Development of a Hypertrophic Cardiomyopathy Consortium

肥厚型心肌病联盟的发展

• 批准号: 8413723
• 负责人: THEODORE P ABRAHAM
• 金额: $ 3.18万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-02-01 至 2013-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8413723
• 关键词: Address; Adverse event; Angiography; Architecture; Arrhythmia; Asia; Atrial Fibrillation; Cardiac; Cardiac Death; Cardiovascular Diseases; Cardiovascular system; Cessation of life; Clinical; Clinical Research; Collection; Communities; Coronary; Custom; Data; Data Analyses; Data Set; Databases; Development; Diagnosis; Diagnostic; Dimensions; Disease; Disease Progression; EFRAC; Echocardiography, Doppler, Color; Electrocardiogram; Electrophysiology (science); Europe; Evaluation; Functional disorder; Genetic; Genetic Heterogeneity; Genotype; Goals; Health Insurance Portability and Accountability Act; Heart Atrium; Heart failure; Hereditary Disease; Holter Electrocardiography; Hour; Hypertrophic Cardiomyopathy; Image; Individual; Informatics; Inherited; Institution; Laboratories; Lead; Life; Magnetic Resonance Imaging; Manuals; Maps; Measures; Mechanics; Methods; Morphology; Myocardial; Ontology; Outcome; Output; Patients; Persons; Phase; Physical Examination; Population; Population Research; Process; Recording of previous events; Registries; Research; Research Infrastructure; Research Personnel; Resources; Risk; Role; Series; Services; Signal Transduction; Site; Structure; Sudden Death; Syncope; System; Testing; Thick; Time; Time Series Analysis; Tissues; Translations; Two-Dimensional Echocardiography; United States; Universities; Ventricular; Width; Work; adverse outcome; clinically relevant; cohort; data modeling; data sharing; design; effective therapy; federated computing; heart imaging; heart motion; improved; indexing; novel; patient population; prevent; programs; public health relevance; research clinical testing; sudden cardiac death; tool

DESCRIPTION (provided by applicant): Hypertrophic cardiomyopathy (HCM) is the commonest inherited cardiovascular disorder occurring in 1 in 500 persons worldwide. It is also the commonest cause of sudden death in the young and is associated with heart failure, cardiac arrhythmias and death. It is likely that routinely captured clinical information pertaining to primary or secondary features of the disease, manifesting as changes in cardiac structure and/or function, may allow identification of patients at risk for these adverse outcomes. Our overall goal is to examine potential novel predictors of clinically important outcomes of HCM by leveraging the power of large numbers of well-characterized HCM population available in a conglomeration of existing research communities across the world. Accordingly, our specific aims are: 1) To determine the role of dyssynchrony in predicting heart failure in HCM; 2) To ascertain the predictors of atrial fibrillation and 3) To determine the electrophysiologic predictors of syncope and sudden cardiac death. A comprehensive evaluation of these issues would ideally require large, well- characterized, systematically accrued, and preferably multi-ethnic populations of patients with HCM that have been followed longitudinally in a well-defined protocolized fashion. Although such research populations are organizationally and geographically dispersed with dissimilar scientific goals, almost all collect key clinical and imaging information that could help address our hypothesis. The challenges in bringing such entities together are manifold but primarily related to the fact that the volume and complexity of information does not lend itself to easy integration and analyses. Merging data from multiple research programs requires sophisticated and powerful computational and informatics tools that will allow collection, storage and analyses of disparate forms of information. This proposal seeks to collaboratively amalgamate several large, distinct research communities with populations of HCM patients to test our hypotheses exploiting the unique architecture and tools offered by the CVRG. We plan to use the CVRG expertise and resources to establish a data sharing infrastructure wherein participating investigators will securely, and in a HIPAA compliant fashion, upload large volumes of information on to a common platform. Subsequently, we will apply existing custom CVRG tools for management and analyses of electrophysiology and imaging data. We will use existing cross-sectional and longitudinal data to ascertain if parameters of electrophysiology, cardiac structure and function, either singly or in combination, predict clinically relevant outcomes in HCM patients. PUBLIC HEALTH RELEVANCE: This project seeks to develop a clinical consortium of hypertrophic cardiomyopathy using the cardiovascular research grid with several participating centers from the United States, Europe and Asia. This consortium, a first of its kind, would allow pooling of clinical and imaging information thus creating a large database capable of answering critical clinical questions concerning the management of hypertrophic cardiomyopathy, a common genetic disorder, not otherwise possible with smaller, single institution volumes.

