Journal of Electrocardiology
Volume 42, Issue 6 , Pages 511-516, November 2009

The many faces of repolarization instability: which one is prognostic?

  • Vladimir Shusterman, MD, PhD

      Affiliations

    • University of Pittsburgh, Pittsburgh, PA, USA
    • PinMed, Inc., Pittsburgh, PA, USA
    • Corresponding Author InformationCorresponding author. University of Pittsburgh, 200 Lothrop Street, Room B535, Pittsburgh, PA 15213, USA.
    • ,
  • Rachel Lampert, MD

      Affiliations

    • Yale University, New Haven, CT, USA
    • ,
  • Barry London, MD, PhD

      Affiliations

    • University of Pittsburgh, Pittsburgh, PA, USA

Received 21 April 2009 published online 31 August 2009.

Article Outline

Abstract 

Instabilities of the STT segment's magnitude, and particularly the 0.5 beat/cycle oscillations (T-wave alternans, or TWA), have been linked to the heightened risk of ventricular tachyarrhythmias (VTA) and sudden cardiac death (SCD). During the last decade theoretical, experimental and clinical research efforts have focused primarily on TWA, examining its mechanisms and predictive value using time-invariant cutoff values. However, recent evidence suggests that such a single-snapshot test of a single-frequency (TWA) oscillation using a constant cutoff value might be suboptimal for risk stratification because of several reasons.

First, it is well known that the risk of VTA/SCD evolves over time with changes in electrophysiologic substrate, environmental and physiologic triggers, and the impact of other physiologic (eg, circadian) rhythmicity. Hence, the outcome of TWA testing might depend on the time of day, as Holter-based TWA studies have demonstrated. Furthermore, currently used single-snapshot testing with a binary cutoff value may not coincide with the periods of heightened risk for VTA/SCD and may not yield prognostic information, as a recent TWA substudy of the sudden cardiac death in heart failure trial has showed. Second, the analysis focused on TWA alone ignores the existence of multiple (alternating and nonalternating) forms of repolarization instability that have been shown to arise or increase before the onset of VTA/SCD.

Summarizing, recent studies have identified multiple forms of repolarization instabilities modulated by distinct mechanisms, which might have different prognostic values. Therefore, the assessment of TWA needs to be dynamic and personalized to take into account the time evolution of risk and individual history.

Keywords: Repolarization instability, T-wave alternans, Ventricular tachyarrhythmias, Sudden cardiac death

 

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Introduction 

Beat-to-beat alterations of the electrocardiographic repolarization segment have long been recognized as a marker of increased risk for ventricular tachyarrhythmias and sudden cardiac death (SCD).1 During the last decade, remarkable progress has been made in this knowledge area. A number of theoretical, experimental, and clinical studies have provided a wealth of evidence linking the 0.5 cycle/beat oscillations in the amplitude of the STT segment, referred to as the T-wave alternans (TWA), to the heightened risk of ventricular tachyarrhythmia (VTA).2, 3 Moreover, the repolarization instability has been shown to have a direct pathophysiologic connection with the initiation of arrhythmias.4 As a result of these multidisciplinary research efforts, T-wave alternans testing has become a clinical tool for arrhythmia risk stratification.5 Recently, an increase in T-wave alternans has been reported preceding the imminent onset of VTA in several animal models6 and clinical studies conducted in patients with structural heart disease, suggesting that the utility of TWA might be further extended to serve as a short-term predictor of these life-threatening events.7, 8

