Abnormal Heart Rate Turbulence Predicts the Initiation of Ventricular Arrhythmias

HRT assessment reviewed: a systematic review of heart rate turbulence methodology

Heart rate turbulence (HRT) is a biphasic reaction to a ventricular premature contraction (VPC) mainly mediated by the baroreflex. It can be used for risk stratification in different disease patterns. Despite existing standards there is a lot of variation in terms of measuring and calculating HRT, which complicates research and application.

OBJECTIVE

This systematic review outlines and evaluates the methodological spectrum of HRT research, especially filtering criteria, parameter calculation and thresholds.

APPROACH

The analysis includes all research papers written in English that have been published before 12.10.2018, are listed on PubMed and involve calculation of HRT parameter values.

MAIN RESULTS

HRT assessment is still being performed in various ways and important specifications of the methodology are not given in many articles. Nevertheless, some suggestions regarding HRT methodology can be made: a normalised turbulence slope should be used to uncouple the parameter from heart rate and frequency of extrasystoles. Filtering criteria as formerly reviewed in the guidelines should be met and mentioned. The minimal number of VPC snippets (VPCSs) as well as new cut-off values for different risks need to be further evaluated. Most importantly, the exact and complete methodology must be described to ensure reproducibility and comparability.

SIGNIFICANCE

Methodical variation hinders comparability of research and medical application. Our continuing questions help to further standardise the measurement and calculation of HRT and increase its value for medical risk stratification.

Abnormalities of heart rate turbulence and heart rate variability as indicators of increased cardiovascular risk in patients with systemic sclerosis

Introduction

Systemic sclerosis (SSc) is a connective tissue disease manifested by progressive fibrosis of many internal organs including the cardiovascular system and development of autonomic disorders with sympathetic predominance. These abnormalities can increase cardiovascular mortality.

Aim

To evaluate heart rate turbulence (HRT) and variability (HRV) parameters (indicator of autonomic imbalance) obtained from 24-hour ECG Holter monitoring, as predictors of the increased cardiovascular risk in patients with scleroderma.

Material and methods

Thirty-twoscleroderma patients and 30 healthy people were included. After clinical examination, ECG, routine laboratory tests and echocardiography, participants performed 24-hour Holter-ECG at home. For HRT assessment, turbulence onset (To) and turbulence slope (Ts) parameters were used. Both time and frequency domain analysis of HRV was used. The HRV circadian rhythm was also evaluated.

Results

Time domain: SDNN, SDNN-ix, SDANN and frequency domain: LF, VLF, ULF, NHF, NLF, parameters were lower, while p50NN was higher in SSc as compared to the control group. There was also a loss of the circadian rhythm for r-MSSD and p50NN present in the control group. Abnormal HRT parameters To and/or Ts occurred in the SSc group only. The median value of To = –1.24% and Ts = 11.13 ms/RR did not differ significantly as compared to the control group.

Conclusions

The study confirmed the presence of HRV disturbances, including HRV circadian rhythm, as it may seem at an early stage of SSc. The HRT disorders may be characterized by the increasing changes with advancing disease. This indicates the presence of autonomic imbalance and an increased cardiovascular risk.

Positive Psychotherapy to Improve Autonomic Function and Mood in ICD Patients (PAM-ICD): Rationale and Design of an RCT Currently Underway

BACKGROUND

Improving mental and physical health of patients with implantable cardioverter defibrillators (ICD) is critical because this group is at high risk for ventricular arrhythmias and sudden death and depressed or anxious cardiovascular disease (CVD) patients appear to be at even higher risk for mortality compared to nondepressed or nonanxious CVD patients. Further, autonomic dysfunction is present in these patients, and negative emotions and arrhythmias form a downward spiral further worsening mood, well-being, and cardiovascular health. Much research demonstrates that positive emotion is related to health benefits, improved physiology, and increased survival.

