Signal-averaged electrocardiography (SAECG) involves computerized analysis of segments of a standard electrocardiogram (ECG) to detect ventricular late potentials (VLPs). VLPs are thought to be associated with an increased risk for ventricular tachyarrhythmia and sudden cardiac death, particularly in individuals who have had a recent myocardial infarction (MI). Proponents of SAECG claim that the presence of VLPs can be used to identify high-risk individuals who may be candidates for an implanted cardiac defibrillator (ICDs) or other interventions.

Remote algorithmic analysis of electrocardiographic-derived data with computer probability assessment involves analysis of a 2-lead resting ECG from leads II and V5 that is amplified and digitized for computer analysis at a centralized data facility. The digital data is then subjected to a variety of mathematical transformations which are used to generate a severity score between 0 and 20, with a higher score indicating a higher likelihood of myocardial ischemia and coronary artery stenosis. The resulting data is then compared to a reference database to generate a final diagnostic output. An example of this technology is the Multifunction CardioGram^TM (MCG), which was formerly known as Digital Database-Driven Multiphase Functional Electromyocardial Tomography (3DMP^TM/mfEMT^TM) (Premier Heart, LLC, Port Washington, NY).

Note: Please see the following related documents for additional information:

• MED.00041 Microvolt T-Wave Alternans
• SURG.00033 Implantable Cardioverter-Defibrillator (ICD)

Investigational and Not Medically Necessary:

Signal-averaged electrocardiography is considered investigational and not medically necessary for all indications, including, but not limited to:

• use as a technique of risk stratification for arrhythmias after prior myocardial infarction
• evaluation of cardiomyopathy (including risk stratification or diagnosis of arrhythmogenic right ventricular dysplasia [ARVD]

Remote algorithmic analysis of electrocardiographic-derived data with computer probability assessment is considered investigational and not medically necessary for all indications.

Signal-Averaged Electrocardiography (SAECG)

Signal-averaged electrocardiography has been thoroughly studied as a risk stratification tool for potentially fatal arrhythmias in individuals with a previous MI. As reviewed by the Agency for Healthcare Research and Quality (formerly the Agency for HealthCare Policy and Research - AHCPR) in 1998, SAECG is associated with a low positive predictive value ranging from 8%–44%, depending on the population studied (U.S. Dept. of Health/Human Services Health Technology Assessment, 1998). In contrast, the negative predictive value, (i.e., the ability to identify those individuals who will not experience ventricular arrhythmias) ranges from 88%–97%, suggesting that the negative predictive value may be used to identify individuals who would not benefit from antiarrhythmic therapy. However, a key statistic underlying the negative predictive value is the underlying prevalence of the outcome. Although sudden cardiac death is the most common cause of death in the 1-year period after infarction, it is relatively uncommon (2.5% – 11.3%) and declining, due to increasing use of thrombolytic therapy, aspirin, and beta-blockers (Hohnloser, 1999). Thus, given the relatively low incidence of arrhythmias, the high negative predictive value is not surprising.

In 1996, the American College of Cardiology (ACC) published an expert consensus document that concluded SAECG has an established value in the following situations:

• Stratification of risk of development of sustained ventricular arrhythmias in individuals recovering from MI who are in sinus rhythm without electrocardiographic evidence of bundle branch block or intraventricular conduction delay (QRS complex greater than 120 ms); and
• Identification of individuals with ischemic heart disease and unexplained syncope who are likely to have inducible sustained ventricular tachycardia.

Although the consensus was that SAECG was valuable in clinical care for the following, further supportive evidence was necessary:

• Stratification of risk of development of sustained ventricular arrhythmias in individuals with nonischemic cardiomyopathy; (In this category, however, the discussion commented that further supportive evidence was needed before the use of SAECG could be definitely recommended. Also, prospective studies to determine the clinical impact of abnormalities detected in SAECGs in individuals with, among other disorders, arrhythmogenic right ventricular dysplasia, had not yet been performed).
• Assessment of success of operation for sustained ventricular tachycardia (Caine, 1996).

