based cohort. The purpose of this study was to assess the role of HRV as a predictor of new onset AF. Method: Ambulatory ECG recordings obtained from the Framingham Heart Study subjects attending a routine examination were processed for HRV. The HRV variables analyzed included standard deviation of normal R‐R intervals (SDNN), low frequency power (LF), high frequency power (HF), and LF/HF ratio. There were 1434 women and 1142 men (54 ± 14.1 years) eligible for the study. Results: In 12 years of follow‐up, 65 women and 67 men had new onset AF. The study had 80% power to detect a hazard ratio (HR) of 1.3 per standard deviation (SD) decrement in HRV. A one SD decrement in log LF/HF was associated with increased risk of developing AF (HR = 1.23; 95% confidence intervals (CI) = 1.06–1.44) in age‐ and sex‐adjusted models; the association was no longer significant (HR = 1.15; 95% CI = 0.98–1.35) after adjusting for potential confounders. Conclusion: Autonomic dysregulation at baseline, as reflected by an altered HRV is associated with risk of AF; however, this association does not persist after adjusting for potential confounders. Much of the apparent association between HRV and AF is mediated by traditional risk factors.     

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     

自主神经介导性心房颤动研究进展

自主神经系统在心房颤动的触发和维持中扮演了重要的角色,因此心房颤动发病机制中的神经源性理论引起越来越多的关注,深入研究心房颤动与自主神经的关系对认识心房颤动的机制及指导治疗很有意义。针对神经节的靶向治疗可提高心房颤动射频消融的成功率并较少复发,正成为新的治疗方法。神经节消融对正常心肌组织创伤较小,但定位神经节的最好方法仍有争议。