Prediction and Prevention in Sudden Cardiac Death

1. Prediction and Prevention in Sudden Cardiac Death

2. Review Article
INTRODUCTION
Despite the significant decline in coronary artery
disease (CAD) mortality in the second half of the 20th
century, sudden cardiac death (SCD) is the most common
cause of death worldwide, accounting for more than 50%
of all deaths from cardiovascular disease [1-4]. The
condition is characterized by an unexpected
cardiovascular collapse due to an underlying cardiac cause
[5]. The International Classification of Diseases, Tenth
Revision, defines sudden cardiac death (SCD) as death due
to any cardiac disease that occurs out of hospital, in an
emergency department, or in an individual reported dead
on arrival at a hospital. In addition, death must have
occurred within 1 hour after the onset of symptoms [6].
The underlying cause may be a ventricular tachycardia
(VT), ventricular fibrillation (VF), asystole, or non-
arrhythmic causes [7]. Sudden cardiac death (SCD)
continues to claim 250000 to 300000 US lives annually
[8]. In North America and Europe the annual incidence of
SCD ranges between 50 to 100 per 100000 in the general
population [9-13]. Because of the absence of emergency
medical response systems in most world regions,
worldwide estimates are currently not available [14]. In
urban India the trend of SCD is similar to the West [15].
SCD represents a major challenge for the clinician because
most episodes occur in individuals without previously
known cardiac disease [1-4]. Even with the best first
responder systems the average survival is approximately
5% [16]. On average, only 8% of those receiving
community-based resuscitation are discharged from the
hospital alive [2]. The discovery of effective prediction &
prevention modalities, therefore, is of great importance.
Pathophysiology
VF is the first recorded rhythm in ~ 75% cases and is
the underlying mechanism for most SCD episodes [17].
PREDICTION AND PREVENTION IN SUDDEN CARDIAC DEATH
Ashish K Govil , Mohit D Gupta, M P Girish and Sanjay Tyagi
Department of Cardiology, GB Pant Hospital, New Delhi 110 002, India.
Correspondence to: Dr Mohit D Gupta, Assistant Professor of Cardiology, Room 125, Academic Block,
First Floor Department of Cardiology, GB Pant Hospital, New Delhi 110 002, India.
E mail: drmohitgupta@yahoo.com
Key words: Coronary artery disease, Cardiovascular disease.
Survival declines by ~10% per minute for patients in
ventricular fibrillation [2]. However, in patients
undergoing continuous ECG monitoring primary VF was
documented in 8%, VT degenerating into VF in 62% &
TdP in 13% of the cases [18]. Patients having implanted
with an ICD have 90% appropriate arrhythmia detections
for VT rather than VF [19]. Cardiac arrest typically arises
suddenly in an individual with the appropriate anatomic
or electrophysiological substrate without an identifiable
trigger [4] (Table 1 & 2).
Prevention of SCD
Various strategies have evolved to predict and prevent
SCD. Recent emphasis has been on primordial prevention
of coronary artery disease. The most common underlying
cardiovascular condition predisposing to SCD is coronary
artery disease. In ~50% of cases, SCD is the first
manifestation of the coronary disease [1-4,8]. Risk factors
for SCD include advanced age, male sex, cigarette
smoking, hypertension, diabetes mellitus, hypercholes-
terolemia, obesity, and a family history of coronary artery
disease [8]. Prevention of development of risk factors
with optimization of blood pressure, weight, glucose,
cholesterol, smoking, diet, and physical activity, through
lifestyle interventions, to reduce cardiovascular disease
and SCD is an intuitive approach. However, robust
evidence supporting this strategy is currently lacking [8].