描述（由申请人提供）：肥厚性心肌病（HCM）是最常见的遗传性心血管疾病，全球每500人中就有1人发生。它也是年轻人猝死的最常见原因，与心力衰竭，心律失常和死亡有关。常规捕获的与疾病的主要或次要特征相关的临床信息（表现为心脏结构和/或功能的变化）可能有助于识别面临这些不良结果风险的患者。我们的总体目标是通过利用世界各地现有研究社区中大量特征良好的HCM人群的力量，研究HCM临床重要结局的潜在新预测因素。因此，我们的具体目标是：1）确定不同步性在预测HCM心力衰竭中的作用; 2）确定房颤的预测因子; 3）确定晕厥和心源性猝死的电生理预测因子。理想情况下，对这些问题的全面评价需要大量、特征明确、系统累积的HCM患者，最好是多种族的HCM患者，这些患者已按照明确的方案方式进行了纵向随访。虽然这些研究人群在组织上和地理上分散，具有不同的科学目标，但几乎所有人都收集了有助于解决我们假设的关键临床和成像信息。将这些实体集中在一起的挑战是多方面的，但主要是因为信息的数量和复杂性不便于整合和分析。合并来自多个研究项目的数据需要复杂而强大的计算和信息学工具，这些工具将允许收集，存储和分析不同形式的信息。该提案旨在将几个大型的，不同的研究社区与HCM患者群体合作合并，以利用CVRG提供的独特架构和工具来测试我们的假设。我们计划利用CVRG的专业知识和资源建立一个数据共享基础设施，参与的研究者将安全地以符合HIPAA的方式将大量信息上传到一个通用平台上。随后，我们将应用现有的定制CVRG工具来管理和分析电生理和成像数据。我们将使用现有的横截面和纵向数据，以确定是否电生理参数，心脏结构和功能，无论是单独或组合，预测HCM患者的临床相关结果。 公共卫生关系： 该项目旨在利用心血管研究网格与来自美国、欧洲和亚洲的几个参与中心建立一个肥厚型心肌病临床联盟。这个联盟，第一个同类的，将允许汇集临床和成像信息，从而创建一个大型数据库，能够回答关键的临床问题，有关管理肥厚型心肌病，一种常见的遗传性疾病，否则不可能与较小的，单一的机构卷。

项目成果

Electromechanical relationship in hypertrophic cardiomyopathy.

• DOI: 10.1007/s12265-013-9481-0
• 发表时间: 2013-08
• 期刊: JOURNAL OF CARDIOVASCULAR TRANSLATIONAL RESEARCH
• 影响因子: 3.4
• 作者: Lin, Xiaoping;Liang, Hsin-Yueh;Pinheiro, Aurelio;Dimaano, Veronica;Sorensen, Lars;Aon, Miguel;Tereshchenko, Larisa G.;Chen, Yihan;Xiang, Meixiang;Abraham, Theodore P.;Abraham, M. Roselle
• 通讯作者: Abraham, M. Roselle

Utilizing ECG-Based Heartbeat Classification for Hypertrophic Cardiomyopathy Identification.

• DOI: 10.1109/tnb.2015.2426213
• 发表时间: 2015-07
• 期刊: IEEE transactions on nanobioscience
• 影响因子: 3.9
• 作者: Rahman QA;Tereshchenko LG;Kongkatong M;Abraham T;Abraham MR;Shatkay H
• 通讯作者: Shatkay H

Cardiac MRI evaluation of hypertrophic cardiomyopathy: left ventricular outflow tract/aortic valve diameter ratio predicts severity of LVOT obstruction.

肥厚型心肌病的心脏 MRI 评估：左心室流出道/主动脉瓣直径比可预测 LVOT 梗阻的严重程度。

• DOI: 10.1002/jmri.23677
• 发表时间: 2012
• 期刊: Journal of magnetic resonance imaging : JMRI
• 作者: Vogel-Claussen,Jens;SantaulariaTomas,Miguel;Newatia,Amit;Boyce,Danielle;Pinheiro,Aurelio;Abraham,Roselle;Abraham,Theodore;Bluemke,DavidA
• 通讯作者: Bluemke,DavidA

Relationship of delayed enhancement by magnetic resonance to myocardial perfusion by positron emission tomography in hypertrophic cardiomyopathy.

• DOI: 10.1161/circimaging.112.000110
• 发表时间: 2013-03-01
• 期刊: Circulation. Cardiovascular imaging
• 作者: Bravo PE;Zimmerman SL;Luo HC;Pozios I;Rajaram M;Pinheiro A;Steenbergen C;Kamel IR;Wahl RL;Bluemke DA;Bengel FM;Abraham MR;Abraham TP
• 通讯作者: Abraham TP

Comparison of Outcomes in Patients With Nonobstructive, Labile-Obstructive, and Chronically Obstructive Hypertrophic Cardiomyopathy.

• DOI: 10.1016/j.amjcard.2015.06.018
• 发表时间: 2015-09-15
• 期刊: The American journal of cardiology
• 作者: Pozios I;Corona-Villalobos C;Sorensen LL;Bravo PE;Canepa M;Pisanello C;Pinheiro A;Dimaano VL;Luo H;Dardari Z;Zhou X;Kamel I;Zimmerman SL;Bluemke DA;Abraham MR;Abraham TP
• 通讯作者: Abraham TP