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 Table of Contents  
PERSPECTIVE
Year : 2016  |  Volume : 1  |  Issue : 1  |  Page : 24-32

Risk Stratification of Sudden Cardiac Death: A Multi-racial Perspective


Division of Cardiology, Medical University of South Carolina, Charleston, South Carolina, USA

Date of Web Publication30-Sep-2016

Correspondence Address:
Jr Michael R Gold
Medical University of South Carolina, 114, Doughty Street, MSC 592, Charleston, South Carolina 29425-5920
USA
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/2352-4197.191479

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  Abstract 

Sudden cardiac death (SCD) is the leading cause of cardiovascular mortality and a major international health problem, with an estimated 3.7 million deaths occurring annually, accounting for approximately 15%–20% of all deaths worldwide. The implantable cardiac defibrillator (ICD) is an effective treatment of SCD and has had a major impact on outcomes. However, this therapy has been largely used in patients with left ventricular dysfunction. A changing epidemiology of SCD with fewer patients having marked reductions in left ventricular ejection fraction (LVEF) has renewed the focus on identifying other high risk populations. This article summarizes the current understanding of the diverse clinical, genetic, racial, electrocardiographic and imaging techniques available to detect patients most at risk. Despite many identified risk factors, no single predictor has been shown to have sufficient predictive value to be used to guide preventative therapy and reduce mortality. More recent effort has been directed towards combining markers to define a risk profile for identifying high risk cohorts.

Keywords: Implantable cardioverter defibrillator, left ventricular ejection fraction, risk stratification, sudden cardiac death


How to cite this article:
Abtahi DM, Kpaeyeh JA, Gold MR. Risk Stratification of Sudden Cardiac Death: A Multi-racial Perspective. Int J Heart Rhythm 2016;1:24-32

How to cite this URL:
Abtahi DM, Kpaeyeh JA, Gold MR. Risk Stratification of Sudden Cardiac Death: A Multi-racial Perspective. Int J Heart Rhythm [serial online] 2016 [cited 2023 Jun 5];1:24-32. Available from: https://www.ijhronline.org/text.asp?2016/1/1/24/191479


  Introduction Top


Sudden cardiac death (SCD) is most commonly defined as death from unexpected circulatory arrest occurring within an hour of the onset of symptoms or during sleep.[1] Worldwide, SCD accounts for around 3.7 million deaths annually or about 6% of deaths.[2] In the majority of cases, SCD is triggered by an arrhythmic event, most frequently ventricular tachycardia degenerating to ventricular fibrillation and asystole; however, more recently, pulseless electrical activity has been noted more frequently.

The leading cause of death in the United States, according to the Centers for Disease Control and Prevention, is cardiovascular disease (611,000 deaths annually).[3] Despite a dramatic decline in mortality from heart disease over the past 30 years, SCD remains the leading cause of cardiovascular death with more than 50% or greater than 300,000 deaths occurring in the United States annually and approximately half of these cases occurring without any known prior cardiac disease.[3],[4] Even this may be an underestimation, as the majority of patients who suffer out of hospital cardiac arrest never survive the initial event.[3] The US and Europe have the highest annual incidence of SCD ranging from 50 – 100 per 100,000 persons however in Asia the annual incidence remains high with an estimated 40 per 100,000.[5]

In order to reduce the burden of SCD, much effort has been directed to identify and better treat those at higher risk. It is well described that underlying structural heart disease in the context of ischemia, systolic heart failure and fibrosis often trigger sustained arrhythmias that may lead to cardiovascular collapse and death. However, a broad range of at risk populations for SCD exists, including patients with family history of coronary artery disease, heart failure with reduced ejection fraction (HFrEF), ambient ventricular arrhythmia (PVC, non-sustained ventricular tachycardia (VT), sustained VT), prior cardiac arrest, advanced age, male sex, African race, left ventricular hypertrophy, congenital heart disease, and cardiac conduction abnormalities, such as bundle branch block. Additionally, patients with underlying channelopathies, including long QT syndrome and Brugada syndrome as well as other myopathies, for example arrhythmogenic right ventricular cardiomyopathy and hypertrophic cardiomyopathy, present differently than those with traditional risk from ischemic and non-ischemic cardiomyopathies. Various electrical markers may predict SCD including T-wave alternans, late potentials on signal averaged electrocardiography, inducibility of sustained tachyarrhythmia by programmed electrical stimulation, prolonged QRS and QT intervals, and/or abnormal heart rate variability or turbulence and abnormal baroreflex sensitivity. Additionally, there are further co-morbidities that contribute to and complicate risk stratification including smoking, hypertension, hyperlipidemia, obesity, diabetes mellitus, renal failure, drug abuse, and congenital heart disease. Finally, life style and social factors play a predictive role including activity levels, socioeconomic status, as well as stress (emotional or physical).[1],[6]

A series of large, multicenter randomized trials demonstrated the benefit of the implantable cardioverter defibrillators (ICD) for preventing sudden death in selected populations.[7],[8],[9] This led to a rapid expansion of this therapy, which has likely contributed to a significant decline in incidence of ventricular fibrillation [3],[10],[11] and deaths [10] during out of hospital cardiac arrest. Due to this success and the changing epidemiology of SCD, there has been a renewed focus on risk stratification in this population.[4],[12] However, despite advances in our understanding, SCD remains a significant problem primarily because of the complexity and diversity of disease states resulting in a lack of a comprehensive and validated approach to detecting high risk patients. The major risk factors evaluated are presented in [Table 1] and will be summarized here.
Table 1: Summary of risk stratification tools for sudden cardiac death