Risk stratification
Accurate and timely prediction of sudden cardiac
death (SCD) is a necessary prerequisite for effective
prevention and therapy. Due to high mortality due to SCD
there is a need for risk stratification techniques to identify
patients at high risk for these events and effective
interventions that can prevent or abort these events. Risk
stratification is useful to identify populations of
Apollo Medicine, Vol. 8, No. 3, September 2011 228

3. Review Article
229 Apollo Medicine, Vol. 8, No. 3, September 2011
individuals at risk for SCD, however, current techniques
to identify high-risk individuals lack sufficient predictive
value to have clinical utility because of the relatively low
event rates or absolute risk [1-4] (Fig 1).
Nearly two-thirds of cardiac arrests occur as the first
clinically manifest event or in the clinical setting of known
disease in the absence of strong risk predictors. Less than
25% of the victims have high-risk markers based on
arrhythmic or hemodynamic parameters. AP = angina
pectoris; MI = myocardial infarction; SCD = sudden
cardiac death [4].
Largely, risk stratification techniques have been
applied to dichotomize patients into low- and high-risk
groups while in actuality, it is a continuum. Furthermore,
the majority of episodes of SCD actually occur in those
with low- to intermediate-risk factors and those without
known risk factors.[20] The highest-risk subgroups, on
which much attention is focused because of the magnitude
of the risk of death, actually constitute only a small
proportion of the total number of deaths annually [4] (Fig
2). Thus, a comprehensive approach to risk stratification
must account for these epidemiological realities.
The overall adult population has an estimated sudden
death incidence of 0.1% to 0.2% per year, accounting for a
total of 300,000 events per year. With the identification of
increasingly powerful risk factors, the incidence increases
progressively, but it is accomplished by a progressive
decrease in the total number of events represented by each
group. The inverse relationship between incidence and
total number of events occurs because of the progressively
smaller denominator pool in the highest subgroup
categories. The blue-hatched incidence bars for the higher
risk groups represent estimates from the original analysis
in the 1990s; the superimposed red-hatched bars reflect
more recent estimates based on the effects of newer
multimodal therapies. Successful interventions among
larger population subgroups require identification of
specific markers to increase the ability to identify specific
patients who are at particularly high risk for a future event.
(Note: The horizontal axis for the incidence figures is not
linear.) CAD = coronary artery disease; EF = ejection
fraction [4].
ASSESSMENT OF SUDDEN CARDIAC DEATH
RISK FACTORS
Left ventricular ejection fraction
Depressed LV systolic function is the most consistent
& powerful predictor of cardiac mortality regardless of its
etiology [21]. Patients who have an LVEF <30-35% are
considered to be high-risk, and qualify as candidates for
Table 1. Cardiovascular conditions associated with
SCD
• IHD
o AMI
o Chronic ICMP
o Anomalous/ hypoplastic coronaries
• Non IHD
o Cardiomyopathies
§ DCMP
§ HCM
§ ARVD
§ LV non compactiono Infiltrative &
• Inflammatory
§ Sarcoidosis
§ Amyloidosis
§ Hemochromatosis
§ Myocarditis
• Valvular
o AS/AR, MVP, IE
• CHD
o TOF
o Ebstein’s
o PVOD
o Congenital AS
• Primary electrical abnormalities
o LQT, SOT
o WPWo Brugada
o CPVT
o Idiopathic VF
o Early repolarization variants
o CongenitalAV blocks
• Drugs & toxins
• Electrolyte abnormalities
Table 2. Triggers of SCD
• Ischemia
• Autonomic changeso
* Increased sympathetic toneo
* Decreased parasympathetic tone
• Physical exertion
• Hypoxia
• Drug effects
• Electrolyte abnormalities
• Myocardial toxins

4. Review Article
Apollo Medicine, Vol. 8, No. 3, September 2011 230
use as a specific predictor of SCD [30]. Despite the
shortcomings of the LVEF, numerous risk stratification
test modalities have been evaluated over the past three
decades and none has been found to be superior to this
parameter [31].
NYHA CLASS
Heart failure symptoms, as reflected in the New York
Heart Association (NYHA) functional class provide a
potent risk stratification tool. Patients with NYHA Class II
and III symptoms are at a higher risk for SCD than death
from progressive pump failure. In contrast, patients with
NYHA Class IV symptoms are less likely to die suddenly
and are much more likely to die of pump failure [32].
