Variation of spectral power immediately prior to spontaneous onset of ventricular tachycardia/ventricular fibrillation in implantable cardioverter defibrillator patients

Heart Rate Variability Analysis to Predict Onset of Ventricular Tachyarrhythmias in Implantable Cardioverter Defibrillators

Implantable cardioverter defibrillators (ICDs) are commonly used in patients at high risk of sudden cardiac death (SCD) to help prevent and treat life-threatening arrhythmia. Up to 80% of cases of sudden cardiac death are caused by ventricular tachyarrhythmias (VTA) and the accurate prediction of VTA in patients with ICDs can help prevent SCD. Early prediction allows tiered and less invasive therapies to be used to help prevent VTA which are more easily tolerated by the patient and are less battery intensive. In this work, a comparative study of three types of frequency domain features (spectral, bispectrum, and Fourier-Bessel) for VTA prediction is presented based on heart rate variability (HRV) signals between one and five minutes prior to known SCD. Using Fourier-Bessel features and a standard classification approach resulted in the best performance of 87.5% accuracy, 89.3% sensitivity and 85.7% specificity. These results suggest that Fourier-Bessel features are a promising approach for SCD prediction, and that new feature development can help improve both the sensitivity and specificity of SCD prediction in ICDs.

Prediction of Sudden Cardiac Death in Implantable Cardioverter Defibrillators: A Review and Comparative Study of Heart Rate Variability Features

Over the last four decades, implantable cardioverter defibrillators (ICDs) have been widely deployed to reduce sudden cardiac death (SCD) risk in patients with a history of life-threatening arrhythmia. By continuous monitoring of the heart rate, ICDs can use decision algorithms to distinguish normal cardiac sinus rhythm or supra-ventricular tachycardia from abnormal cardiac rhythms like ventricular tachycardia and ventricular fibrillation and deliver appropriate therapy such as an electrical stimulus. Despite the success of ICDs, more research is still needed, particularly in decision-making algorithms. Because of low specificity in practical devices, patients with ICDs still receive inappropriate shocks, which may lead to inadvertent mortality and reduction of quality of life. At the same time, higher sensitivity can lead to the use of newer tiered therapies. The purpose of this study is to review the literature on common signal features used in detection algorithms for abnormal cardiac sinus rhythm, as well as reviewing datasets used for algorithm development in previous studies. More than 50 different features to address heart rate changes before SCD have been reviewed and general methodology on this area proposed based on variety of studies on ICDs functionality. A comparative study on the prediction performance of these features, using a common database, is also presented. By combining these features with a support vector machine classifier, achieved results have compared well with other studies.

Multipole analysis of heart rate variability as a predictor of imminent ventricular arrhythmias in ICD patients

BACKGROUND

Contemporary implantable cardiac defibrillators (ICD) enable storage of multiple, preepisode R-R recordings in patients who suffered from ventricular tachyarrhythmia (VTA). Timely prediction of VTA, using heart rate variability (HRV) analysis techniques, may facilitate the implementation of preventive and therapeutic strategies.

AIM

To evaluate the novel multipole method of the HRV analysis in prediction of imminent VTAs in ICD patients.

METHODS

We screened patients from the Biotronik HAWAI Registry (Heart Rate Analysis with Automated ICDs). A total of 28 patients from the HAWAI registries (phase I and II), having medical records, who had experienced documented, verified VTA during the 2-year follow-up, were included in our analysis. HRV during preepisode recordings of 4,500 R-R intervals were analyzed using the Dyx parameter and compared to HRV of similar length recordings from the same patients that were not followed by arrhythmia.

RESULTS

Our study population consisted mainly of men 25 of 28 (89%), average age of 64.8 ± 9.4 years, 92% with coronary artery disease. HRV during 64 preevent recordings (2.3 events per patient on average) was analyzed and compared with 60 control recordings. The multipole method of HRV analysis showed 50% sensitivity and 91.6% specificity for prediction of ventricular tachycardia/ventricular fibrillation in the study population, with 84.5% positive predictive value. No statistically significant correlation was found between various clinical parameters and the sensitivity of imminent VTA predetection in our patients.

CONCLUSION

The multipole method of HRV analysis emerges as a highly specific, possible predictor of imminent VTA, providing an early warning allowing to prepare for an arrhythmic episode.

