Development of a Hypertrophic Cardiomyopathy Consortium

肥厚型心肌病联盟的发展

基本信息

批准号：
8307586
负责人：
THEODORE P ABRAHAM
金额：
$ 3.44万
依托单位：
JOHNS HOPKINS UNIVERSITY
依托单位国家：
美国
项目类别：
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/8307586
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

项目摘要

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）：肥厚的心肌病（HCM）是全球500人中有1人中最常见的遗传性心血管疾病。这也是年轻人突然死亡的最常见原因，与心力衰竭，心律不齐和死亡有关。与疾病的原发性或次要特征有关的常规捕获的临床信息可能表现为心脏结构和/或功能的变化，可以识别出患有这些不良结果的患者。我们的总体目标是通过利用全球现有研究社区的集合中提供大量特征良好的HCM人群的能力来检查HCM临床重要结果的潜在新型预测指标。因此，我们的具体目的是：1）确定失调在预测HCM心力衰竭中的作用； 2）确定房颤的预测因子和3）确定晕厥和心脏猝死的电生理学预测因子。理想情况下，对这些问题进行全面评估将需要大型，特征性的，系统地应计，并且最好是以明确的协议方式纵向纵向遵循的HCM患者的多种族。尽管此类研究人群在组织和地理上都以不同的科学目标散布，但几乎所有人都收集了可以帮助解决我们假设的关键临床和成像信息。将此类实体汇总在一起的挑战是多种多样的，但主要与信息的数量和复杂性并不适合容易集成和分析。从多个研究程序中合并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，存储和分析不同的信息形式。该提案旨在与HCM患者人群进行协作合并几个大型的，不同的研究社区，以测试我们利用CVRG提供的独特建筑和工具的假设。我们计划使用CVRG的专业知识和资源来建立数据共享基础架构，其中参与调查人员将安全，并以HIPAA符合HIPAA的方式，将大量信息上传到一个通用平台上。随后，我们将应用现有的自定义CVRG工具来管理和分析电生理学和成像数据。我们将使用现有的横截面和纵向数据来确定电生理学，心脏结构和功能的参数是否单独或合并，可以预测HCM患者的临床相关结果。公共卫生相关性：该项目旨在使用心血管研究网格建立一个肥厚性心肌病的临床财团，并从美国，欧洲和亚洲的几个参与中心。该财团是其中的第一个财团，将允许汇总临床和成像信息，从而创建一个大型数据库，能够回答有关肥厚性心肌病的管理的关键临床问题，这是一种常见的遗传疾病，没有其他可能的单一机构量。