Development and Validation of a Sudden Cardiac Death Prediction Model for the General Population

Heart Disease and Stroke Statistics-2020 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports on the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2020 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population, metrics to assess and monitor healthy diets, an enhanced focus on social determinants of health, a focus on the global burden of cardiovascular disease, and further evidence-based approaches to changing behaviors, implementation strategies, and implications of the American Heart Association's 2020 Impact Goals.

RESULTS

Each of the 26 chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policy makers, media professionals, clinicians, healthcare administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Racial Differences in Sudden Cardiac Death

BACKGROUND

Blacks have a higher incidence of out-of-hospital sudden cardiac death (SCD) in comparison with whites. However, the racial differences in the cumulative risk of SCD and the reasons for these differences have not been assessed in large-scale community-based cohorts. The objective of this study is to compare the lifetime cumulative risk of SCD among blacks and whites, and to evaluate the risk factors that may explain racial differences in SCD risk in the general population.

METHODS

This is a cohort study of 3832 blacks and 11 237 whites participating in the Atherosclerosis Risk in Communities Study (ARIC). Race was self-reported. SCD was defined as a sudden pulseless condition from a cardiac cause in a previously stable individual, and SCD cases were adjudicated by an expert committee. Cumulative incidence was computed using competing risk models. Potential mediators included demographic and socioeconomic factors, cardiovascular risk factors, presence of coronary heart disease, and electrocardiographic parameters as time-varying factors.

RESULTS

The mean (SD) age was 53.6 (5.8) years for blacks and 54.4 (5.7) years for whites. During 27.4 years of follow-up, 215 blacks and 332 whites experienced SCD. The lifetime cumulative incidence of SCD at age 85 years was 9.6, 6.6, 6.5, and 2.3% for black men, black women, white men, and white women, respectively. The sex-adjusted hazard ratio for SCD comparing blacks with whites was 2.12 (95% CI, 1.79-2.51). The association was attenuated but still statistically significant in fully adjusted models (hazard ratio, 1.38; 95% CI, 1.11-1.71). In mediation analysis, known factors explained 65.3% (95% CI 37.9-92.8%) of the excess risk of SCD in blacks in comparison with whites. The single most important factor explaining this difference was income (50.5%), followed by education (19.1%), hypertension (22.1%), and diabetes mellitus (19.6%). Racial differences were evident in both genders but stronger in women than in men.

CONCLUSIONS

Blacks had a much higher risk for SCD in comparison with whites, particularly among women. Income, education, and traditional risk factors explained ≈65% of the race difference in SCD. The high burden of SCD and the racial-gender disparities observed in our study represent a major public health and clinical problem.

Risk prediction of future cardiac arrest by evaluation of a genetic risk score alone and in combination with traditional risk factors

OBJECTIVES

Coronary heart disease (CHD) is a leading cause of death globally, commonly through sudden cardiac death. Cardiac arrest of cardiac origin (CA) is associated with a poor prognosis and there is a great need for risk assessment and intensified preventive actions. In this study we aim to assess if a genetic risk score for CHD, composed of 50 common CHD susceptibility variants (GRS), predicts CA and to evaluate a novel composite risk score including traditional risk factors as well as GRS.

METHODS

The GRS score alone and in combination with traditional CHD risk factors were examined in relation to CA incidence among 23 000 middle aged subjects during 18.9 years of follow-up. The cohort excluded patients with a diagnosed history of CHD, heart failure or stroke.

RESULTS

Two-hundred-fifty-two patients suffered a cardiac arrest during the follow up, of which 181 were CA. In a multivariate model with CHD risk factors, high versus low genetic risk predicted CA with a hazard ratio (HR) of 2.49 {(95% CI 1.50-4.12) (P < 0.001)}, surpassed only by higher estimates for male sex {HR = 2.91 (95% CI 2.09-4.06) (P < 0.001)}, ages 50-65 {HR = 2.74 (95% CI 1.42-5.25) (P = 0.003)} and ages 65-74 {HR = 5.10 (95% CI 2.56-10.16) (P < 0.001)}. Smoking, dyslipidemia, hypertension and diabetes mellitus also predicted CA but with lower HRs than GRS. A novel composite risk score including CHD risk factors as well as GRS predicted CA with a HR = 110.81 {(95% CI 15.43-795.63) (P < 0.001)} for the highest (5) versus the lowest quintile (1) of the risk score.

CONCLUSIONS

Genetic risk of CHD is strongly associated with incident CA and when combined with traditional CHD risk factors may identify individuals who benefit from intensified preventive pharmacological treatment.

Clinical risk prediction with random forests for survival, longitudinal, and multivariate (RF-SLAM) data analysis

Background

Clinical research and medical practice can be advanced through the prediction of an individual’s health state, trajectory, and responses to treatments. However, the majority of current clinical risk prediction models are based on regression approaches or machine learning algorithms that are static, rather than dynamic. To benefit from the increasing emergence of large, heterogeneous data sets, such as electronic health records (EHRs), novel tools to support improved clinical decision making through methods for individual-level risk prediction that can handle multiple variables, their interactions, and time-varying values are necessary.

Methods

We introduce a novel dynamic approach to clinical risk prediction for survival, longitudinal, and multivariate (SLAM) outcomes, called random forest for SLAM data analysis (RF-SLAM). RF-SLAM is a continuous-time, random forest method for survival analysis that combines the strengths of existing statistical and machine learning methods to produce individualized Bayes estimates of piecewise-constant hazard rates. We also present a method-agnostic approach for time-varying evaluation of model performance.

Results

We derive and illustrate the method by predicting sudden cardiac arrest (SCA) in the Left Ventricular Structural (LV) Predictors of Sudden Cardiac Death (SCD) Registry. We demonstrate superior performance relative to standard random forest methods for survival data. We illustrate the importance of the number of preceding heart failure hospitalizations as a time-dependent predictor in SCA risk assessment.