However, recent evidence suggests that currently used single-snapshot testing of a single-frequency (0.5 cycle/beat) oscillation using a one-size-fits-all cutoff value might be suboptimal for risk stratification because of several reasons. First, the underlying assumption that both T-wave alternans and the risk of arrhythmias do not change over time is oversimplified.9, 10 T-wave alternans has been shown to exhibit circadian changes, peaking in the morning and declining at night.11 Thus, the outcome of TWA testing is likely to be different if the testing is done at different times of day. Furthermore, the risk of arrhythmias and sudden death also evolves over longer time scales as well, following the changes in the underlying electrophysiologic substrate. In particular, a recent sudden cardiac death in heart failure trial has failed to show that T-wave alternans predicts arrhythmic events or mortality in patients with heart failure (n = 490, ischemic heart disease in 49% of subjects, left ventricular ejection fraction of 25%) but showed that its prognostic significance gradually evolves over 15- to 30-month time scale with the progression of changes in the underlying heart disease.9, 10 This provides further support for the notion that currently used single-snapshot testing may not coincide with the periods of heightened risk for VTA/SCD and may not yield prognostic information. In addition, the analysis focused on TWA alone ignores the existence of multiple forms of repolarization instability that have been shown to arise or increase before the onset of VTA/SCD both in patients with cardiomyopathy7 and those with long-QT syndrome.12 Analysis of such instabilities may provide complementary information that may help to improve the risk assessment with respect to arrhythmias and sudden death.

To clarify the predictive value of T-wave alternans and other forms of repolarization instability, one needs to determine the physiologic covariates and their respective weights, modulating the relationship between the instability and arrhythmogenesis (Fig. 1).

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The restitution covariate 

The restitution curve, that is, the relationship between the cardiac electrical action-potential duration (APD) and a preceding diastolic interval (DI), has been introduced by Nolasco and Dahlen.13 In their seminal study conducted in the frog ventricular muscle strips more than 40 years ago, the researchers noticed striking similarities between the cardiac APD/DI relationship and a simple electronic amplifier with a negative feedback. In such an electronic system, if G is a gain function, I is an input, F is a fraction of an output O, and X is an independent signal, then the output is O = G(I) and I = X − F(O). Similarly, the transfer functions for the cardiac tissue paced at the cycle length (CL) can be expressed as: APD1 = f(DI0) and DI1 = f(APD1) = CL1 − APD1.13

Assuming that an APD depends only on the preceding DI (a “no-memory” assumption), the relationship between the 2 variables can be expressed by a nonlinear curve resembling a logarithmic function. If the pacing CL is kept constant, then d(DI)1/d(APD) = −1, and a simple 1-dimensional, iterative map, referred to as the cobweb, can be used to examine this nonlinear system's dynamics. It is not difficult to show that the slope of the curve defining the relationship between APD and DI determines the stability of this dynamical system.13 In particular, if the slope is between 0 and 1, the system is stable, and a small perturbation δ would produce damped oscillations (transients) that will return to the equilibrium (steady state). In contrast, if the slope is more than 1, a small perturbation would lead to an ever-growing oscillation (underdamping). And if the slope of the APD curve is exactly equal to 1, then the system is bistable, producing sustained, period-2 oscillations (ie, alternans).13, 14

This method provides an intuitive tool for tracking the nonlinear dynamics of the cardiac electrical activity at the expense of several important simplifications. First, it assumes that an APD depends only on a single DI, which is not realistic for cardiac myocytes. It has been shown by several investigators that an APD strongly depends on a much longer (at least 60 seconds) history of CL, which can be better approximated by 1 or 2 exponential functions.15, 16 Second, the simplified, restitution-only approach also ignores the inverse relationship between conduction velocity and CL, which plays a crucial role in cardiac physiology and may become compromised in heart failure.17, 18 Finally, this method disregards the impact of Ca2+ handing and several other important covariates (discussed later in this article), and as expected, several recent studies have showed that this theoretical construct, taken alone, fails to predict T-wave alternans or arrhythmias in clinical settings.19 Nevertheless, the restitution-based approach has proved useful in several settings, where fast pacing protocols could be used to achieve a relatively short CL (Fig. 2, A), while all other covariates are kept constant.13, 20, 21

A recent analysis of the spatial distribution of the restitution curves in different regions of the human heart has showed a wide spectrum of results.22 This spatial heterogeneity suggests that the analysis needs to be extended from a single restitution curve to the entire spatial distribution of the curves in different regions of the heart. Furthermore, the restitution-based approach can also be extended from a “memoryless” APD, which depends on a single DI, to an APD, which has “memory” of a longer history of cardiac beats.23 Yet, the recently proposed theoretical constructs incorporating such a memory still could not provide an accurate approximation of the real-life dynamical behavior of the cardiac electrophysiologic parameters.23 This implicitly suggests the importance of other physiologic covariates that remain unaccounted for by the restitution-only based approach.

