- Email: [email protected]
Evidence-based analysis of risk factors for sudden cardiac death
Evidence-based analysis of risk factors for sudden cardiac death Jeffrey J. Goldberger, MD, FHRS From the Northwestern University Feinberg School of Medicine, Division of Cardiology, Chicago, Illinois. Identifying risk factors to predict sudden cardiac death (SCD) is an important area of investigation. Current techniques are limited. Several issues result in limitations in the design and interpretation of studies focused on risk stratification to identify patients at risk for fatal ventricular tachyarrhythmias. These include the uncertainty in the identification of SCD, the plurality of causes of SCD, and the complexity of the pathophysiology of the development of fatal ventricular tachyarrhythmias. Understanding the ways in
Introduction In the last several decades, important advances have been made in the identification and treatment of patients at risk for sudden cardiac death (SCD). Vast amounts of data have been accumulated regarding identification of risk factors and interventions designed to reduce the incidence of SCD. Because there are several purposes for the pursuit and identification of risk factors for SCD, it stands to reason that the process of accumulating evidence varies. Some of the issues related to evidence-based analysis of risk factors are elaborated herein.
Linking risk factors to SCD One of the main reasons to identify risk factors is so that risk can be modified, lowered, or eliminated by some form of intervention. In general, the more closely linked the risk factor is to the disease/problem whose risk is being predicted, the more likely it is that interventions based on this risk factor will modify the risk. Hence, arises the first challenge in the evidence based analysis of risk for SCD arises. In general, the risk factors discussed in this supplement and related documents focus on risk for arrhythmic SCD, specifically that caused by ventricular tachycardia or ventricular fibrillation. The interest in this entity relates to the availability of both medical and device therapies to prevent SCD caused by these arrhythmias. Although SCD is an entity familiar to practitioners who treat cardiac patients, it is nevertheless not a disease or a specific diagnosis. SCD is typically defined as death of any cardiac disease that occurs out of hospital, in an emergency
Dr Goldberger receives support from the Path to Improved Risk Stratification, a not for profit think tank on risk stratification. Address reprint requests and correspondence: Dr. Jeffrey Goldberger, Northwestern University Feinberg School of Medicine, Division of Cardiology, 251 East Huron, Feinberg Pavilion, Chicago, Illinois 60611. E-mail address: [email protected].
which evidence is accumulated to identify a risk factor for SCD and the strength of evidence that is required for clinical decisionmaking, as opposed to identifying associations, are critical steps to advancing the field. KEYWORDS Risk stratification; Sudden cardiac death (Heart Rhythm 2009;6:S2–S7) © 2009 Published by Elsevier Inc. on behalf of Heart Rhythm Society.
department, or in an individual reported dead on arrival to a hospital within 1 hour after the onset of symptoms, although various durations up to 24 hours have been used. However, SCD may be caused by bradyarrhythmias or nonarrhythmic causes; in patients with an implantable cardioverter defibrillator (ICD) and SCD, ventricular tachyarrhythmias are recorded by the device in only approximately 40% to 70% of cases.1-3 For example, Pratt et al1 evaluated the precision of the classification of SCD. They noted that only 7 of 17 patients who were classified to have sudden deaths had ICD discharges near the time of death. Other causes of sudden death were myocardial infarction, pulmonary embolism, cerebral infarction, and ruptured thoracic and abdominal aortic aneurysms. Thus, the clinical diagnosis of SCD is not synonymous with a fatal ventricular tachyarrhythmia. Although it is often inferred that SCD is arrhythmic SCD, particularly in the context of studies evaluating risk factors for fatal ventricular tachyarrhythmias, in the remainder of this document, the term SCD will continue to refer to the common usage of this term as defined above, understanding that many of these events may not be arrhythmic. Arrhythmic SCD or fatal ventricular tachyarrhythmias will be used to refer only to those SCDs caused by these arrhythmias. Many risk factors have been identified as being associated with increased risk for ventricular tachycardia/fibrillation and/or SCD (Table 1). However, many of these risk factors are also associated with increased risk for nonsudden death. For example, patients with low left ventricular ejection fraction are at increased risk for both SCD and nonsudden death. Thus, the utility of risk factors will depend on the strength of the competing risks. Given the imprecision of the diagnosis of SCD and the competing risks related to risk factors for SCD, it is critical to examine the nature of studies providing the evidence linking a risk factor to subsequent fatal ventricular tachyarrhythmias. Based on the previous discussion, it would seem appealing to use fatal ventricular tachyarrhythmias as the end point
1547-5271/$ -see front matter © 2009 Published by Elsevier Inc. on behalf of Heart Rhythm Society.
doi:10.1016/j.hrthm.2008.11.007
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Analysis of Risk Factors for SCD
Table 1 Potential risk factors identifying patients with coronary artery disease at increased risk for sudden cardiac death Imaging-based modalities Left ventricular ejection fraction Infarct size Infarct border zone (MRI) ECG-based variables QRS duration QT interval/QT dispersion Signal averaged ECG Exercise test–based variables Heart rate recovery Recovery ventricular ectopy T-wave alternans Exercise capacity/functional class Long-term ambulatory ECG (Holter) Ventricular ectopic activity Heart rate variability Heart rate turbulence Other Baroreceptor sensitivity Electrophysiologic testing Myocardial ischemia ECG ⫽ electrocardiograph; MRI ⫽ magnetic resonance imaging.