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  Demographics Top


Despite the variability in mechanism and the broad spectrum of heritability of SCD there are observed differences across populations. SCD increases with age and men have a higher incidence of SCD than women.[13] Women, however, are more successfully resuscitated from shockable rhythms. When comparing race differences in the United States, African American men and women have a two-fold higher incidence than their Caucasian counterparts, as noted in the Oregon Sudden Unexpected Death Study (Oregon UDS).[14] Interestingly, ischemic burden in African Americans, who underwent autopsies, is lower than would be expected for the significantly increased risk seen.[14] These findings, supported by older studies, have been attributed to socioeconomic and genetic differences. Hispanic Americans have lower rates of SCD than non-Hispanic populations despite higher prevalence of cardiac risk factors.[15] Additionally, Asian Americans are noted to have the lowest incidence of SCD [16] [Figure 1] and population studies in Asia report an overall lower incidence of SCD than in the United States and Europe.
Figure 1: Sudden cardiac death in the United States, 1989 to 1998. Age-adjusted death rates (per 100,000 US population) for sudden cardiac death among men aged 35 years and older by race in the US from 1989 to 1990 (Reproduced with permission from Zheng et al.[18]).

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The leading cause of SCD worldwide is myocardial infarction (MI); however, the proportion of ischemic heart disease associated with SCD is believed to be lower in Asian countries (50% in Japan) as compared to the United States and Europe (75%).[17] In a retrospective Japanese study, patients who met MADIT II criteria for ICD implantation but did not receive an ICD had similar survival rates compared to the MADIT II defibrillator group but improved survival as compared to the conventional therapy group, suggesting a lower prevalence of SCD in this Japanese population.[18] However, a retrospective study of the mainland of China and Hong Kong (China) patients, suggests the opposite, with lower survival than the MADIT II defibrillator group.[19] Another recent study showed that Asian race was an independent predictor of SCD after acute coronary syndrome.[20] Though Asian populations have a trend towards lower prevalence of ischemic disease causing SCD, the discrepancy between these studies points out our limited understanding currently, as there is likely significant variation between different represented groups within the Asian population. This may be due in part to bias in the reporting between different countries as the epidemiologic oversight is variable. In addition, the risk of SCD associated with ischemic heart disease may be higher even if the prevalence of coronary artery disease is lower.

Finally, the prevalence of inherited arrhythmia syndromes causing SCD is higher in Asian countries (10% in Japan) than in the United States and Europe (1%–2%)[21] [Figure 2]. Despite the higher prevalence, SCD event rates in Asian patients appear similar to or less than in Western patients.[22]
Figure 2: The spectrum of epidemiology underlying sudden cardiac death. Causes of sudden cardiac death (SCD) and rates (a) and age of SCD onset in each disease (b). A, Coronary heart disease is the leading cause of SCD, but the rates of baseline heart disease differ between Western countries and Japan. B, SCDs occur in elderly populations in coronary heart disease and valvular disease, whereas most SCDs in catecholaminergic polymorphic ventricular tachycardia (CPVT) and long-.QT syndrome (LQTS) develop at age <35 years. ARVC indicates arrhythmogenic right ventricular cardiomyopathy; BrS, Brugada syndrome; ERS, early repolarization syndrome; HCM, hypertrophic cardiomyopathy; NIDCM, non-.ischemic dilated cardiomyopathy; and PUFA, polyunsaturated fatty acids. (Reproduced with permission from Hayashi et al.[21]

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  Genetics and Genomics Top


Multiple population based studies exist suggesting a strong genetic contribution to individual SCD risk, independent of traditional cardiovascular risk factors. The landmark Paris Prospective Study showed increased risk of SCD in middle aged men with parental sudden death.[23] Similarly, the Seattle case-controlled study, demonstrated increased risk of SCD among patients with a parental history of early onset sudden death (age <65 years).[24] Additionally, family history of sudden death has been shown to be an independent risk factor for primary ventricular fibrillation in acute myocardial infarction,[25] the leading pathogenic mechanism of SCD. Despite multiple studies demonstrating a strong association between family history and SCD, there has yet to be a specific genetic variant or clinical marker identified that has proven effective in predicting individual risk.

In individuals under 40 years of age, SCD occurs in a Mendelian pattern with cardiomyopathies and electrical disorders being the most prevalent.[26] In individuals above 40 years old, which account for the majority of events, SCD is most commonly caused by ventricular fibrillation in the setting of acute or prior myocardial infarction. To attain a better understanding, genome-wide association studies (GWAS) are now being performed to isolate genetic variants modulating SCD risk, with specific interest in genes that play a role in structural abnormalities, as well as heart rate and ECG indices of slowed conduction and abnormal repolarization.[26],[27],[28],[29],[30]

GWAS use dense maps of hundreds of thousands of single nucleotide polymorphism (SNP) arrays to identify genotype patterns associated with a particular phenotype,[26] in this case SCD. GWAS holds future promise as costs decrease and gene-scanning technologies improve.

