Cardiac structural and functional profile of patients with delayed QRS transition zone and sudden cardiac death

Delayed QRS transition zone in the precordial leads of the 12-lead electrocardiogram (ECG) has been recently associated with increased risk of sudden cardiac death (SCD), but the underlying mechanisms are unknown. We correlated echocardiographic findings with ECG and clinical characteristics to investigate how alterations in cardiac structure and function contribute to this risk marker. From the ongoing population-based Oregon Sudden Unexpected Death Study (catchment population similar to 1 million), SCD cases with prior ECG available (n = 627) were compared with controls (n = 801). Subjects with delayed transition at V-5 or later were identified, and clinical and echocardiographic patterns associated with delayed transition were analysed. Delayed transition was present in 31% of the SCD cases and 17% of the controls. These subjects were older and more likely to have cardiovascular risk factors and history of myocardial infarction. Delayed transition was associated with increased left ventricular (LV) mass (122.7 +/- 40.2 vs. 102.9 +/- 33.7 g/m(2); P <0.001), larger LV diameter (53.3 +/- 10.4 vs. 49.2 +/- 8.0 mm; P <0.001), and lower LV ejection fraction (LVEF) (46.4 +/- 15.7 vs. 55.6 +/- 12.5%; P <0.001). In multivariate analysis, delayed transition was independently associated with myocardial infarction, reduced LVEF, and LV hypertrophy. The association between delayed transition and SCD was independent of the LVEF (OR 1.57; 95% CI 1.04-2.38; P = 0.032). The underpinnings of delayed QRS transition zone extend beyond previous myocardial infarction and reduced LVEF. Since the association with sudden death is independent of these factors, this novel marker of myocardial electrical remodelling should be explored as a potential risk predictor of SCD.Peer reviewe

Left Ventricular Geometry and Risk of Sudden Cardiac Arrest in Patients With Severely Reduced Ejection Fraction

Background-Recent reports indicate that specific left ventricular (LV) geometric patterns predict recurrent ventricular arrhythmias in patients with implantable cardioverter-defibrillators and reduced left ventricular ejection fraction (LVEF). However, this relationship has not been evaluated among patients at risk of sudden cardiac arrest (SCA) in the general population. Methods and Results-Adult SCA cases from the Oregon Sudden Unexpected Death Study were compared with geographic controls with no prior history of SCA. Archived echocardiograms performed closest and prior to the SCA event were reviewed. LV geometry was defined as normal (normal LV mass index [LVMI] and relative wall thickness [RWT]), concentric remodeling (normal LVMI and increased RWT), concentric hypertrophy (increased LVMI and RWT), or eccentric hypertrophy (increased LVMI and normal RWT). Analysis was restricted to those with LVEF Conclusions-Eccentric LV hypertrophy was independently associated with increased risk of SCA in subjects with EFPeer reviewe

Syncope and risk of sudden cardiac arrest in coronary artery disease

Background: Syncope has been associated with increased risk of sudden cardiac arrest (SCA) in specific patient populations, such as hypertrophic cardiomyopathy, heart failure, and long QT syndrome, but data are lacking on the risk of SCA associated with syncope among patients with coronary artery disease (CAD), the most common cause of SCA. We investigated this association among CAD patients in the community. Methods: All cases of SCA due to CAD were prospectively identified in Portland, Oregon (population approximately 1 million) as part of the Oregon Sudden Unexpected Death Study 2002-2015, and compared to geographical controls. Detailed clinical information including history of syncope and cardiac investigations was obtained from medical records. Results: 2119 SCA cases (68.4 +/- 13.8 years, 66.9% male) and 746 controls (66.7 +/- 11.7 years, 67.0% male) were included in the analysis. 143 (6.8%) of cases had documented syncope prior to the SCA. SCA cases with syncope were > 5 years older and had more comorbidities than other SCA cases. After adjusting for clinical factors and left ventricular ejection fraction (LVEF), syncope was associated with increased risk of SCA (OR 2.8; 95%CI 1.68-4.85). When analysis was restricted to subjects with LVEF >= 50%, the risk of SCA associated with syncope remained significantly elevated (adjusted OR 3.1; 95%CI 1.68-5.79). Conclusions: Syncope was associated with increased risk of SCA in CAD patients even with preserved LV function. These findings suggest a role for this clinical marker among patients with CAD and normal LVEF, a large subgroup without any current means of SCA risk stratification. (C) 2016 Published by Elsevier Ireland Ltd.Peer reviewe

