RR Interval Length Research Articles

СARDIAC ARRHYTHMIAS ANALYSIS BASED ON THE PHASE PORTRAIT OF ECG SIGNAL

The article illustrates the development of virtual system in LabVIEW software environment for processing and analysis of electrocardiographic signals. In the system, the issues of processing ECG signal with classical methods and in phase space have been considered, the comparison of these methods have been carried out, characteristic changes of the shapes of ECG phase portraits corresponding to the change of diagnostic signs haveb been analyzed, and additional diagnostic signs determined on the the base of phase portrait in order to increase the reliability of ECG diagnosis have been interpreted. As a result of the analysis of the sequence of RR intervals using the developed program, a histogram, a scatterogram, a fast Fourier transform, an autoregressive spectrum, a short-term Fourier transform and the corresponding informative parameters characterizing heart rate variability were obtained: the average length and standard deviation of RR intervals, the mean value and standard deviation heart rate, spectral parameters, etc. The results obtained during the processing and analysis of ECG files taken from the MIT BIH databases using the HRV analysis program and the determination of informative parameters implemented in the LabVIEW environment confirm the adequacy of the developed program. Keywords: ECG signal, phase space, phase portrait, RR intervals, LabVIEW software, heart rate, QRS complexes.

Respiratory Sinus Arrhythmia in Children-Predictable or Random?

Background: Respiratory sinus arrhythmia (RSA) is associated with better health in children.Aim: The study was conducted to analyze the trajectory of RSA in 10-year-olds.Methods: A follow-up study on 120 healthy children (62 boys) aged 10.7 ± 0.5 years consisted of a standard 12-lead electrocardiogram, measurements of height, weight and blood pressure. The protocol was repeated after 3 years. Assessment of RSA based on semi-automatic measurements of RR intervals included: the difference between the longest and shortest RR interval duration (pvRSA), the root mean square of differences between successive RR intervals (RMSSD), the standard deviation of the RR interval length (SDNN) and their equivalents corrected for heart rate (RMSSDc and SDNNc).Results: A the first visit 61.7% of children presented with RSA; 51.7% 3 years later. 23.3% of them had RSA only on the first examination; 13.3% only on the second one. The pvRSA, RMSSD, and SDNN measured in 2019 did not differ significantly from their 2016 equivalents (p > 0.05). The decline in RSA defined by RMSSD was noted in 52.5% of children and in 54.2% when defined by SDNN. The corrected values decreased in 68.3 and 64.2% of the participants for RMSSDc and SDNNc, respectively. The students with RSA at both visits had lower heart rate (p < 0.001) and systolic blood pressure (p = 0.010) compared to those with rhythmic electrocardiograms.Conclusions: RSA in children is changeable, though its measurable indices should be adjusted to heart rate.

Pulmonary blood volume estimation in mice by magnetic particle imaging and magnetic resonance imaging

This methodical work describes the measurement and calculation of pulmonary blood volume in mice based on two imaging techniques namely by using magnetic particle imaging (MPI) and cardiac magnetic resonance imaging (MRI). Besides its feasibility aspects that may influence quantitative analysis are studied. Eight FVB mice underwent cardiac MRI to determine stroke volumes and anatomic MRI as morphological reference for functional MPI data. Arrival time analyses of boli of 1 µl of 1 M superparamagnetic tracer were performed by MPI. Pulmonary transit time of the bolus was determined by measurements in the right and left ventricles. Pulmonary blood volume was calculated out of stroke volume, pulmonary transit time and RR-interval length including a maximal error analysis. Cardiac stroke volume was 31.7 µl ± 2.3 µl with an ejection fraction of 71% ± 6%. A sharp contrast bolus profile was observed by MPI allowing subdividing the first pass into three distinct phases: tracer arrival in the right ventricle, pulmonary vasculature, and left ventricle. The bolus full width at half maximum was 578 ms ± 144 ms in the right ventricle and 1042 ms ± 150 ms in the left ventricle. Analysis of pulmonary transit time revealed 745 ms ± 81 ms. Mean RR-interval length was 133 ms ± 12 ms. Pulmonary blood volume resulted in 177 µl ± 27 µl with a mean maximal error limit of 27 µl. Non-invasive assessment of the pulmonary blood volume in mice was feasible. This technique can be of specific value for evaluation of pulmonary hemodynamics in mouse models of cardiac dysfunction or pulmonary disease. Pulmonary blood volume can complement cardiac functional parameters as a further hemodynamic parameter.

