Prognostic Value of Heart Rate Variability in Time Domain Analysis in Congestive Heart Failure

AIMS: Analysis of heart rate variability is a noninvasive tool that allows to study autonomic control of the heart. Several studies have shown disturbed heart rate variability in patients with chronic heart failure (CHF). We sought to assess the prognostic value of time domain measures of heart rate variability in CHF. METHODS AND RESULTS: We prospectively enrolled 190 patients with CHF in sinus rhythm, mean age 61+/-12 years, 109 (57.4 %) in NYHA class II and 81 (42.6 %) in class III or IV, mean cardiothoracic ratio 57.6+/-6.4 % and mean left ventricular ejection fraction 28.2+/-8.8 %, 85 (45 %) with ischemic and 105 (55 %) with idiopathic dilated cardiomyopathy. Time domain measures of heart rate variability were obtained from 24 h Holter ECG recordings. During follow-up (22+/-18 months), 55 patients died. In multivariate analysis, independent predictors for all-cause mortality were: ischemic heart disease, cardiothoracic ratio > or =60 % and standard deviation of all normal RR intervals <67 ms (RR=2.5, 95 % CI 1.5--4.2). CONCLUSIONS: Depressed heart rate variability has independent prognostic value in patients with CHF.     

Effects of Postectopic Heart Rate Turbulence on Measures of Heart Rate Variability in Patients after an Acute Myocardial Infarction

Background: Heart rate (HR) turbulence lasting up to 15 beats after ventricular premature beats (VPBs) may have profound effects on HR variability measures. Aim of this study was to examine the effects of HR turbulence on HR variability measures. Methods: We developed an algorithm, which deletes 15 consecutive RR intervals after VPBs and examined the effects of the HR turbulence removal on the HR variability measures in patients after an acute myocardial infarction (AMI). Two hundred and sixty seven patients with left ventricular ejection fraction (LVEF) ≤ 0.40 and occurrence of VPBs were included in the study. Differences (%) between original HR data and HR turbulence edited data were compared. Results: HR turbulence editing had variable effects on different HR variability indexes. Ultra low (ULF) and very low frequency (VLF) spectral components were mostly affected by the HR turbulence removal. Both ULF and VLF decreased significantly both at baseline Holter recordings (ULF: P = 0.006, VLF: P = 0.031) and at 6 weeks from AMI (ULF: P < 0.001, VLF: P = 0.001). The number of VPBs had a marked influence on results, e.g., when the number of VPBs exceeded the highest decile (≈50 VPBs/hour), the ULF and VLF spectral component were >30% lower after removal of turbulence. In addition, the prediction of arrhythmic events by ULF component improved after turbulence removal (AUC: 0.69 ‐>0.74). Conclusions: HR turbulence affects HR variability measures, especially the ULF and VFL spectral components. Editing of the HR turbulence should be considered when HR variability is measured from Holter recordings. Ann Noninvasive Electrocardiol 2011;16(2):123–130     

Fractal and Complexity Measures of Heart Rate Variability

Heart rate variability has been analyzed conventionally with time and frequency domain methods, which measure the overall magnitude of RR interval fluctuations around its mean value or the magnitude of fluctuations in some predetermined frequencies. Analysis of heart rate dynamics by methods based on chaos theory and nonlinear system theory has gained recent interest. This interest is based on observations suggesting that the mechanisms involved in cardiovascular regulation likely interact with each other in a nonlinear way. Furthermore, recent observational studies suggest that some indexes describing nonlinear heart rate dynamics, such as fractal scaling exponents, may provide more powerful prognostic information than the traditional heart rate variability indexes. In particular, the short-term fractal scaling exponent measured by the detrended fluctuation analysis method has predicted fatal cardiovascular events in various populations. Approximate entropy, a nonlinear index of heart rate dynamics, that describes the complexity of RR interval behavior, has provided information on the vulnerability to atrial fibrillation. Many other nonlinear indexes, e.g., Lyapunov exponent and correlation dimensions, also give information on the characteristics of heart rate dynamics, but their clinical utility is not well established. Although concepts of chaos theory, fractal mathematics, and complexity measures of heart rate behavior in relation to cardiovascular physiology or various cardiovascular events are still far away from clinical medicine, they are a fruitful area for future research to expand our knowledge concerning the behavior of cardiovascular oscillations in normal healthy conditions as well as in disease states.     