Conclusions

RF-SLAM is a novel statistical and machine learning method that improves risk prediction by incorporating time-varying information and accommodating a large number of predictors, their interactions, and missing values. RF-SLAM is designed to easily extend to simultaneous predictions of multiple, possibly competing, events and/or repeated measurements of discrete or continuous variables over time.Trial registration: LV Structural Predictors of SCD Registry (clinicaltrials.gov, NCT01076660), retrospectively registered 25 February 2010

Primary prevention implantable cardioverter-defibrillator and opportunities for sudden cardiac death risk assessment in non-ischaemic cardiomyopathy

Sudden cardiac death (SCD) accounts for approximately one-third of all deaths among patients with non-ischaemic cardiomyopathy (NICM). Implantable cardioverter-defibrillator (ICD) therapy has been the primary intervention for managing individuals at high risk for SCD. However, individual ICD trials in the NICM population have failed to demonstrate a mortality benefit with prophylactic ICD implantation. Current guidelines recommend ICD implantation in NICM patients with symptomatic heart failure and a left ventricular ≤35% and are based on meta-analyses of multiple trials that span three decades and include the recent Danish Study to Assess the Efficacy of ICDs in Patients with Non-ischaemic Heart Failure on Mortality (DANISH) trial. These pooled analyses report a significant reduction in all-cause mortality with ICD implantation compared with medical therapy alone. In addition, each of these trials has demonstrated consistently a reduction in the risk of SCD compared with medical therapy alone. As a result, a refined approach of risk stratification that selects patients at the highest risk for SCD may lead to a significant improvement in ICD efficacy. In this clinical review, we first discuss the evolution of clinical trials that have evaluated ICDs in the NICM population. We then highlight some key markers of arrhythmia risk that hold promise in personalizing risk stratification for SCD.

Predicting sudden cardiac death in a general population using an electrocardiographic risk score

OBJECTIVE

We investigated whether combining several ECG abnormalities would identify general population subjects with a high sudden cardiac death (SCD) risk.

METHODS

In a sample of 6830 participants (mean age 51.2±13.9 years; 45.5% male) in the Mini-Finland Health Survey, a general population cohort representative of the Finnish adults aged ≥30 years conducted in 1978-1980, we examined their ECGs, following subjects for 24.3±10.4 years. We analysed the association between individual ECG abnormalities and 10-year SCD risk and developed a risk score using five ECG abnormalities independently associated with SCD risk: heart rate >80 beats per minute, PR duration >220 ms, QRS duration >110 ms, left ventricular hypertrophy and T-wave inversion. We validated the score using an external general population cohort of 10 617 subjects (mean age 44.0±8.5 years; 52.7% male).

RESULTS

No ECG abnormalities were present in 4563 subjects (66.8%), while 96 subjects (1.4%) had ≥3 ECG abnormalities. After adjusting for clinical factors, the SCD risk increased progressively with each additional ECG abnormality. Subjects with ≥3 ECG abnormalities had an HR of 10.23 (95% CI 5.29 to 19.80) for SCD compared with those without abnormalities. The risk score similarly predicted SCD risk in the validation cohort, in which subjects with ≥3 ECG abnormalities had HR 10.82 (95% CI 3.23 to 36.25) for SCD compared with those without abnormalities.

CONCLUSION

The ECG risk score successfully identified general population subjects with a high SCD risk. Combining ECG risk markers may improve the risk stratification for SCD.

Dynamic predictive accuracy of electrocardiographic biomarkers of sudden cardiac death within a survival framework: the Atherosclerosis Risk in Communities (ARIC) study

BACKGROUND

The risk of sudden cardiac death (SCD) is known to be dynamic. However, the accuracy of a dynamic SCD prediction is unknown. We aimed to measure the dynamic predictive accuracy of ECG biomarkers of SCD and competing non-sudden cardiac death (non-SCD).

METHODS

Atherosclerosis Risk In Community study participants with analyzable ECGs in sinus rhythm were included (n = 15,716; 55% female, 73% white, age 54.2 ± 5.8 y). ECGs of 5 follow-up visits were analyzed. Global electrical heterogeneity and traditional ECG metrics (heart rate, QRS, QTc) were measured. Adjudicated SCD was the primary outcome; non-SCD was the competing outcome. Time-dependent area under the receiver operating characteristic curve (ROC(t) AUC) analysis was performed to assess the prediction accuracy of a continuous biomarker in a period of 3,6,9 months, and 1,2,3,5,10, and 15 years using a survival analysis framework. Reclassification improvement as compared to clinical risk factors (age, sex, race, diabetes, hypertension, coronary heart disease, stroke) was measured.

RESULTS

Over a median 24.4 y follow-up, there were 577 SCDs (incidence 1.76 (95%CI 1.63-1.91)/1000 person-years), and 829 non-SCDs [2.55 (95%CI 2.37-2.71)]. No ECG biomarkers predicted SCD within 3 months after ECG recording. Within 6 months, spatial ventricular gradient (SVG) elevation predicted SCD (AUC 0.706; 95%CI 0.526-0.886), but not a non-SCD (AUC 0.527; 95%CI 0.303-0.75). SVG elevation more accurately predicted SCD if the ECG was recorded 6 months before SCD (AUC 0.706; 95%CI 0.526-0.886) than 2 years before SCD (AUC 0.608; 95%CI 0.515-0.701). Within the first 3 months after ECG recording, only SVG azimuth improved reclassification of the risk beyond clinical risk factors: 18% of SCD events were reclassified from low or intermediate risk to a high-risk category. QRS-T angle was the strongest long-term predictor of SCD (AUC 0.710; 95%CI 0.668-0.753 for ECG recorded within 10 years before SCD).

CONCLUSION

Short-term and long-term predictive accuracy of ECG biomarkers of SCD differed, reflecting differences in transient vs. persistent SCD substrates. The dynamic predictive accuracy of ECG biomarkers should be considered for competing SCD risk scores. The distinction between markers predicting short-term and long-term events may represent the difference between markers heralding SCD (triggers or transient substrates) versus markers identifying persistent substrate.

Sudden Death in Patients With Coronary Heart Disease Without Severe Systolic Dysfunction

Importance

The majority of sudden and/or arrhythmic deaths (SAD) in patients with coronary heart disease occur in those without severe systolic dysfunction, for whom strategies for sudden death prevention are lacking.

Objective

To provide contemporary estimates of SAD vs other competing causes of death in patients with coronary heart disease without severe systolic dysfunction to search for high-risk subgroups that might be targeted in future trials of SAD prevention.

Design, Setting, and Participants

This prospective observational cohort study included 135 clinical sites in the United States and Canada. A total of 5761 participants with coronary heart disease who did not qualify for primary prevention implantable cardioverter defibrillator therapy based on left ventricular ejection fraction (LVEF) of more than 35% or New York Heart Association (NYHA) heart failure class (LVEF >30%, NYHA I).