METHODS AND RESULTS

This is a two-arm randomized controlled trial aiming to recruit 60 adult ICD patients comparing 12 individually delivered, weekly sessions of: (1) a positive emotion-focused cognitive-behavioral therapy (Quality of Life Therapy [QOLT]), and (2) Heart Healthy Education. Autonomic functioning, heart rhythm indices, and psychosocial health are measured at baseline, 3 months, and 9 months. The first goal is feasibility and acceptability, with the primary outcome being arrhythmic event frequency data.

CONCLUSION

This study is designed to test whether QOLT produces changes in mood, quality of life/well-being, autonomic function, and arrhythmic and ICD therapy event rates. This feasibility trial is a foundational step for the next trial of QOLT to help determine whether a 3-month QOLT trial can reduce arrhythmias occurrences among ICD patients, and examine a mechanism of autonomic functioning. This study may help to develop and implement new medical or psychological therapies for ICD patients.

Semisupervised ECG Ventricular Beat Classification With Novelty Detection Based on Switching Kalman Filters

Automatic processing and accurate diagnosis of pathological electrocardiogram (ECG) signals remains a challenge. As long-term ECG recordings continue to increase in prevalence, driven partly by the ease of remote monitoring technology usage, the need to automate ECG analysis continues to grow. In previous studies, a model-based ECG filtering approach to ECG data from healthy subjects has been applied to facilitate accurate online filtering and analysis of physiological signals. We propose an extension of this approach, which models not only normal and ventricular heartbeats, but also morphologies not previously encountered. A switching Kalman filter approach is introduced to enable the automatic selection of the most likely mode (beat type), while simultaneously filtering the signal using appropriate prior knowledge. Novelty detection is also made possible by incorporating a third mode for the detection of unknown (not previously observed) morphologies, and denoted as X-factor. This new approach is compared to state-of-the-art techniques for the ventricular heartbeat classification in the MIT-BIH arrhythmia and Incart databases. F1 scores of 98.3% and 99.5% were found on each database, respectively, which are superior to other published algorithms' results reported on the same databases. Only 3% of all the beats were discarded as X-factor, and the majority of these beats contained high levels of noise. The proposed technique demonstrates accurate beat classification in the presence of previously unseen (and unlearned) morphologies and noise, and provides an automated method for morphological analysis of arbitrary (unknown) ECG leads.

Classification of holter registers by dynamic clustering using multi-dimensional particle swarm optimization

In this paper, we address dynamic clustering in high dimensional data or feature spaces as an optimization problem where multi-dimensional particle swarm optimization (MD PSO) is used to find out the true number of clusters, while fractional global best formation (FGBF) is applied to avoid local optima. Based on these techniques we then present a novel and personalized long-term ECG classification system, which addresses the problem of labeling the beats within a long-term ECG signal, known as Holter register, recorded from an individual patient. Due to the massive amount of ECG beats in a Holter register, visual inspection is quite difficult and cumbersome, if not impossible. Therefore the proposed system helps professionals to quickly and accurately diagnose any latent heart disease by examining only the representative beats (the so called master key-beats) each of which is representing a cluster of homogeneous (similar) beats. We tested the system on a benchmark database where the beats of each Holter register have been manually labeled by cardiologists. The selection of the right master key-beats is the key factor for achieving a highly accurate classification and the proposed systematic approach produced results that were consistent with the manual labels with 99.5% average accuracy, which basically shows the efficiency of the system.

Heart rate turbulence impairment and ventricular arrhythmias in patients with systemic sclerosis

BACKGROUND

Arrhythmias, conduction disturbances, and cardiac autonomic nervous system dysfunction are the most frequent cardiovascular complications in systemic sclerosis (scleroderma). The aim of the study was to assess heart rate turbulence (HRT) in systemic sclerosis patients and to identify the relationship between HRT and occurrence of arrhythmias.