Nonlinear Analysis of Heart Rate Variability: Fractal and Complexity Measures of Heart Rate Behavior

Many new methods of analyzing heart rate (HR) variability have been developed to describe the features in HR behavior that cannot be detected by traditional time‐ and frequency‐domain methods. Some of the new methods, such as analysis of fractal correlation properties and complexity of HR dynamics, have provided clinically useful information in various patient populations. Importantly, some fractal analysis methods are better risk predictors of mortality than traditional HR variability measures, and analysis of complexity of HR dynamics has been shown to predict the spontaneous onset of atrial fibrillation. New analysis methods based on nonlinear dynamics are a promising tool for better understanding of normal and abnormal HR behavior. More work will be needed to establish the clinical applicability of traditional and new analysis methods of HR variability.     

Heart Rate Variability in Obstructive Sleep Apnea: A Prospective Study and Frequency Domain Analysis

Background: Cyclic variation of the heart rate is observed during apneic spells in obstructive sleep apnea (OSA). We hypothesized that autonomic changes would affect frequency‐domain measures of heart rate variability (HRV). Methods: We studied 20 patients (15 men, 5 women, mean age 47.2 ± 12.2 years) with suspected OSA undergoing overnight polysomnography, and five patients (4 men, 1 woman, mean age 49.2 ± 8.6 years) with recently diagnosed sleep apnea undergoing polysomnography while wearing continuous positive airway pressure (CPAP). Holter monitors were applied during sleep studies and data were analyzed in 5‐minute blocks over the course of the night. Using spectral analysis, low frequency (LF) and high frequency (HF) powers were calculated for each interval. Overall mean and standard deviation (SD) for LF power, HF power, and the LF:HF ratio were recorded for each patient. Comparisons were made between patients with severe OSA (apnea hypopnea index (AHI) > 30, n = 8 ), moderate OSA (AHI 1–30, n = 5 ), without OSA (AHI < 10, n = 7 ), and patients wearing CPAP (n = 5 ). Results: Assessment of overnight LF or HF power revealed no significant difference between the four groups. The LF:HF ratio, which represents sympathovagal balance, was higher among those with moderate disease compared to normals and those with severe OSA (both P = 0.037 ). The standard deviation of the LF:HF ratio was higher among those with moderate disease compared to normals (P = 0.0064) and those with severe OSA (P = 0.0006) . OSA patients receiving CPAP behaved like patients with moderate OSA, with increased SD of the LF:HF ratio. Conclusions: The observed changes in the LF:HF ratio and its SD suggest an increased sympathetic tone and discordance in sympathovagal activity in moderate OSA, which is blunted in severe OSA. CPAP may restore autonomic defects, characteristic of severe OSA, to moderate levels.     

心率变异时域分析对糖尿病患者自主神经功能的评价

采用２４小时动态心电图对８２例糖尿病患者进行心率变异（ＨＲＶ）和心率（ＨＲ）检测。８２例分为五组：Ａ组（无血管合并症）３０例、Ｂ组（合并大血管病变）１１例、Ｃ组（合并小血管病变）１２例、Ｄ组（同时合并大、小血管病变）１９例和Ｅ组（心肾功能不全）１０例，并设正常对照组。结果：糖尿病各组ＨＲＶ显著降低，Ａ组仅２４ｈ内全部正常ＲＲ间期标准差（ＳＤＮＮ，１０４．２０±２９．１９ｍｓ）和２４ｈ内５ｍｉｎ节段平均正常ＲＲ间期的标准差（ＳＤＡＮＮｉｎｄｅｘ，９３．７３±２７．５８ｍｓ）降低（对照组分别为１２７．５２±３８．５７ｍｓ和１１６．１９±３５．７０ｍｓ），Ｐ均＜０．０１；ＨＲ异常主要表现为夜间平均ＨＲ增快，白昼平均ＨＲ仅Ｅ组（８６．７６±１１．３６ｂｐｍ）高于对照组（７６．３８±９．４０ｂｐｍ），Ｐ＜０．０１。表明糖尿病患者存在自主神经受累，白昼心率增快可能是病情严重的征兆。     

