T-wave alternans and arrhythmia risk stratification

Heart Failure and Sudden Cardiac Death

The Centers for Diseases Control and Prevention estimates that 5.7 million adults in the United States suffer from heart failure and 1 in 9 deaths in 2009 cited heart failure as a contributing cause. Almost 50% of patients who are diagnosed with heart failure die within 5 years of diagnosis. Cardiovascular disease is a public health burden. The prognosis of patients with heart failure has improved significantly. However, the risk for death remains high. Managing sudden death risk and intervening appropriately with primary or secondary prevention strategies are of paramount importance.

A class of Monte-Carlo-based statistical algorithms for efficient detection of repolarization alternans

Cardiac repolarization alternans is an electrophysiologic condition identified by a beat-to-beat fluctuation in action potential waveform. It has been mechanistically linked to instances of T-wave alternans, a clinically defined ECG alternation in T-wave morphology, and associated with the onset of cardiac reentry and sudden cardiac death. Many alternans detection algorithms have been proposed in the past, but the majority have been designed specifically for use with T-wave alternans. Action potential duration (APD) signals obtained from experiments (especially those derived from optical mapping) possess unique characteristics, which requires the development and use of a more appropriate alternans detection method. In this paper, we present a new class of algorithms, based on the Monte Carlo method, for the detection and quantitative measurement of alternans. Specifically, we derive a set of algorithms (one an analytical and more efficient version of the other) and compare its performance with the standard spectral method and the generalized likelihood ratio test algorithm using synthetic APD sequences and optical mapping data obtained from an alternans control experiment. We demonstrate the benefits of the new algorithm in the presence of Gaussian and Laplacian noise and frame-shift errors. The proposed algorithms are well suited for experimental applications, and furthermore, have low complexity and are implementable using fixed-point arithmetic, enabling potential use with implantable cardiac devices.

Microvolt T-wave alternans: a review of techniques, interpretation, utility, clinical studies, and future perspectives

Microvolt T-wave alternans (TWA) testing involves measuring variation in the morphology of the T-wave on an every other beat basis. The magnitude of the variation observed is typically on the order of a few microvolts. Thus in order to detect microvolt TWA, specialized recording and signal processing methods must be employed for reliable measurement. Additionally, microvolt TWA is not generally present at rest even in patients at risk of ventricular tachyarrhythmias and therefore exercise stress, pharmacologic stress, or atrial pacing must be utilized in order to elevate the heart rate. A positive MTWA test is one in which sustained TWA is present with an onset heart rate < or = 110 bpm. With current instrumentation, microvolt TWA represents an inexpensive, convenient non-invasive testing modality. Microvolt TWA has been evaluated prospectively in a variety of patient populations as a means of predicting occurrence of ventricular tachyarrhythmic events and its association with the genesis of ventricular arrhythmias has been demonstrated. Future role of microvolt TWA testing in noninvasive risk stratification is awaiting results of ongoing clinical trials. In this article, we tried to review the techniques, interpretation, indications, clinical studies, and future perspectives of microvolt TWA.

Noninvasive sudden death risk stratification by ambulatory ECG-based T-wave alternans analysis: evidence and methodological guidelines

Extensive experimental and clinical evidence supports the utility of T-wave alternans (TWA) as a marker of risk for ventricular fibrillation. This entity appears to reflect the fundamental arrhythmogenic property of enhanced dispersion of repolarization. This relationship probably accounts for its relative ubiquity in patients with diverse types of cardiac disease, as has been recognized with the development of analytical tools. A basic premise of this review is that ambulatory ECG monitoring of TWA as patients experience the provocative stimuli of daily activities can expose latent electrical instability in individuals at heightened risk for arrhythmias. We will discuss the literature that supports this concept and summarize the current state of knowledge regarding the use of routine ambulatory ECGs to evaluate TWA for arrhythmia risk stratification. The dynamic, nonspectral modified moving average analysis method for assessing TWA, which is compatible with ambulatory ECG monitoring, is described along with methodological guidelines for its implementation. Finally, the rationale for combined monitoring of autonomic markers along with TWA will be presented.