Traffic-related air pollution exposures and changes in heart rate variability in Mexico City: a panel study

BACKGROUND

While air pollution exposures have been linked to cardiovascular outcomes, the contribution from acute gas and particle traffic-related pollutants remains unclear. Using a panel study design with repeated measures, we examined associations between personal exposures to traffic-related air pollutants in Mexico City and changes in heart rate variability (HRV) in a population of researchers aged 22 to 56 years.

METHODS

Participants were monitored for approximately 9.5 hours for eight days while operating a mobile laboratory van designed to characterize traffic pollutants while driving in traffic and "chasing" diesel buses. We examined the association between HRV parameters (standard deviation of normal-to-normal intervals (SDNN), power in high frequency (HF) and low frequency (LF), and the LF/HF ratio) and the 5-minute maximum (or average in the case of PM(2.5)) and 30-, 60-, and 90-minute moving averages of air pollutants (PM(2.5), O(3), CO, CO(2), NO(2), NO(x), and formaldehyde) using single- and two-pollutant linear mixed-effects models.

RESULTS

Short-term exposure to traffic-related emissions was associated with statistically significant acute changes in HRV. Gaseous pollutants - particularly ozone - were associated with reductions in time and frequency domain components (α = 0.05), while significant positive associations were observed between PM(2.5) and SDNN, HF, and LF. For ozone and formaldehyde, negative associations typically increased in magnitude and significance with increasing averaging periods. The associations for CO, CO(2), NO(2), and NO(x) were similar with statistically significant associations observed for SDNN, but not HF or LF. In contrast, PM(2.5) increased these HRV parameters.

CONCLUSIONS

Results revealed an association between traffic-related PM exposures and acute changes in HRV in a middle-aged population when PM exposures were relatively low (14 μg/m(3)) and demonstrate heterogeneity in the effects of different pollutants, with declines in HRV - especially HF - with ozone and formaldehyde exposures, and increases in HRV with PM(2.5) exposure. Given that exposure to traffic-related emissions is associated with increased risk of cardiovascular morbidity and mortality, understanding the mechanisms by which traffic-related emissions can cause cardiovascular disease has significant public health relevance.

Scaling Characteristics of Heart Rate Time Series Before the Onset of Ventricular Tachycardia

Ventricular tachycardia (VT) provokes sudden cardiac death (SCD), which is a major cause of mortality in developed countries. Implantable cardioverter-defibrillators (ICDs) are an efficient therapy for SCD prevention. In this study we analyze heart rate variability (HRV) in data stored by ICDs. In 29 patients exhibiting VT episodes, the last 1000 normal beat-to-beat intervals are analyzed and compared to an individually acquired control time series (CON). HRV analysis is performed with standard parameters of time and frequency domain as suggested by the HRV Task Force. For scaling analyses of heart rate time series, the fractal dimension is analysed, applying Higuchi's algorithm (HFD). Furthermore, detrended fluctuation analysis (DFA) is performed. None of the standard HRV parameters shows significant differences between CON and VT. Before the onset of VT, the scaling characteristics by means of HFD and DFA are significantly changed. In conclusion, scaling analysis reveals changes in autonomic heart rate modulation preceding VT.

Wavelet transform for analysis of heart rate variability preceding ventricular arrhythmias in patients with ischemic heart disease

INTRODUCTION

Studies evaluating changes in HRV preceding the onset of ventricular arrhythmias using conventional techniques have shown inconsistent results. Time-frequency analysis of HRV is traditionally performed using short-term Fourier transform (STFT). Wavelet transform (WT) may however be better suited for analyzing non-stationary signals such as heart rate recordings.

METHODS AND RESULTS

We studied patients with a history of myocardial infarction implanted with a defibrillator with an extended memory. The RR intervals during the 51 min preceding ventricular events requiring electrical therapy were retrieved, and HRV studied by WT and STFT. 111 episodes of ventricular arrhythmia were retrieved from 41 patients (38 males, age 64 +/- 8 years). Heart rate increased significantly before arrhythmia. There was no significant variation in low frequency / high frequency components (LF/HF) observed for the group as a whole, probably due to a great degree of heterogeneity amongst individuals. A subset of 30 patients also had heart rate recordings performed during normal ICD follow-up. WT did not show any difference in HRV before arrhythmia onset and during control conditions.