Short-Term Adjuvant Atorvastatin Improves Frequency Domain Indices of Heart Rate Variability in Stable Systolic Heart Failure

The autonomic nervous system marks beneficial drug responses in systolic heart failure management. The impact of statin therapy in this broad disease class is unclear and patient studies are extremely limited.Methods: We studied a group of 23 patients with stable systolic ventricular impairment and randomised them single (patient) blind to high dose Atorvastatin 40 mg daily or placebo in addition to standard therapies over a 12-week treatment interval. Impact on the autonomic nervous system was assessed by anonymised short-term (20 min) standardised supine heart rate variability analyses.Results: Two subjects withdrew one due to decompensation and one due to gastric intolerance. The remaining subjects completed both monitoring events without changes in standard medicines. Frequency domain but not time domain HRV indices improved with active statin therapy suggesting beneficial effects in attenuating sympathetic tone.Conclusions: In this small study we saw short-term high potency statin treatment had a beneficial impact on frequency domain HRV measures suggestive of an impact on sympatho-activation. We found no effect on time domain HRV indices. This may suggest a lesser or no effect on parasympathetic tone.     

非持续性室性心动过速患者心率变异的研究

对非持续性室性心动过速（ＮＳＶＴ）患者进行心率变异（ＨＲＶ）分析。记录２４ｈ动态心电图分析６个ＨＲＶ时域指标，并对照分析ＮＳＶＴ发作前、后的窦性Ｒ－Ｒ间期标准差（ＳＤ）。结果：ＮＳＶＴ患者（ｎ＝３５）之ＨＲＶ时域指标中２４ｈ平均Ｒ－Ｒ间期（ＭＲＲＩ）、ＳＤ、５ｍｉｎ节段Ｒ－Ｒ间期均值的标准差（ＳＤＡ）、５ｍｉｎ节段Ｒ－Ｒ间期标准差的均值（ＭＳＤ）较正常对照组（ｎ＝１０５）明显下降（其中ＳＤ为９０．８８±３７．７７ｍｓｖｓ１４３．１８±３１．００ｍｓ，Ｐ＜０．０１），与病例对照组（ｎ＝４４）比较无显著性差异（Ｐ＞０．０５）。ＮＳＶＴ发作前、后５ｍｉｎ和１ｈ的ＳＤ（５ｍｉｎＲ－Ｒ节段）无显著性差异。结论：ＮＳＶＴ患者ＨＲＶ较正常对照组下降，但ＨＲＶ下降与ＮＳＶＴ无明显关系。     

Influence of Atropine on Fractal and Complexity Measures of Heart Rate Variability

Background: Measurement of short‐term fractal‐like correlation properties of heart rate dynamics has been shown to be a useful prognostic indicator of adverse events in cardiac patients. Complexity measurements of heart rate variability (HRV) have already provided important information in many cardiac conditions. However, data on the physiological background of these newer nonlinear measures of HRV are limited. Methods: Nine healthy subjects (aged from 22 to 35 years, 6 males, 3 females) had an electro‐cardiographic (ECG) recording during controlled breathing in supine position. HRV was analyzed for 5 min periods before and after intravenous injection of 0.6 mg of atropine using conventional HRV measures and newer nonlinear HRV measures including the short‐term scaling exponent (a,) and approximate entropy (ApEn). Results: The short‐term scaling exponent a₁ increased significantly after atropine injection (1.01 ± 0.23 vs 1.43 ± 0.19, P = 0.001). There was no significant difference between ApEn values before and after atropine injection (0.87 ± 0.17 vs 0.70 ± 0.31, respectively, P = 0.27). At baseline before atropine administration, a₁ had a significant negative correlation with SDNN, RMSSD, and HF (r = ‐0.70, ‐0.76, ‐0.67, respectively, P <0.05 for all), and a significant positive correlation with heart rate (r = 0.76, P < 0.05). After atropine injection, a, did not have significant correlation with any of the HRV parameters or heart rate. There were no significant correlations between ApEn and any of the HRV measures or heart rate either before or after atropine administration. Conclusions: Vagal tone has an important influence on the values of the short‐term scaling exponent a,. However, vagal modulation is not a major determinant of the values of ApEn. A.N.E. 2002;7(4):326–331     