Exposures

Clinical risk factors measured at baseline including age, LVEF, and NYHA heart failure class.

Main Outcomes and Measures

Primary outcome of SAD, which is a composite of SAD and resuscitated ventricular fibrillation arrest.

Results

The mean (SD) age of the cohort was 64 (11) years. During a median of 3.9 years, the cumulative incidence of SAD and non-SAD was 2.1% and 7.7%, respectively. Sudden and/or arrhythmic death was the most common mode of cardiovascular death accounting for 114 of 202 cardiac deaths (56%), although noncardiac death was the primary mode of death in this population. The 4-year cumulative incidence of SAD was lowest in those with an LVEF of more than 60% (1.0%) and highest among those with LVEF of 30% to 40% (4.9%) and class III/IV heart failure (5.1%); however, the cumulative incidence of non-SAD was similarly elevated in these latter high-risk subgroups. Patients with a moderately reduced LVEF (40%-49%) were more likely to die of SAD, whereas those with class II heart failure and advancing age were more likely to die of non-SAD. The proportion of deaths due to SAD varied widely, from 14% (18 of 131 deaths) in patients with NYHA II to 49% (37 of 76 deaths) in those younger than 60 years.

Conclusions and Relevance

In a contemporary population of patients with coronary heart disease without severe systolic dysfunction, SAD accounts for a significant proportion of overall mortality. Moderately reduced LVEF, age, and NYHA class distinguished SAD and non-SAD, whereas other markers were equally associated with both modes of death. Absolute and proportional risk of SAD varied significantly across clinical subgroups, and both will need to be maximized in future risk stratification efforts.

Prospective Countywide Surveillance and Autopsy Characterization of Sudden Cardiac Death: POST SCD Study

BACKGROUND

Studies of out-of-hospital cardiac arrest and sudden cardiac death (SCD) use emergency medical services records, death certificates, or definitions that infer cause of death; thus, the true incidence of SCD is unknown. Over 90% of SCDs occur out-of-hospital; nonforensic autopsies are rarely performed, and therefore causes of death are presumed. We conducted a medical examiner-based investigation to determine the precise incidence and autopsy-defined causes of all SCDs in an entire metropolitan area. We hypothesized that postmortem investigation would identify actual sudden arrhythmic deaths among presumed SCDs.

METHODS

Between February 1, 2011, and March 1, 2014, we prospectively identified all incident deaths attributed to out-of-hospital cardiac arrest (emergency medical services primary impression, cardiac arrest) between 18 to 90 years of age in San Francisco County for autopsy, toxicology, and histology via medical examiner surveillance of consecutive out-of-hospital deaths, all reported by law. We obtained comprehensive records to determine whether out-of-hospital cardiac arrest deaths met World Health Organization (WHO) criteria for SCD. We reviewed death certificates filed quarterly for missed SCDs. Autopsy-defined sudden arrhythmic deaths had no extracardiac cause of death or acute heart failure. A multidisciplinary committee adjudicated final cause.

RESULTS

All 20 440 deaths were reviewed; 12 671 were unattended and reported to the medical examiner. From these, we identified 912 out-of-hospital cardiac arrest deaths; 541 (59%) met WHO SCD criteria (mean 62.8 years, 69% male) and 525 (97%) were autopsied. Eighty-nine additional WHO-defined SCDs occurred within 3 weeks of active medical care with the death certificate signed by the attending physician, ineligible for autopsy but included in the countywide WHO-defined SCD incidence of 29.6/100 000 person-years, highest in black men (P<0.0001). Of 525 WHO-defined SCDs, 301 (57%) had no cardiac history. Leading causes of death were coronary disease (32%), occult overdose (13.5%), cardiomyopathy (10%), cardiac hypertrophy (8%), and neurological (5.5%). Autopsy-defined sudden arrhythmic deaths were 55.8% (293/525) of overall, 65% (78/120) of witnessed, and 53% (215/405) of unwitnessed WHO-defined SCDs (P=0.024); 286 of 293 (98%) had structural cardiac disease.

CONCLUSIONS

Forty percent of deaths attributed to stated cardiac arrest were not sudden or unexpected, and nearly half of presumed SCDs were not arrhythmic. These findings have implications for the accuracy of SCDs as defined by WHO criteria or emergency medical services records in aggregate mortality data, clinical trials, and cohort studies.

Refining the World Health Organization Definition: Predicting Autopsy-Defined Sudden Arrhythmic Deaths Among Presumed Sudden Cardiac Deaths in the POST SCD Study

BACKGROUND

Conventional definitions of sudden cardiac death (SCD) presume cardiac cause. We studied the World Health Organization-defined SCDs autopsied in the POST SCD study (Postmortem Systematic Investigation of SCD) to determine whether premortem characteristics could identify autopsy-defined sudden arrhythmic death (SAD) among presumed SCDs.

METHODS

Between January 2, 2011, and January 4, 2016, we prospectively identified all 615 World Health Organization-defined SCDs (144 witnessed) 18 to 90 years in San Francisco County for medical record review and autopsy via medical examiner surveillance. Autopsy-defined SADs had no extracardiac or acute heart failure cause of death. We used 2 nested sets of premortem predictors-an emergency medical system set and a comprehensive set adding medical record data-to develop Least Absolute Selection and Shrinkage Operator models of SAD among witnessed and unwitnessed cohorts.

RESULTS

Of 615 presumed SCDs, 348 (57%) were autopsy-defined SAD. For witnessed cases, the emergency medical system model (area under the receiver operator curve 0.75 [0.67-0.82]) included presenting rhythm of ventricular tachycardia/fibrillation and pulseless electrical activity, while the comprehensive (area under the receiver operator curve 0.78 [0.70-0.84]) added depression. If only ventricular tachycardia/fibrillation witnessed cases (n=48) were classified as SAD, sensitivity was 0.46 (0.36-0.57), and specificity was 0.90 (0.79-0.97). For unwitnessed cases, the emergency medical system model (area under the receiver operator curve 0.68 [0.64-0.73]) included black race, male sex, age, and time since last seen normal, while the comprehensive (area under the receiver operator curve 0.75 [0.71-0.79]) added use of β-blockers, antidepressants, QT-prolonging drugs, opiates, illicit drugs, and dyslipidemia. If only unwitnessed cases <1 hour (n=59) were classified as SAD, sensitivity was 0.18 (0.13-0.22) and specificity was 0.95 (0.90-0.97).