Multiple gene polymorphisms have been implicated in the racial variation seen in the risk of SCD. One of the most significant allele mutations found to be higher in African American, West Africans and Caribbeans is the Y1102 mutation in the cardiac sodium channel (SCN5A).[31],[32] In Caucasians, mutations in the beta 2 adrenergic receptor has been of interest as a risk factor for SCD.[32] Asians who have a higher incidence of SCD related to arrhythmogenic syndromes have high rates of mutations in SCN5A associated with Brugada syndrome, RYR2 in catecholaminergic polymorphic ventricular tachycardia (CPVT) and KCNQ1 in congenital long QT syndrome.[33]

Though an increasing number of genetic variants are starting to be uncovered with strong associations [34],[35] for SCD, this approach remains limited in clinical applicability at this time due to small sample size.


  Left Ventricular Ejection Fraction Top


Left ventricular systolic function, estimated by ejection fraction (LVEF), is the most common studied marker of SCD risk, and it is clearly a powerful predictor of cardiac mortality.[36],[37],[38] LVEF is easy to measure, reproducible and predictive in both ischemic and non-ischemic cardiomyopathies. In clinical practice, LVEF has become the primary criterion used for ICD placement. The MADIT II trial demonstrated a significant reduction in SCD and all-cause mortality after ICD placement among patients with previous myocardial infarction and LVEF ≤30%.[39] The SCD-HeFT trial demonstrated decreased all-cause and sudden death mortality after ICD placement in patients with both ischemic and non-ischemic cardiomyopathy, NYHA class II or III functional status and LVEF ≤35%.[9] However, not all studies show a benefit of ICDs among patients with reduced LVEF. The CABG-Patch trial showed no benefit of ICD therapy in patients with EF <35% undergoing surgical coronary revascularization,[40] possibly due to the antiarrhythmic effect or the improved systolic function following revascularization. Similarly, the DINAMIT and IRIS studies showed no benefit of early implantation of ICDs following myocardial infarction despite a reduced ejection fraction.[41],[42] Again, this may be due to improvement in LVEF post MI or competing non-arrhythmic causes of mortality.[41] Hence, the timing of LVEF assessment and of intervention and changes in underlying myocardial status are also important variables to consider. Finally, as noted above, most patients that survive cardiac arrest in more contemporary studies only have mildly depressed or near normal systolic function [7],[43] and the predictive role of LVEF is therefore limited in these populations without significant underlying cardiomyopathy. It should be noted that Asians were markedly underrepresented in all of these landmark studies.


  Resting Electrocardiogram (Qrs and Qt Intervals) Top


The resting electrocardiogram is a non-invasive, inexpensive diagnostic tool that is available in most clinical settings and can provide useful prognostic information. QRS duration represents interventricular conduction time and when prolonged may promote ventricular arrhythmias by altering electrical and mechanical function through abnormal dispersion of depolarization and repolarization and resultant cardiac dyssynchrony. QRS prolongation may also be a marker of more advanced LV dilation and dysfunction. QRS prolongation (>120 ms) has been shown to predict both overall mortality and SCD in patients with ischemic and non-ischemic cardiomyopathy, independent of LVEF.[44]

The QT interval represents ventricular repolarization, which is routinely corrected for heart rate or RR interval and measured as QTc. A QTc duration greater than 420–440 ms (longer upper limit of normal in females than in males) is associated with a 2–3 fold increase in cardiac mortality among patients with and without coronary artery disease.[45],[46],[47] Applied to the general population, a prolonged QT interval and/or increased QT interval dispersion (the maximal inter-lead QT variance in 12 lead electrocardiogram) predicts increased cardiac and total mortality.[48] However, in patients with advance heart failure, QT interval and interval dispersion were unable to predict mortality independent of LVEF,[49] thus limiting its clinical applicability in patients with significant underlying cardiomyopathy. Of note, these studies did not include subjects with genetic channelopathies including Long QT syndrome in whom a QTc >500 ms (or the rarer Short QT syndrome with QTC <350 ms) is associated with increased risk of SCD independent of structural heart disease.[50],[51]


  Ambulatory Electrocardiogram (Holter recording of Ventricular Ectopy and Heart Rate Turbulence) Top


Historically, long term ambulatory electrocardiography by Holter monitoring was used to predict SCD in survivors of myocardial infarction. Patients with complex ventricular ectopy defined as more than 10 premature ventricular beats per hour or non-sustained ventricular tachycardia (NSVT) were shown to have increased mortality.[52],[53] However, in one more recent multivariate analysis performed in the thrombolytic/reperfusion era, complex ventricular ectopy was not shown to be an independent predictor of mortality and the presence of post infarct NSVT no longer predicted mortality or arrhythmic events.[54] Studies evaluating complex ventricular ectopy, specifically NSVT among patients with non-ischemic cardiomyopathy have also had conflicting results.[55],[56],[57]

Heart rate turbulence is a non-invasive marker of electrical instability that can be assessed on Holter monitor and has been shown to identify patients at high risk for all-cause mortality and sudden death, specifically in post-infarction and congestive heart failure patients.[58],[59],[60],[61] Heart rate turbulence is believed to reflect baroreflex sensitivity and is a surrogate marker of cardiac autonomic tone. Under normal conditions, a ventricular premature beat (VPB) results in a transient drop in blood pressure triggering baroreceptor activated inhibition of vagal tone and subsequent increase in heart rate. Increased myocardial contractility following a VPB then results in a transient increase in blood pressure with a decrease in sinus node activity. To analyse this marker, the RR intervals following VPBs are assessed for an initial short acceleration followed by a deceleration of heart rate. Absent or diminished biphasic pattern reflects an abnormal response and increased risk of cardiac arrhythmic death.[61]

Advanced electrocardiographic techniques such as the signal averaged ECG and microvolt T-wave alternans have also been used in the past but their role is limited in contemporary risk stratification. Similarly, electrophysiology studies with programmed ventricular stimulation is rarely used anymore and largely confined to subjects with ischemic heart disease or syncope.