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The calcium covariate 

The Ca2+-related mechanisms play a pivotal role in the excitation-contraction coupling, and L-type Ca2+ channels also determine a key ionic current that is active during the plateau phase of cardiac repolarization. In the course of the development of heart failure, calcium handling becomes compromised, including decreased peak systolic Ca2+, elevated diastolic Ca2+, and prolongation of the Ca2+ transient.18 In humans with heart failure, these changes are associated with the decreased expression of the sarco(endo)plasmic reticulum Ca2+-ATPase, decreases in phospholamban, and increased expression of the Na/Ca exchanger.24 The resulting prolongation of the Ca2+ transient and intracellular Ca2+ overload can lead to premature Ca2+ release from the sarcoplasmic reticulum and delayed afterdepolarizations.18 As a result, the Ca2+ alternans can often emerge at near-normal heart rates, giving rise to APD-alternans and T-wave alternans (Fig. 2, B). In particular, our group has demonstrated pronounced alternans (alternation of up to 40% of the peak amplitude of the Ca2+ transient) in a tumor necrosis factor α (TNF-α) genetic mouse model of heart failure, using optical mapping of Ca2+ in isolated, Langendorff-perfused hearts.18 In this model, the Ca2+ alternans was found at relatively long pacing CLs. Furthermore, changes in the Ca2+ concentration affected arrhythmia inducibility in this genetic mouse model, confirming the essential role of abnormal calcium handling in the mechanism of arrhythmogenesis.18 Similarly, Wilson et al25 has recently reported that Ca2+ alternans was the driving force generating action-potential alternans at slow heart rates in a canine heart-failure wedge preparation.

Of note, repolarization alternans associated with Ca2+ alternans has been also observed in pharmacologically induced long-QT syndrome in arterially perfused canine left ventricular wedge preparations (Fig. 2, C).26

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The adrenergic covariate 

It has long been recognized that sympathetic nervous system activity modulates the magnitude of repolarization instability. In a canine model of ischemia, Nearing et al27 have shown that modifications of the stellate ganglion activity directly affect the level of T-wave alternans. In contrast, β-adrenergic blockade has been shown to suppress the magnitude of T-wave alternans in humans with ischemic cardiomyopathy and left ventricular ejection fraction of less than 40%.28 Further support for the role of autonomic activity in the emergence of T-wave alternans has been provided by the observations of circadian changes in the magnitude of T-wave alternans in Holter recordings obtained from patients with a prior myocardial infarction (Fig. 2, F).11 Mental stress in humans with implantable devices has been shown to exacerbate the level of T-wave alternans, and the magnitude of the increase in T-wave alternans was strongly correlated with the level of norepinephrine and the incidence of arrhythmic events in a 2-year follow-up (Fig. 2, E).29, 30, 31

The mechanisms by which adrenergic stimulation promotes repolarization alternans may involve additional influx of Ca2+ into the myocytes, overloading the calcium-handling cascades, which are chronically impaired in heart failure.32, 33 In particular, it is likely that Ca2+ alternans and impaired Ca2+ handling are the driving forces behind the emergence of T-wave alternans with β-adrenergic stimulation in our studies of the TNF-α genetic mouse model of heart failure because Ca2+ alternans play a pivotal role in the mechanisms of repolarization instability and arrhythmias accompanying development of heart failure in these animals.34

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The conduction velocity covariate 

The inverse relationship between the conduction velocity and basic CL is well documented.17 This relationship plays a particularly important role at short CL, and conduction-velocity alternans have been observed at faster heart rates, during various types of a narrow-QRS tachycardia.35 Preferential conduction slowing at short pacing CLs (CL< 80 milliseconds) has been also observed in a TNF-α genetic mouse model of heart failure, suggesting that impaired adaptation of the conduction system to faster heart rates may contribute to the emergence of alternans in the setting of heart failure (Fig. 2, D).18