Study on the mechanism of atrioventricular reentrant tachycardia with RR interval alternation

Objective To explore the mechanism of the alternation of RR interval length in atrioventricular reentrant tachycardia (AVRT). Methods From August 2009 to August 2016, 317 patients with AVRT were treated by radiofrequency catheter ablation in cardiology department of TEDA International Cardiovascular Hospital were analyzed retrospectively.During AVRT, 5 mg of verapamil was given slowly intravenously for 10 min.After administration, the changes of RR interval, AH interval, HV interval and VA interval were observed and the time of changes was also observed. Results After administration of verapamil, there were 8 patients with RR interval alternation and QRS wave alternation.When RR interval alternation occurred, the difference of AH interval between adjacent heart beats was gradually extended, without AH jump, and the HV interval and VA interval were constant.This phenomenon occurred 6-17 minutes after administration, and the average cycle of tachycardia was 16-42 ms longer than before administration.In 3 patients, RR interval alternation occurred.When the phenomenon disappeared, the difference of AH interval between adjacent heart beats was gradually shortened, there was no AH jump, and the interval between HV and VA was constant until AH interval was equal, the disappearance time was 19-57 min after administration; AVRT was terminated in 5 patients after administration. Conclusion It can be concluded that the mechanism is due to the frequency dependent decreasing conduction of AH interval in tachycardia, which can not be induced by program stimulation. Key words: Verapamil; Atrioventricular reciprocating tachycardia; Electrophysiology; Catheter ablation; RR interval alternative

CHF Detection with LSTM Neural Network.

Heart rate variability has been proven to be an effective prediction of risk of heart failure. The tradition method required manual feature extraction, thus may lead to potential error. In order to improve the robustness, a deep learning method based on long short-term memory has been presented in this paper. Three RR interval length (N) for detection are used. Without pre-processing, this method obtain 82.47%, 85.13% and 84.91% accuracy for N=50 (average time length is 37. 8s), N=100 (average time length is 73. 9s), N=500 (average time length is 369. 5s), respectively. This method makes it possible to detect CHF through intelligent hardware or mobile application.

Benchmarking Heart Rate Variability to Overcome Sex-Related Bias.

Since the seminal studies by Sayers (Ergonomics 16:17-32, 1973) and Akselrod et al. (Science 213:220-222, 1981) a few decades ago, it became clear that beat-by-beat oscillations in RRinterval length (i.e.heart-rate variability [HRV]) contain information on underlying neural-control mechanisms based on the instantaneous balance between parasympathetic and sympathetic innervation. Over the years, the number of studies addressing HRV has increased markedly and now outnumbers 23,000. Despite such a large interest, there is still a continuing debate about interpretation of indices produced by computer analysis of HRV.The main part of studies relies on spectral techniques to extract parameters that are linked to hidden information. The general idea is that these proxies of autonomic regulation can be useful to clinical applications in various conditions in which autonomic dysregulation may play a role. There are, however, serious shortcomings related to algorithms, interpretation, and the hidden value of individual indices. In particular, it appears that specific training is necessary to interpret the hidden informational value of HRV. This technical complexity represents a severe barrier to large-scale clinical applications. Moreover, important differences in HRV separate the sexes, and age plays an additional confounding role.We present here a preliminary application of a novel unitary index of RR variability (Autonomic Nervous System Index of cardiac regulation) capable of providing information on the performanceof autonomic regulation using a percentile rank position as projected on a large benchmark population. A summary of the underlying sympatho-vagal model is also presented.

Multiscale Entropy Analysis of the Differential RR Interval Time Series Signal and Its Application in Detecting Congestive Heart Failure