In 2004, the ACC/American Heart Association (AHA) published guidelines on the management of individuals with ST-elevation MI that indicated that, although the negative predictive value of most of these tests (SAECG, 24-hour ambulatory monitoring, heart rate variability, micro T-wave alternans, and T-wave variability) taken in isolation is high, the positive predictive value is unacceptably low. Whereas the positive predictive value of noninvasive testing for future arrhythmic events can be modestly increased by combining several test results, the therapeutic implications of positive findings are unclear (Antman, 2004). In addition, the 2008 ACC/AHA/Heart Rhythm Society (HRS) guideline on device-based therapy of cardiac rhythm abnormalities does not recommend SAECG as an individual selection tool for an ICD (Epstein, 2008). However, regardless of the predictive value of SAECG, the ultimate clinical validation of the test is to determine how it is used in the management of individuals and whether the management decisions result in improved health outcomes. SAECG has been primarily investigated in two settings:

• A risk assessment tool for cardiac arrhythmias to guide primary prevention therapy
• As a diagnostic technique for arrhythmogenic right ventricular dysplasia (ARVD)

A Risk Assessment Tool For Cardiac Arrhythmias To Guide Primary Prevention Therapy
Individuals with congestive heart failure or who have suffered an MI are at risk for subsequent arrhythmias and sudden cardiac death.

Over the past two decades, a large number of randomized clinical trials have evaluated both drug therapy and automatic internal cardiac defibrillator (AICDs) as primary preventive measures in these individuals. These trials have generally used a variety of risk stratification criteria to select participants for intervention. The most relevant studies are those that look at individuals who have not experienced a prior episode of near fatal ventricular arrhythmia or aborted sudden death, as these individuals are already considered candidates for an AICD. As detailed in the discussion below, SAECG has not emerged as a risk-assessment technique that reliably impacts treatment options after an MI.

In the 1990s, research focused on pharmacological suppression of premature ventricular contractions (PVCs) and reduction of the incidence of subsequent sustained and symptomatic arrhythmias. Randomized trials of class I antiarrhythmic drugs (encainide, flecainide, or moricizine) reported that these drugs were associated with an increase in the incidence of arrhythmic death (Toubol, 1999). Research then focused on class III agents which prolong repolarization. The most commonly researched member of this class of drugs was amiodarone. These randomized trials did not use SAECG as a factor for the selection of participants. Furthermore, the trial results did not clearly establish the effectiveness of amiodarone therapy (Cairns, 1997; Julian, 1997).

With the somewhat disappointing results of these drug trials, attention turned toward the use of ICDs as a primary preventive strategy. Several randomized studies have now been completed, but SAECG has not been consistently used as an individual selection factor. Notably, the Multicenter Automatic Defibrillator Implantation Trial (MADIT) recruited participants who were post-MI with left ventricular ejection fraction of less than 35%, non-sustained ventricular tachycardia identified on Holter monitoring or stress test, and inducible, procainide-resistant, sustained ventricular arrhythmia on electrophysiologic (EPS) study (Moss, 1996). The Sudden Cardiac Death- Heart Failure Trial (SCD-HeFT) focused on individuals with congestive heart failure who were randomized to receive conventional therapy plus amiodarone or an AICD (Bardy, 2005). This trial demonstrated that ICDs were associated with a reduction in cardiac mortality. However, SAECG was not used as an individual selection criteria.