Observations from various trials have been the subject of
ongoing debate. SCD-HeFT: decreased benefit in Class III
compared with Class II. DEFINITE: greater benefit of
ICD in class III than with class II. MADIT-II: no
significant differences on survival when stratified
according to NYHA. The use of NYHA class to identify
patients with systolic dysfunction at risk for SCD is
limited by its subjectivity. Also, frequent transition from
one class to another over time limits the utility of this risk
marker.
ELECTROCARDIOGRAM
QRS duration
QRS duration is a simple measure of the duration of
ventricular activation. Observational studies suggest that
QRS prolongation is a significant marker for poor
outcome in patients with depressed LVEF, especially due
to coronary artery disease [36]. Subgroup analyses of
randomized, controlled ICD trials examining the role of
QRS prolongation as a predictor of overall mortality and
arrhythmic death have given varied results [37-39]. In the
absence of prospective trials specifically designed to
address this issue, the use of QRS duration to further risk-
stratify patients with congestive heart failure for SCD is
not recommended at this time.
QT interval & QT dispersion
Various studies have shown conflicting results
regarding total and cardiovascular mortality in relation to
QTc prolongation. The Framingham study failed to show
any association of baseline QTc prolongation with total
mortality, sudden death, or coronary mortality. In the
Rotterdam study prolonged QTc interval was
independently associated with SCD [40]. Oregon-Sudden
Unexpected Death Study showed fivefold increase in
SCD amongst patients with CAD having idiopathic
prolongation of the QTc in the absence of diabetes or QT-
Fig 1. Distribution of clinical status of victims at time of SCD.
Fig 2. Estimates of incidence and total annual population
burden for general adult population and increasingly
high-risk subgroups.
primary prevention using an implantable defibrillator
[22,23]. On the other hand, most patients who survive
cardiac arrest have only mildly depressed or near-normal
EF. Community-based studies have shown that less than
one-third of all SCD cases have severely decreased LVEF
that meets criteria for high risk of SCD [24-26].
Although, there are abundant data supporting the use
of LVEF to risk-stratify patients with ischemic and non-
ischemic cardiomyopathies [23,27-29], clinical scenarios,
such as the immediate post-MI period may confound its

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231 Apollo Medicine, Vol. 8, No. 3, September 2011
prolonging drugs [26]. In the MADIT-II substudy
increased QT variability was associated with increased
spontaneous VT or VF, but 22% of patients in the lowest
quartile for QT variability also experienced arrhythmias,
which suggests a poor negative predictive value.
QT dispersion (the maximal difference between QT
intervals in the surface ECG) was postulated to reflect
dispersion of myocardial recovery and to be associated
with arrhythmia risk. Several recent studies have found no
relation between QT dispersion and outcome [35,41,42].
Lack of a clear physiological correlate further clouds the
utility of this parameter.
Early repolarization syndrome
Early repolarization is a common electrocardiographic
finding that affects 2%-5% of the population characterized
by a notch producing a positive hump (J-wave) at the end
of QRS. It is seen most often in young men, blacks &
athletes with potential risk of idiopathic VF. In a study by
Haïssaguerre [43] early repolarization was observed in
31% of survivors of SCD in the absence of structural or
molecular causes, compared to 5% amongst normal
controls. The pattern was limited to inferior & lateral leads
with greater magnitude of J-point elevation in survivors.
EPS & Holter studies
Inducibility of monomorphic VT with programmed
ventricular stimulation predicts a high risk of future
arrhythmic events in patients with a history of MI &
reduced EF, ICMP presenting with syncope, resuscitated
cardiac arrest, or asymptomatic NSVT [27]. Although
inducibility is a powerful marker of SCD risk, non-
inducibility may not confer a benign prognosis. Predictive
value of EPS in non-ischaemic or HCM is limited [21].