Microvolt T-wave alternans as predictor of electrophysiological testing results in professional competitive athletes

BACKGROUND

Several studies have confirmed the equivalence of the microvolt T-wave alternans (mTWA) and the electrophysiology (EPS) tests in cardiac disease. No data are available in populations of competitive athletes with arrhythmias that might jeopardize the pursuit of their professional career.

METHODS

We prospectively studied 100 trained competitive athletes, including elite types (72/100), (mean age +/- standard deviation: 26.1 +/- 4.5 years). Forty-eight of them were wholly normal (Group A, mean age: 24.5 +/- 8.5 years) and 52 of them had severe arrhythmias (Group B, mean age: 28.2 +/- 11.5 years) and were symptomatic in 85% of cases for prolonged palpitations and syncope, but lacked any overt structural heart disease at standardized cardiological screening. All athletes were evaluated with the microvolt T-wave alternans exercise-stress test, using the Heart Wave System with Microvolt Sensors. Group B underwent EPS to evaluate inducibility to sustained ventricular tachycardia (VT) during programmed electrical stimulation.

RESULTS

In Group A, the mTWA outcome was determinate in 45 subjects (94%) and indeterminate in 3 (6%). No symptomatic event was reported in a follow-up of 36.1 months. In Group B, the mTWA test was positive in 7 symptomatic subjects (15%), indeterminate in 3 (7%), and negative for the remaining 42 subjects (76%). Forty-one of 42 negative mTWA subjects were also negative in the EPS test, without any syncope or sustained VT during 25.3 months of follow-up. In the positive mTWA test subjects, 5 (72%) were positive for inducibility of rapid sustained monomorphic VT in EPS, 1 was positive for severe sustained atrial tachyarrhythmias, and 1 refused EPS. We were able to pronounce a correct diagnosis of lymphocytic myocarditis for only 1 mTWA and EPS-positive subject. For the other 4 positive patients with arrhythmogenic micropathology, severe arrhythmic events were revealed in the follow-up and aggressive hybrid treatment was necessary.

CONCLUSION

Microvolt-TWA study seems to be a useful, noninvasive, and feasible tool for evaluating arrhythmic risk in the athletic population. The mTWA test showed a high negative predictive value, using both EPS and the follow-up observation for severe arrhythmic cardiac events as an endpoint. The positive predictive value was present in a limited number of cases that were, however, subjects with a high risk of sudden arrhythmic death.

Tracking repolarization dynamics in real-life data

Ambulatory (Holter) electrocardiographic recordings provide the tools for tracking temporal instabilities of repolarization during various daily activities. However, analysis of low-amplitude repolarization changes in this setting is challenging due to the presence of multiple artifacts, variable activity levels, and other uncontrolled factors. Here we compare performance of different methods for continuous analysis of repolarization dynamics using simulated signals and real-life Holter recordings. Selection of relatively stable segments with a low baseline drift and accurate correction of baseline wander constitute the first step in repolarization analysis. We describe application of adaptive filtering, which yields more accurate results than non-adaptive techniques. Because small (microvolt-level) residual baseline drifts can be a source of error in tracking repolarization changes, stability of isoelectrical segment has to be controlled. To compare robustness of spectral and time-domain techniques for tracking temporal repolarization instabilities (T-wave alternans, TWA), we used simulated signals with changing heart rate, variable levels of TWA, noise, phase shifts, spurious artifacts, and period-four oscillations. In addition, we compared performances of the inter-beat and intra-beat averaging techniques for tracking dynamics of T-wave alternans. Using the simulated signals and real-life Holter data, we showed that analysis of information both in time and frequency domains combined with control of baseline drifts (surrogate analysis) gives a more reliable estimate of the low-amplitude repolarization dynamics than each of these techniques alone. To summarize, dynamic tracking of low-amplitude repolarization changes in ambulatory recordings is possible during most of the recording time but requires accurate control of baseline wander and stability of isoelectrical segments. Analysis of time-frequency distributions embedded in repolarization dynamics facilitates detection of abrupt and transient repolarization instabilities, including changes in the level of T-wave alternans and slower periodicities.