As A Diagnostic Technique For Arrhythmogenic Right Ventricular Dysplasia (ARVD)
Arrhythmogenic right ventricular dysplasia (ARVD) is a form of non-ischemic cardiomyopathy. While the presence of late potentials seen on SAECG has been considered one of several "minor diagnostic criteria" by a 1994 international task force (McKenna), it is noteworthy that the 1996 American College of Cardiology (ACC) expert consensus document on SAECG stated that further supportive evidence was needed before it could be definitely recommended in non-ischemic cardiomyopathy. Also, with regard to SAECG abnormalities detected in ARVD, prospective studies to determine the clinical impact of these observations had not yet been performed. In general, the literature suggests late potentials seen on SAECG are present in 50%-80% of individuals with ARVD. Nava and colleagues (2000) found the sensitivity to be 57% in 138 individuals with ARVD, and correlation with the presence of arrhythmias was not close. They concluded SAECG was not helpful in the diagnosis of minor forms of ARVD. Nasir and colleagues (2003) noted a 54% sensitivity and pointed out that there are no accepted guidelines for the optimal cutoff for abnormal SAECGs in ARVD.

However, the literature is inconsistent on the issues of both sensitivity and prognostic value of SAECG, and, in the case of the latter, several authors including Windhagen-Mahnert (2000), Nasir (2003), Attari (2004), and Corrado (2001), found that the predictive value of SAECG for the development of serious ventricular arrhythmias has not been established in ARVD. The sensitivity of SAECG in ARVD would suggest it is not a sufficiently reliable screening or diagnostic tool for individuals with suspected ARVD or for relatives of individuals with known ARVD (a family history is present in 30-70% of cases), since further testing would be required whether SAECG were normal or abnormal in suspected cases.

Summary
Although there has been research interest in SAECG as a risk assessment tool for individuals at risk for cardiac arrhythmias, SAECG has not been incorporated into the pivotal trials of ICD or a primary preventive therapy. Therefore, there is inadequate data to demonstrate how SAECG can be used to direct patient management and improve outcomes. A 2006 ACC/American Heart Association/ESC (European Society of Cardiology) guideline update for the management of individuals with ventricular arrhythmias and the prevention of sudden cardiac death (Zipes, 2006) discusses the use of SAECG for diagnostic and risk stratification of individuals with ventricular arrhythmias who are at risk for life threatening arrhythmias. This guideline provides only Class IIb recommendations for SAECG, which indicates that its usefulness and efficacy are not well established.

The diagnostic and prognostic value of SAECG in ARVD remains unclear therefore, as does how management and treatment decisions, particularly related to antiarrhythmic strategies, would be influenced by SAECG findings. It is also unclear that SAECG would provide clinically useful additional information regarding the diagnosis and risk stratification of individuals with ARVD, over and above the presence of typical ARVD-associated arrhythmias and findings from other forms of testing, (e.g., ECG, echocardiography, Holter monitoring). The impact of SAECG on health outcomes does not appear to have been definitively established for individuals with known or suspected ARVD.

An Agency for Healthcare Research and Quality (AHRQ) technology assessment assessed the use of ECG-based signal analysis technologies for the evaluation of individuals with suspected CAD (AHRQ, 2010). After reviewing clinical and scientific evidence available the assessment concluded:

"There is currently little available evidence that pertains to the utility of ECG-based signal analysis technologies as a diagnostic test among patients at low to intermediate risk of CAD who present in the outpatient setting with the chief complaint of chest pain. The limited evidence that is available demonstrates proof of concept, particularly for the 3DMP and PRIME ECG devices. Further research is needed to better characterize the performance characteristics of these devices to determine in what circumstances, if any, these devices might precede, replace, or add to the standard ECG in test strategies for the diagnosis of CAD in the patient population of interest. The RCT study design is best suited for evaluating the impact that ECG-based signal analysis technologies may have on clinical decision making and patient outcomes, but there are indirect approaches that might be applied to answer these questions."

Algorithmic Analysis of Electrocardiographic-Derived Data with Computer Probability Assessment (Multifunction CardioGram)

The Multifunction CardioGram has been proposed as a technique to improve the sensitivity of a resting ECG to detect coronary artery disease (CAD) and ischemia. As such, the technique could potentially provide a non-invasive and convenient office-based alternative to other anatomic or functional techniques to evaluate CAD, including coronary angiography, stress tests or echocardiography. Additionally, most testing for CAD focuses on its diagnosis in symptomatic individuals. Therefore, there has been interest in developing better prognostic tests for CAD in the much larger group of asymptomatic but at-risk individuals. Published studies of MCG have focused on individuals with known CAD. For example, all studies enrolled individuals scheduled for angiography (Grube, 2008; Grube, 2007; Hosokawa, 2008; Weiss, 2002). No study was identified that focused on the diagnostic and predictive ability of MCG compared to other imaging techniques or prognostic factors. Additionally, there were no studies that focused on how MCG could be used in the management of individuals with different symptoms and risk factors.