Cardiovascular systems essentially have multiscale control mechanisms. Multiscale entropy (MSE) analysis permits the dynamic characterization of the cardiovascular time series for both short-term and long-term processes, and thus can be more illuminating. The traditional MSE analysis for heart rate variability (HRV) is performed on the original RR interval time series (named as MSE_RR). In this study, we proposed an MSE analysis for the differential RR interval time series signal, named as MSE_dRR. The motivation of using the differential RR interval time series signal is that this signal has a direct link with the inherent non-linear property of electrical rhythm of the heart. The effectiveness of the MSE_RR and MSE_dRR were tested and compared on the long-term MIT-Boston’s Beth Israel Hospital (MIT-BIH) 54 normal sinus rhythm (NSR) and 29 congestive heart failure (CHF) RR interval recordings, aiming to explore which one is better for distinguishing the CHF patients from the NSR subjects. Four RR interval length for analysis were used ( N = 500 , N = 1000 , N = 2000 and N = 5000 ). The results showed that MSE_RR did not report significant differences between the NSR and CHF groups at several scales for each RR segment length type (Scales 7, 8 and 10 for N = 500 , Scales 3 and 10 for N = 1000 , Scales 2 and 3 for both N = 2000 and N = 5000 ). However, the new MSE_dRR gave significant separation for the two groups for all RR segment length types except N = 500 at Scales 9 and 10. The area under curve (AUC) values from the receiver operating characteristic (ROC) curve were used to further quantify the performances. The mean AUC of the new MSE_dRR from Scales 1–10 are 79.5%, 83.1%, 83.5% and 83.1% for N = 500 , N = 1000 , N = 2000 and N = 5000 , respectively, whereas the mean AUC of MSE_RR are only 68.6%, 69.8%, 69.6% and 67.1%, respectively. The five-fold cross validation support vector machine (SVM) classifier reports the classification Accuracy ( A c c ) of MSE_RR as 73.5%, 75.9% and 74.6% for N = 1000 , N = 2000 and N = 5000 , respectively, while for the new MSE_dRR analysis accuracy was 85.5%, 85.6% and 85.6%. Different biosignal editing methods (direct deletion and interpolation) did not change the analytical results. In summary, this study demonstrated that compared with MSE_RR, MSE_dRR reports better statistical stability and better discrimination ability for the NSR and CHF groups.

Real-time Algorithm for Detection of Atrial Fibrillation

One of the objectives of population screening programs is to control and prevent heart disease. This particular problem is solved within the framework of the project CardioQVARK. Among the most important functions of the ECG monitoring equipment is identification of atrial fibrillation (AF), which refers to the most common and dangerous arrhythmias. Today, there are many algorithms to identify this disorder, but the accuracy of the best algorithms does not exceed 94.5%. In this paper, we propose an algorithm based on graphical representation of regularities in the order and length of RR-intervals (distances between adjacent R-waves of the ECG) and consider method for its implementation.

A 6-weeks Treatment Program Improves HRV in Eating Disorder Patients

Background: Eating disorders such as anorexia nervosa present with a significant cardiovascular associated risk of sudden cardiac death. Bradycardia is a serious complication of eating disorders. Methods: Eating Disorder (ED) patients were admitted to a 6-week treatment program and assessed for of heart rate variability (HRV) at entrance to the program and at discharge from hospital. Linear heart rate variability measures were determined using Kubios software from Lead 3 ECG recordings following a 5-minute rest period. Nonparametric statistics were applied and significance set at p < 0.05. Results: No significant differences in HRV parameters were noted for the control group following the 6-week treatment program. For the ED group, mean RR interval length decreased significantly following treatment compared (median ± IQR; -64 ± 76; p = 0.002). Sympathovagal function was abnormal in the ED group on admission but improved following treatment, showing a decrease in RMSSD (median ± IQR; -9 ± 18; p = 0.048) and SD1 (median ± IQR; -6 ± 13; p = 0.048). Sample entropy, a, measure of heart rate complexity did not change significantly. Conclusion: At admission to hospital the ED group was more parasympathetic during rest compared to controls, but they became more sympathetic after the intervention and approached the HRV measures of the controls.

Heart rate variability (HRV) and muscular system activity (EMG) in cases of crash threat during simulated driving of a passenger car

The aim of the study was to verify whether simultaneous responses from the muscular and circulatory system occur in the driver's body under simulated conditions of a crash threat. The study was carried out in a passenger car driving simulator. The crash was included in the driving test scenario developed in an urban setting. In the group of 22 young male subjects, two physiological signals - ECG and EMG were continuously recorded. The length of the RR interval in the ECG signal was assessed. A HRV analysis was performed in the time and frequency domains for 1-minute record segments at rest (seated position), during undisturbed driving as well as during and several minutes after the crash. For the left and right side muscles: m. trapezius (TR) and m. flexor digitorum superficialis (FDS), the EMG signal amplitude was determined. The percentage of maximal voluntary contraction (MVC) was compared during driving and during the crash. As for the ECG signal, it was found that in most of the drivers changes occurred in the parameter values reflecting HRV in the time domain. Significant changes were noted in the mean length of RR intervals (mRR). As for the EMG signal, the changes in the amplitude concerned the signal recorded from the FDS muscle. The changes in ECG and EMG were simultaneous in half of the cases. Such parameters as mRR (ECG signal) and FDS-L amplitude (EMG signal) were the responses to accident risk. Under simulated conditions, responses from the circulatory and musculoskeletal systems are not always simultaneous. The results indicate that a more complete driver's response to a crash in road traffic is obtained based on parallel recording of two physiological signals (ECG and EMG).