Ambulatory ECG monitoring of T-Wave alternans for arrhythmia risk assessment

Experimental and clinical studies indicate a basic linkage between T-wave alternans (TWA) and susceptibility to malignant arrhythmias. In a variety of clinical populations with elevated risk of ventricular tachyarrhythmias, Fast Fourier Transform (FFT)-based assessment of TWA during fixed-rate atrial pacing or bicycle ergometry has shown predictive ability for arrhythmic events. However, after more than a decade since the introduction of TWA testing in human subjects, few studies have explored its utility in ambulatory ECG (AECG) recordings. This gap probably relates to major technical obstacles associated with monitoring of ambulatory subjects, including motion artifact and the requirement of data stationarity, which mandates fixing heart rate. To circumvent these difficulties, we devised a time-domain method, "Modified Moving Average Beat Analysis" (MMA) to determine TWA level accurately in freely moving subjects. Recently, MMA analysis was employed to analyze ambulatory ECG (AECG) records of post-myocardial infarction patients who were were at low risk of arrhythmic death. An increased risk of arrhythmic death was predicted by TWA level above the 75th percentile of controls (p<.05). Thus, the predictive power of TWA obtained with MMA analysis from AECG records obtained appears promising.

Ambulatory electrocardiogram-based tracking of T wave alternans in postmyocardial infarction patients to assess risk of cardiac arrest or arrhythmic death

INTRODUCTION

This is the first study to assess T wave alternans (TWA) analyzed from routine ambulatory electrocardiograms (AECGs) to identify postmyocardial infarction (post-MI) patients at increased risk for arrhythmic events.

METHODS AND RESULTS

The new method of modified moving average (MMA) analysis was used to measure TWA magnitude in 24-hour AECGs from ATRAMI, a prospective study of 1,284 post-MI patients. Using a nested case-control approach, we defined cases as patients who experienced cardiac arrest due to documented ventricular fibrillation or arrhythmic death during the follow-up period of 21 +/- 8 months. We analyzed 15 cases and 29 controls matched for sex, age, site of MI, left ventricular ejection fraction, thrombolysis, and beta-blockade therapy. TWA was reported as the maximum 15-second value at three predetermined times associated with cardiovascular stress: maximum heart rate, 8:00 A.M., and maximum ST segment deviation. TWA increased significantly from baseline in both leads at each time point (P <<0.01) in cases and controls. TWA in V5 increased more in cases than controls during peak heart rate (P = 0.005) and at 8:00 A.M. (P = 0.02). A 4- to 7-fold higher odds of life-threatening arrhythmias was predicted by TWA level above the 75th percentile during maximum heart rate in leads V1 (odds ratio [OR] 4.2, 95% confidence interval [CI]: 1.1-16.3, P = 0.04) and V5 (OR 7.9, 95% CI: 1.9-33.1, P = 0.005). TWA at 8:00 A.M. also predicted risk in leads V1 (OR = 5.0, 95% CI: 1.2-20.5, P = 0.02) and V5 (OR = 4.2, 95% CI: 1.1-16.3, P = 0.04).

CONCLUSION

TWA measurement from routine 24-hour AECGs is a promising approach for risk stratification for cardiac arrest and arrhythmic death in relatively low-risk post-MI patients.

Torsade de pointes

Torsade de pointes ventricular tachyarrhythmia in the long QT syndrome is a prime example of how molecular biology, ion channel, and cellular and organ physiology, coupled with clinical observations, promise to be the future paradigm for advancement of medical knowledge. Both the congenital and the acquired long QT syndrome are caused by abnormalities (intrinsic, acquired, or both) of the ionic currents underlying ventricular repolarization. In this review, the continually unraveling molecular biology of congenital long QT syndrome is discussed. The various pharmacologic agents associated with the acquired long QT syndrome are listed. Although it is difficult to predict which patients are at risk for torsade de pointes, careful assessment of the risk to benefit ratio is important before prescribing drugs known to cause QT prolongation. The in vivo electrophysiologic mechanism of torsade de pointes in the long QT syndrome is described, using as a paradigm the anthopleurin-A canine model, a surrogate for LQT3. The characteristic association of torsade de pointes with T-wave alternans and short-long cardiac sequences is discussed, with emphasis on electrophysiologic mechanisms. Finally, the expanding knowledge of genetic mutations other than long QT syndrome associated with polymorphic ventricular tachyarrhythmia is emphasized.