METHODS

Forty-five patients with scleroderma (aged 54.6 +/- 14.7 years) and 30 healthy sex- and age-matched subjects were examined. In addition to routine studies, 24-hour Holter monitoring with assessment of HRT was performed.

RESULTS

As compared to controls, HRT was significantly impaired in systemic sclerosis patients. Abnormal HRT defined as turbulence onset (TO) > or =0.0% and/or turbulence slope (TS) < or =2.5 ms/RR (ms/RR interval) was found in 19 (42%) scleroderma patients and in no members of the control group. Serious ventricular arrhythmias Lown class IV (VA-LownIV), for example, couplets and/or nonsustained ventricular tachycardias, were observed in 16 (36%) scleroderma patients. The median value of TS was significantly lower in systemic sclerosis patients with VA-LownIV than in patients without VA-LownIV (3.68 vs 7.00 ms/RR, P = 0.02). The area under curve of ROC analysis for prediction of VA-LownIV was 0.72 (95% confidence interval [CI] 0.56-0.87) and revealed that TS <9.0 ms/RR was associated with VA-Lown IV occurrence, with sensitivity of 93.7% and specificity of 44.8%. Univariate and multivariate analyses confirmed that lower values of TS were associated with VA-LownIV occurrence (odds ratio 1.52, 95% CI 1.09-2.12, P = 0.01).

CONCLUSIONS

Patients with systemic sclerosis are characterized by significant HRT impairment. Assessment of HRT and especially TS is useful in the identification of patients at risk for ventricular arrhythmias.

A personalized classification system for Holter registers

In this paper we present a personalized long-term electrocardiogram (ECG) classification framework, which can be applied to any Holter register recorded from an individual patient. Due to the massive amount of ECG beats in a Holter register, visual inspection is quite difficult and cumbersome, if not impossible. Therefore the proposed system helps professionals to quickly and accurately diagnose any latent heart disease by examining only the representative beats (the so called master key-beats) each of which is automatically extracted from a time frame of homogeneous (similar) beats. We tested the system on a benchmark database where beats of each Holter register have been manually labeled by cardiologists. The selection of the right master key-beats is the key factor for achieving a highly accurate classification and thus we used exhaustive K-means clustering in order to find out (near-) optimal number of key-beats as well as the master key-beats. The classification process produced results that were consistent with the manual labels with over 99% average accuracy, which basically shows the efficiency and the robustness of the proposed system over massive data (feature) collections in high dimensions.

Robust detection of premature ventricular contractions using a wave-based Bayesian framework

Detection and classification of ventricular complexes from the ECG is of considerable importance in Holter and critical care patient monitoring, being essential for the timely diagnosis of dangerous heart conditions. Accurate detection of premature ventricular contractions (PVCs) is particularly important in relation to life-threatening arrhythmias. In this paper, we introduce a model-based dynamic algorithm for tracking the ECG characteristic waveforms using an extended Kalman filter. The algorithm can work on single or multiple leads. A "polargram"--a polar representation of the signal--is introduced, which is constructed using the Bayesian estimations of the state variables. The polargram allows the specification of a polar envelope for normal rhythms. Moreover, we propose a novel measure of signal fidelity by monitoring the covariance matrix of the innovation signals throughout the filtering procedure. PVCs are detected by simultaneous tracking the signal fidelity and the polar envelope. Five databases, including 40 records from MIT-BIH arrhythmia database, are used for differentiating normal, PVC, and other beats. Performance evaluation results show that the proposed method has an average detection accuracy of 99.10%, aggregate sensitivity of 98.77%, and aggregate positive predictivity of 97.47%. Furthermore, the method is capable of 100% accuracy for records that contain only PVCs and normal sinus beats. The results illustrate that the method can contribute to, and enhance the performance of clinical PVC detection.