  Imaging: Assessing Scar Burden Top


Contrast enhanced cardiac magnetic resonance (cCMR) is an imaging modality that utilizes the power and spatial resolution of MRI images to assess SCD risk associated with abnormal cardiac anatomy.[62],[63]

In 2007, Roes et al. published data that suggested cCMR delineated myocardial scar may be a superior predictor of mortality than LVEF and LV volume in patients with healed myocardial infarction [Figure 3].[64] Despite a number of studies showing a clear association between risk of malignant arrhythmia and myocardial scar, a quantitative continuous relationship has not yet been demonstrated.[65] This suggests that, while scar is an important substrate for VT in patients with ischemic cardiomyopathy, it alone does not correlate with risk for malignant arrhythmia.[65]
Figure 3: Impact of scar on mortality. Kaplan–Meier curve analysis showing difference in mortality when patients are stratified according to a large extent (≥6) versus a small extent (<6) of scar tissue on contrast-enhanced magnetic resonance imaging (Reproduced with permission from Roes et al.[64]).

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  Imaging: Assessing Sympathetic Denervation (Mibg) Top


In 1993, Mitrani et al. first showed in a small cohort of 18 patients with sympathetic denervation an increase in risk of ventricular tachycardia, even in the absence of coronary artery disease.[66] Computed tomography using radioiodinated metaiodobenzylguanidine (mIBG) is now recognized as a powerful tool to identify inhomogeneity of the sympathetic nervous system within the cardiac myocardium, a potentially important substrate for sudden cardiac death.[67],[68],[69] mIBG is an analog of norepinephrine that is able to concentrate in sympathetic neurons within the heart.[70] The concentration of mIBG within cardiac neurons directly correlate with the neuronal integrity and function.[70] In a study of 116 patients who underwent mIBG imaging prior to implantation of ICD, Boogers and colleagues showed that this marker was an independent predictor of ventricular arrhythmias that would require ICD therapy.[71]

The late heart to mediastinum ratio (HMR) on mIBG has also been found to be an independent predictor of mortality.[71] In the prospective AdreView Myocardial Imaging for Risk Evaluation of Heart Failure (ADMIRE-HF) study of 961 patients with NYHA functional class II/III CHF with an LVEF less than 35%, 237 subjects experienced functional class progression, life threatening arrhythmic events or cardiac death.[72] These investigators compared patients with a late HMR less than 1.6 to those with values greater than or equal to 1.6.[72] They observed that patients with HMR less than 1.6 were at significant risk for all endpoints including progression of heart failure, arrhythmic events, cardiac death and all-cause mortality [Figure 4].[72] Multivariable analysis found that HMR, LVEF, BNP, and NYHA class were independent contributors to risk model.[72]
Figure 4: Sympathetic denervation and cardiac outcomes. Cumulative event curves comparing patients with H/M <1.6 versus >1.6 (a) composite primary end point; (b) heart failure progression; (c) arrhythmic event; (d) cardiac death; (e) all-cause mortality. H/M = heart/mediastinum ratio on computed tomography using radioiodinated metaiodobenzylguanidine (Reproduced with permission from Jacobson et al.[72]).

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Finally, the wash out rate (WR), which assesses the retention of norepinephrine by neurons, has been shown to be a potent predictor of sudden cardiac death.[71] Among patients with LVEF > 35%, there was a significantly higher rate of sudden cardiac death in those with abnormal WR.[73] Their results were validated by meta-analysis of 18 studies with a total of 1755 patients by Verberne et al.[74] WR has also been shown to be a significant independent predictor of MACE in patients with STEMI.[75] The applicability of this approach may be limited as beta blocker use is ubiquitous and a Class I indication among patients with prior myocardial infarction.


  Imaging: Assessing Sympathetic Denervation (Positron Emission Tomography) Top


Positron emission tomography (PET) is another imaging modality used in the evaluation of myocardial sympathetic innervation.[3] [11C]-meta-Hydroxyephedrine (HED) is a radioligand developed for PET to evaluate the sympathetic nervous system.

The PAREPET trial was a prospective observational trial designed to study the hypothesis that inhomogeneity in human myocardial sympathetic innervation and/or hibernating myocardium could predict risk for arrhythmic death independent of left ventricular function.[76] Infarct volume and LVEF were not predictors of sudden cardiac arrest [Figure 5].[76] However, patients who later suffered from sudden cardiac arrest had a greater sympathetic denervation burden as seen in viable denervated myocardium ((33% ±10%) vs. (26% ± 11%) of LV; P = 0.001). Interestingly, infarct size, left ventricular ejection fraction, BNP and other variables did not improve their predictive model.
Figure 5: Positron emission tomography scan and other clinical factors to predict sudden cardiac death. Kaplan-Meier curves illustrating significant differences in the incidence of sudden cardiac arrest (SCA) in relation to the number of risk factors present (P < 0.0001). Subjects with no risk factors had an annual rate of SCA <1%; 1 risk factor had an annual rate of ~4% and 2 or more risk factors had an annual risk of ~12%. (Reproduced with permission from Fallavollita et al[76]).