CONCLUSION

Variations in HRV before onset of ventricular arrhythmias were not apparent in this large dataset, despite use of optimal tools for studying time-frequency analysis.

Beta receptor blockade potentiates the antiarrhythmic actions of d-sotalol on reentrant ventricular tachycardia in a canine model of myocardial infarction

INTRODUCTION

The importance of beta receptor blockade for the antiarrhythmic action of sotalol has not been completely elucidated. We determined how beta receptor blockade interacts with the effects of potassium channel blockade on reentrant circuits.

METHODS AND RESULTS

Sustained ventricular tachycardia was induced by programmed stimulation in dogs 4 days after left anterior coronary artery occlusion and reentrant circuits in the epicardial border zone (EBZ) mapped. The effects of the beta receptor-blocking drug, esmolol, the potassium channel-blocking drug d-sotalol, which lacks beta receptor-blocking effects, and the combination of the two drugs on the reentrant circuits that cause tachycardia were determined. Esmolol did not alter the ability to induce tachycardia. Small changes in the location or extent of lines of block in reentrant circuits accounted for small decreases or increases in tachycardia cycle lengths. d-Sotalol prolonged the lines of block in reentrant circuits, slowed propagation around the circuits, and prolonged tachycardia cycle length, but it did not stop tachycardia or prevent the induction of tachycardia. The combination of esmolol and d-sotalol prevented the initiation of sustained tachycardia. The stimulated premature impulse either blocked before reentering or traversed the circuit several times prior to blocking in a region of fractionated electrograms. The addition of esmolol to d-sotalol abolished the reverse use-dependent effects of d-sotalol alone on effective refractory period (ERP) and significantly prolonged ERP in the area of the reentrant circuit.

CONCLUSION

Beta receptor blockade is important for the antiarrhythmic effects of d,l-sotalol on reentrant ventricular tachycardia in this model. The mechanism is speculative but may involve potentiation of d-sotalol actions to prolong ERP or effects on gap junctions.

Detecting instabilities of cardiac rhythm

Diminished beat-to-beat variations in cardiac cycle lengths (CLs) are associated with poor prognosis after acute myocardial infarction and in patients with heart failure. Short-long-short sequences of cardiac cycles, or ultra-short rhythm instabilities, precede initiation of ventricular tachyarrhythmias in some patients. However, little is known about clinical or prognostic significance of abrupt short-term instabilities in CL (AICL) that occur minutes to hours before the event, in part because appropriate analytical methods are lacking. Although various techniques have been used to analyze CL changes, methods for analysis of AICL are limited. We compared performance of time domain, spectral, nonlinear, and pattern recognition techniques with respect to the detection and quantification of AICL. Because of high intra- and inter-subject variability of CL, pattern recognition techniques compared favorably to other studied methods. In continuous ambulatory ECG recordings, AICL occurred hours before spontaneous initiation of sustained atrial and ventricular arrhythmias in different patient populations. AICL were also found prior to the onset of spontaneous ventricular arrhythmias in a mouse model of congestive heart failure. To quantify AICL, we used the number of unstable orthogonal projection coefficients; this number gradually increased hours before the event. Removal of ectopic beats reduced but did not eliminate AICL. To illustrate potential physiological effects and temporal evolution of AICL, we used a simple, continuous, two-dimensional model of cardiac tissue governed by the Morris-Lecar equations. Computer simulations in this model showed that AICL may lead to gradual accumulation of spatial irregularities of the propagation wavefront giving rise to the initiation of reentry. Time-frequency analysis of the most significant eigenvectors of cardiac rhythm in subjects undergoing head-up tilt showed that AICL could indicate instabilities and unsuccessful adaptation of autonomic nervous system activity to physiological stimuli.