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Other physiologic covariates 

In addition to the L-type Ca2+ channels, an incomplete recovery, temporal instability, or heterogeneous distribution of other ionic currents, which are active during repolarization, may also lead to the emergence of repolarization instability. Indeed, a number of intracellular processes, including modifications of repolarizing potassium currents (IKr) and changes in excitability, have been implicated in the mechanisms of repolarization instability.4, 36, 37 We note also that functional changes in the repolarizing ionic channels, including diminished repolarizing K+ currents (Ito and IK1), have been documented in heart failure, suggesting possible involvement of these channels (in addition to the Ca2+-related mechanisms discussed earlier) in the emergence of instabilities in this setting.18

Adding to the complexity of the “repolarization-instability” conundrum, the alternans has been also reported in association with pharmacologically induced Brugada syndrome in the right ventricular canine tissue (Fig. 2, G). In contrast to the other settings described above, the alternans occurred at slow pacing rates and disappeared when the pacing accelerated. The presumable mechanism of this instability includes the alternating INa causing alternations in Ito and L-type Ca2+ currents in the right ventricular epicardium.38

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Discerning the impact of physiologic covariates in real-life data 

Summarizing, the results of clinical, experimental, and theoretical studies have provided a wealth of evidence supporting statistical and mechanistic links between the occurrence of repolarization instability and arrhythmias. The notion that the measurement of repolarization instability may provide important diagnostic and prognostic information for the arrhythmia risk assessment has become well recognized.1, 2, 5, 7, 8, 9, 11, 31

Several clinical trials have confirmed the predictive value of T-wave alternans,1, 2, 11, 31 whereas other trials have failed to demonstrate a strong predictive value.10 The inconsistencies most likely arise from the differences in the underlying physiologic mechanisms driving the instabilities in different settings, leading to a common end point from a multitude of subcellular, intracellular, and multicellular processes (Fig. 1). Thus, a better understanding of these physiologic covariates, along with the measurement caveats,39 is needed for improving the accuracy of arrhythmia risk assessment.

In a real-life setting, electrophysiologic data are usually collected at the time when at least some of the covariates exhibit simultaneous changes. Thus, the algorithms are needed to differentiate the respective impacts and weights of each participating covariate. Fig. 2 shows one possible algorithm that allows, to a first approximation, determine the relative weights of the primary physiologic covariates. We view the flow chart in Fig. 2 as a working hypothesis guiding our ongoing studies. More experimental and clinical data will be needed to determine the quantitative weight of each covariate and refine the probabilities of transition from one mechanism to another. We note, however, that the flow chart might fail when all covariates have similar weights, making it difficult to discern predominant, major effects. The practical implementation and testing of this algorithm will require continuous or serial tracking of individual repolarization dynamics, along with other electrophysiologic parameters, including changes in heart rate, QRS duration, circadian variability, physical activity, and psychological status.11, 31 The improvement can also be achieved by tracking the changes against the individual's baseline and using “personalized” (ie, individually tailored) pattern recognition analysis.7, 39, 40

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Acknowledgment 

The project was supported in part by National Institutes of Health National Heart, Lung, and Blood Institute grants R44HL077116 (Dr Shusterman) and R01 HL62300 (Dr London), and American Heart Association Established Investigator Award (Dr. London).