Heart Rate Variability in Heart Failure

The autonomic nervous system has an important role in the development and progression of the heart failure syndrome. Increased sympathetic, reduced parasympathetic, and impaired baroreceptor activity are well-documented features of heart failure. The analysis of heart rate variability can give insight into these autonomic abnormalities. A number of techniques now exist for assessing heart rate variability, and in general they reflect the known autonomic abnormalities. Power spectral analysis of RR variability has been claimed to reflect sympathovagal balance, but the reduced or absent low-frequency component in heart failure is paradoxical. It is likely that the absent low-frequency component in heart failure reflects impaired baroreceptor function. Although these various techniques of heart rate variability may be useful, reliability and reproducibility are problematic in this area. Better, more refined techniques for the noninvasive assessment of autonomic and baroreceptor function are still needed.     

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.     

早搏对急性心肌梗死患者心率变异的重复性及稳定性的影响

通过对４７例急性心肌梗死（ＡＭＩ）患者进行连续４８ｈ心电记录,并重复长程心电图ＨＲＶ时域及频域分析,以了解房性早搏（ＡＰＢ）、室性早搏（ＶＰＢ）对ＨＲＶ重复性和稳定性的影响。以ＡＰＢ与ＶＰＢ之和达５次／ｈ为界划分Ⅰ组（早搏＜５次／ｈ,ｎ＝３２,２４ｈ内ＡＰＢ３１．５±３３．９次、ＶＰＢ１１．３±２０．２次）及Ⅱ组（早搏≥５次／ｈ,ｎ＝１５,２４ｈ内ＡＰＢ１０３．８±１５１．６次、ＶＰＢ１５３．１±２５７．２次）,按常规方法进行ＨＲＶ各指标比较分析。结果总体上两组ＨＲＶ时域及频域指标均具有重复性。Ⅰ组反映高频心率波动的指标,如单位时间内连续的窦性ＲＲ间期差的均方根、单位时间内相邻窦性ＲＲ间期差值大于５０ｍｓ所占的百分比（ＰＮＮ５０）、高频带（ＨＦ）（ｒ分别为０．７６,０．７３,０．８９）,以及低频带与高频带比值（ｒ＝０．９３）重复检测相关性明显较Ⅱ组高（ｒ分别为０．３４,０．５９,０．６４,０．３０）。Ⅰ组除单位时间内连续５ｍｉｎ窦性ＲＲ间期标准差的均数、ＰＮＮ５０外各时域指标相对误差（ＲＥ）均值（０．１０～０．１８）及频域指标ＲＥ均值（０．２０～０．３４）均低于Ⅱ组。Ｗｉｌｃｏｘｏｎ检验两组各项指标重复检测?     

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.     

The Relationship Between Heart Rate Recovery and Heart Rate Variability in Coronary Artery Disease