Signal-Averaged Electrocardiography (SAECG)

Signal-averaged electrocardiography is a technique involving computerized analysis of small segments of a standard EKG to detect abnormalities, termed VLPs that would be otherwise obscured by background skeletal muscle activity. Ventricular late potentials reflect aberrant, asynchronous electrical impulses arising from viable isolated cardiac muscle bordering an infarcted area and are thought to be responsible for ventricular tachyarrhythmias. Therefore VLPs, as measured by SAECG, have been investigated as a risk factor for arrhythmic events in individuals with a variety of cardiac conditions, including cardiomyopathy and prior history of MI. Individuals considered to be at high risk of ventricular arrhythmias and thus, sudden death, may be treated with drugs to suppress the emergence of arrhythmias or implantable cardiac defibrillators (ICD) to promptly detect and terminate tachyarrhythmias when they occur. Since sudden cardiac death, whether from arrhythmias or pump failure, is one of the most common causes of death after a previous MI, there is intense interest in risk stratification to target therapy. Individuals are divided into those who have not experienced a life-threatening arrhythmia, (i.e., primary prevention) and those who have, (i.e., secondary prevention). Signal-averaged electrocardiography is just one of many diagnostic tests that have been investigated for use in assessment of risk factors. Others include left ventricular ejection fraction, arrhythmias detected on Holter monitor or electrophysiologic studies, heart rate variability, and baroreceptor sensitivity. T-wave alternans is another technique for risk stratification. T-wave alternans measures beat-to-beat variability, while SAECG measures beat-averaged conduction.

Algorithmic Analysis of Electrocardiographic-Derived Data with Computer Probability Assessment (Multifunction CardioGram) 

Multifunction CardioGram represents a diagnostic computer program that is designed to enhance the specificity of resting ECGs to detect coronary artery disease. An ECG device records a 2-lead resting ECG that is amplified and digitized for computer analysis at a centralized data facility. The digital data is then subjected to a variety of mathematical transformations which are used to generate a severity score between 0 and 20, with a higher score indicating a higher likelihood of myocardial ischemia and coronary artery stenosis. The resulting data is then compared to a reference database to generate a final diagnostic output. The reference database is comprised of data from trials conducted between 1978 and 2000 from 30 different institutions. In the preliminary investigation of MCG all diagnoses of coronary artery disease were validated based on expert diagnosticians, laboratory values (i.e. changes in cardiac enzymes) or angiography.

Arrhythmogenic right ventricular dysplasia (ARVD): A genetically-determined heart muscle disease associated with the development of arrhythmia, heart failure and sudden death; the characteristic pathological feature of this condition is the loss of myocardium tissue in the right ventricle with fibro-fatty replacement; individuals may remain asymptomatic until sudden cardiac death occurs as the first clinical manifestation of ARVD.

Tachycardia: A rapid heart rate, especially one above 100 beats per minute in an adult.

Ventricular tachyarrhythmia: Tachycardia that starts in one of the ventricles of the heart; it is a potentially unstable rhythm that may result in fainting, low blood pressure, shock, or sudden death.

The following codes for treatments and procedures applicable to this document are included below for informational purposes.  Inclusion or exclusion of a procedure, diagnosis or device code(s) does not constitute or imply member coverage or provider reimbursement policy.  Please refer to the member's contract benefits in effect at the time of service to determine coverage or non-coverage of these services as it applies to an individual member.