Study of precursors of ventricular tachycardia from data stored in the memory of a dual chamber implantable cardioverter defibrillator

This study was performed to examine precursors of ventricular tachyarrhythmias in patients who experienced a sustained ventricular tachyarrhythmia and received appropriate therapy by ICD. From an overall consecutive population of 77 patients, 18 patients (1 woman, mean age 61.7 +/- 10.8 years) were selected for having experienced a sustained ventricular tachyarrhythmia and received at least one appropriate ICD therapy preceded by 20 minutes of internal information. The number of premature ventricular complexes (PVCs)/min for each of the 20 minutes preceding the onset of ventricular tachyarrhythmia, the shortest coupling intervals between PVC and normal sinus beat, and the presence of short-long-short (SLS) interval sequences were examined. Data were stratified according to underlying disease, left ventricular ejection fraction, rate of ventricular tachyarrhythmia, and antiarrhythmic therapy. One hundred twenty-eight episodes of spontaneous ventricular tachyarrhythmia were retrieved. Rapid ventricular tachyarrhythmia (>160 beats/min) were preceded by a significantly greater mean number (3.71 +/- 6.36)of PVCs than slower ventricular tachyarrhythmia (<or=160 beats/min) (0.63 +/- 0.88, P = 0.0004). The mean shortest PVC coupling interval was significantly shorter in patients with (588 +/- 99 ms) versus without (643 +/- 111 ms, P = 0.03)ischemic heart disease, before episodes of rapid(527 +/- 55 ms)versus slower (636 +/- 105 ms, P = 0.0001)ventricular tachyarrhythmia, and in the absence (538 +/- 80 ms)versus the presence(620 +/- 105 ms, P = 0.006)of amiodarone. SLS sequences preceded 29% of rapid ventricular tachyarrhythmic episodes, versus 8% of the slower ventricular tachyarrhythmia (P < 0.01). Significant differences were found in the characteristics of PVCs preceding ventricular tachyarrhythmic episodes in accordance to their rate and the underlying cardiomyopathy. Though insufficient in isolation, these findings may be helpful when combined with other observations to develop preventive algorithms, or to refine the programming of implantable devices.

Heart rate variability before the onset of ventricular tachycardia: differences between slow and fast arrhythmias

BACKGROUND

We tested whether or not heart rate variability (HRV) changes can serve as early signs of ventricular tachycardia (VT) and predict slow and fast VT in patients with an implantable cardioverter defibrillator (ICD).

METHODS AND RESULTS

We studied the ICD stored 1000 beat-to-beat intervals before the onset of VT (131 episodes) and during a control time without VT (74 series) in 63 chronic heart failure ICD patients. Standard HRV parameters as well as two nonlinear parameters, namely 'Polvar10' from symbolic dynamics and the finite time growth rates 'Fitgra9' were calculated. Comparing the control and the VT series, no linear HRV parameter showed a significant difference. The nonlinear parameters detected a significant increase in short phases with low variability before the onset of VT (for time series with less than 10% ectopy, P<0.05). Subdividing VT into fast (cycle length <or=270 ms) and slow (>270 ms) events, we found that the onset of slow VT was characterized by a significant increase in heart rate, whereas fast VT was triggered during decreased heart rates, compared to the control series.

CONCLUSIONS

Our data may permit the development of automatic ICD algorithms based on nonlinear dynamic HRV parameters to predict VT before it starts. Furthermore, they may facilitate improved prevention strategies.

Multidimensional rhythm disturbances as a precursor of sustained ventricular tachyarrhythmias

Cardiac cycle dynamics reflect underlying physiological changes that could predict imminent arrhythmias but are obscured by high complexity, nonstationarity, and large interindividual differences. To overcome these problems, we developed an adaptive technique, referred to as the modified Karhunen-Loeve transform (MKLT), that identifies an individual characteristic ("core") pattern of cardiac cycles and then tracks the changes in the pattern by projecting the signal onto characteristic eigenvectors. We hypothesized that disturbances in the core pattern, indicating progressive destabilization of cardiac rhythm, would predict the onset of spontaneous sustained ventricular tachyarrhythmias (VTAs) better than previously reported methods. We analyzed serial ambulatory ECGs recorded in 57 patients at the time of VTA and non-VTA 24-hour periods. The disturbances in the pattern were found in 82% of the recordings before the onset of impending VTA, and their dimensionality, defined as the number of unstable orthogonal projections, increased gradually several hours before the onset. MKLT provided greater sensitivity and specificity (70% and 93%) compared with the best traditional method (68% and 67%, respectively). We present a theoretical analysis of MKLT and describe the effects of ectopy and slow changes in cardiac cycles on the disturbances in the pattern. We conclude that MKLT provides greater predictive accuracy than previously reported methods. The improvement is due to the use of individual patterns as a reference for tracking the changes. Because this approach is independent of the group reference values or the underlying clinical context, it should have substantial potential for predicting other forms of arrhythmic events in other populations.