Artificial Intelligence Model Predicts Sudden Cardiac Arrest Manifesting With Pulseless Electric Activity Versus Ventricular Fibrillation

BACKGROUND: There is no specific treatment for sudden cardiac arrest (SCA) manifesting as pulseless electric activity (PEA) and survival rates are low; unlike ventricular fibrillation (VF), which is treatable by defibrillation. Development of novel treatments requires fundamental clinical studies, but access to the true initial rhythm has been a limiting factor. METHODS: Using demographics and detailed clinical variables, we trained and tested an AI model (extreme gradient boosting) to differentiate PEA-SCA versus VF-SCA in a novel setting that provided the true initial rhythm. A subgroup of SCAs are witnessed by emergency medical services personnel, and because the response time is zero, the true SCA initial rhythm is recorded. The internal cohort consisted of 421 emergency medical services-witnessed out-of-hospital SCAs with PEA or VF as the initial rhythm in the Portland, Oregon metropolitan area. External validation was performed in 220 emergency medical services-witnessed SCAs from Ventura, CA. RESULTS: In the internal cohort, the artificial intelligence model achieved an area under the receiver operating characteristic curve of 0.68 (95% CI, 0.61-0.76). Model performance was similar in the external cohort, achieving an area under the receiver operating characteristic curve of 0.72 (95% CI, 0.59-0.84). Anemia, older age, increased weight, and dyspnea as a warning symptom were the most important features of PEA-SCA; younger age, chest pain as a warning symptom and established coronary artery disease were important features associated with VF. CONCLUSIONS: The artificial intelligence model identified novel features of PEA-SCA, differentiated from VF-SCA and was successfully replicated in an external cohort. These findings enhance the mechanistic understanding of PEA-SCA with potential implications for developing novel management strategies

Identification of a Sudden Cardiac Death Susceptibility Locus at 2q24.2 through Genome-Wide Association in European Ancestry Individuals

Sudden cardiac death (SCD) continues to be one of the leading causes of mortality worldwide, with an annual incidence estimated at 250,000–300,000 in the United States and with the vast majority occurring in the setting of coronary disease. We performed a genome-wide association meta-analysis in 1,283 SCD cases and >20,000 control individuals of European ancestry from 5 studies, with follow-up genotyping in up to 3,119 SCD cases and 11,146 controls from 11 European ancestry studies, and identify the BAZ2B locus as associated with SCD (P = 1.8×10−10). The risk allele, while ancestral, has a frequency of ∼1.4%, suggesting strong negative selection and increases risk for SCD by 1.92–fold per allele (95% CI 1.57–2.34). We also tested the role of 49 SNPs previously implicated in modulating electrocardiographic traits (QRS, QT, and RR intervals). Consistent with epidemiological studies showing increased risk of SCD with prolonged QRS/QT intervals, the interval-prolonging alleles are in aggregate associated with increased risk for SCD (P = 0.006)

Novel loci associated with increased risk of sudden cardiac death in the context of coronary artery disease.

BACKGROUND: Recent genome-wide association studies (GWAS) have identified novel loci associated with sudden cardiac death (SCD). Despite this progress, identified DNA variants account for a relatively small portion of overall SCD risk, suggesting that additional loci contributing to SCD susceptibility await discovery. The objective of this study was to identify novel DNA variation associated with SCD in the context of coronary artery disease (CAD). METHODS AND FINDINGS: Using the MetaboChip custom array we conducted a case-control association analysis of 119,117 SNPs in 948 SCD cases (with underlying CAD) from the Oregon Sudden Unexpected Death Study (Oregon-SUDS) and 3,050 controls with CAD from the Wellcome Trust Case-Control Consortium (WTCCC). Two newly identified loci were significantly associated with increased risk of SCD after correction for multiple comparisons at: rs6730157 in the RAB3GAP1 gene on chromosome 2 (P = 4.93×10(-12), OR = 1.60) and rs2077316 in the ZNF365 gene on chromosome 10 (P = 3.64×10(-8), OR = 2.41). CONCLUSIONS: Our findings suggest that RAB3GAP1 and ZNF365 are relevant candidate genes for SCD and will contribute to the mechanistic understanding of SCD susceptibility

Sudden cardiac arrest in patients with schizophrenia: A population-based study of resuscitation outcomes and pre-existing cardiovascular disease.