CONCLUSIONS

Our models identify premortem characteristics that can better specify autopsy-defined SAD among presumed SCDs and suggest the World Health Organization definition can be improved by restricting witnessed SCDs to ventricular tachycardia/fibrillation or nonpulseless electrical activity rhythms and unwitnessed cases to <1 hour since last normal, at the cost of sensitivity.

Sudden Cardiac Death Risk Distribution in the United States Population (from NHANES, 2005 to 2012)

Sudden cardiac death (SCD) accounts for more than half of all deaths from cardiovascular disease and is the first manifestation of heart disease in 50% of these subjects. We aimed to describe the distribution of predicted SCD risk in the general US population using a recently developed risk score. We previously developed a population-based, 10-year risk score for SCD using data from the multiracial Atherosclerosis Risk in Communities cohort, validated in the Framingham Study. We now estimate 10-year predicted SCD risk in National Health and Nutrition Examination Survey participants (pooled from cycles in 2005 to 2012) and evaluate the clinical profile of participants in lower risk (0 to 80th percentile of risk) or high risk (81st to 100th percentile of risk) strata. A total of 10,811 participants were included; the mean age of participants was 48 years, and 50% were women. The average predicted 10-year risk of SCD was 3.6% in high-risk participants (81st to 100th percentile), and 0.37% in low-risk participants (0 to 80th percentile). High-risk participants were older, had higher blood pressure, total cholesterol and body mass index, lower high-density lipoprotein, and were more likely to be men, black, smokers, and diabetic. In US adults free of cardiovascular disease, the majority of SCD risk appears confined to 10% to 20% of the population. This risk score, comprised of readily available clinical variables, identifies a subset of individuals in the population who are at an appreciably higher risk of SCD. This enriched cohort represents candidates for additional nuanced and selective screening techniques to further quantify SCD risk.

Electrocardiographic conduction and repolarization markers associated with sudden cardiac death: moving along the electrocardiography waveform

The QT interval along with its heart rate corrected form (QTc) are well-established ECG markers that have been found to be associated with malignant ventricular arrhythmogenesis. However, extensive preclinical and clinical investigations over the years have allowed for novel clinical ECG markers to be generated as predictors of arrhythmogenesis and sudden cardiac death. Repolarization markers include the older QTc, QT dispersion and newer Tpeak - Tend intervals, (Tpeak - Tend) / QT ratios, T-wave alternans (TWA), microvolt TWA and T-wave area dispersion. Meanwhile, conduction markers dissecting the QRS complex, such as QRS dispersion (QRSD) and fragmented QRS, were also found to correlate conduction velocity and unidirectional block with re-entrant substrates in various cardiac conditions. Both repolarization and conduction parameters can be combined into the excitation wavelength (λ). A surrogate marker for λ is the index of Cardiac Electrophysiological Balance (iCEB: QT / QRSd). Other markers based on conduction-repolarization are [QRSD x (Tpeak-Tend) / QRSd] and [QRSD x (Tpeak-Tend) / (QRSd x QT)]. Advancement in technology permitted sophisticated electrophysiological analyses such as principal component analysis and periodic repolarization dynamics to further improve risk stratification. This was closely followed by other novel indices including ventricular ectopic QRS interval, the f99 index and EntropyXQT, which integrates mathematical and physical calculations for determining the risk markers. Though proven to be effective in limited patient cohorts, more clinical studies across different cardiac pathologies are required to confirm their validity. As such, this review seeks to encapsulate the development of old and new ECG markers along with their associated utility and shortcomings in clinical practice.

Modes of death and prognostic outliers in chronic heart failure

BACKGROUND

The impact of incident sudden cardiac death (SCD) on the predictive accuracy of prognostic risk scores for patients with chronic heart failure (HF) has rarely been examined. We assessed the relationship between estimated probability of death and modes of death in this population, as well as the predictors of death and survival in prognostic outliers.

METHODS AND RESULTS

The MAGGIC 3-year probability of death was estimated in 6,859 participants of the GISSI-HF trial (mean age 67±11 years, 78% men, 91% with ejection fraction <40%, mean follow-up 3.5±1.3 years, observed mortality 28.4%). The incidence of SCD progressively decreased with increased probability of death, and occurred in 52.5% of patients estimated at low-risk (N = 61 with probability <14%) vs. in 23.5% of the high-risk ones (N = 375 with probability >56%, P < .0001). On the contrary, death from worsening HF was significantly more frequent in the latter group (19.7% vs. 46.1%, P < .0001). The overall predictive accuracy of the MAGGIC model improved after excluding deaths from SCD (AUC from 0.731 to 0.760, P = .0034). Among patients estimated at low-risk (N = 61 dead, 743 alive), independent predictors of death were older age, longer history of HF, higher serum uric acid and chronic obstructive pulmonary disease. The only predictor of survival in patients estimated at high-risk (N = 210 alive, 375 dead) was higher systolic blood pressure.

CONCLUSIONS

The MAGGIC risk score demonstrated its scarce ability to capture SCD, particularly in chronic HF patients estimated at low risk of death. Newer and better prognostic tools in the evolving horizon of HF are needed.

Autoantibodies for Cardiac Channels and Sudden Cardiac Death and its Relationship to Autoimmune Disorders

Background:

Sudden Cardiac Death (SCD) is an unexpected death caused by heart dys-function. Autoantibodies against cardiac proteins may be potentially involved in the occurrence and progression of cardiac disease and SCD. The first report on the role of autoantibodies in idiopathic dilated cardiomyopathy appeared in the 1980s. In recent years new studies on the effects of the pres-ence of specific autoantibodies and their relationship to ventricular arrhythmias and SCD were pub-lished. The purpose of the current mini-review is to analyze the results of the research studies focused on the relationship between anti-cardiomyocyte autoantibodies and SCD with respect to autoimmune disorders.

Conclusion:

According to our analysis, more research is needed to understand the role of these auto-antibodies against cardiac proteins in the SCD pathogenesis, and potentially employ this knowledge for improving prognosis of SCD.