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  Summary Top


SCD remains a major health care problem. Early studies identified LVEF, ischemic heart disease, heart failure and ambient arrhythmias as predictors of events. This led to large multicenter trials establishing the role of the ICD for primary prevention of SCD. However, a changing epidemiology of SCD has confirmed an unmet need for risk stratification. In addition, there is interest in improved risk stratification of ICD eligible patients [Table 2] and [Table 3]. In this regard, newer imaging, advanced electrocardiographic and genetic techniques raise hope that specific markers or a combinations of tests will allow identification of high risk subjects who can benefit from specific antiarrhythmic treatment.
Table 2: Composite risk scores for SCD in primary prevention cohorts

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Table 3: Sudden cardiac death risk algorithm for consideration of implantable cardioverter defibrillators placement

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Financial support and sponsorship

Nil.

Conflicts of interest

Dr. Gold has received research grants and served as a consultant to Boston Scientific, St Jude and Medtronic.

 
  References Top

1.
European Heart Rhythm Association; Heart Rhythm Society, Zipes DP, Camm AJ, Borggrefe M, Buxton AE, Chaitman B, 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). J Am Coll Cardiol 2006;48:e247-346.  Back to cited text no. 1
    
2.
Mehra R. Global public health problem of sudden cardiac death. J Electrocardiol 2007;40 6 Suppl: S118-22.  Back to cited text no. 2
    
3.
Goldberger JJ, Basu A, Boineau R, Buxton AE, Cain ME, Canty JM Jr., et al. Risk stratification for sudden cardiac death: A plan for the future. Circulation 2014;129:516-26.  Back to cited text no. 3
    
4.
Johnson CC, Spitz MR. Childhood nervous system tumours: An assessment of risk associated with paternal occupations involving use, repair or manufacture of electrical and electronic equipment. Int J Epidemiol 1989;18:756-62.  Back to cited text no. 4
    
5.
Fishman GI, Chugh SS, Dimarco JP, Albert CM, Anderson ME, Bonow RO, et al. Sudden cardiac death prediction and prevention: Report from a National Heart, Lung, and Blood Institute and Heart Rhythm Society Workshop. Circulation 2010;122:2335-48.  Back to cited text no. 5
    
6.
Huikuri HV, Castellanos A, Myerburg RJ. Sudden death due to cardiac arrhythmias. N Engl J Med 2001;345:1473-82.  Back to cited text no. 6
    
7.
A comparison of antiarrhythmic-drug therapy with implantable defibrillators in patients resuscitated from near-fatal ventricular arrhythmias. The Antiarrhythmics versus Implantable Defibrillators (AVID) Investigators. N Engl J Med 1997;337:1576-83.  Back to cited text no. 7
    
8.
Greenberg H, Case RB, Moss AJ, Brown MW, Carroll ER, Andrews ML; MADIT-II Investigators. Analysis of mortality events in the Multicenter Automatic Defibrillator Implantation Trial (MADIT-II). J Am Coll Cardiol 2004;43:1459-65.  Back to cited text no. 8
    
9.
Bardy GH, Lee KL, Mark DB, Poole JE, Packer DL, Boineau R, et al. Amiodarone or an implantable cardioverter-defibrillator for congestive heart failure. N Engl J Med 2005;352:225-37.  Back to cited text no. 9
    
10.
Hulleman M, Berdowski J, de Groot JR, van Dessel PF, Borleffs CJ, Blom MT, et al. Implantable cardioverter-defibrillators have reduced the incidence of resuscitation for out-of-hospital cardiac arrest caused by lethal arrhythmias. Circulation 2012;126:815-21.  Back to cited text no. 10
    
11.
Bunch TJ, White RD, Friedman PA, Kottke TE, Wu LA, Packer DL. Trends in treated ventricular fibrillation out-of-hospital cardiac arrest: A 17-year population-based study. Heart Rhythm 2004;1:255-9.  Back to cited text no. 11
    
12.
Stecker EC, Reinier K, Marijon E, Narayanan K, Teodorescu C, Uy-Evanado A, et al. Public health burden of sudden cardiac death in the United States. Circ Arrhythm Electrophysiol 2014;7:212-7.  Back to cited text no. 12
    
13.
Iwami T, Hiraide A, Nakanishi N, Hayashi Y, Nishiuchi T, Yukioka H, et al. Age and sex analyses of out-of-hospital cardiac arrest in Osaka, Japan. Resuscitation 2003;57:145-52.  Back to cited text no. 13
    
14.
Reinier K, Nichols GA, Huertas-Vazquez A, Uy-Evanado A, Teodorescu C, Stecker EC, et al. Distinctive clinical profile of blacks versus whites presenting with sudden cardiac arrest. Circulation 2015;132:380-7.  Back to cited text no. 14
    
15.
Willey JZ, Rodriguez CJ, Moon YP, Paik MC, Di Tullio MR, Homma S, et al. Coronary death and myocardial infarction among Hispanics in the Northern Manhattan Study: Exploring the Hispanic paradox. Ann Epidemiol 2012;22:303-9.  Back to cited text no. 15
    
16.
Zheng ZJ, Croft JB, Giles WH, Mensah GA. Sudden cardiac death in the United States, 1989 to 1998. Circulation 2001;104:2158-63.  Back to cited text no. 16
    
17.
Nagata M, Ninomiya T, Doi Y, Hata J, Ikeda F, Mukai N, et al. Temporal trends in sudden unexpected death in a general population: The Hisayama study. Am Heart J 2013;165:932-8.e1.  Back to cited text no. 17
    