for studies evaluating risk factors for arrhythmic SCD. However, it is fairly uncommon to have monitoring information at the time of death in large populations, precluding the use of this end point. Because fatal ventricular tachyarrhythmias do cause SCD, this entity has emerged as a surrogate. In addition to the multiple diagnoses that may be the actual cause of SCD, the circumstances surrounding an individual’s death may not be clear enough to differentiate sudden from nonsudden death or to establish a cardiac cause. For this reason, cardiac or total mortality are also often used as surrogates to identify risk factors. As these surrogates are used that incorporate deaths not related to fatal ventricular tachyarrhythmias, the strength of evidence linking the risk factor to fatal ventricular tachyarrhythmias diminishes. There are several potential evidentiary sources for identifying a risk factor as predictive of fatal ventricular tachyarrhythmias. One could perform an observational trial to evaluate a cohort of patients with and without a particular risk factor and evaluate for the presence of SCD in these 2 groups. Because of the imprecision of the diagnosis of SCD, even if the risk factor is shown to be associated with an increased risk of SCD, the risk factor may be predictive of other cardiovascular events, rather than fatal ventricular tachyarrhythmias. Another possibility is to identify patients with a risk factor and perform an interventional trial in which the intervention is designed to reduce the incidence of arrhythmic SCD. Because many interventions (i.e., betablockers, angiotensin-converting enzyme inhibitors, statins) that may reduce the incidence of fatal ventricular tachyarrhythmias may also prevent other cardiovascular events, this approach may also misidentify the risk factor as predictive of fatal ventricular tachyarrhythmias. The one inter-
S3 vention that is specific for prevention of fatal ventricular tachyarrhythmias is the ICD. The ICD treats ventricular tachyarrhythmias and has been shown to have an efficacy rate of 98% for these arrhythmias.4 The normally functioning ICD neither prevents nor promotes these arrhythmias, but instead treats them when they occur. Because the ICD does not affect mortality unrelated to fatal ventricular tachyarrhythmias, the difference in total mortality between an ICD-treated group and a similar group not treated with ICDs represents the deaths caused by fatal ventricular tachyarrhythmias. As such, the ICD can be a very specific probe to identify whether a hypothesized risk factor is indeed a risk factor for fatal ventricular tachyarrhythmias. Ideally, one would like to show that patients with the risk factor have a much higher event rate than those without the risk factor. However, ICD intervention trials are generally not structured in this manner. Evidence for the utility or lack of utility of a specific risk factor cannot always be determined. For example, in the Multicenter Automatic Defibrillator Implantation Trial,5 patients with left ventricular ejection fraction ⱕ35%, nonsustained ventricular tachycardia, and inducible ventricular tachyarrhythmia on electrophysiologic study (but not suppressible by procainamide) were enrolled. ICD therapy in these patients was associated with improved survival. Although one could conclude that the use of the combination of enrollment criteria identified a high-risk group that benefits from an ICD, it is not possible to know which of the risk factors were important as a comparison group without the risk factor was not studied. Table 2 lists a number of ICD trials in patients with coronary artery disease. All trials included only patients with a low ejection fraction. The first 4 trials showed a reduction in mortality, whereas the last 2 did not. Although there were clearly other selection criteria for each of the trials, it is clear that even low ejection fraction does not always identify a group of patients with high risk for fatal ventricular tachyarrhythmias that benefits from an ICD. Table 2 Summary of selected studies using ICD therapy and identified risk predictors in patients with coronary artery disease
5
MADIT MUSTT28 MADIT-II19 SCD-HeFT20 ABCD29 CABG-Patch30 DINAMIT21
NYHA
NSVT
LVEF
I-III I-III I-III II-III I-III I-III I-III
Yes Yes
ⱕ35% ⱕ40% ⱕ30% ⱕ35% ⱕ40% ⱕ35% ⱕ35%
Yes
Other tests EPS EPS TWA, EPS SAECG HRV
Improved survival in ICD group Yes Yes Yes Yes Yes No No
CABG ⫽ coronary artery bypass graft surgery; EPS ⫽ electrophysiology study; HRV ⫽ heart rate variability; ICD ⫽ implantable cardioverterdefibrillator; LVEF ⫽ left ventricular ejection fraction; MI ⫽ myocardial infarction; NSVT ⫽ nonsustained ventricular tachycardia; NYHA ⫽ New York Heart Association class for congestive heart failure; SAECG ⫽ signalaveraged ECG; TWA ⫽ T-wave alternans.
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Another approach for evaluating risk factors for arrhythmic SCD that has been used is to employ a long-term implantable monitor, as in the Cardiac Arrhythmias and RIsk Stratification after Myocardial infArction (CARISMA)6 trial. In this way, if SCD occurs, the presence or absence of a fatal ventricular tachyarrhythmia can be documented. It is clear that our inability to capture the specific end point of interest—fatal ventricular tachyarrhythmias—in most studies evaluating risk factors for this is a critical difficulty in accumulating evidence on the utility of a specific risk factor to predict future fatal ventricular tachyarrhythmias. However, given the multiple types of studies that can be performed, observational and interventional, and the availability of rigorous adjudication protocols, a strong case for an important risk factor for arrhythmic SCD can be established when they are all considered.
There may also be risk factors for SCD that by their very nature are unmodifiable. For example, it has recently been shown that family history of SCD is an important risk factor for SCD.10,11 Presently, this risk is not modifiable but further study of the genetic underpinnings of this risk factor could potentially identify etiologies or predisposing factors that are linked pathophysiologically to SCD. Thus, the nature of risk factors for arrhythmic SCD varies. When a risk factor is identified, it is important to examine the evidence for whether the risk factor is linked by an association or a pathophysiologic link, and whether it is modifiable or treatable. Better understanding of the relationship of risk factors to the pathogenesis of SCD may improve future therapeutic approaches.