New Concepts in Sudden Cardiac Arrest to Address an Intractable Epidemic: JACC State-of-the-Art Review

Sudden cardiac arrest (SCA) is one of the largest causes of mortality globally, with an out-of-hospital survival below 10% despite intense research. This document outlines challenges in addressing the epidemic of SCA, along the framework of respond, understand and predict, and prevent. Response could be improved by technology-assisted orchestration of community responder systems, access to automated external defibrillators, and innovations to match resuscitation resources to victims in place and time. Efforts to understand and predict SCA may be enhanced by refining taxonomy along phenotypical and pathophysiological "axes of risk," extending beyond cardiovascular pathology to identify less heterogeneous cohorts, facilitated by open-data platforms and analytics including machine learning to integrate discoveries across disciplines. Prevention of SCA must integrate these concepts, recognizing that all members of society are stakeholders. Ultimately, solutions to the public health challenge of SCA will require greater awareness, societal debate and focused public policy.

Establishment of a predictive model for inpatient sudden cardiac death in a Chinese cardiac department population

Background:

Little is known about the risk factors for sudden cardiac death (SCD) in the overall hospitalized cardiac department population. This study was conducted to investigate the risk factors and develop a predictive model for SCD in a hospitalized cardiac department population.

Methods:

We conducted a retrospective study of patients admitted to the cardiac department of the First Affiliated Hospital of Xinjiang Medical University from June 2015 to February 2017. We collected the clinical data from medical records. Multiple stepwise logistic regression analysis was carried out to confirm the risk factors for SCD and develop a predictive risk model. The risk score was assessed by the area under receiver operating characteristic (AUROC) curve and the Hosmer-Lemeshow goodness-of-fit test.

Results:

A total of 262 patients with SCD and 4485 controls were enrolled in our study. Logistic regression modeling identified eight significant risk factors for in-hospital SCD: age, main admitting diagnosis, diabetes, corrected QT interval, QRS duration, ventricular premature beat burden, left ventricular ejection fraction, and estimated glomerular filtration rate. A predictive risk score including these variables showed an AUROC curve of 0.774 (95% confidence interval: 0.744–0.805). The Hosmer-Lemeshow goodness-of-fit test showed the chi-square value was 2.527 (P = 0.640). The incidence of in-hospital SCD was 1.3%, 4.1%, and 18.6% for scores of 0 to 2, 3 to 5 and ≥6, respectively (P < 0.001).

Conclusions:

Age, main admitting diagnosis, diabetes, QTc interval, QRS duration, ventricular premature beat burden, left ventricular ejection fraction, and estimated glomerular filtration rate are factors related to in-hospital SCD in a hospitalized cardiac department population. We developed a predictive risk score including these factors that could identify patients who are predisposed to in-hospital SCD.

Importance of the heart vector origin point definition for an ECG analysis: The Atherosclerosis Risk in Communities (ARIC) study

AIM

Our goal was to investigate the effect of a global XYZ median beat construction and the heart vector origin point definition on predictive accuracy of ECG biomarkers of sudden cardiac death (SCD).

METHODS

Atherosclerosis Risk In Community study participants with analyzable digital ECGs were included (n = 15,768; 55% female, 73% white, mean age 54.2 ± 5.8 y). We developed an algorithm to automatically detect the heart vector origin point on a median beat. Three different approaches to construct a global XYZ beat and two methods to locate origin point were compared. Global electrical heterogeneity was measured by sum absolute QRST integral (SAI QRST), spatial QRS-T angle, and spatial ventricular gradient (SVG) magnitude, azimuth, and elevation. Adjudicated SCD served as the primary outcome.

RESULTS

There was high intra-observer (kappa 0.972) and inter-observer (kappa 0.984) agreement in a heart vector origin definition between an automated algorithm and a human. QRS was wider in a median beat that was constructed using R-peak alignment than in time-coherent beat (88.1 ± 16.7 vs. 83.7 ± 15.9 ms; P < 0.0001), and on a median beat constructed using QRS-onset as a zeroed baseline, vs. isoelectric origin point (86.7 ± 15.9 vs. 83.7 ± 15.9 ms; P < 0.0001). ROC AUC was significantly larger for QRS, QT, peak QRS-T angle, SVG elevation, and SAI QRST if measured on a time-coherent median beat, and for SAI QRST and SVG magnitude if measured on a median beat using isoelectric origin point.

CONCLUSION

Time-coherent global XYZ median beat with physiologically meaningful definition of the heart vector's origin point improved predictive accuracy of SCD biomarkers.

Differences in Risk of Sudden Cardiac Death Between Blacks and Whites

BACKGROUND

Prior studies have consistently demonstrated that blacks have an approximate 2-fold higher incidence of sudden cardiac death (SCD) than whites; however, these analyses have lacked individual-level sociodemographic, medical comorbidity, and behavioral health data.

OBJECTIVES

The purpose of this study was to evaluate whether racial differences in SCD incidence are attributable to differences in the prevalence of risk factors or rather to underlying susceptibility to fatal arrhythmias.

METHODS

The Reasons for Geographic and Racial Differences in Stroke study is a prospective, population-based cohort of adults from across the United States. Associations between race and SCD defined per National Heart, Lung, and Blood Institute criteria were assessed.

RESULTS

Among 22,507 participants (9,416 blacks and 13,091 whites) without a history of clinical cardiovascular disease, there were 174 SCD events (67 whites and 107 blacks) over a median follow-up of 6.1 years (interquartile range: 4.6 to 7.3 years). The age-adjusted SCD incidence rate (per 1,000 person-years) was higher in blacks (1.8; 95% confidence interval [CI]: 1.4 to 2.2) compared with whites (0.7; 95% CI: 0.6 to 0.9), with an unadjusted hazard ratio of 2.35; 95% CI: 1.74 to 3.20. The association of black race with SCD risk remained significant after adjustment for sociodemographics, comorbidities, behavioral measures of health, intervening cardiovascular events, and competing risks of non-SCD mortality (hazard ratio: 1.97; 95% CI: 1.39 to 2.77).

CONCLUSIONS

In a large biracial population of adults without a history of cardiovascular disease, SCD rates were significantly higher in blacks as compared with whites. These racial differences were not fully explained by demographics, adverse socioeconomic measures, cardiovascular risk factors, and behavioral measures of health.

Outcomes of patients admitted with ventricular arrhythmias and sudden cardiac death in the United States

BACKGROUND

Mortality caused by ventricular arrhythmias (VAs) remains a problem of epidemic proportions. Understanding current trends on admission of VA, patient characteristics, morbidity, mortality, and health care utilization could help us improve allocation of health care resources and risk prediction.