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References 

  1. Rosenbaum DS, Jackson LE, Smith JM, Garan H, Ruskin JN, Cohen RJ. Electrical alternans and vulnerability to ventricular arrhythmias. N Engl J Med. 1994;330:235
  2. Rosenbaum DS, Albrecht P, Cohen RJ. Predicting sudden cardiac death from T wave alternans of the surface electrocardiogram: promise and pitfalls. J Cardiovasc Electrophysiol. 1996;7:1095
  3. Jordan PN, Christini DJ. Characterizing the contribution of voltage- and calcium-dependent coupling to action potential stability: implications for repolarization alternans. Am J Physiol Heart Circ Physiol. 2007;293:H2109
  4. Armoundas AA, Tomaselli GF, Esperer HD. Pathophysiological basis and clinical application of T-wave alternans. J Am Coll Cardiol. 2002;40:207
  5. Costantini O, Hohnloser SH, Kirk MM, et al. The ABCD (Alternans Before Cardioverter Defibrillator) Trial: strategies using T-wave alternans to improve efficiency of sudden cardiac death prevention. J Am Coll Cardiol. 2009;53:471
  6. Nearing BD, Verrier RL. Progressive increases in complexity of T-wave oscillations herald ischemia-induced ventricular fibrillation. Circ Res. 2002;91:727
  7. Shusterman V, Goldberg A, London B. Upsurge in T-wave alternans and nonalternating repolarization instability precedes spontaneous initiation of ventricular tachyarrhythmias in humans. Circulation. 2006;113:2880
  8. Swerdlow CD, Zhou X, Voroshilovsky O, Abeyratne A, Gillberg J. High amplitude T-wave alternans precedes spontaneous ventricular tachycardia or fibrillation in ICD electrograms. Heart Rhythm. 2008;5:670
  9. Rosenbaum DS. T-wave alternans in the sudden cardiac death in heart failure trial population: signal or noise?. Circulation. 2008;118:2015
  10. Gold MR, Ip JH, Costantini O, et al. Role of microvolt T-wave alternans in assessment of arrhythmia vulnerability among patients with heart failure and systolic dysfunction: primary results from the T-Wave Alternans Sudden Cardiac Death in Heart Failure Trial Substudy. Circulation. 2008;118:2022
  11. Verrier RL, Nearing BD, La Rovere MT, et al. Ambulatory electrocardiogram-based tracking of T wave alternans in postmyocardial infarction patients to assess risk of cardiac arrest or arrhythmic death. J Cardiovasc Electrophysiol. 2003;14:705
  12. Nemec J, Buncová M, Shusterman V, Winter B, Shen WK, Ackerman MJ. QT interval variability and adaptation to heart rate changes in patients with long QT syndrome. Pacing Clin Electrophysiol. 2009;32:72
  13. Nolasco JB, Dahlen RW. A graphic method for the study of alternation in cardiac action potentials. J Appl Physiol. 1968;25:191
  14. Weiss JN, Karma A, Shiferaw Y, Chen PS, Garfinkel A, Qu Z. From pulsus to pulseless: the saga of cardiac alternans. Circ Res. 2006;98:1244
  15. Elharrar V, Atarashi H, Surawicz B. Cycle length-dependent action potential duration in canine cardiac Purkinje fibers. Am J Physiol. 1984;247(6 Pt 2):H936
  16. Lux RL, Hilbel T, Brockmeier K. Electrocardiographic measures of repolarization revisited: why? what? how?. J Electrocardiol. 2001;34:259
  17. Cherry EM, Fenton FH. Suppression of alternans and conduction blocks despite steep APD restitution: electrotonic, memory, and conduction velocity restitution effects. Am J Physiol Heart Circ Physiol. 2004;286:2332
  18. London B, Baker LC, Lee JS, et al. Calcium-dependent arrhythmias in transgenic mice with heart failure. Am J Physiol Heart Circ Physiol. 2003;284:H431
  19. Narayan SM, Franz MR, Lalani G, Kim J, Sastry A. T-wave alternans, restitution of human action potential duration, and outcome. J Am Coll Cardiol. 2007;50:2385
  20. Garfinkel A, Kim YH, Voroshilovsky O, et al. Preventing ventricular fibrillation by flattening cardiac restitution. PNAS. 2000;97:6061