Background: Reduced heart rate recovery (HRR) in coronary artery disease (CAD) is predictive of increased cardiovascular mortality and is related to reduced parasympathetic tonus. Objective: To investigate HRR and heart rate variability (HRV) measured at steady state condition and the relationship between these two parameters in CAD. Materials and Methods: In our study, we enrolled 33 (28 males, mean age 52.4 ± 9.6 years) patients with CAD who did not have heart failure, atrial fibrillation, pacemaker, and any disease state that could affect the autonomic functions and 38 age‐matched healthy subjects (21 males, mean age 48.3 ± 7.8 years). All the patients underwent submaximal treadmill exercise testing (Bruce protocol). HRR was calculated by subtracting the heart rate values at the 1st, 2nd, and 3rd minutes of the recovery phase from the peak heart rate (HRR₁, HRR₂, HRR₃). Before exercise testing, short‐term steady state HRV analyses of all subjects were obtained with the time‐ and frequency‐domain methods and were correlated to HRR. For frequency‐domain analysis, low‐frequency HRV (LF, 0.004–0.15 Hz), high‐frequency HRV (HF, 0.15–0.5 Hz), and LF/HF ratio were measured for 5 minutes in the morning. For time‐domain analysis, standard deviation of the normal‐to‐normal NN intervals (SDNN), square root of the mean squared differences of successive N‐N intervals (RMSSD), and proportion derived by dividing the number of interval differences of successive N‐N intervals greater than 50 ms by the total number of N‐N intervals (pNN50) were obtained. Only HRR₃ was used for the correlation analysis. Results: In CAD groups, the HF, an indicator of parasympathetic activation, was significantly reduced, whereas the LF and LF/HF values, which are indicators of sympathetic activity, were increased (P = 0.0001 for each parameter). The time‐domain parameters SDNN, RMSSD, and pNN50 were significantly reduced in the patient group (P = 0.0001, P = 0.009, and P = 0.0001, respectively). Similar to the HRV parameters, the HRR₁, HRR₂, and HRR₃ values were significantly reduced in the patient group (P = 0.0001 for each parameter). We observed a significant negative correlation between HRR₃ and LF (r =?0.67, P = 0.0001) and between HRR₃ and LF/HF (r =?0.62, P < 0.0001), while there was a significant positive correlation between HRR₃ and HF, SDNN, RMSSD, and pNN50 (r = 0.69, P = 0.0001; r = 0.41, P = 0.0001; r = 0.31, P = 0.008; and r = 0.44, P = 0.0001). Conclusions: HRR and HRV are significantly reduced in CAD. The reduction in HRR is parallel to the changes in HRV parameters. HRR, which can be measured easily in the recovery phase of exercise testing, can be used to detect the depression of parasympathetic tonus and to evaluate the basal autonomic balance in this patient group.     

Effects of Hormone Replacement Therapy on Heart Rate Variability in Postmenopausal Women

Background: Hormone replacement therapy (HRT) is associated with reduced cardiovascular risk, but the underlying mechanism(s) are not fully understood. This study investigated the effects of a 6‐month course of HRT on cardiac autonomic function parameters assessed by heart rate variability (HRV) in postmenopausal women. Methods: Forty‐six healthy postmenopausal women (age 48 ± 5, range 40–60) with normal baseline electrocardiogram and negative exercise testing were enrolled. HRT, which was either 0.625 mg/day conjugated equine estrogen (CEE) plus 2.5 mg/day medroxyprogesterone acetate or 0.625 mg/day CEE alone were administered depending on hysterectomy status. Power spectral analysis of HRV was performed to calculate the low frequency component in absolute (LF) and normalized units (LF nu), high frequency component in absolute (HF), and normalized units (HF nu), and the LF/HF ratio. The standard deviation of RR intervals (SDNN) was calculated from the time series of RR intervals. Results: A 6‐month course of HRT did not significantly alter resting heart rate (P > 0.05). The LF/HF ratio and LF nu significantly decreased after HRT (P = 0.022 and P = 0.032), whereas a significant increase was noted in the HF component of HRV (P = 0.043), indicating an improvement in cardiac autonomic function. The SDNN value, which was 28.8 ± 11.8 ms before HRT significantly increased to 35.4 ± 16.7 ms after 6 months (P = 0.011). Conclusion: Our results indicate that a 6‐month course of HRT may significantly improve cardiac autonomic function parameters, a finding that could at least partly explain the potential cardiopro‐tective effect(s) of HRT. A.N.E. 2001;6(4):280–284     