Improved 3D late gadolinium enhancement MRI for patients with arrhythmia or heart rate variability

Background Arrhythmia and heart rate variability have adverse effects on the image quality of Late Gadolinium Enhancement (LGE). Due to the incomplete recovery after an inversion pulse, changes in the RR-interval length induce a k-space weighting, which results in ghosting artifacts in the images. While the impact of heart-rate variability is less pronounced in 2D LGE due to short scan times (10-15 sec), it often results in non-diagnostic image quality in 3D LGE (scan time 6-10 min). Our aim is to develop a novel LGE imaging sequence for patients with heart rate variability or arrhythmia.

The relation of ventromedial prefrontal cortex activity and heart rate fluctuations at rest

Recent studies applying functional magnetic resonance imaging have focused on the description of cerebral substrates of changes in cardiac function during diverse autonomic maneuvers or stressful cognitive tasks. These studies might be limited by the indistinguishable neuronal activity due to cognitive processes, which are known to influence autonomic function, and the 'baseline' activity in the central autonomic network. We therefore investigated 26 healthy volunteers in the magnetic resonance scanner to simultaneously obtain functional brain images and RR intervals (intervals between ventricular depolarizations) of the high-resolution electrocardiogram. The mean RR interval length within each functional scan was computed, which was finally convolved with the canonical hemodynamic response function to obtain a regressor for the functional time series. The resulting individual contrast image indicated a positive covariation of the blood oxygen level-dependent signal and RR interval length in the ventromedial prefrontal cortex (vmPFC). Furthermore, a reduced mean cross-approximate entropy value was shown for the interaction between the vmPFC and individual RR intervals. This suggests reduced asynchrony between the heart rate and vmPFC activity in contrast to other brain areas. Our findings confirm data obtained in animals describing the vmPFC as an important forebrain structure of the central autonomic network and an influence of the vmPFC in the cortical generation of efferent vagal activity. This finding needs to be investigated in diseases with known suppression of efferent vagal modulation.

Heart rate variability in weightlifters

On the basis of the literature and original data, heart rate variability (HRV) in weightlifters has been studied. The results showed that the distribution mode (a parameter of mathematical analysis that is equal to the most frequent length of RR intervals) indicates the intensity of physical exercise. Specific changes in the autonomic balance in athletes as dependent on their degree of training and sports qualification are important characteristics of adaptations to physical loads. For example, the degree of training of weightlifters is reflected by the level of the respiratory component as an index of the activity of the parasympathetic nervous system. Adaptation to physical exercise leads to an increase in the power of the spectrum of neurohumoral modulation and to changes in the ratio between the levels of the total spectral power of HRV.

The relationships between self-assessed habitual physical activity and non-invasive measures of cardiac autonomic modulation in young healthy volunteers

Heart rate variability estimates cardiac autonomic modulation, but the relationship between habitual physical activity and heart rate variability remains unclear. The aims of this study were to compare RR-interval and heart rate variability indices in individuals of different habitual physical activity levels, and examine the relationship between habitual physical activity and heart rate variability. Ninety-two healthy volunteers (47 men, 45 women; mean age 23.1 years, s = 2.1) were divided into tertiles according to the Baecke Questionnaire score. Standard heart rate variability indices were derived from 5-min resting RR-interval recordings with paced respiration (0.25 Hz). Between-group differences and the relationship between habitual physical activity and heart rate variability were assessed. More active participants (tertiles 2–3) had longer RR-intervals than those in tertile 1 (P < 0.05). Participants in tertile 2 had higher root mean squared differences of successive normal RR-intervals than those in tertile 1 and a higher standard deviation of normal RR-intervals than those in tertiles 1 and 3. There was a positive linear relationship between habitual activity and RR-interval. Differing RR-interval lengths were found in subgroups of young individuals according to level of habitual physical activity. More active individuals showed resting bradycardia without evidence of enhanced cardiac parasympathetic modulation. The mechanism linking habitual physical activity and RR-interval length appears to be independent of physiological mechanisms that can be measured by heart rate variability.

