Novel ECG Measures and Risk of Sudden Cardiac Death

心源性猝死（SCD）是一个主要的公共卫生问题，在美国有40万人死亡。 美国每年。临床和尸检研究一致表明， 西方人群中常见的病理生理学，表明最常见的 SCD的电生理机制是心室颤动（VF）， 病理基础是冠心病（CHD）。在大约一半的SCD病例中，死亡是 CHD的首次临床表现。然而，在自然病程的早期， 诱发SCD的条件尚未完全确定，SCD风险分层策略 一般人口还没有发展起来。心电图是容易获得的，不昂贵的和无创的 该工具携带关于心脏电生理特性的有价值的信息。 然而，传统的ECG分析包括非常有限的致心律失常的评估。 衬底最近，我们开发了新的12导联ECG SCD风险评分，包括参数 测量（1）缓慢中断传导，（2）时间复极不稳定性，和（3） 不利的电重构初步性别、种族和年龄匹配的病例对照 对社区动脉粥样硬化（ARIC）研究的分析显示， 与单独的Fragrance风险评分相比，重新分类改善了86.0%。我们 假设（1） SCD ECG风险评分，由以下机械ECG标记物组成： 静息12导联ECG分析中得出的致炎底物准确分层 将残疾人分为高危、中危和低危群体，并在比较中改进分类 根据传统的冠心病危险因素进行危险分层;（2）冠心病的遗传因素， 新的ECG表型与SCD风险增加相关。此应用程序将 对SCD机制的理解和SCD风险分层之间存在关键差距， 一般人口。我们将利用两个独特的大型NIH资助的前瞻性社区住宅 具有可用数字12导联ECG存储库的GWAS队列：ARIC和CHS。基线数字 12-将在PI中通过定制的Matlab软件分析导联ECG的实验室。SCD ECG 将在ARIC中制定风险评分，并在CHS队列中进行验证。净重新分类 将评估改进情况。20年间研究的ECG参数的纵向变化 随访的时间将被评估为心脏结构和功能表型的预测因子， 在第5次ARIC访视时通过超声心动图进行评估。我们的研究将确定基因， 具有特定的心电图特征，这将导致新的治疗目标，并在未来将 启用SCD预防。

Sudden cardiac death (SCD) is a major public health concern, accounting for 400,000 deaths in the US each year. Clinical and autopsy studies have consistently demonstrated a predominant, common pathophysiology in Western populations, showing that the most common electrophysiologic mechanism for SCD is ventricular fibrillation (VF) and the most common pathologic substrate is coronary heart disease (CHD). In about half of SCD cases, death is the first clinical manifestation of CHD. Yet risk factors of SCD early in the natural history of conditions predisposing SCD have not been fully identified, and SCD risk stratification strategy in general population has not been developed. ECG is easy available, non-expensive and noninvasive tool, which carries valuable information on electrophysiological properties of the heart. However, traditional analysis of ECG includes very limited assessment of the arrhythmogenic substrate. Recently we developed novel 12-lead ECG SCD risk score, composed of parameters that measure (1) slow discontinued conduction, (2) temporal repolarization lability, and (3) adverse electrical remodeling. Preliminary gender-, race-, and age-matched case-control analysis of the Atherosclerosis In Community (ARIC) study showed a total continuous net reclassification improvement of 86.0% as compared to the Framingham risk score alone. We hypothesize that (1) the SCD ECG risk score, comprised of the mechanistic ECG markers of arrhythmogenic substrate derived in the resting 12-lead ECG analysis accurately stratify persons into high-, intermediate- and low-risk groups and improve classification in comparison to the risk stratification on the basis of traditional CHD risk factors; (2) heritable factors of the novel ECG phenotype are associated with the increased SCD risk. This application bridges a critical gap between understanding of the SCD mechanisms and SCD risk stratification in a general population. We will leverage 2 unique large NIH-funded prospective community-dwelling GWAS cohorts with an available digital 12-lead ECG repository: ARIC and CHS. Baseline digital 12-lead ECG will be analyzed by customized Matlab software in PIs laboratory. The SCD ECG risk score will be developed in ARIC and validated in the CHS cohort. Net reclassification improvement will be assessed. Longitudinal changes in studied ECG parameters over 20 years of follow-up will be evaluated as predictors of cardiac structural and functional phenotype, assessed by echocardiography at the 5th ARIC visit. Our study will identify genes, associated with specific ECG traits, which will lead to novel targets for treatments and in the future will enable SCD prevention.