OBJECTIVE

The purpose of this study was to investigate clinical outcomes of VA, including ventricular tachycardia (VT), implantable cardioverter-defibrillator (ICD) shocks, and sudden cardiac death (SCD); and to identify predictors of morbidity and mortality, patterns of utilization of ICD and VT ablation, and the impact of such metrics on overall health care utilization.

METHODS

From 2010-2015, we identified 290,998 VA hospitalizations, which were stratified into group 1: normal heart; group 2: ischemic heart disease (IHD); group 3: nonischemic heart disease (non-IHD); group 4: ICD shocks; and group 5: SCD (cardiac arrest without ICD shock).

RESULTS

The number of admissions for VA decreased during the study period (except for patients with SCD and ICD shock, which increased); in-hospital mortality in patients admitted with VA and SCD increased; utilization of VT ablation in patients with ICD shocks and IHD increased; ICD implantation decreased in non-IHD patients and IHD patients; and admission for SCD was the strongest predictor of in-hospital mortality, followed by patients with non-IHD, patients with ICD shocks, and all patients with a Charlson comorbidity index ≥2.

CONCLUSION

We report a decrease in admissions for VA, decreased ICD utilization, a change in pattern of VT ablation utilization, and an increase of in-hospital mortality in SCD patients. Predictors of adverse outcomes identified in our study should be considered when developing risk models for patients undergoing risk assessment for SCD.

Race, ethnicity, and the risk of sudden death<sup/>

Sudden cardiac death (SCD) is a major cause of death worldwide, with an estimated U.S. annual incidence of 350,000 [1]. This review will examine the influence of race and ethnicity on SCD burden and risk factors, and review the available literature on resuscitation outcomes and primary prevention of SCD. An improved understanding of associations between race, ethnicity, and SCD may provide clues to mechanisms, lead to improved prevention of SCD, and ultimately reduce racial and ethnic disparities in the burden of SCD.

Electrical risk score beyond the left ventricular ejection fraction: prediction of sudden cardiac death in the Oregon Sudden Unexpected Death Study and the Atherosclerosis Risk in Communities Study

Aims

There is an urgent need to extend sudden cardiac death (SCD) risk stratification beyond the left ventricular ejection fraction (LVEF). We evaluated whether a cumulative electrocardiogram (ECG) risk score would improve identification of individuals at high risk of SCD.

Methods and results

In the community-based Oregon Sudden Unexpected Death Study (catchment population ∼1 million), 522 SCD cases with archived 12-lead ECG available (65.3 ± 14.5 years, 66% male) were compared with 736 geographical controls to assess the incremental value of multiple ECG parameters in SCD prediction. Heart rate, LV hypertrophy, QRS transition zone, QRS-T angle, QTc, and Tpeak-to-Tend interval remained significant in the final model, which was externally validated in the Atherosclerosis Risk in Communities (ARIC) Study. Sixteen percent of cases and 3% of controls had ≥4 abnormal ECG markers. After adjusting for clinical factors and LVEF, increasing ECG risk score was associated with progressively greater odds of SCD. Overall, subjects with ≥4 ECG abnormalities had an odds ratio (OR) of 21.2 for SCD [95% confidence interval (CI) 9.4-47.7; P < 0.001]. In the LVEF >35% subgroup, the OR was 26.1 (95% CI 9.9-68.5; P < 0.001). The ECG risk score increased the C-statistic from 0.625 to 0.753 (P < 0.001), with net reclassification improvement of 0.319 (P < 0.001). In the ARIC cohort validation, risk of SCD associated with ≥4 ECG abnormalities remained significant after multivariable adjustment (hazard ratio 4.84; 95% CI 2.34-9.99; P < 0.001; C-statistic improvement 0.759-0.774; P = 0.019).

Conclusion

This novel cumulative ECG risk score was independently associated with SCD and was particularly effective for LVEF >35% where risk stratification is currently unavailable. These findings warrant further evaluation in prospective clinical investigations.

Association of cardiac implantable electronic devices with survival in bifascicular block and prolonged PR interval on electrocardiogram

PURPOSE

Bifascicular block and prolonged PR interval on the electrocardiogram (ECG) have been associated with complete heart block and sudden cardiac death. We sought to determine if cardiac implantable electronic devices (CIED) improve survival in these patients.

METHODS

We assessed survival in relation to CIED status among 636 consecutive patients with bifascicular block and prolonged PR interval on the ECG. In survival analyses, CIED was considered as a time-varying covariate.

RESULTS

Average age was 76 ± 9 years, and 99% of the patients were men. A total of 167 (26%) underwent CIED (127 pacemaker only) implantation at baseline (n = 23) or during follow-up (n = 144). During 5.4 ± 3.8 years of follow-up, 83 (13%) patients developed complete or high-degree atrioventricular block and 375 (59%) died. Patients with a CIED had a longer survival compared to those without a CIED in the traditional, static analysis (log-rank p < 0.0001) but not when CIED was considered as a time-varying covariate (log-rank p = 0.76). In the multivariable model, patients with a CIED had a 34% lower risk of death (hazard ratio 0.66, 95% confidence interval 0.52-0.83; p = 0.001) than those without CIED in the traditional analysis but not in the time-varying covariate analysis (hazard ratio 1.05, 95% confidence interval 0.79-1.38; p = 0.76). Results did not change in the subgroup with a pacemaker only.

CONCLUSIONS

Bifascicular block and prolonged PR interval on ECG are associated with a high incidence of complete atrioventricular block and mortality. However, CIED implantation does not have a significant influence on survival when time-varying nature of CIED implantation is considered.

Sudden death risk markers for patients with left ventricular ejection fractions greater than 40

The major burden of sudden cardiac death (SCD) in patients with heart disease occurs in those with a left ventricular ejection fraction > 40%. Although the annual risk of SCD may be lower in these patients compared to those with lower LVEF, their lifetime cumulative risk of SCD may be greater due to a better overall prognosis. It is plausible that those with LVEF > 40% who are at highest risk of life-threatening arrhythmia will benefit from implantable cardioverter defibrillators. Features that identify patients with a LVEF > 40% at high risk of SCD are urgently needed. We review existing studies examining SCD markers in this sub-group and discuss gaps in the current evidence base.