Risk factors for arrhythmic SCD—association and causation
As noted above, ICD intervention trials provide very specific information related to arrhythmic SCD. However, it is important to consider what information ICD intervention trials provide relative to risk stratification. The inclusion criteria generally identify a group of patients who are believed to be at risk for SCD. Patients are then randomized to receive an ICD or standard medical therapy. If the ICD intervention group experiences improved survival, this is presumed to be related to a reduction in arrhythmic SCD in this group. Thus, the identified risk factors are verified to identify a group of patients at risk for SCD. However, this does not establish that patients without these risk factors are not at risk for SCD. Because they were not included in the inclusion criteria, this issue was not studied. The best example of this issue relates to left ventricular ejection fraction. Since its early identification as an important risk factor for total mortality after a myocardial infarction,12 much of the focus on prevention of SCD has been targeted to patients with low ejection fraction. Given the higher risk in this group, this is an appropriate first step. Table 2 lists a number of ICD trials that have studied patients with low ejection fraction and shown benefit from an ICD. These studies did not include patients in the higher ejection fraction group. Although these patients are generally at lower risk than patients with a more depressed ejection fraction, there is still substantial risk in this group. Because of this risk and the much larger size of this group, the absolute number of SCDs in patients with ejection fractions ⬎35% is higher than among those with ejection fractions ⬍35%. This was shown in the Oregon Sudden Unexpected Death Study,13 in which only one-third of patients who experienced SCD had ejection fractions ⬍35%. In addition, not all patients meeting the inclusion criteria for ICD intervention trials necessarily benefit from the ICD. There are 2 main reasons why this may be the case. If the inclusion criteria are broad enough, there may be very-lowrisk patients within the patient population who have a very low rate of arrhythmic SCD and therefore experience no significant benefit from ICD implantation. There may also be a high-risk subgroup that has competing risks for non-
There is a long history of identification of risk factors to identify groups of patients at risk for SCD (Table 1). Many of these have been reviewed in a recent scientific statement.7 Among those on the list are some readily identifiable risk factors that are used today in clinical decision making and a host of other risk factors that have shown either limited utility or applicability. Identification of a risk factor may provide several pieces of information. The risk factor may be linked to the pathogenesis of the fatal ventricular arrhythmias, or it may not. For example, inducible ventricular tachycardia by electrophysiologic testing is considered to be a risk factor that is linked to pathogenesis of the ventricular tachyarrhythmias, because this identifies the presence of a fixed substrate. In contrast, the presence of ventricular ectopy, although clearly a risk factor, is no longer believed to be etiologically necessarily related to the pathogenesis of ventricular tachyarrhythmias. Eradication of premature ventricular complexes in the Cardiac Arrhythmia Suppression Trial8 was paradoxically associated with an increased risk of mortality. Although this may not be a specific target for treatment, it could serve as the catalyst to initiate other treatments to reduce arrhythmic SCD. When a risk factor is identified, there are frequently attempts to modify the risk factor. If a risk factor is modifiable and its modification reduces the incidence of SCD, this provides evidence that the risk factor is related to the pathogenesis of the ventricular arrhythmias responsible for SCD. There are multiple examples of modifiable risk factors whose modification does not reduce the incidence of SCD. As noted above, the presence of premature ventricular complexes is a modifiable risk factor, but their eradication does not reduce the risk of SCD.8 Hull et al9 showed that heart rate variability can be increased in a canine post–myocardial infarction model, but this is not associated with a reduction in ventricular fibrillation associated with exercise and ischemia. As yet, there is no specific risk factor for SCD that can be modified to reduce its incidence.
Inferring evidence regarding risk factors from ICD intervention trials
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Analysis of Risk Factors for SCD
sudden cardiac death that are so substantial that there may be no benefit related to the ICD. A number of retrospective analyses demonstrate these possibilities. Below are several examples that must be prefaced with the caveat that tremendous caution is required in the interpretation of secondary, retrospective analyses. However, the questions posed by these analyses are thought provoking, provide areas for further research, and highlight some of the limitations inherent in extrapolating information about risk factors from ICD intervention trials. In a retrospective analysis of the Multicenter Automatic Defibrillator Implantation Trial II (MADIT-II) study,14 the investigators identified several risk factors in their population. These included New York Heart Association functional class ⬎ II, age ⬎ 70 years, blood urea nitrogen ⬎ 26 mg/dl, QRS duration ⬎ 0.12 s, and atrial fibrillation. The investigators showed a U-shaped curve for ICD benefit, in which patients with no risk factors and those with very high risk showed no benefit of ICD therapy. ICD benefit was noted in those with one to several of the risk factors. In a retrospective analysis of the Multicenter Unsustained Tachycardia Trial,15 several variables were identified that delineated risk for SCD and total mortality, allowing for identification of low-risk subgroups within the patient population, even those with ejection fractions ⬍30%. This analysis also highlighted the fact that risk is a continuous function, despite the fact that clinicians tend to dichotomize risk so that binary treatment decisions can be made. ICD intervention trials often exclude high-risk subjects, such as those with end-stage renal disease. Because the competing mortality risks in this population may be significant, it is unclear whether the same set of risk factors that are used to identify patients without end-stage renal disease who benefit from an ICD can be used in this population.16 The most recent published guidelines17 and the Center for Medicare and Medicaid Services18 note that primary prevention ICDs should be considered when patients are beyond 40 days from their myocardial infarction. It is interesting to evaluate the evidence for this recommendation. The MADIT-II19 and Sudden Cardiac Death in Heart Failure Trial20 enrolled patients beyond 30 days after myocardial infarction and showed a benefit to ICD therapy. In contrast, the Defibrillator in Acute Myocardial Infarction Trial (DINAMIT)21 enrolled patients between 6 and 40 days after myocardial infarction with ejection fractions of 35% or less and impaired autonomic function manifested by depressed heart rate variability or elevated average 24-hour heart rate. Patients were randomized to receive an ICD or not. During a mean follow-up of 30 months, there was no difference in mortality between the 2 groups (hazard ratio for death in the ICD group 1.08, P ⫽ .66). On the surface, therefore, it seems reasonable to use the evidence from these trials to set the time frame for implantation to be beyond 40 days after a myocardial infarction, as in the current guidelines. As the guidelines have set this demarcation, it is reasonable to query whether the evidence supports a change
S5 in risk to the patient as he or she crosses the 40-day time mark after myocardial infarction. When considering DINAMIT,21 patients were enrolled between 6 and 40 days (mean 18 days). One could imagine a very similar study that would have enrolled the very same patients, but at 41 days after their myocardial infarction rather than between 6 and 40 days. The mean delay in enrollment would be 23 days. By examining the survival curve of the study, it is apparent that a very small number of people in both treatment groups would have died in this 3-week window before the new 41-day enrollment time, but a similar number in both groups. If one then extrapolates the survival curves from 41 days to 30 months, it is also clear that there is no difference in survival; even though these patients would have been enrolled at day 41, they still would not have benefited from an ICD. In the MADIT-II, a retrospective analysis was performed evaluating the time dependence of mortality risk and ICD benefit after myocardial infarction.22 This revealed that only patients beyond 18 months from their myocardial infarction benefited from the ICD. Another observational study of 700 post–myocardial infarction patients also showed that the risk for SCD begins to significantly increase approximately 20 months after myocardial infarction.6 It is important to reconcile these observations with other data that do suggest an increased risk for SCD in this early time period.23,24 It is interesting to note that eplerenone, a selective aldosterone blocker with numerous properties including inhibition of ventricular remodeling and collagen deposition, decreased the overall risk of SCD by 21% when given to patients with acute myocardial infarction complicated by left ventricular dysfunction and heart failure.24 This collection of studies shows that there is an early risk of SCD after myocardial infarction that can be ameliorated by eplerenone but not an ICD. A potential explanation is that the pathophysiology of SCD may vary in different clinical situations, specifically early postinfarction versus the later time period.