ObjectiveIndividuals with schizophrenia carry a high burden of cardiovascular disease and elevated rates of sudden cardiac arrest (SCA), but little published data is available regarding survival from SCA in this population. The authors compared cardiovascular disease burden and resuscitation outcomes following SCA in individuals with and without schizophrenia.MethodsCase-control analysis drawn from a prospective community-based study of SCA in a large community. The authors defined cases as having a pre-SCA history of schizophrenia, and controls as individuals with SCA without a history of schizophrenia. SCA cases with schizophrenia were compared to a 1:5 age- and sex-frequency-matched sample of SCA cases without schizophrenia.ResultsThe 103 SCA schizophrenia cases were as likely as the 515 cases without schizophrenia to have resuscitation attempted (75% vs. 80%; p&nbsp;=&nbsp;0.24) and had a shorter 911 call mean response time (5.8&nbsp;min vs. 6.9&nbsp;min, p&nbsp;&lt;&nbsp;0.001). However, they were significantly less likely to present with a shockable rhythm (ventricular fibrillation/pulseless ventricular tachycardia 16% vs. 43%, p&nbsp;&lt;&nbsp;0.001), and less likely to survive to hospital discharge (3% vs. 14%, p&nbsp;=&nbsp;0.008). Pre-arrest cardiovascular disease burden was similar in patients with and without schizophrenia.ConclusionsDespite comparable resuscitation characteristics and cardiovascular disease burden, patients with schizophrenia had significantly lower rates of SCA survival. The paucity of previous research into this phenomenon warrants further investigation to identify factors that may improve survival

Cumulative effects of common genetic variants on risk of sudden cardiac death

Genome-wide association studies and candidate-gene based approaches have identified multiple common variants associated with increased risk of sudden cardiac death (SCD). However, the independent contribution of these individual loci to disease risk is modest. To investigate the cumulative effects of genetic variants previously associated with SCD risk. A total of 966 SCD cases from the Oregon-Sudden Unexpected Death Study and 1926 coronary artery disease controls from the Wellcome Trust Case–Control Consortium were investigated. We generated genetic risk scores (GRSs) for each trait composed of variants previously associated with SCD or with abnormalities in specific electrocardiographic traits such as QRS duration, QTc interval and heart rate. GRSs were calculated using a weighted approach based on the number of risk alleles weighted by the beta coefficients derived from the original studies. We also compared the highest and lowest quintiles for the GRS composed of SCD SNPs. Increased cumulative risk was observed for a GRS composed of 14 SCD-SNPs (OR = 1.17 [1.05–1.29], P = 0.002). The risk for SCD was 1.5 fold greater in the highest risk quintile when compared to the lowest risk quintile (OR = 1.46 [1.11–1.92]). We did not observe significant associations with SCD for SNPs that determine electrocardiographic traits. A modest but significant effect on SCD risk was identified for a GRS composed of 14 previously associated SCD SNPs. While next generation sequencing methodology will continue to identify additional novel variants, these findings represent proof of concept for the additive effects of gene variants on SCD risk

An ECG-based artificial intelligence model for assessment of sudden cardiac death risk

Abstract Background Conventional ECG-based algorithms could contribute to sudden cardiac death (SCD) risk stratification but demonstrate moderate predictive capabilities. Deep learning (DL) models use the entire digital signal and could potentially improve predictive power. We aimed to train and validate a 12 lead ECG-based DL algorithm for SCD risk assessment. Methods Out-of-hospital SCD cases were prospectively ascertained in the Portland, Oregon, metro area. A total of 1,827 pre- cardiac arrest 12 lead ECGs from 1,796 SCD cases were retrospectively collected and analyzed to develop an ECG-based DL model. External validation was performed in 714 ECGs from 714 SCD cases from Ventura County, CA. Two separate control group samples were obtained from 1342 ECGs taken from 1325 individuals of which at least 50% had established coronary artery disease. The DL model was compared with a previously validated conventional 6 variable ECG risk model. Results The DL model achieves an AUROC of 0.889 (95% CI 0.861–0.917) for the detection of SCD cases vs. controls in the internal held-out test dataset, and is successfully validated in external SCD cases with an AUROC of 0.820 (0.794–0.847). The DL model performs significantly better than the conventional ECG model that achieves an AUROC of 0.712 (0.668–0.756) in the internal and 0.743 (0.711–0.775) in the external cohort. Conclusions An ECG-based DL model distinguishes SCD cases from controls with improved accuracy and performs better than a conventional ECG risk model. Further detailed investigation is warranted to evaluate how the DL model could contribute to improved SCD risk stratification