Time-Frequency Analysis of Heart Rate Variability

Background: The heart rate variability (HRV) signal is mainly analyzed in frequency-domain and the signal's spectrum is estimated using either Fast Fourier Transformation (FFT) or the autoregressive (AR) model. These two methods assume that the HRV signal is stationary and additionally the AR method is based on the assumption that the model is linear and the signal is monocomponent in nature. Qualities of spectral estimates are thus closely related to the validity of the above assumptions. Evidence has accumulated indicating that HRV is a multicomponent, nonlinear and nonstationary signal. Then the spectral representations currently used would yield global, approximate, and smoothed view of HRV dynamics. Methods: We applied time-frequency (TF) analysis methods, smoothed pseudo-Wigner distribution (SPWD), and spectrogram and complemented for validation by FT spectrum to the HRV signal of fifteen apparently healthy volunteers (mean age 27.2 ± 5.6 years). Short-term electrocardiograms (ECG) were recorded during supine and upright tilting positions (baseline recording). After baseline recording we induced parasympathetic, sympathetic, and total autonomic blockade correspondingly to six, nine, and four subjects. In addition, in four patients ECGs were recorded during controlled respiration. Results: SPWD and spectrogram revealed strips in frequency, or TF components, corresponding to FT components. High frequency (HF) components appeared stationary (in wide sense), with slight mean frequency shifts during spontaneous respiration, concurrent with respiratory motions. Low frequency (LF) and very low frequency (VLF) components had a nonstationary character displaying activity burst in time and interrelation in frequency. Upright tilting caused a uniform reduction in intensity and bandwidth of the HF component and enhancement of intensity and burst activity of the LF component. There was a pronounced decline of HF and LF components’intensity and decrease of HF component's bandwidth after parasympathetic blockade and total autonomic blockade, while the VLF component did not change. Sympathetic blockade was accompanied by augmentation of the LF and HF components’intensity associated with an increase in the HF component's bandwidth and the spreading of it in the region between the LF and HF. The LF component exhibited less burst activity during tilting under sympathetic blockade, as compared to baseline recordings during tilt. The VLF component's behavior did not change after sympathetic, parasympathetic, and total autonomic blockades. Conclusion: Application of TF distributions to the HRV signal offers a new representation of HRV dynamics. SPWD unveiled features in the HRV signal not available in separate time- and frequency-domains. TF components display idiosyncratic behavior patterns in time and were effected by physiological and pharmacological interventions. A.N.E. 1996;1(4):411–418     

Different Action of Beta‐blockers on Daytime and Nighttime Heart Rate Variability

Background: Beta‐blockers in patients surviving acute myocardial infarction (AMI) and in those with dilated cardiomyopathy have proven to be of beneficial effect, particularly for the sudden cardiac death rate. They are also used to control various forms of arrhythmias because of the strong correlation between cardiac arrhythmias and adrenergic reaction. Heart rate variability (HRV) variables provide valuable information related to the autonornic nervous system function. The present prospective study was undertaken to investigate the effects of beta‐blockers on 24‐hour HRV. Methods: We studied 60 patients, aged 39 to 76 years (mean 56 ± 15). Forty of the patients had survived a myocardial infarction 12 to 24 months previously (group I). Twenty patients did not have apparent cardiac heart disease (group II). Twenty‐four‐hour monitoring was performed at baseline and after 8 to 10 days of atenolol (100 mg/day, n = 35) or metoprolol (100 to 150 mg/day, n = 25) (BB). Measures of HRV in the time and frequency domains were calculated and printed for the the entire 24 hours and from 09:00 to 21:00 (daytime) and 23:00 to 6:00 (nighttime). The 24‐hour analysis of HRV shows an improvement over control values in indices of parasympathetic tone, but the results were statistically significant only for high frequency power (HF) in groups I (P < 0.01) and II (P < 0.05). A significant decrease of the coefficient of variance was noted in group II (P < 0.05). The analysis during the day and the night revealed a predominant action of beta‐blockers during the night with a high frequency increase in both groups from 64.5 ± 45 to 161 ± 111 ms² in group I (P < 0.001) and from 99 ± 89 to 268 ± 348 ms2 in group II (P < 0.02). In group II, the daily high frequency power did not vary after beta‐blockers. The decrease of the coefficient of variance in group II disappeared in the daily and nightly analysis Conclusions: Beta‐blockers enhance the HRV indexes reflecting the parasympathetic activity especially during the night in patients with and without ischemic heart disease. Although an indirect effect of beta‐blockers on respiration cannot be excluded, this effect could explain one of the beneficial effects of beta‐blockers on general survival in patients with and without myocardial infarction.     