How strong a predictor is necessary to discriminate patients at high versus low risk for SCD? Identification of risk factors for SCD may provide useful information for several venues. Some risk factors may identify areas for further investigation into the pathogenesis of life-threatening arrhythmias. For example, the identification of a positive family history for SCD as a risk factor serves as a springboard for exploring underlying genetic propensities. From a clinical perspective, given the large public health problem of SCD, it is important to focus on strategies to use these risk factors to discriminate those at risk from those not at risk for SCD. Ideally, one would wish to have a test or strategy that was able to reliably identify all those patients who will experience SCD (within some time frame) and classify all others as low risk. The ability to discriminate between these groups is related to the odds or hazard ratio of the test. If the identification of risk factors is needed to make clinical decisions, the risk factors need to have high discrimination ability.25 This is most appropriately assessed
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Figure 1 Probability distributions of a marker or risk factor in cases (i.e., patients with sudden cardiac death, solid curves) and controls (i.e., patients without sudden cardiac death, dashed curves). It has been assumed that the marker has a mean of 0 and a standard deviation of 0.5 and is normally distributed with the same variance in cases and controls. The odds ratio (OR) per unit increase in the marker is shown. Reprinted with permission.26
by the receiver-operator characteristic (ROC) curve. It has been well demonstrated that for an individual risk factor alone to substantially affect the ROC curve, the hazard ratio associated with that risk factor must be quite large. Pepe et al26 note that extremely strong associations are required for meaningful classification accuracy. They further note that “it is common for a marker to have independent association with outcome that is considered strong by epidemiologic standards, but does not contribute meaningfully to improved risk discrimination”. Figure 1 shows the overlap between cases (i.e., those with SCD) and controls based on the presence or absence of a hypothesized risk factor. Large overlaps (poor discrimination) are noted even with an odds ratio of 9. As the odds ratio begins to exceed 20, the marker begins to provide good separation between the groups. Bailey et al27 summarized the results of multiple studies evaluating risk factors for SCD. Although there are isolated studies that demonstrate relative risks or hazard ratios for various tests in the 20s, in aggregate, the relative risk or hazard ratios for these risk factors were generally in the 2 to 6 range. This holds true even for left ventricular ejection fraction,27 considered to be one of the strongest risk factors for SCD. Thus, current individual techniques or risk factors are not likely to have adequate discriminatory power for a complete evaluation of risk for SCD. As discussed previously, it is well known that even left ventricular ejection fraction lacks adequate discriminatory power. Given the limitations of current risk factors to adequately discriminate risk for SCD, what does the future hold? New techniques for risk stratification are constantly being developed and evaluated. Although it is possible that a new imaging, genetic testing, or proteomic approach could identify a risk factor with high discriminatory power, the multifactoral nature/etiology of SCD may limit our ability to identify such a marker. An alternative approach was modeled by Bailey et al.27 They suggested a 3-stage approach in which testing is performed at each stage to identify patients at low, intermediate, and high risk for a major arrhythmic event. The patient proceeds for further testing in the next
Heart Rhythm, Vol 6, No 3S, March Supplement 2009 stage only if the testing in the current stage suggests intermediate risk. They calculated event rates based on the data available in the literature (this was not an actual patient study). Thus, stage 1 testing would include a signal-averaged electrocardiogram and measurement of left ventricular ejection fraction. If both are positive, the risk for a major arrhythmic event is 38.7%. If both are negative, the risk is 2.2%. In both of these cases, no further testing would be recommended. However, if only 1 is positive, the probability of a major arrhythmic event over 2 years was predicted to be 10.6% and would justify further testing. Stage 2 testing is similarly performed with a Holter monitor for assessment of ventricular arrhythmias and heart rate variability. Stage 3 consists of performing electrophysiologic studies on the stage 2 patients in whom only 1 is positive. Using this algorithm, they determined that 80% of the population would be classified as low risk with a 2.9% probability of a major arrhythmic event, whereas 11.8% would be classified as high risk with a 41.4% risk of a major arrhythmic event. Only 8.2% of the population would be unstratified with an 8.9% probability of a major arrhythmic event over 2 years. The use of this kind of tiered testing can therefore result in a strategy with high discrimination. Several studies are underway in which data from multiple risk stratifiers are being collected. Ultimately, clinical data on using such a strategy will be needed to establish its utility for adequate patient discrimination. Accumulating evidence for risk stratification of patients at risk for arrhythmic SCD is extremely challenging. Our knowledge of the specific precipitants of arrhythmic SCD just before the event is poor. Our ability to identify the event is limited. The risk factors that are used are also often predictors for nonsudden cardiac death. Large-scale clinical trials are often not designed focused on the question of risk stratification. However, the mosaic of evidence that is available from many observational and interventional studies provides important information regarding these risk factors and serves as a useful guide for directing future efforts to improve our ability to stratify risk.