A few studies have suggested an association between
post-AMI nonsustained ventricular tachycardia (NSVT)
and an increased risk of mortality; however, the value of
NSVT in predicting SCD has not been consistently
demonstrated [33]. Non-sustained ventricular tachycardia
(nsVT) in patients with prior myocardial infarction and
left ventricular dysfunction has been associated with a
two-year mortality around 30% [27]. In a large study of
2130 post-AMI patients, although the presence of NSVT
on 24 h electrocardiographic (ECG) recordings predicted
SCD, it could not discriminate between risk of SCD and
risk of non-SCD [34]. Patients with LVEF between 35%
and 40% [28] may warrant holter recording to assess for
NSVT, because this group has been shown to benefit from
an ICD if VT is induced at electrophysiological study.
Patients with preserved left ventricular function after MI
are generally at low risk, and current data suggest that they
would not benefit from undergoing risk stratification with
holter recording. Finally, in patients with dilated
cardiomyopathy, DEFINITE [29] required the presence of
ventricular ectopy or NSVT on holter, whereas SCD-
HeFT [22] did not; thus, the utility of holter for risk
stratification in this population remains unclear.
Measures of cardiac autonomic modulation
Many measures of cardiac autonomic modulation have
been proposed to risk stratify patients for SCD. These
include heart rate variability (HRV), baroreflex sensitivity
(BRS), heart rate turbulence (HRT), and deceleration
capacity of heart rate. In theATRAMI study [44] low HRV
& BRS significantly predicted a high risk of cardiac
mortality independently of LVEF and spontaneous VTs. In
a recent study low heart-rate turbulence was significantly
associated with increased risk of cardiac death in older
adults otherwise considered low risk for cardiovascular
events [45]. Improved autonomic function with greater
heart-rate variability may partly explain benefits of
Mediterranean diet [46].
Signal averaged ECG
The signal averaged ECG (SAECG) can be used to
detect low-amplitude signals in the terminal part of the
QRS complex. These low-amplitude signals are known as
late potentials and represent delayed activation of the
ventricular myocardium triggering arrhythmia. SAECG
has predicted SCD and total mortality in some studies [47]
but not in others [35,48,49]. Given the high negative
predictive value of this test, it may be useful for the
identification of patients at low risk. Routine use of the
SAECG to identify patients at high risk for SCD is not
adequately supported at this time [6].
Microscopic T-wave alternans
It is defined as a change in T-wave amplitude, width, or
shape occurring in alternate beats. Microscopic T-wave
alternans is a heart rate dependent measure detected with
computerized signal processing techniques. In a meta-
analysis of 19 studies it was found that exercise-induced
MTWAT-wave alternans was a strong univariate predictor
of arrhythmic events in patients with ischemic and
nonischemic heart failure with a negative predictive value
of 97.2% and positive predictive value of 19.3% [50]. In the
ABCD trial, a positive T-wave alternans test was as
predictive of arrhythmic events as a positive electro-
physiology study. However, substudy of SCD-HeFT found
no significant difference in arrhythmic events between
those who had a positive versus a negativeT-wave alternans
test. The value of T-wave alternans may be enhanced when
combined with other major risk predictors.

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Apollo Medicine, Vol. 8, No. 3, September 2011 232
Challenges of early risk prediction
No symptoms have been identified as specific for SCD
in those patients who do develop symptoms before the
event. Patients can experience diverse symptoms such as
palpitations, chest discomfort, dyspnoea, pre-syncope or
syncope; or SCD can manifest in the complete absence of
warning symptoms. There is also a considerable overlap
between the risk factors for related conditions, such as
acute coronary syndrome and congestive heart failure,
which makes it difficult to identify patients who are likely
to suffer from SCD. The challenges of early risk
stratification in SCD are compounded by the generally
accepted paradigm of requiring both a substrate and a
trigger for occurrence of the final dynamic event [10]. A
large body of literature provides evidence for
environmental influences on SCD, ranging from low
socioeconomic status being an important determinant of
risk, to psychological stress being a likely trigger of this
dynamic event [14]. Since a large proportion of patients
who suffer SCD will be asymptomatic until the fatal event
and the etiology of SCD is multi factorial, it is logical that
any identified risk factors could either consist of several
related factors, or abnormal results from the tests that are
employed to determine risk.