Apnea‐Related Heart Rate Variability and Its Clinical Utility in Congestive Heart Failure Outpatients

Background: Cheyne‐Stokes breathing (CSB) is an abnormal cyclical pattern of respiratory fluctuations observed during sleep in congestive heart failure (CHF) of poor prognosis. We examined the clinical usefulness of CSB screening using the heart rate variability (HRV) data from the ambulatory electrocardiogram. Methods: We monitored ambulatory electrocardiograms and respiration simultaneously in 86 heart disease patients of both sexes, aged 57 ± 1 years. HRV was analyzed by the maximum entropy method during the sleeping period (11 PM—S AM). The 43 CHF patients underwent a 1‐year follow‐up study. Results: In the power spectra of the HRV, peaks were observed within the CSB band (0.005 to 0.03 Hz). Statistically significant differences in HRV were observed between CSB patients and CSB‐free patients in very low frequency (VLF) (P = 0.04), VLF/total frequency (TF) (P = 0.02), CSB (P = 0.01), CSB/TF (P = 0.003), and CSB/VLF (P < 0.0001). Cardiac events occurred in 23% of patients, including cardiac death in two, and rehospitalization for aggravated CHF in eight. In a multivariate Cox regression analysis in which age, sex, ejection fraction, NYHA functional class, beta blocker use, and basic heart disease were included, absence of ACE inhibitor use (RR 5.5, 95% Cl 1.0–31) and CSB/VLF ≧ 80% (RR 4.2, 95% Cl 1.1–17) remained significant predictors of cardiac events. Conclusions: HRV can act as an indicator of the presence of CSB in CHF patients, and could therefore be used, under outpatient conditions, to identify a CHF patients with a poor prognosis. A.N.E. 2002;7(2):127–132     

Reproducibility and Comparability of Short- and Long-Term Heart Rate Variability Measures in Healthy Young Men

Background: In heart rate variability (HRV) studies, the duration of the electrocardiographic recordings may vary between 20 seconds and 24 hours. Little is known about the reproducibility or comparability of HRV measures calculated over observation periods of different duration. Methods: To assess the reproducibility and comparability of HRV measures computed from short recordings under standardized conditions and from ambulatory 24-hour recordings, 15 healthy young males were studied on three occasions. Results: The reliability coefficient (between subject variation divided by summed between and within subject variation) for 20-second intervals was low for all measures. For 5-minute intervals in supine position, but not standing position, the reliability coefficients of the standard deviation, root of mean squared successive differences, proportion of successive differences > 50 ms, and the proportion low frequency power were about 70%. The reliability coefficients of the 24-hour HRV measures were > 80% for all measures. Short- and long-term measures of heart rate and HRV appeared to be correlated, implying that these measures result in similar ranking of subjects. Conclusions: The results indicate that HRV measures based on 24-hour monitoring during regular activities are better reproducible than short-term measures under standardized conditions. A single 5-minute recording may suffice to characterize a group of persons in a population study, but, because of considerable day-to-day variation, it is not adequate for individual characterization.     

高血压病患者胰岛素抵抗与心率变异的关系

目的探讨高血压病患者心率变异指标变化和胰岛素抵抗之间的关系。方法３７例高血压病患者和１６例正常人行糖耐量试验和测定胰岛素释放曲线的同时测定心率变异各项指标。结果高血压病人中６２％存在高胰岛血素症和胰岛素抵抗，其２４小时ＲＲ间期均值的标准差指数（ＳＤＮＮＩ）明显高于正常人，而２４小量内ＲＲ间期的标准差（ＳＤＮＮ）５分钟ＲＲ间期均值标准差指数（ＳＤＡＮＮＩ）和相邻心搏ＲＲ间期差值的均方根（ｒＭＳＳＤ）及相邻心搏ＲＲ间期大于５０ｍｓ的百分比（ＰＮＮ５０）明显低于正常人。结论高血压病患者的心率变异和胰岛素抵抗所引起的交感神经增强和副交感神经的活性减弱有关