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Introduction In the last several decades, important advances have been made in the identification and treatment of patients at risk for sudden cardiac death (SCD). Vast amounts of data have been accumulated regarding identification of risk factors and interventions designed to reduce the incidence of SCD. Because there are several purposes for the pursuit and identification of risk factors for SCD, it stands to reason that the process of accumulating evidence varies. Some of the issues related to evidence-based analysis of risk factors are elaborated herein.
Linking risk factors to SCD One of the main reasons to identify risk factors is so that risk can be modified, lowered, or eliminated by some form of intervention. In general, the more closely linked the risk factor is to the disease/problem whose risk is being predicted, the more likely it is that interventions based on this risk factor will modify the risk. Hence, arises the first challenge in the evidence based analysis of risk for SCD arises. In general, the risk factors discussed in this supplement and related documents focus on risk for arrhythmic SCD, specifically that caused by ventricular tachycardia or ventricular fibrillation. The interest in this entity relates to the availability of both medical and device therapies to prevent SCD caused by these arrhythmias. Although SCD is an entity familiar to practitioners who treat cardiac patients, it is nevertheless not a disease or a specific diagnosis. SCD is typically defined as death of any cardiac disease that occurs out of hospital, in an emergency
Dr Goldberger receives support from the Path to Improved Risk Stratification, a not for profit think tank on risk stratification. Address reprint requests and correspondence: Dr. Jeffrey Goldberger, Northwestern University Feinberg School of Medicine, Division of Cardiology, 251 East Huron, Feinberg Pavilion, Chicago, Illinois 60611. E-mail address: [email protected].
which evidence is accumulated to identify a risk factor for SCD and the strength of evidence that is required for clinical decisionmaking, as opposed to identifying associations, are critical steps to advancing the field. KEYWORDS Risk stratification; Sudden cardiac death (Heart Rhythm 2009;6:S2–S7) © 2009 Published by Elsevier Inc. on behalf of Heart Rhythm Society.
department, or in an individual reported dead on arrival to a hospital within 1 hour after the onset of symptoms, although various durations up to 24 hours have been used. However, SCD may be caused by bradyarrhythmias or nonarrhythmic causes; in patients with an implantable cardioverter defibrillator (ICD) and SCD, ventricular tachyarrhythmias are recorded by the device in only approximately 40% to 70% of cases.1-3 For example, Pratt et al1 evaluated the precision of the classification of SCD. They noted that only 7 of 17 patients who were classified to have sudden deaths had ICD discharges near the time of death. Other causes of sudden death were myocardial infarction, pulmonary embolism, cerebral infarction, and ruptured thoracic and abdominal aortic aneurysms. Thus, the clinical diagnosis of SCD is not synonymous with a fatal ventricular tachyarrhythmia. Although it is often inferred that SCD is arrhythmic SCD, particularly in the context of studies evaluating risk factors for fatal ventricular tachyarrhythmias, in the remainder of this document, the term SCD will continue to refer to the common usage of this term as defined above, understanding that many of these events may not be arrhythmic. Arrhythmic SCD or fatal ventricular tachyarrhythmias will be used to refer only to those SCDs caused by these arrhythmias. Many risk factors have been identified as being associated with increased risk for ventricular tachycardia/fibrillation and/or SCD (Table 1). However, many of these risk factors are also associated with increased risk for nonsudden death. For example, patients with low left ventricular ejection fraction are at increased risk for both SCD and nonsudden death. Thus, the utility of risk factors will depend on the strength of the competing risks. Given the imprecision of the diagnosis of SCD and the competing risks related to risk factors for SCD, it is critical to examine the nature of studies providing the evidence linking a risk factor to subsequent fatal ventricular tachyarrhythmias. Based on the previous discussion, it would seem appealing to use fatal ventricular tachyarrhythmias as the end point
1547-5271/$ -see front matter © 2009 Published by Elsevier Inc. on behalf of Heart Rhythm Society.
doi:10.1016/j.hrthm.2008.11.007
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Analysis of Risk Factors for SCD
Table 1 Potential risk factors identifying patients with coronary artery disease at increased risk for sudden cardiac death Imaging-based modalities Left ventricular ejection fraction Infarct size Infarct border zone (MRI) ECG-based variables QRS duration QT interval/QT dispersion Signal averaged ECG Exercise test–based variables Heart rate recovery Recovery ventricular ectopy T-wave alternans Exercise capacity/functional class Long-term ambulatory ECG (Holter) Ventricular ectopic activity Heart rate variability Heart rate turbulence Other Baroreceptor sensitivity Electrophysiologic testing Myocardial ischemia ECG ⫽ electrocardiograph; MRI ⫽ magnetic resonance imaging.