Association between RR interval and high-frequency heart rate variability acquired during short-term, resting recordings with free and paced breathing

High-frequency (HF) oscillations in RR interval from 0.15–0.40 Hz are widely accepted as a measure of cardiac vagal outflow but the HF/RR relationship appears complex, particularly with longer RR intervals. The aim of this study was to evaluate the HF/RR interval relationship during free and paced breathing. HF power and mean RR interval length were recorded in 150 men and 120 women (mean age 34.5 ± 11.4) during 5 min of supine rest with either free or paced (12 cycles min−1) breathing. Linear and quadratic models were used to assess the relationship between RR interval and the natural logarithm of HF power (lnHF). The RR interval length at which there was no further increase in lnHF was determined as the deflection point. ANCOVA was used to determine differences in the linear regression slopes for lnHF/RR with paced or free breathing. With free breathing (n = 131), the adjusted R2 was similar between linear (15.3%) and quadratic (17.5%) fits and saturation of lnHF occurred within the recorded RR interval range (1326 ms). With paced breathing (n = 139), adjusted R2 values were again similar between linear (22.4%) and quadratic (23.2%) fits. The deflection point was outside the range of recorded RR intervals at 1458 ms. ANCOVA showed a significant difference in the slope of the lnHF/RR regression lines between free and paced breathing. The lnHF/RR relationship is weaker when derived from between-subject recordings than from repeated within-subject samples. lnHF/RR showed evidence of saturation at ∼45 bpm with free breathing. With paced breathing, a deflection in lnHF was found outside the recorded RR interval range (∼41 bpm). Paced breathing creates a stronger lnHF/RR relationship. The slope of the lnHF/RR regression line with paced breathing is significantly different from that observed with free breathing. It appears that lnHF is a valid index of vagal outflow, except in subjects with very low heart rates. Paced breathing data collection protocols appear preferable.

Connection between RR-interval length and the pulsatile microcirculatory flow

The present study used laser Doppler flowmetry (LDF) to investigate the connection between skin microcirculatory flow and the length of the RR interval (LRR). Local heating was performed on healthy volunteers to further elucidate its effect on LDF index. ECG and LDF signals were measured in 102 trials on seven volunteers. Each experiment involved a 5 min control and a 5 min heating-effect sequence. Each laser Doppler flux pulse was categorized into four groups according to its LRR compared with the 5 min average LRR. Synchronized averaging analysis was applied to the four groups of pulses to obtain their averaged waveforms, from which four flux parameters were calculated. The ac component of the flux increased significantly with increasing LRR, and the differences therein between the groups with LRR more than 4% smaller and more than 4% larger than the average LRR increased from 15.8% during the control period to 23.9% during the heating period. Understanding of the different flux responses between the control and local-heating experiments may aid the development of a new index, which helps to avoid LDF's main drawback of providing only qualitative measurement.

Correlation properties of heartbeat dynamics

In this study, we investigate correlation properties of fluctuations in heart interbeat (RR) time series in a broad range of physiological and pathological conditions. Using detrended fluctuation analysis (DFA) method we determined short-term (alpha 1) and long-term (alpha 2) scaling exponent. In addition, we calculated standard deviation of RR intervals (SDRR) as the simplest variability measure. We found that the difference between alpha 1 and alpha 2 is related to RR interval length. At the shortest RR intervals, which correspond to extreme physiological and pathological conditions, we found the highest reduction of variability and the biggest difference between scaling exponents. In this case, DFA reveals a white noise over short scales (alpha 1 about 0.5) and strongly correlated noise over large scales (alpha 2 about 1.5). With an increase in RR interval, accompanied by increased variability (increase in parasympathetic control), the difference between alpha 1 and alpha 2 decreases. The difference between scaling exponents disappeared in a state of efficient autonomic control. We suggest that the complexity in heart rhythm is achieved through coupling between intrinsically controlled heart rhythm and autonomic control, and that the model of stochastic resonance mechanism could be applied to this system.

Unsupervised classification of ventricular extrasystoles using bounded clustering algorithms and morphology matching

Ventricular extrasystoles (VE) are ectopic heartbeats involving irregularities in the heart rhythm. VEs arise in response to impulses generated in some part of the heart different from the sinoatrial node. These are caused by the premature discharge of a ventricular ectopic focus. VEs after myocardial infarction are associated with increased mortality. Screening of VEs is typically a manual and time consuming task that involves analysis of the heartbeat morphology, QRS duration, and variations of the RR intervals using long-term electrocardiograms. We describe a novel algorithm to perform automatic classification of VEs and report the results of our validation study. The proposed algorithm makes use of bounded clustering algorithms, morphology matching, and RR interval length to perform automatic VE classification without prior knowledge of the number of classes and heartbeat features. Additionally, the proposed algorithm does not need a training set.