Influence of heavy cigarette smoking on heart rate variability and heart rate turbulence parameters

BACKGROUND

Cigarette smoking increases the risk of cardiovascular events related with several mechanisms. The most suggested mechanism is increased activity of sympathetic nervous system. Heart rate variability (HRV) and heart rate turbulence (HRT) has been shown to be independent and powerful predictors of mortality in a specific group of cardiac patients. The goal of this study was to assess the effect of heavy cigarette smoking on cardiac autonomic function using HRV and HRT analyses.

METHODS

Heavy cigarette smoking was defined as more than 20 cigarettes smoked per day. Heavy cigarette smokers, 69 subjects and nonsmokers 74 subjects (control group) were enrolled in this study. HRV and HRT analyses [turbulence onset (TO) and turbulence slope (TS)] were assessed from 24-hour Holter recordings.

RESULTS

The values of TO were significantly higher in heavy cigarette smokers than control group (-1.150 +/- 4.007 vs -2.454 +/- 2.796, P = 0.025, respectively), but values of TS were not statistically different between two groups (10.352 +/- 7.670 vs 9.613 +/- 7.245, P = 0.555, respectively). Also, the number of patients who had abnormal TO was significantly higher in heavy cigarette smokers than control group (23 vs 10, P = 0.006). TO was correlated with the number of cigarettes smoked per day (r = 0.235, P = 0.004). While LF and LF/HF ratio were significantly higher, standard deviation of all NN intervals (SDNN), standard deviation of the 5-minute mean RR intervals (SDANN), root mean square of successive differences (RMSSD), and high-frequency (HF) values were significantly lower in heavy smokers. While, there was significant correlation between TO and SDNN, SDANN, RMSSD, LF, and high frequency (HF), only HF was correlated with TS.

CONCLUSION

Heavy cigarette smoking has negative effect on autonomic function. HRT is an appropriate noninvasive method to evaluate the effect of cigarette on autonomic function. Simultaneous abnormal HRT and HRV values may explain increased cardiovascular event risk in heavy cigarette smokers.

Model-based detection of heart rate turbulence

In this study, the integral pulse frequency modulation model is extended to account for the presence of ectopic beats and heart rate turbulence (HRT). Based on this model, a new statistical approach to the detection and characterization of HRT is presented. The detector structure involves a set of Karhunen-LoEve basis functions and a generalized likelihood ratio test statistic T(x) . The three most significant basis functions reflect the difference in heart rate prior to a ventricular ectopic beat (VEB) compared to after HRT, the "average" HRT, and a delayed contribution to HRT, respectively. Detector performance was studied on both simulated and ECG signals. Three different simulations were performed for the purpose of studying the influence of SNR, QRS jitter, and ECG sampling rate. The results show that the HRT test statistic T(x) performs better in all simulations than do the commonly used parameters known as turbulence onset (TO) and turbulence slope (TS). In order to attain the same performance as T(x), TS needs at least twice the amount of VEBs for averaging, and TO at least four times. The detector performance was also studied on ECGs acquired from eight patients who underwent hemodialysis treatment with the goal to discriminate between patients considered to be hypotension-resistant (HtR) and hypotension-prone (HtP). The results show that T(x) exhibits larger mean values in HtR patients than in HtP, suggesting that HRT is mostly present in HtR patients. The overlap between the two groups was larger for TO and TS than for T(x).

Heart rate turbulence: standards of measurement, physiological interpretation, and clinical use: International Society for Holter and Noninvasive Electrophysiology Consensus