for studies evaluating risk factors for arrhythmic SCD. However, it is fairly uncommon to have monitoring information at the time of death in large populations, precluding the use of this end point. Because fatal ventricular tachyarrhythmias do cause SCD, this entity has emerged as a surrogate. In addition to the multiple diagnoses that may be the actual cause of SCD, the circumstances surrounding an individual’s death may not be clear enough to differentiate sudden from nonsudden death or to establish a cardiac cause. For this reason, cardiac or total mortality are also often used as surrogates to identify risk factors. As these surrogates are used that incorporate deaths not related to fatal ventricular tachyarrhythmias, the strength of evidence linking the risk factor to fatal ventricular tachyarrhythmias diminishes. There are several potential evidentiary sources for identifying a risk factor as predictive of fatal ventricular tachyarrhythmias. One could perform an observational trial to evaluate a cohort of patients with and without a particular risk factor and evaluate for the presence of SCD in these 2 groups. Because of the imprecision of the diagnosis of SCD, even if the risk factor is shown to be associated with an increased risk of SCD, the risk factor may be predictive of other cardiovascular events, rather than fatal ventricular tachyarrhythmias. Another possibility is to identify patients with a risk factor and perform an interventional trial in which the intervention is designed to reduce the incidence of arrhythmic SCD. Because many interventions (i.e., betablockers, angiotensin-converting enzyme inhibitors, statins) that may reduce the incidence of fatal ventricular tachyarrhythmias may also prevent other cardiovascular events, this approach may also misidentify the risk factor as predictive of fatal ventricular tachyarrhythmias. The one inter-
S3 vention that is specific for prevention of fatal ventricular tachyarrhythmias is the ICD. The ICD treats ventricular tachyarrhythmias and has been shown to have an efficacy rate of 98% for these arrhythmias.4 The normally functioning ICD neither prevents nor promotes these arrhythmias, but instead treats them when they occur. Because the ICD does not affect mortality unrelated to fatal ventricular tachyarrhythmias, the difference in total mortality between an ICD-treated group and a similar group not treated with ICDs represents the deaths caused by fatal ventricular tachyarrhythmias. As such, the ICD can be a very specific probe to identify whether a hypothesized risk factor is indeed a risk factor for fatal ventricular tachyarrhythmias. Ideally, one would like to show that patients with the risk factor have a much higher event rate than those without the risk factor. However, ICD intervention trials are generally not structured in this manner. Evidence for the utility or lack of utility of a specific risk factor cannot always be determined. For example, in the Multicenter Automatic Defibrillator Implantation Trial,5 patients with left ventricular ejection fraction ⱕ35%, nonsustained ventricular tachycardia, and inducible ventricular tachyarrhythmia on electrophysiologic study (but not suppressible by procainamide) were enrolled. ICD therapy in these patients was associated with improved survival. Although one could conclude that the use of the combination of enrollment criteria identified a high-risk group that benefits from an ICD, it is not possible to know which of the risk factors were important as a comparison group without the risk factor was not studied. Table 2 lists a number of ICD trials in patients with coronary artery disease. All trials included only patients with a low ejection fraction. The first 4 trials showed a reduction in mortality, whereas the last 2 did not. Although there were clearly other selection criteria for each of the trials, it is clear that even low ejection fraction does not always identify a group of patients with high risk for fatal ventricular tachyarrhythmias that benefits from an ICD. Table 2 Summary of selected studies using ICD therapy and identified risk predictors in patients with coronary artery disease
5
MADIT MUSTT28 MADIT-II19 SCD-HeFT20 ABCD29 CABG-Patch30 DINAMIT21
NYHA
NSVT
LVEF
I-III I-III I-III II-III I-III I-III I-III
Yes Yes
ⱕ35% ⱕ40% ⱕ30% ⱕ35% ⱕ40% ⱕ35% ⱕ35%
Yes
Other tests EPS EPS TWA, EPS SAECG HRV
Improved survival in ICD group Yes Yes Yes Yes Yes No No
CABG ⫽ coronary artery bypass graft surgery; EPS ⫽ electrophysiology study; HRV ⫽ heart rate variability; ICD ⫽ implantable cardioverterdefibrillator; LVEF ⫽ left ventricular ejection fraction; MI ⫽ myocardial infarction; NSVT ⫽ nonsustained ventricular tachycardia; NYHA ⫽ New York Heart Association class for congestive heart failure; SAECG ⫽ signalaveraged ECG; TWA ⫽ T-wave alternans.
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Another approach for evaluating risk factors for arrhythmic SCD that has been used is to employ a long-term implantable monitor, as in the Cardiac Arrhythmias and RIsk Stratification after Myocardial infArction (CARISMA)6 trial. In this way, if SCD occurs, the presence or absence of a fatal ventricular tachyarrhythmia can be documented. It is clear that our inability to capture the specific end point of interest—fatal ventricular tachyarrhythmias—in most studies evaluating risk factors for this is a critical difficulty in accumulating evidence on the utility of a specific risk factor to predict future fatal ventricular tachyarrhythmias. However, given the multiple types of studies that can be performed, observational and interventional, and the availability of rigorous adjudication protocols, a strong case for an important risk factor for arrhythmic SCD can be established when they are all considered.
There may also be risk factors for SCD that by their very nature are unmodifiable. For example, it has recently been shown that family history of SCD is an important risk factor for SCD.10,11 Presently, this risk is not modifiable but further study of the genetic underpinnings of this risk factor could potentially identify etiologies or predisposing factors that are linked pathophysiologically to SCD. Thus, the nature of risk factors for arrhythmic SCD varies. When a risk factor is identified, it is important to examine the evidence for whether the risk factor is linked by an association or a pathophysiologic link, and whether it is modifiable or treatable. Better understanding of the relationship of risk factors to the pathogenesis of SCD may improve future therapeutic approaches.