Dependence of heart rate variability on heart period in disease and aging

The aim of this study was to compare the dependence of heart rate variability (HRV) on heart period (RR interval length) under different physiological and pathological states in order to detect changes in HR modulation. The dependence of HRV on the RR interval length in healthy elderly subjects, congestive heart failure (CHF) patients and one patient with a transplanted heart (T) was compared with healthy young subjects. Spectral powers, sample entropy (SampEn) and short-term fractal scaling exponent (α1) were determined from 24 h free-running recordings. For the same HR, HRV measures were different in different groups. In healthy subjects HRV measures depended on RR interval length and all spectral powers were highly correlated, although reduced in elderly subjects. SampEn at high HR was the most sensitive quantity to changes induced by aging. In disease, CHF and T, an achievable HR range was decreased, all spectral powers were reduced, but correlated, and the dependence of HRV measures on RR was lost. There was an evident difference in the dependence of nonlinear on linear measures between young subjects and all the other studied groups. In disease the reduction in autonomic control was associated with the decrease in short-range correlation and regularity in RR series. We have concluded that the analysis of HRV measures as functions of RR interval length can reveal important aspects of HR control that might be lost in averaging.

Assessment of Cardiac Autonomic Regulation and Ventricular Repolarization after Off-Pump Coronary Artery Bypass Grafting

Altered autonomic regulation precipitates cardiac arrhythmias and increases the risk of sudden cardiac death. This risk is further increased by changes in ventricular repolarization. Autonomic regulation is deranged in patients after myocardial on-pump revascularization. We aimed to clarify how off-pump coronary artery bypass grafting (CABG) affects postoperative cardiac autonomic regulation and ventricular repolarization within 4 weeks after CABG. Forty-two patients (mean age, 61.9 +/- 9.3 years; mean EURO score 2.6 +/- 1.9) were electively admitted for off-pump CABG. The electrocardiographic and respiratory waveform recordings were performed in the afternoon in the supine position for 10 minutes. Autonomic modulation was assessed using heart rate variability analysis. Power spectra were computed from 5-minute stable RR intervals using Fourier Transform analysis. Total power of spectra was defined in the range of 0.01 to 0.40 Hz, high-frequency power within 0.15 to 0.40 Hz, and low-frequency power within 0.04 to 0.15 Hz. Normalized power was defined as a ratio of power in each band/total power. The high- and low-frequency power as well as their normalized values indicated cardiac vagal and sympathetic modulation, respectively. Ventricular repolarization was assessed using QT interval, QT interval variability, and QT-RR interdependence analysis. QT intervals were determined from the beginning of the 5-minute segments. QT interval variability was evaluated by a T-wave template-matching algorithm. Pearson correlation between length of RR and QT interval was applied to study QT-RR characteristics. The results were tested for significance using the Fisher exact test, nonpaired t test, and analysis of variance; a P <.05 was considered significant. The frequency of arrhythmic events and heart rate increased from the fourth to the seventh postoperative day and returned to preoperative levels 4 weeks after CABG. Heart rate variability measures indicating autonomic modulation remained depressed even 4 weeks after the procedure. QT variability index increased from -1.2 +/- 0.5 to -0.8 +/- 0.4 on the fourth day after the operation (P <.05) and returned to -1.0 +/- 0.5 4 weeks after CABG (P = not significant). QT-RR correlation decreased from 0.41 to 0.23 (P <.05) and remained significantly impaired as long as 4 weeks after CABG. Observed faster heart rates until 1 week after off-pump CABG imply excessive adrenergic activation, which is comparable to on-pump CABG procedure rates. The results indicate profound autonomic derangement and loss of rate-dependent regulation after off-pump CABG even 4 weeks after operation. Restituted repolarization as assessed by QT variability index 4 weeks postoperatively corresponded with decreased frequency of rhythm disturbances 4 weeks after CABG. The loss of coupling between QT and RR intervals shows increased electrical instability postoperatively, which may serve as an additional promoter for postoperative arrhythmias, especially at higher heart rates.