18.
Tanno K, Miyoshi F, Watanabe N, Minoura Y, Kawamura M, Ryu S, et al. Are the MADIT II criteria for ICD implantation appropriate for Japanese patients? Circ J 2005;69:19-22.  Back to cited text no. 18
    
19.
Siu CW, Pong V, Ho HH, Liu S, Lau CP, Li SW, et al. Are MADIT II criteria for implantable cardioverter defibrillator implantation appropriate for Chinese patients? J Cardiovasc Electrophysiol 2010;21:231-5.  Back to cited text no. 19
    
20.
Hess PL, Wojdyla DM, Al-Khatib SM, Lokhnygina Y, Wallentin L, Armstrong PW, et al. Sudden cardiac death after non-ST-segment elevation acute coronary syndrome. JAMA Cardiol 2016;1:73-9.  Back to cited text no. 20
    
21.
Hayashi M, Shimizu W, Albert CM. The spectrum of epidemiology underlying sudden cardiac death. Circ Res 2015;116:1887-906.  Back to cited text no. 21
    
22.
Chan NY. Sudden cardiac death in Asia and China: Are we different? J Am Coll Cardiol 2016;67:590-2.  Back to cited text no. 22
    
23.
Jouven X, Desnos M, Guerot C, Ducimetière P. Predicting sudden death in the population: The Paris Prospective Study I. Circulation 1999;99:1978-83.  Back to cited text no. 23
    
24.
Friedlander Y, Siscovick DS, Arbogast P, Psaty BM, Weinmann S, Lemaitre RN, et al. Sudden death and myocardial infarction in first degree relatives as predictors of primary cardiac arrest. Atherosclerosis 2002;162:211-6.  Back to cited text no. 24
    
25.
Dekker LR, Bezzina CR, Henriques JP, Tanck MW, Koch KT, Alings MW, et al. Familial sudden death is an important risk factor for primary ventricular fibrillation: A case-control study in acute myocardial infarction patients. Circulation 2006;114:1140-5.  Back to cited text no. 25
    
26.
Kolder IC, Tanck MW, Bezzina CR. Common genetic variation modulating cardiac ECG parameters and susceptibility to sudden cardiac death. J Mol Cell Cardiol 2012;52:620-9.  Back to cited text no. 26
    
27.
Arking DE, Junttila MJ, Goyette P, Huertas-Vazquez A, Eijgelsheim M, Blom MT, et al. Identification of a sudden cardiac death susceptibility locus at 2q24.2 through genome-wide association in European ancestry individuals. PLoS Genet 2011;7:e1002158.  Back to cited text no. 27
    
28.
Hong KW, Lim JE, Kim JW, Tabara Y, Ueshima H, Miki T, et al. Identification of three novel genetic variations associated with electrocardiographic traits (QRS duration and PR interval) in East Asians. Hum Mol Genet 2014;23:6659-67.  Back to cited text no. 28
    
29.
Arking DE, Reinier K, Post W, Jui J, Hilton G, O'Connor A, et al. Genome-wide association study identifies GPC5 as a novel genetic locus protective against sudden cardiac arrest. PLoS One 2010;5:e9879.  Back to cited text no. 29
    
30.
Aouizerat BE, Vittinghoff E, Musone SL, Pawlikowska L, Kwok PY, Olgin JE, et al. GWAS for discovery and replication of genetic loci associated with sudden cardiac arrest in patients with coronary artery disease. BMC Cardiovasc Disord 2011;11:29.  Back to cited text no. 30
    
31.
Fender EA, Henrikson CA, Tereshchenko L. Racial differences in sudden cardiac death. J Electrocardiol 2014;47:815-8.  Back to cited text no. 31
    
32.
Deo R, Albert CM. Epidemiology and genetics of sudden cardiac death. Circulation 2012;125:620-37.  Back to cited text no. 32
    
33.
Murakoshi N, Aonuma K. Epidemiology of arrhythmias and sudden cardiac death in Asia. Circ J 2013;77:2419-31.  Back to cited text no. 33
    
34.
Albert CM, MacRae CA, Chasman DI, VanDenburgh M, Buring JE, Manson JE, et al. Common variants in cardiac ion channel genes are associated with sudden cardiac death. Circ Arrhythm Electrophysiol 2010;3:222-9.  Back to cited text no. 34
    
35.
Keating MT, Sanguinetti MC. Molecular and cellular mechanisms of cardiac arrhythmias. Cell 2001;104:569-80.  Back to cited text no. 35
    
36.
Risk stratification and survival after myocardial infarction. N Engl J Med 1983;309:331-6.  Back to cited text no. 36
    
37.
Huikuri HV, Tapanainen JM, Lindgren K, Raatikainen P, Mäkikallio TH, Juhani Airaksinen KE, et al. Prediction of sudden cardiac death after myocardial infarction in the beta-blocking era. J Am Coll Cardiol 2003;42:652-8.  Back to cited text no. 37
    
38.
Grimm W, Christ M, Bach J, Müller HH, Maisch B. Noninvasive arrhythmia risk stratification in idiopathic dilated cardiomyopathy: Results of the Marburg Cardiomyopathy Study. Circulation 2003;108:2883-91.  Back to cited text no. 38
    
39.
Moss AJ, Zareba W, Hall WJ, Klein H, Wilber DJ, Cannom DS, et al. Prophylactic implantation of a defibrillator in patients with myocardial infarction and reduced ejection fraction. N Engl J Med 2002;346:877-83.  Back to cited text no. 39
    