  21. Koller ML, Maier SKG, Gelzer AR, Bauer WR, Meesmann M, Gilmour RF. Altered dynamics of action potential restitution and alternans in humans with structural heart disease. Circulation. 2005;112:1542
  22. Nash MP, Bradley CP, Sutton PM, et al. Whole heart action potential duration restitution properties in cardiac patients: a combined clinical and modelling study. Exp Physiol. 2006;91:339
  23. Kalb SS, Dobrovolny HM, Tolkacheva EG, Idriss SF, Krassowska W, Gauthier DJ. The restitution portrait: a new method for investigating rate-dependent restitution. J Cardiovasc Electrophysiol. 2004;15:698
  24. Arai M, Alpert NR, MacLennan DH, Barton P, Periasamy M. Alterations in sarcoplasmic reticulum gene expression in human heart failure: a possible mechanism for alterations in systolic and diastolic properties of the failing myocardium. Circ Res. 1993;72:463
  25. Wilson LD, Jeyaraj D, Wan X, et al. Heart failure enhances susceptibility to arrhythmogenic cardiac alternans. Heart Rhythm. 2009;6:251
  26. Shimizu W, Antzelevitch C. Cellular and ionic basis for t-wave alternans under long-QT conditions. Circulation. 1999;99:1499
  27. Nearing BD, Huang AH, Verrier RL. Dynamic tracking of cardiac vulnerability by complex demodulation of the T wave. Science. 1991;252:437
  28. Rashba EJ, Cooklin M, MacMurdy K, et al. Effects of selective autonomic blockade on T-wave alternans in humans. Circulation. 2002;105:837
  29. Kop WJ, Krantz DS, Nearing BD, et al. Effects of acute mental stress and exercise on t-wave alternans in patients with implantable cardioverter defibrillators and controls. Circulation. 2004;109:1864
  30. Lampert R, Shusterman V, Burg MM, et al. Effects of psychologic stress on repolarization and relationship to autonomic and hemodynamic factors. J Cardiovasc Electrophysiol. 2005;16:372
  31. Lampert R, Shusterman V, Burg M, et al. Anger-induced T-wave alternans predicts future ventricular arrhythmias in patients with implantable cardioverter-defibrillators. J Am Coll Cardiol. 2009;53:774
  32. Jin YT, Hasebe N, Matsusaka T, et al. Magnesium attenuates isoproterenol-induced acute cardiac dysfunction and β-adrenergic desensitization. Am J Physiol Heart Circ Physiol. 2007;292:H1593
  33. Chatelain P, Laruel A, Beaufort P, Meysmans L, Clinet M. Prevention of calcium overload and down-regulation of calcium channels in rat heart by SR 33557, a novel calcium entry blocker. Cardioscience. 1992;3:117
  34. Shusterman V, Goldberg A, London B. Adrenergic stimulation promotes T-wave alternans in a TNF-α genetic mouse model of congestive heart failure. Heart Rhythm. 2005;2:S142
  35. Morady F, DiCarlo LA, Baerman JM, de Buitleir M, Kou WH. Determinants of QRS alternans during narrow QRS tachycardia. J Am Coll Cardiol. 1987;9:489
  36. Hua F, Gilmour RF. Contribution of IKr to rate-dependent action potential dynamics in canine endocardium. Circ Res. 2004;94:810
  37. O'Rourke B, Ramza BM, Marban E. Oscillations of membrane current and excitability driven by metabolic oscillations in heart cells. Science. 1994;265:962
  38. Morita H, Zipes DP, Lopshire J, Morita ST, Wu J. T wave alternans in an in vitro canine tissue model of Brugada syndrome. Am J Physiol Heart Circ Physiol. 2006;291:421
  39. Shusterman V, Goldberg A. Tracking repolarization dynamics in real-life data. J Electrocardiol. 2004;37:180
  40. Shusterman V, Aysin B, Anderson KP, Beigel A. Multidimensional rhythm disturbances as a precursor of sustained ventricular tachyarrhythmias. Circ Res. 2001;88(Suppl):705

PII: S0022-0736(09)00253-2

doi:10.1016/j.jelectrocard.2009.06.008

Journal of Electrocardiology
Volume 42, Issue 6 , Pages 511-516, November 2009

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