Genetic factors
The number of cardiac syndromes being linked with
familial forms of SCD is increasing rapidly. Several
genetic markers have already been identified in the
channelopathies (long-QT syndrome, short-QT syndrome,
Brugada synd-rome, catecholaminergic polymorphic
ventricular tachy-cardia) and arrhythmogenic
cardiomyopathies (arrhythmo-genic right ventricular
cardiomyopathy, hypertrophic cardiomyopathy, familial
dilated cardiomyopathy). In less rare diseases related to
SCD, such as coronary artery disease, there are strong
indications as well that there is a role for a genetic basis.
Family history appears to be a strong independent risk
factor for SCD. In the Paris Prospective Study [51],
relative risk of SCD associated with parental SCD was
1.8. If both parents have a positive family history, the
relative risk was increased by a factor 9. The Finnish
Genetic Study ofArrhythmic Events reported that a family
history of SCD was significantly more likely in the SCD
group compared with the nonfatal AMI group [52]. This
suggests that at least some genetic factors may predispose
to VA specifically rather than to ischemic heart disease
alone. A genetic marker in those patients has not been
identified yet, and progress in this search is slow, probably
due to the polygenic nature of SCD. The number of genes
involved may be large, and the contribution of variations
in each gene may be small.
ADVANCES IN THE EARLY RISK DETECTION
Measuring genetic susceptibility
In the post-genomic era genetic studies are being
conducted among unrelated individuals and two distinct
approaches are rapidly contributing knowledge regarding
genetic variants associated with SCD [55,56]. The
candidate gene approach examines association of SCA
risk with common variations in genes selected from
established molecular pathways leading to ventricular
arrhythmogenesis [57]. The technique utilizes linkage
disequilibrium in the genome to evaluate genotype-
phenotype associations. Therefore, all known common
variants in the gene can be efficiently evaluated using a
limited set of genetic markers. However, the inherent
shortcoming of this approach is that genetic variants are
uncovered only from the candidate genes that are
tested, with no consideration given to the remainder of the
genome. Studies using this approach have contributed and
evaluated multiple and diverse genetic variants that either
confer risk or protection from SCD, but many were not
reproducible in separate populations [26,54]. By
contrast, genome-wide association studies (GWAS)
examine and compare the genetic sequence of individuals
to identify regions of common variants. Since a survey is
conducted of the entire genome, GWAS are unbiased, with
a potentially higher yield than the candidate gene
approach.
New recommendations for genetic testing: HRS/
EHRA [58]
• The strongest recommendations for patients with a
“strong clinical index of suspicion” for:
* LQTS, CPVT &HCM based on clinical history,
family history, and other phenotypic information.
* DCMP with either first, second, or third-degree
heart block, and/or a family history of unexpected
sudden death.
• May be considered in SQTS, Progressive conduction
disease & RCMP.
• Considered useful in suspected Brugada syndrome,
ARVC & LV Non-compaction.
• Not currently indicated for AF or out-of-hospital
cardiac arrest if there is no index suspicion of a
specific underlying disorder.
• Testing family members & appropriate relatives on
identification of a causative gene in various
channelopathies & cardiomyopathies.

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Serum markers
Various serum markers have been proposed for risk
prediction. The Physicians’ Health Study identified C-
reactive protein levels as a potential risk marker in men,
where men in the highest quartile of C-reactive protein
levels had significantly greater risk of SCD than men in
the lowest quartile [59]. The Nurses’ Health Study,
however, reported N-terminal pro b-type natriuretic
peptide (NT-proBNP) levels as a risk marker in women.