A Simple Community-Based Risk-Prediction Score for Sudden Cardiac Death

BACKGROUND

Although sudden cardiac death is a leading cause of death in the United States, most victims of sudden cardiac death are not identified as at risk prior to death. We sought to derive and validate a population-based risk score that predicts sudden cardiac death.

METHODS

The Atherosclerosis Risk in Communities (ARIC) Study recorded clinical measures from men and women aged 45-64 years at baseline; 11,335 white and 3780 black participants were included in this analysis. Participants were followed over 10 years and sudden cardiac death was physician adjudicated. Cox proportional hazards models were used to derive race-specific equations to estimate the 10-year sudden cardiac death risk. Covariates for the risk score were selected from available demographic and clinical variables. Utility was assessed by calculating discrimination (Harrell's C-index) and calibration (Hosmer-Lemeshow chi-squared test). The white-specific equation was validated among 5626 Framingham Heart Study participants.

RESULTS

During 10 years' follow-up among ARIC participants (mean age 54.4 years, 52.4% women), 145 participants experienced sudden cardiac death; the majority occurred in the highest quintile of predicted risk. Model covariates included age, sex, total cholesterol, lipid-lowering and hypertension medication use, blood pressure, smoking status, diabetes, and body mass index. The score yielded very good internal discrimination (white-specific C-index 0.82; 95% confidence interval [CI], 0.78-0.85; black-specific C-index 0.75; 95% CI, 0.68-0.82) and very good external discrimination among Framingham participants (C-index 0.82; 95% CI, 0.79-0.86). Calibration plots indicated excellent calibration in ARIC (white-specific chi-squared 5.3, P = .82; black-specific chi-squared 4.1, P = .77), and a simple recalibration led to excellent fit within Framingham (chi-squared 2.1, P = 0.99).

CONCLUSIONS

The proposed risk scores may be used to identify those at risk for sudden cardiac death within 10 years and particularly classify those at highest risk who may merit further screening.

Tobacco smoking and the risk of sudden cardiac death: a systematic review and meta-analysis of prospective studies

Smoking is an established risk factor for cardiovascular disease including coronary heart disease and stroke, however, data regarding smoking and sudden cardiac death have not been summarized in a meta-analysis previously. We therefore conducted a systematic review and meta-analysis to clarify this association. We searched the PubMed and Embase databases for studies of smoking and sudden cardiac death up to July 20th 2017. Prospective studies were included if they reported adjusted relative risk (RR) estimates and 95% confidence intervals (CIs) for smoking and sudden cardiac death. Summary RRs were estimated by use of a random effects model. Twelve prospective studies were included. The summary RR was 3.06 (95% CI 2.46–3.82, I² = 41%, p_{heterogeneity} = 0.12, n = 7) for current smokers and 1.38 (95% CI 1.20–1.60, I² = 0%, p_{heterogeneity} = 0.55, n = 7) for former smokers compared to never smokers. For four studies using non-current (never + former) smokers as the reference category the summary RR among current smokers was 2.08 (95% CI 1.70–2.53, I² = 18%, p_{heterogeneity} = 0.30). The results persisted in most of the subgroup analyses. There was no evidence of publication bias. These results confirm that smoking increases the risk of sudden cardiac death. Any further studies should investigate in more detail the effects of duration of smoking, number of cigarettes per day, pack-years, and time since quitting smoking and sudden cardiac death.

Predictors of sudden cardiac death in atrial fibrillation: The Atherosclerosis Risk in Communities (ARIC) study

We previously reported that incident atrial fibrillation (AF) is associated with an increased risk of sudden cardiac death (SCD) in the general population. We now aimed to identify predictors of SCD in persons with AF from the Atherosclerosis Risk in Communities (ARIC) study, a community-based cohort study. We included all participants who attended visit 1 (1987-89) and had no prior AF (n = 14,836). Incident AF was identified from study electrocardiograms and hospitalization discharge codes through 2012. SCD was physician-adjudicated. We used cause-specific Cox proportional hazards models, followed by stepwise selection (backwards elimination, removing all variables with p>0.10) to identify predictors of SCD in participants with AF. AF occurred in 2321 (15.6%) participants (age 45-64 years, 58% male, 18% black). Over a median of 3.3 years, SCD occurred in 110 of those with AF (4.7%). Predictors of SCD in AF included higher age, body mass index (BMI), coronary heart disease, hypertension, diabetes, current smoker, left ventricular hypertrophy, increased heart rate, and decreased albumin. Predictors associated only with SCD and not other cardiovascular (CV) death included increased BMI (HR per 5-unit increase, 1.15, 95% CI, 0.97-1.36, p = 0.10), increased heart rate (HR per SD increase, 1.18, 95% CI 0.99-1.41, p = 0.07), and low albumin (HR per SD decrease 1.23, 95% CI 1.02-1.48, p = 0.03). In the ARIC study, predictors of SCD in AF that are not associated with non-sudden CV death included increased BMI, increased heart rate, and low albumin. Further research to confirm these findings in larger community-based cohorts and to elucidate the underlying mechanisms to facilitate prevention is warranted.

The Metabolic Syndrome and Risk of Sudden Cardiac Death: The Atherosclerosis Risk in Communities Study

BACKGROUND

Prior studies have demonstrated a link between the metabolic syndrome and increased risk of cardiovascular mortality. Whether the metabolic syndrome is associated with sudden cardiac death is uncertain.

METHODS AND RESULTS

We characterized the relationship between sudden cardiac death and metabolic syndrome status among participants of the ARIC (Atherosclerosis Risk in Communities) Study (1987-2012) free of prevalent coronary heart disease or heart failure. Among 13 168 participants, 357 (2.7%) sudden cardiac deaths occurred during a median follow-up of 23.6 years. Participants with the metabolic syndrome (n=4444) had a higher cumulative incidence of sudden cardiac death than those without it (n=8724) (4.1% versus 2.3%, P<0.001). After adjustment for participant demographics and clinical factors other than components of the metabolic syndrome, the metabolic syndrome was independently associated with sudden cardiac death (hazard ratio, 1.70, 95% confidence interval, 1.37-2.12, P<0.001). This relationship was not modified by sex (interaction P=0.10) or race (interaction P=0.62) and was mediated by the metabolic syndrome criteria components. The risk of sudden cardiac death varied according to the number of metabolic syndrome components (hazard ratio 1.31 per additional component of the metabolic syndrome, 95% confidence interval, 1.19-1.44, P<0.001). Of the 5 components, elevated blood pressure, impaired fasting glucose, and low high-density lipoprotein were independently associated with sudden cardiac death.