40.
Suliman FA. Prophylactic use of implanted cardiac defibrillators in patients at high risk for ventricular arrhythmias after coronary-artery bypass graft surgery. N Engl J Med 1998;338:1228.  Back to cited text no. 40
    
41.
Hohnloser SH, Kuck KH, Dorian P, Roberts RS, Hampton JR, Hatala R, et al. Prophylactic use of an implantable cardioverter-defibrillator after acute myocardial infarction. N Engl J Med 2004;351:2481-8.  Back to cited text no. 41
    
42.
Steinbeck G, Andresen D, Seidl K, Brachmann J, Hoffmann E, Wojciechowski D, et al. Defibrillator implantation early after myocardial infarction. N Engl J Med 2009;361:1427-36.  Back to cited text no. 42
    
43.
Connolly SJ, Gent M, Roberts RS, Dorian P, Roy D, Sheldon RS, et al. Canadian implantable defibrillator study (CIDS): A randomized trial of the implantable cardioverter defibrillator against amiodarone. Circulation 2000;101:1297-302.  Back to cited text no. 43
    
44.
Iuliano S, Fisher SG, Karasik PE, Fletcher RD, Singh SN; Department of Veterans Affairs Survival Trial of Antiarrhythmic Therapy in Congestive Heart Failure. QRS duration and mortality in patients with congestive heart failure. Am Heart J 2002;143:1085-91.  Back to cited text no. 44
    
45.
Peters RW, Byington RP, Barker A, Yusuf S. Prognostic value of prolonged ventricular repolarization following myocardial infarction: The BHAT experience. The BHAT Study Group. J Clin Epidemiol 1990;43:167-72.  Back to cited text no. 45
    
46.
Schouten EG, Dekker JM, Meppelink P, Kok FJ, Vandenbroucke JP, Pool J. QT interval prolongation predicts cardiovascular mortality in an apparently healthy population. Circulation 1991;84:1516-23.  Back to cited text no. 46
    
47.
Karjalainen J, Reunanen A, Ristola P, Viitasalo M. QT interval as a cardiac risk factor in a middle aged population. Heart 1997;77:543-8.  Back to cited text no. 47
    
48.
Elming H, Holm E, Jun L, Torp-Pedersen C, Køber L, Kircshoff M, et al. The prognostic value of the QT interval and QT interval dispersion in all-cause and cardiac mortality and morbidity in a population of Danish citizens. Eur Heart J 1998;19:1391-400.  Back to cited text no. 48
    
49.
Brendorp B, Elming H, Jun L, Køber L, Malik M, Jensen GB, et al. Qt dispersion has no prognostic information for patients with advanced congestive heart failure and reduced left ventricular systolic function. Circulation 2001;103:831-5.  Back to cited text no. 49
    
50.
Berul CI. Congenital long-QT syndromes: Who's at risk for sudden cardiac death? Circulation 2008;117:2178-80.  Back to cited text no. 50
    
51.
Patel C, Yan GX, Antzelevitch C. Short QT syndrome: From bench to bedside. Circ Arrhythm Electrophysiol 2010;3:401-8.  Back to cited text no. 51
    
52.
Bigger JT Jr., Fleiss JL, Kleiger R, Miller JP, Rolnitzky LM. The relationships among ventricular arrhythmias, left ventricular dysfunction, and mortality in the 2 years after myocardial infarction. Circulation 1984;69:250-8.  Back to cited text no. 52
    
53.
Maggioni AP, Zuanetti G, Franzosi MG, Rovelli F, Santoro E, Staszewsky L, et al. Prevalence and prognostic significance of ventricular arrhythmias after acute myocardial infarction in the fibrinolytic era. GISSI-2 results. Circulation 1993;87:312-22.  Back to cited text no. 53
    
54.
Hohnloser SH, Klingenheben T, Zabel M, Schöpperl M, Mauss O. Prevalence, characteristics and prognostic value during long-term follow-up of nonsustained ventricular tachycardia after myocardial infarction in the thrombolytic era. J Am Coll Cardiol 1999;33:1895-902.  Back to cited text no. 54
    
55.
Grimm W, Christ M, Maisch B. Long runs of non-sustained ventricular tachycardia on 24-hour ambulatory electrocardiogram predict major arrhythmic events in patients with idiopathic dilated cardiomyopathy. Pacing Clin Electrophysiol 2005;28 Suppl 1:S207-10.  Back to cited text no. 55
    
56.
Zecchin M, Di Lenarda A, Gregori D, Merlo M, Pivetta A, Vitrella G, et al. Are nonsustained ventricular tachycardias predictive of major arrhythmias in patients with dilated cardiomyopathy on optimal medical treatment? Pacing Clin Electrophysiol 2008;31:290-9.  Back to cited text no. 56
    
57.
de Sousa MR, Morillo CA, Rabelo FT, Nogueira Filho AM, Ribeiro AL. Non-sustained ventricular tachycardia as a predictor of sudden cardiac death in patients with left ventricular dysfunction: A meta-analysis. Eur J Heart Fail 2008;10:1007-14.  Back to cited text no. 57
    
58.
Kusmirek SL, Gold MR. Sudden cardiac death: The role of risk stratification. Am Heart J 2007;153 4 Suppl: 25-33.  Back to cited text no. 58
    