Rates of SCD were twofold higher in the highest quartile
than in the lowest quartile when adjusted for CAD risk
factors and biomarkers [60]. Further work is needed
before these biomarkers can be employed for early
detection of SCD risk [61]. Prospective cohort studies
have also identified some markers of membrane stability,
such as non-esterified fatty acids, n-3 fatty acids, and trans
fatty acids that are associated with SCD risk [59, 62].
Cause and effect has yet not been proven for the
association between elevated levels of specific fatty acids
and increased SCD risk. However it has been
hypothesized that free fatty acids are likely to alter the
configuration of the cell membrane lipid bilayer, resulting
in deleterious effects on the function of cardiac ion
channels [63]. A small study of 32 healthy human subjects
reported that increase in serum FFA correlated with
prolonged QTc interval as well as independently increased
levels of serum epinephrine, both of which have potential
arrhythmogenic effects [64].
Troponin (cTnI) is a cardiac specific marker of
myocardial damage. Detectable cTnI levels are associated
with a high mortality in patients with reduced left
ventricular function. In patients with chronic heart failure,
serum cTnI is closely related to increased occurrence of
VA on Holter monitoring [65]. No data about cTnl in
relation to ICD therapy have been reported yet. The role of
these markers in risk stratification for ICD implantation
certainly needs further research.
Imaging to detect risk of SCD
Abnormal remodeling of the myocardial interstitium,
with excessive and abnormal deposition of collagen is an
established determinant of ventricular arrhythmogenesis
[66]. Therefore, techniques that detect diffuse fibrosis are
likely to play a role in SCD risk assessment. Early studies
with conventional Gadolinium-based contrast agents have
focused on quantifying the extent of infarct border-zone
[67] or intermediate (“gray”) zones in other SCD high-risk
conditions [68]. Prior research have revealed that scar
mass and surface were significantly larger in patients with
inducible monomorphic VT than in those without
inducible VT [54,56]. This was found both in patients with
ischemic and non-ischemic cardiomyopathy. In a clinical
setting, patients with hypertrophic cardiomyopathy were
investi-gated.Asignificantly higher occurrence of delayed
enhancement (DE) was found in patients with non-
sustained VT (NSVT), compared with patients without
NSVT. Another possible point of interest is the infarct
heterogeneity. In scar tissue, areas with enhancement of a
lower intensity can be found. In a study by Schmidt et al.,
heterogeneity at the infarct periphery was strongly
associated with inducibility for monomorphic VT in
patients with left ventricular dysfunction.
The role of CMR in risk stratification is promising;
however more research is needed to evaluate the ability to
predict clinically important VA in ischemic and non-
ischemic cardiomyopathy.
Three are early reports of successful imaging directed
at other targets of potential interest. Cardiomyocyte
apoptosis has been imaged with MRI using an annexin-
labeled magneto-fluorescent nanoparticle [69].
Abnormalities of autonomic tone have long been
associated with increased risk of SCD [70] and there are
imaging techniques that can evaluate both sympathetic
and parasympathetic nerve activity in the heart. Specific
cardiac sympathetic nerve activity can be assessed in vivo
by 123I-metaiodobenzyl-guanidine (MIBG) scintigraphy
and increased MIBG washout represents increased
sympathetic nerve activity. In a study of 106 patients with
mild to moderate congestive heart failure followed for 65
± 31 months, those with abnormal MIBG washout rate
(>27%) had a significantly higher risk of SCD compared
with those who had a normal washout rate (adjusted
hazard ratio 4.79, 95% CI 1.55–14.76) [71]. In humans,
the cardiac parasympathetic system can be imaged in vivo
using positron emission tomography (PET) and the
specific muscarinic antagonist [11C]methylquinuclidinyl
benzilate ([11C]MQNB). A recent small study of 20
patients reported that following a myocardial infarction,
this technique can identify regional differences in
muscarinic receptor density within myocardium, which
could indicate regional differences in parasympathetic
innervation [72]. In the future, such techniques could be of
potential utility for SCD risk stratification and merit
evaluations in larger numbers of patients.