Risk factors for arrhythmic SCD—association and causation
As noted above, ICD intervention trials provide very specific information related to arrhythmic SCD. However, it is important to consider what information ICD intervention trials provide relative to risk stratification. The inclusion criteria generally identify a group of patients who are believed to be at risk for SCD. Patients are then randomized to receive an ICD or standard medical therapy. If the ICD intervention group experiences improved survival, this is presumed to be related to a reduction in arrhythmic SCD in this group. Thus, the identified risk factors are verified to identify a group of patients at risk for SCD. However, this does not establish that patients without these risk factors are not at risk for SCD. Because they were not included in the inclusion criteria, this issue was not studied. The best example of this issue relates to left ventricular ejection fraction. Since its early identification as an important risk factor for total mortality after a myocardial infarction,12 much of the focus on prevention of SCD has been targeted to patients with low ejection fraction. Given the higher risk in this group, this is an appropriate first step. Table 2 lists a number of ICD trials that have studied patients with low ejection fraction and shown benefit from an ICD. These studies did not include patients in the higher ejection fraction group. Although these patients are generally at lower risk than patients with a more depressed ejection fraction, there is still substantial risk in this group. Because of this risk and the much larger size of this group, the absolute number of SCDs in patients with ejection fractions ⬎35% is higher than among those with ejection fractions ⬍35%. This was shown in the Oregon Sudden Unexpected Death Study,13 in which only one-third of patients who experienced SCD had ejection fractions ⬍35%. In addition, not all patients meeting the inclusion criteria for ICD intervention trials necessarily benefit from the ICD. There are 2 main reasons why this may be the case. If the inclusion criteria are broad enough, there may be very-lowrisk patients within the patient population who have a very low rate of arrhythmic SCD and therefore experience no significant benefit from ICD implantation. There may also be a high-risk subgroup that has competing risks for non-
There is a long history of identification of risk factors to identify groups of patients at risk for SCD (Table 1). Many of these have been reviewed in a recent scientific statement.7 Among those on the list are some readily identifiable risk factors that are used today in clinical decision making and a host of other risk factors that have shown either limited utility or applicability. Identification of a risk factor may provide several pieces of information. The risk factor may be linked to the pathogenesis of the fatal ventricular arrhythmias, or it may not. For example, inducible ventricular tachycardia by electrophysiologic testing is considered to be a risk factor that is linked to pathogenesis of the ventricular tachyarrhythmias, because this identifies the presence of a fixed substrate. In contrast, the presence of ventricular ectopy, although clearly a risk factor, is no longer believed to be etiologically necessarily related to the pathogenesis of ventricular tachyarrhythmias. Eradication of premature ventricular complexes in the Cardiac Arrhythmia Suppression Trial8 was paradoxically associated with an increased risk of mortality. Although this may not be a specific target for treatment, it could serve as the catalyst to initiate other treatments to reduce arrhythmic SCD. When a risk factor is identified, there are frequently attempts to modify the risk factor. If a risk factor is modifiable and its modification reduces the incidence of SCD, this provides evidence that the risk factor is related to the pathogenesis of the ventricular arrhythmias responsible for SCD. There are multiple examples of modifiable risk factors whose modification does not reduce the incidence of SCD. As noted above, the presence of premature ventricular complexes is a modifiable risk factor, but their eradication does not reduce the risk of SCD.8 Hull et al9 showed that heart rate variability can be increased in a canine post–myocardial infarction model, but this is not associated with a reduction in ventricular fibrillation associated with exercise and ischemia. As yet, there is no specific risk factor for SCD that can be modified to reduce its incidence.
Inferring evidence regarding risk factors from ICD intervention trials
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Analysis of Risk Factors for SCD
sudden cardiac death that are so substantial that there may be no benefit related to the ICD. A number of retrospective analyses demonstrate these possibilities. Below are several examples that must be prefaced with the caveat that tremendous caution is required in the interpretation of secondary, retrospective analyses. However, the questions posed by these analyses are thought provoking, provide areas for further research, and highlight some of the limitations inherent in extrapolating information about risk factors from ICD intervention trials. In a retrospective analysis of the Multicenter Automatic Defibrillator Implantation Trial II (MADIT-II) study,14 the investigators identified several risk factors in their population. These included New York Heart Association functional class ⬎ II, age ⬎ 70 years, blood urea nitrogen ⬎ 26 mg/dl, QRS duration ⬎ 0.12 s, and atrial fibrillation. The investigators showed a U-shaped curve for ICD benefit, in which patients with no risk factors and those with very high risk showed no benefit of ICD therapy. ICD benefit was noted in those with one to several of the risk factors. In a retrospective analysis of the Multicenter Unsustained Tachycardia Trial,15 several variables were identified that delineated risk for SCD and total mortality, allowing for identification of low-risk subgroups within the patient population, even those with ejection fractions ⬍30%. This analysis also highlighted the fact that risk is a continuous function, despite the fact that clinicians tend to dichotomize risk so that binary treatment decisions can be made. ICD intervention trials often exclude high-risk subjects, such as those with end-stage renal disease. Because the competing mortality risks in this population may be significant, it is unclear whether the same set of risk factors that are used to identify patients without end-stage renal disease who benefit from an ICD can be used in this population.16 The most recent published guidelines17 and the Center for Medicare and Medicaid Services18 note that primary prevention ICDs should be considered when patients are beyond 40 days from their myocardial infarction. It is interesting to evaluate the evidence for this recommendation. The MADIT-II19 and Sudden Cardiac Death in Heart Failure Trial20 enrolled patients beyond 30 days after myocardial infarction and showed a benefit to ICD therapy. In contrast, the Defibrillator in Acute Myocardial Infarction Trial (DINAMIT)21 enrolled patients between 6 and 40 days after myocardial infarction with ejection fractions of 35% or less and impaired autonomic function manifested by depressed heart rate variability or elevated average 24-hour heart rate. Patients were randomized to receive an ICD or not. During a mean follow-up of 30 months, there was no difference in mortality between the 2 groups (hazard ratio for death in the ICD group 1.08, P ⫽ .66). On the surface, therefore, it seems reasonable to use the evidence from these trials to set the time frame for implantation to be beyond 40 days after a myocardial infarction, as in the current guidelines. As the guidelines have set this demarcation, it is reasonable to query whether the evidence supports a change
S5 in risk to the patient as he or she crosses the 40-day time mark after myocardial infarction. When considering DINAMIT,21 patients were enrolled between 6 and 40 days (mean 18 days). One could imagine a very similar study that would have enrolled the very same patients, but at 41 days after their myocardial infarction rather than between 6 and 40 days. The mean delay in enrollment would be 23 days. By examining the survival curve of the study, it is apparent that a very small number of people in both treatment groups would have died in this 3-week window before the new 41-day enrollment time, but a similar number in both groups. If one then extrapolates the survival curves from 41 days to 30 months, it is also clear that there is no difference in survival; even though these patients would have been enrolled at day 41, they still would not have benefited from an ICD. In the MADIT-II, a retrospective analysis was performed evaluating the time dependence of mortality risk and ICD benefit after myocardial infarction.22 This revealed that only patients beyond 18 months from their myocardial infarction benefited from the ICD. Another observational study of 700 post–myocardial infarction patients also showed that the risk for SCD begins to significantly increase approximately 20 months after myocardial infarction.6 It is important to reconcile these observations with other data that do suggest an increased risk for SCD in this early time period.23,24 It is interesting to note that eplerenone, a selective aldosterone blocker with numerous properties including inhibition of ventricular remodeling and collagen deposition, decreased the overall risk of SCD by 21% when given to patients with acute myocardial infarction complicated by left ventricular dysfunction and heart failure.24 This collection of studies shows that there is an early risk of SCD after myocardial infarction that can be ameliorated by eplerenone but not an ICD. A potential explanation is that the pathophysiology of SCD may vary in different clinical situations, specifically early postinfarction versus the later time period.