59.
Berkowitsch A, Zareba W, Neumann T, Erdogan A, Nitt SM, Moss AJ, et al. Risk stratification using heart rate turbulence and ventricular arrhythmia in MADIT II: Usefulness and limitations of a 10-minute holter recording. Ann Noninvasive Electrocardiol 2004;9:270-9.  Back to cited text no. 59
    
60.
Schmidt G, Malik M, Barthel P, Schneider R, Ulm K, Rolnitzky L, et al. Heart-rate turbulence after ventricular premature beats as a predictor of mortality after acute myocardial infarction. Lancet 1999;353:1390-6.  Back to cited text no. 60
    
61.
Cygankiewicz I. Heart rate turbulence. Prog Cardiovasc Dis 2013;56:160-71.  Back to cited text no. 61
    
62.
Kim RJ, Fieno DS, Parrish TB, Harris K, Chen EL, Simonetti O, et al. Relationship of MRI delayed contrast enhancement to irreversible injury, infarct age, and contractile function. Circulation 1999;100:1992-2002.  Back to cited text no. 62
    
63.
Kim RJ, Wu E, Rafael A, Chen EL, Parker MA, Simonetti O, et al. The use of contrast-enhanced magnetic resonance imaging to identify reversible myocardial dysfunction. N Engl J Med 2000;343:1445-53.  Back to cited text no. 63
    
64.
Roes SD, Kelle S, Kaandorp TA, Kokocinski T, Poldermans D, Lamb HJ, et al. Comparison of myocardial infarct size assessed with contrast-enhanced magnetic resonance imaging and left ventricular function and volumes to predict mortality in patients with healed myocardial infarction. Am J Cardiol 2007;100:930-6.  Back to cited text no. 64
    
65.
Lee DC, Goldberger JJ. CMR for sudden cardiac death risk stratification: Are we there yet? JACC Cardiovasc Imaging 2013;6:345-8.  Back to cited text no. 65
    
66.
Mitrani RD, Klein LS, Miles WM, Hackett FK, Burt RW, Wellman HN, et al. Regional cardiac sympathetic denervation in patients with ventricular tachycardia in the absence of coronary artery disease. J Am Coll Cardiol 1993;22:1344-53.  Back to cited text no. 66
    
67.
Raffel DM, Wieland DM. Development of mIBG as a cardiac innervation imaging agent. JACC Cardiovasc Imaging 2010;3:111-6.  Back to cited text no. 67
    
68.
Klein T, Dilsizian V, Cao Q, Chen W, Dickfeld TM. The potential role of iodine-123 metaiodobenzylguanidine imaging for identifying sustained ventricular tachycardia in patients with cardiomyopathy. Curr Cardiol Rep 2013;15:359.  Back to cited text no. 68
    
69.
Luisi AJ Jr., Suzuki G, Dekemp R, Haka MS, Toorongian SA, Canty JM Jr., et al. Regional 11C-hydroxyephedrine retention in hibernating myocardium: Chronic inhomogeneity of sympathetic innervation in the absence of infarction. J Nucl Med 2005;46:1368-74.  Back to cited text no. 69
    
70.
Sisson JC, Shapiro B, Meyers L, Mallette S, Mangner TJ, Wieland DM, et al. Metaiodobenzylguanidine to map scintigraphically the adrenergic nervous system in man. J Nucl Med 1987;28:1625-36.  Back to cited text no. 70
    
71.
Carrió I, Cowie MR, Yamazaki J, Udelson J, Camici PG. Cardiac sympathetic imaging with mIBG in heart failure. JACC Cardiovasc Imaging 2010;3:92-100.  Back to cited text no. 71
    
72.
Jacobson AF, Senior R, Cerqueira MD, Wong ND, Thomas GS, Lopez VA, et al. Myocardial iodine-123 meta-iodobenzylguanidine imaging and cardiac events in heart failure. Results of the prospective ADMIRE-HF (AdreView Myocardial Imaging for Risk Evaluation in Heart Failure) study. J Am Coll Cardiol 2010;55:2212-21.  Back to cited text no. 72
    
73.
Tamaki S, Yamada T, Okuyama Y, Morita T, Sanada S, Tsukamoto Y, et al. Cardiac iodine-123 metaiodobenzylguanidine imaging predicts sudden cardiac death independently of left ventricular ejection fraction in patients with chronic heart failure and left ventricular systolic dysfunction: Results from a comparative study with signal-averaged electrocardiogram, heart rate variability, and QT dispersion. J Am Coll Cardiol 2009;53:426-35.  Back to cited text no. 73
    
74.
Verberne HJ, Brewster LM, Somsen GA, van Eck-Smit BL. Prognostic value of myocardial 123I-metaiodobenzylguanidine (MIBG) parameters in patients with heart failure: A systematic review. Eur Heart J 2008;29:1147-59.  Back to cited text no. 74
    
75.
de Benedictis FM, Bush A. Rhinosinusitis and asthma: Epiphenomenon or causal association? Chest 1999;136:550-6.  Back to cited text no. 75
    
76.
Fallavollita JA, Heavey BM, Luisi AJ Jr., Michalek SM, Baldwa S, Mashtare TL Jr., et al. Regional myocardial sympathetic denervation predicts the risk of sudden cardiac arrest in ischemic cardiomyopathy. J Am Coll Cardiol 2014;63:141-9.  Back to cited text no. 76
    


    Figures

  [Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5]
 
 
    Tables

  [Table 1], [Table 2], [Table 3]


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