Pharmacological intervention
Pharmacological interventions demonstrated to reduce
the risk of sudden cardiac arrest in patients with impaired
left ventricular function from coronary disease or
cardiomyopathy include â blockers, angiotensin-
converting enzyme inhibitors, and statins [1]. Suppression
of spontaneous ventricular arrhythmias with

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Apollo Medicine, Vol. 8, No. 3, September 2011 234
antiarrhythmic agents has been shown to have a neutral or
negative effect on mortality in prospective, randomized
trials [1].
Role of ICD
Use of the ICD has been demonstrated to reduce
sudden death and improve total mortality in selected
patient populations, including those with impaired
ventricular function and those with ischemic or non-
ischemic cardiomyopathy [53]. Multiple clinical trials
randomizing several thousand patients have demonstrated
that the ICD prevents sudden death and significantly
reduces overall mortality among patients with left
ventricular dysfunction due to dilated non-ischemic
cardiomyopathy or ischemic heart disease. For secondary
prevention, the ICD has proven superior to antiarrhythmic
drug therapy for prolonging survival (Tables 3 & 4).
Recommendations for ICD therapy apply only to
patients who are receiving optimal medical therapy and
have a reasonable expectation of survival with good
functional status for >1 year. When indicated for primary
and secondary prevention, ICD use is beneficial and cost-
effective. Unfortunately, studies suggest that most patients
who have indications for this therapy for primary or
secondary prevention of SCD are not receiving ICDs [73].
Table 3. Primary prevention trials in ICD
Trial Study group EF Control ICD RRR ARR
MADIT Prior MI, EFd” 35%, NS VT, inducible VT, failed IV PA 26 ± 7% 32% 13% - 59% - 19%
CABG Patch Coronary bypass surgery, EF <36%, SAECG (+) 27 ± 6% 18% 18% 0 0
MUSTT Prior MI, EFd” 40%, NSVT, inducible VT 30% 55% 24% -58% - 31%
MADIT II Prior MI (>1 mo), EFd” 30% 23 ± 5% 22% 16% - 28% -6%
DEFINITE Nonischemic CMP, EFd” 35% 21% 14% 8% - 35% -6%
DINAMIT Recent MI (6-40 days) EFd”35%, abnormal HRV,
mean 24 hr HR > 80/min 28 ± 5% 17% 19% NA NA
SCD- HeFT Class II/III CHF, EFd” 35% 25% 36% 29% - 23% - 7%
IRIS <30 days post MI, HR>90, NSVT 35 ± 9% 23% 22% NA NA
Table 4. Secondary prevention trials in ICD
Trial Study group EF Control ICD RRR ARR
AVID VF, VT-syncopeVT with EF d” 40% 32 ± 13% 25% 18% - 27% - 7%
CIDS VF, VT-syncopeVT with EF d” 35% & CL<400 ms,
unmonitored syncope with subsequent spontaneous
or induced VT 34 ± 14% 21% 15% - 30% - 6%
CASH Cardiac arrest survivors (VF, VT) 46 ± 18% 44% 12% - 37% - 8%
Table 5. Clinical strategies to improve outcomes
from sudden cardiac death
Prevention of risk factor development for CAD.
Primary prevention and secondary prevention of SCD.
Appropriate use of -blocker, ACE inhibitor &
statins.
ICD use in selected patientsCommunity-based
public access to defibrillation programs.
Regionalized systems of post-resuscitation hospital
care.
Improving outcomes in clinical practice and the
community
There are many opportunities for clinicians to predict
and prevent SCD in their practices and their communities
(Tables 5).
Although there has been considerable progress in
understanding the mechanisms, risk factors, and
epidemiology of sudden cardiac arrest, it is evident that
much remains unknown. Further basic, translational,
clinical, and population research is needed to develop
novel strategies to reduce the burden of SCD.

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