When services are Investigational and Not Medically Necessary:

Peer Reviewed Publications:

1. Attari M, Dhala A. Role of invasive and noninvasive testing in risk stratification of sudden cardiac death in children and young adults: an electrophysiologic perspective. Pediatr Clin North Am. 2004; 51(5):1355-1378.
2. Bauer A, Guzik P, Barthel P, et al. Reduced prognostic power of ventricular late potential in post-infarction patients of the reperfusion era. Eur Heart J. 2005; 26(8):755-761.
3. Cairns JA, Connolly SJ, Roberts R, Gent M. Randomized trial of outcome after myocardial infarction in patients with frequent or repetitive ventricular premature depolarization: CAMIAT. Canadian Amiodarone Myocardial Infarction Arrhythmia Trial Investigators. Lancet. 1997; 349(9053):675-682.
4. Corrado D, Basso C, Nava A, Thiene G. Arrhythmogenic right ventricular cardiomyopathy: current diagnostic and management strategies. Cardiol Rev. 2001; 9(5):259-265.
5. Grimm W, Christ M, Bach J, et al. Noninvasive arrhythmia risk stratification in idiopathic dilated cardiomyopathy: results of the Marburg Cardiomyopathy Study. Circulation. 2003; 108(23):2883-2891.
6. Grube E, Bootsveld A, Buellesfeld L, et al. Computerized two-lead resting ECG analysis for the detection of coronary artery stenosis after coronary revascularization. Int J Med Sci. 2008; 5(2):50-61.
7. Grube E, Bootsveld A, Yuecel S, et al. Computerized two-lead resting ECG analysis for the detection of coronary artery stenosis. Int J Med Sci. 2007; 16; 4(5):249-263.
8. Hosokawa J, Shen JT, Imhoff M. Computerized 2-lead resting ECG analysis for the detection of relevant coronary stenosis in comparison with angiographic findings. Congest Heart Fail. 2008; 14(5):251-260.
9. Julian DG, Camm AJ, Frangin G, et al. Randomized trial of effect of amiodarone on mortality in patients with left ventricular dysfunction after recent myocardial infarction: EMIAT. European Myocardial Infarct Amiodarone Trial Investigators. Lancet. 1997; 439(9053):667-674.
10. McKenna WJ, Thiene G, Nava A, et al. Diagnosis of arrhythmogenic right ventricular dysplasia/cardiomyopathy. Br Heart J. 1994; 71(3):215-218.
11. Moss AJ, Hall WJ, Cannom DS, et al. Improved survival with an implanted defibrillator in patients with coronary disease at high risk for ventricular arrhythmia. Multicenter Automatic Defibrillator Implantation Trial Investigators. N Engl J Med. 1996; 335(26):1933-1940.
12. Moss AJ, Zareba W, Hall WJ, et al. Prophylactic implantation of a defibrillator in patients with myocardial infarction and reduced ejection fraction. N Engl J Med. 2002; 346(12):877-883.
13. Nasir K, Bomma C, Khan FA, et al. Utility of a combined signal-averaged electrocardiogram and QT dispersion algorithm in identifying arrhythmogenic right ventricular dysplasia in patients with tachycardia of right ventricular origin. Am J Cardiol. 2003; 92(1):105-109.
14. Nasir K, Tandri H, Rutberg J, et al. Filtered QRS duration on signal-averaged electrocardiography predicts inducibility of ventricular tachycardia in arrhythmogenic right ventricle dysplasia. Pacing Clin Electrophysiol. 2003; 26(10):1955-1960.
15. Nava A, Folino AF, Bauce B, et al. Signal-averaged electrocardiogram in patients with arrhythmogenic right ventricular cardiomyopathy and ventricular arrhythmias. Eur Heart J. 2000; 21(1):58-65.
16. Sen-Chowdhry S, Lowe MD, Sporton SC, McKenna WJ. Arrhythmogenic right ventricular cardiomyopathy: clinical presentation, diagnosis and management. Am J of Med. 2004; 117(9):685-695.
17. Toubol P. A decade of clinical trials; CAST to AVID. Eur Heart J. 1999; 1(Suppl C):C2-10.
18. Weiss MB, Narasimhadevara SM, Feng GQ, Shen JT. Computer-enhanced frequency-domain and 12-lead electrocardiography accurately detect abnormalities consistent with obstructive and nonobstructive coronary artery disease. Heart Dis. 2002; 4(1):2-12.
19. Windhagen-Mahnert B, Kadish AH. Ventricular arrhythmias: Application of noninvasive and invasive tests for risk assessment in patients with ventricular arrhythmias. Cardiol Clin. 2000; 18(2):243-263.