How strong a predictor is necessary to discriminate patients at high versus low risk for SCD? Identification of risk factors for SCD may provide useful information for several venues. Some risk factors may identify areas for further investigation into the pathogenesis of life-threatening arrhythmias. For example, the identification of a positive family history for SCD as a risk factor serves as a springboard for exploring underlying genetic propensities. From a clinical perspective, given the large public health problem of SCD, it is important to focus on strategies to use these risk factors to discriminate those at risk from those not at risk for SCD. Ideally, one would wish to have a test or strategy that was able to reliably identify all those patients who will experience SCD (within some time frame) and classify all others as low risk. The ability to discriminate between these groups is related to the odds or hazard ratio of the test. If the identification of risk factors is needed to make clinical decisions, the risk factors need to have high discrimination ability.25 This is most appropriately assessed
S6
Figure 1 Probability distributions of a marker or risk factor in cases (i.e., patients with sudden cardiac death, solid curves) and controls (i.e., patients without sudden cardiac death, dashed curves). It has been assumed that the marker has a mean of 0 and a standard deviation of 0.5 and is normally distributed with the same variance in cases and controls. The odds ratio (OR) per unit increase in the marker is shown. Reprinted with permission.26
by the receiver-operator characteristic (ROC) curve. It has been well demonstrated that for an individual risk factor alone to substantially affect the ROC curve, the hazard ratio associated with that risk factor must be quite large. Pepe et al26 note that extremely strong associations are required for meaningful classification accuracy. They further note that “it is common for a marker to have independent association with outcome that is considered strong by epidemiologic standards, but does not contribute meaningfully to improved risk discrimination”. Figure 1 shows the overlap between cases (i.e., those with SCD) and controls based on the presence or absence of a hypothesized risk factor. Large overlaps (poor discrimination) are noted even with an odds ratio of 9. As the odds ratio begins to exceed 20, the marker begins to provide good separation between the groups. Bailey et al27 summarized the results of multiple studies evaluating risk factors for SCD. Although there are isolated studies that demonstrate relative risks or hazard ratios for various tests in the 20s, in aggregate, the relative risk or hazard ratios for these risk factors were generally in the 2 to 6 range. This holds true even for left ventricular ejection fraction,27 considered to be one of the strongest risk factors for SCD. Thus, current individual techniques or risk factors are not likely to have adequate discriminatory power for a complete evaluation of risk for SCD. As discussed previously, it is well known that even left ventricular ejection fraction lacks adequate discriminatory power. Given the limitations of current risk factors to adequately discriminate risk for SCD, what does the future hold? New techniques for risk stratification are constantly being developed and evaluated. Although it is possible that a new imaging, genetic testing, or proteomic approach could identify a risk factor with high discriminatory power, the multifactoral nature/etiology of SCD may limit our ability to identify such a marker. An alternative approach was modeled by Bailey et al.27 They suggested a 3-stage approach in which testing is performed at each stage to identify patients at low, intermediate, and high risk for a major arrhythmic event. The patient proceeds for further testing in the next
Heart Rhythm, Vol 6, No 3S, March Supplement 2009 stage only if the testing in the current stage suggests intermediate risk. They calculated event rates based on the data available in the literature (this was not an actual patient study). Thus, stage 1 testing would include a signal-averaged electrocardiogram and measurement of left ventricular ejection fraction. If both are positive, the risk for a major arrhythmic event is 38.7%. If both are negative, the risk is 2.2%. In both of these cases, no further testing would be recommended. However, if only 1 is positive, the probability of a major arrhythmic event over 2 years was predicted to be 10.6% and would justify further testing. Stage 2 testing is similarly performed with a Holter monitor for assessment of ventricular arrhythmias and heart rate variability. Stage 3 consists of performing electrophysiologic studies on the stage 2 patients in whom only 1 is positive. Using this algorithm, they determined that 80% of the population would be classified as low risk with a 2.9% probability of a major arrhythmic event, whereas 11.8% would be classified as high risk with a 41.4% risk of a major arrhythmic event. Only 8.2% of the population would be unstratified with an 8.9% probability of a major arrhythmic event over 2 years. The use of this kind of tiered testing can therefore result in a strategy with high discrimination. Several studies are underway in which data from multiple risk stratifiers are being collected. Ultimately, clinical data on using such a strategy will be needed to establish its utility for adequate patient discrimination. Accumulating evidence for risk stratification of patients at risk for arrhythmic SCD is extremely challenging. Our knowledge of the specific precipitants of arrhythmic SCD just before the event is poor. Our ability to identify the event is limited. The risk factors that are used are also often predictors for nonsudden cardiac death. Large-scale clinical trials are often not designed focused on the question of risk stratification. However, the mosaic of evidence that is available from many observational and interventional studies provides important information regarding these risk factors and serves as a useful guide for directing future efforts to improve our ability to stratify risk.
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