This consensus statement has been compiled on behalf of the International Society for Holter and Noninvasive Electrophysiology. It reviews the topic of heart rate turbulence (HRT) and concentrates on technologies for measurement, physiologic background and interpretation, and clinical use of HRT. It also lists suggestions for future research. The phenomenon of HRT refers to sinus rhythm cycle-length perturbations after isolated premature ventricular complexes. The physiologic pattern of HRT consists of brief heart rate acceleration (quantified by the so-called turbulence onset) followed by more gradual heart rate deceleration (quantified by the so-called turbulence slope) before the rate returns to a pre-ectopic level. Available physiologic investigations confirm that the initial heart rate acceleration is triggered by transient vagal inhibition in response to the missed baroreflex afferent input caused by hemodynamically inefficient ventricular contraction. A sympathetically mediated overshoot of arterial pressure is responsible for the subsequent heart rate deceleration through vagal recruitment. Hence, the HRT pattern is blunted in patients with reduced baroreflex. The HRT pattern is influenced by a number of factors, provocations, treatments, and pathologies reviewed in this consensus. As HRT measurement provides an indirect assessment of baroreflex, it is useful in those clinical situations that benefit from baroreflex evaluation. The HRT evaluation has thus been found appropriate in risk stratification after acute myocardial infarction, risk prediction, and monitoring of disease progression in heart failure, as well as in several other pathologies.

EFFECT OF BENAZEPRIL ON HEART RATE TURBULENCE IN PATIENTS WITH DILATED CARDIOMYOPATHY

1. Heart rate (HR) turbulence describes short-term sinus rhythmic fluctuation after a single premature ventricular beat. Turbulence onset (TO) and turbulence slope (TS) are two essential parameters in HR turbulence. Turbulence onset and TS have been used to evaluate cardiac autonomic nerve function. 2. In the present study, we measured the HR turbulence in dilated cardiomyopathy (DCM) and determined the possible role of benazepril, an angiotensin-converting enzyme inhibitor (ACEI), on these parameters. There were three groups: control, DCM and DCM treated with benazepril. The control group consisted of normal subjects with PVB, but no structural heart disease. Ambulatory electrocardiogram, blood pressure and echocardiography were analysed. 3. There was an increase in TO and a decrease in TS in DCM patients. Benazepril treatment (10 mg/day, p.o.) reduced those changes. There were no significant differences in blood pressure and left ventricular ejection fraction (LVEF) between DCM patients and DCM patients treated with benazepril. 4. Linear regression analysis showed that TO was negatively correlated with LVEF, whereas TS was positively correlated with LVEF, in the DCM group. After benazepril treatment, the correlations between TO and TS and LVEF disappeared. 5. It is concluded that the TO and TS of HR turbulence are altered in patients with DCM. These alterations indicate a dysfunction of the autonomic control of cardiac electrophysiology in DCM patients. Although TO and TS are correlated with LVEF in DCM patients, the effect of benazepril in improving HR turbulence parameters is not a result of its action on heart function, which suggests a new beneficial effect of ACEI in the treatment of DCM patients.

Utility of microvolt T-wave alternans to predict sudden cardiac death in patients with cardiomyopathy

PURPOSE OF REVIEW

Sudden cardiac death remains a major cause of mortality among patients with cardiomyopathy and implantable cardioverter-defibrillator therapy has been shown to improve survival in these patients. Effective use of prophylactic implantable cardioverter-defibrillator therapy requires accurate risk stratification beyond assessment of ejection fraction, however. Repolarization alternans is a harbinger of ventricular arrhythmias and its measurement from body-surface recordings, also known as microvolt T-wave alternans, is emerging as an effective prognostic tool in these patients based on recent clinical trials.

RECENT FINDINGS

We review the pathogenesis and determinants of repolarization alternans. The current techniques for measuring T-wave alternans from the body surface are compared, including the spectral and modified moving average methods. Recent clinical trials evaluating the prognostic utility of T-wave alternans in patients with ischemic and nonischemic cardiomyopathy and no prior arrhythmic events are summarized. The findings of these studies are discussed in the context of implantable cardioverter-defibrillator prophylaxis. Body-surface T-wave alternans is an evolving technique and its limitations are presented along with approaches to improve its predictive accuracy.

SUMMARY

Risk stratification with T-wave alternans has the potential to guide prophylactic implantable cardioverter-defibrillator therapy in a growing population of patients with cardiomyopathy.