CONCLUSIONS

We observed that the metabolic syndrome was associated with a significantly increased risk of sudden cardiac death irrespective of sex or race. The risk of sudden cardiac death was proportional to the number of metabolic syndrome components.

Personalizing Risk Stratification for Sudden Death in Dilated Cardiomyopathy: The Past, Present, and Future

Results from the DANISH Study (Danish Study to Assess the Efficacy of ICDs in Patients With Non-Ischemic Systolic Heat Failure on Mortality) suggest that for many patients with dilated cardiomyopathy (DCM), implantable cardioverter-defibrillators do not increase longevity. Accurate identification of patients who are more likely to die of an arrhythmia and less likely to die of other causes is required to ensure improvement in outcomes and wise use of resources. Until now, left ventricular ejection fraction has been used as a key criterion for selecting patients with DCM for an implantable cardioverter-defibrillator for primary prevention purposes. However, registry data suggest that many patients with DCM and an out-of-hospital cardiac arrest do not have a markedly reduced left ventricular ejection fraction. In addition, many patients with reduced left ventricular ejection fraction die of nonsudden causes of death. Methods to predict a higher or lower risk of sudden death include the detection of myocardial fibrosis (a substrate for ventricular arrhythmia), microvolt T-wave alternans (a marker of electrophysiological vulnerability), and genetic testing. Midwall fibrosis is identified by late gadolinium enhancement cardiovascular magnetic resonance imaging in ≈30% of patients and provides incremental value in addition to left ventricular ejection fraction for the prediction of sudden cardiac death events. Microvolt T-wave alternans represents another promising predictor, supported by large meta-analyses that have highlighted the negative predictive value of this test. However, neither of these strategies have been routinely adopted for risk stratification in clinical practice. More convincing data from randomized trials are required to inform the management of patients with these features. Understanding of the genetics of DCM and how specific mutations affect arrhythmic risk is also rapidly increasing. The finding of a mutation in lamin A/C, the cause of ≈6% of idiopathic DCM, commonly underpins more aggressive management because of the malignant nature of the associated phenotype. With the expansion of genetic sequencing, the identification of further high-risk mutations appears likely, leading to better-informed clinical decision making and providing insight into disease mechanisms. Over the next 5 to 10 years, we expect these techniques to be integrated into the existing algorithm to form a more sensitive, specific, and cost-effective approach to the selection of patients with DCM for implantable cardioverter-defibrillator implantation.

A sudden death risk score specifically for hypertension: based on 25 648 individual patient data from six randomized controlled trials

OBJECTIVE

To construct a sudden death risk score specifically for hypertension (HYSUD) patients with or without cardiovascular history.

METHODS

Data were collected from six randomized controlled trials of antihypertensive treatments with 8044 women and 17 604 men differing in age ranges and blood pressure eligibility criteria. In total, 345 sudden deaths (1.35%) occurred during a mean follow-up of 5.16 years. Risk factors of sudden death were examined using a multivariable Cox proportional hazards model adjusted on trials. The model was transformed to an integer system, with points added for each factor according to its association with sudden death risk.

RESULTS

Antihypertensive treatment was not associated with a reduction of the sudden death risk and had no interaction with other factors, allowing model development on both treatment and placebo groups. A risk score of sudden death in 5 years was built with seven significant risk factors: age, sex, SBP, serum total cholesterol, cigarette smoking, diabetes, and history of myocardial infarction. In terms of discrimination performance, HYSUD model was adequate with areas under the receiver operating characteristic curve of 77.74% (confidence interval 95%, 74.13-81.35) for the derivation set, of 77.46% (74.09-80.83) for the validation set, and of 79.17% (75.94-82.40) for the whole population.

CONCLUSION

Our work provides a simple risk-scoring system for sudden death prediction in hypertension, using individual data from six randomized controlled trials of antihypertensive treatments. HYSUD score could help assessing a hypertensive individual's risk of sudden death and optimizing preventive therapeutic strategies for these patients.

Opening a new front in the fight against sudden cardiac death: Is it time for near-term prevention?

Sudden cardiac death (SCD) is a major issue of public health with more than 350,000 deaths per year in the United States, accounting for almost half of cardiovascular mortality. Despite major investments in both prevention and resuscitation, SCD mortality remains high, highlighting the need for a novel approach to reduce SCD burden. We hereby propose a new approach - near-term prevention - that is based on Anticipation, aiming to ensure that resuscitation will be initiated early enough after SCD, or even that prophylactic therapy will be initiated in this well targeted population for preventing SCD occurrence.

Hemoglobin A1c levels and risk of sudden cardiac death: A nested case-control study

BACKGROUND

Sudden cardiac death (SCD) is often the first manifestation of cardiovascular disease (CVD), and preventive strategies within this broad population are lacking. Patients with diabetes represent a high-risk subgroup, but few data exist regarding whether measures of glycemia mediate risk and/or add to SCD risk stratification.

OBJECTIVE

The purpose of this study was to examine the association between hemoglobin A1c (HbA1c) and SCD.

METHODS

We performed a case-control analysis among individuals enrolled in 6 prospective cohort studies. HbA1c levels were determined for 482 cases of SCD and 914 matched controls. Conditional logistic regression with fixed effects meta-analysis was used for analysis.

RESULTS

In multivariable models, HbA1c levels were linearly associated with SCD risk over follow-up of 11.3 years (P <.001). Each 1% increment in HbA1c was associated with a hazard ratio (HR) of 1.32 (95% confidence interval [CI] 1.16-1.50). The magnitude of the association was greater in subjects without vs those with known CVD [HR per 1% increment 1.64 (95% CI 1.31-2.06) vs 1.15 (95% CI 0.99-1.33), P interaction = .009]. In models simultaneously controlling for diabetes status and HbA1c, the association between HbA1c and SCD remained significant (HR 1.29, 95% CI 1.07-1.55, P = .01), whereas the association between diabetes and SCD was attenuated (relative risk 1.21, 95% CI 0.64-2.27, P = .56).

CONCLUSION

In these prospective cohorts, HbA1c levels associated with SCD risk, particularly among those without known CVD, even after controlling for diabetes status. These data support the hypothesis that hyperglycemia mediates SCD risk among patients with diabetes.