Government Agency, Medical Society, and other Authoritative Publications:

1. Agency for Healthcare Research and Quality. ECG-based signal analysis technologies. Technology Assessment Report. 2010 May. Project ID CRDD1008. Available at: http://www.ahrq.gov/clinic/techix.htm. Accessed on January 6, 2011.
2. American College of Cardiology. Available at: http://www.cardiosource.org/. Accessed on January 5, 2011.
3. Antman EM, Anbe DT, Armstrong PW, et al. ACC/AHA guidelines for the management of patients with ST-elevation myocardial infarction: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (Committee to Revise the 1999 Guidelines for the Management of Patients With Acute Myocardial Infarction). 2004. Available at: http://www.cardiosource.org/Science-And-Quality/Practice-Guidelines-and-Quality-Standards.aspx. Accessed on January 5, 2011.
4. Cain ME, Anderson JL, Arnsdorf MF, et al. ACC expert consensus document. Signal-averaged electrocardiography. J Am Coll Cardiol. 1996; 27(1):238-249.
5. Epstein AE, DiMarco JP, Ellenbogen KA, et. al. ACC/AHA/HRS 2008 guidelines for device-based therapy of cardiac rhythm abnormalities: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (Writing Committee to Revise the ACC/AHA/NASPE 2002 Guideline Update for Implantation of Cardiac Pacemakers and Antiarrhythmia Devices) Developed in Collaboration With the American Association for Thoracic Surgery and Society of Thoracic Surgeons. 2008. Available at: http://www.cardiosource.org/Science-And-Quality/Practice-Guidelines-and-Quality-Standards.aspx. Accessed on January 5, 2011.
6. Goldberger JJ, Cain FM, Hohnloser SH, et al. AHA/ACC/Heart Rhythm Society Scientific statement on noninvasive risk stratification techniques for identifying patients at risk for sudden cardiac death. J Am Coll Cardiol 2008; 52:1179-1199.
7. Gregoratos G, Cheitlin MD, Conill A, et al. ACC/AHA guidelines for implantation of cardiac pacemakers and antiarrhythmia devices: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (Committee on Pacemaker Implantation). J Am Coll Cardiol. 1998; 31(5);1175-1209.
8. U.S. Department of Health and Human Services. Agency for Healthcare Research and Quality (AHRQ) Health Technology Assessment. Signal-averaged electrocardiography. 1998. Publication No. PB98-137227.
9. Zipes DP, Camm AJ, Borggrefe M, et al. ACC/AHA/ESC 2006 guidelines for management of patients with ventricular arrhythmias and the prevention of sudden cardiac death: a report of the American College of Cardiology/American Heart Association Task Force and the European Society of Cardiology Committee for Practice Guidelines (Writing Committee to develop guidelines for management of patients with ventricular arrhythmias and the prevention of sudden cardiac death). Circ. 2006; 114:1088-1132. Available at: http://www.cardiosource.org/Science-And-Quality/Practice-Guidelines-and-Quality-Standards.aspx. Accessed on January 5, 2011.

1. American Heart Association. Available at: http://www.americanheart.org/presenter.jhtml?identifier=1200000. Accessed on December 20, 2010.

Computerized Electrocardiograph Analysis
Digital Database-Driven Multiphase Electromyocardial Tomography
Electrocardiography, Signal-Averaged
Multifunction CardioGram™ MCG
SAECG
Signal-Averaged Electrocardiography
3DMP/mfEMT