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中文摘要
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描述(由申请人提供):心房颤动(AF)是最常见的心律失常,影响到2-5百万美国人,可能导致心跳跳过、头晕、中风甚至死亡。不幸的是,房颤的治疗是有限的。开发更好的房颤治疗方法的主要缺点之一是我们对房颤病因(其“机制”)的了解尚不清楚。这个更新项目建立在该小组在上一个资助期的发现之上,即人类自动对焦不是随机的或混乱的,而是经常由少数以转子(类似于电旋转陀螺)或焦拍形式的“源”维持(驱动),这些“源”随着时间的推移是稳定的。来源可能位于每个患者不同的心脏区域(心房或上腔),通常远离医生通常靶向烧灼治疗(消融)的地方。在这个项目中,我们将研究1)单独消融旋翼和焦点源(驱动AF)的有效性;2)消融如何改变转子、肺静脉附近的触发部位或其他机制;3)部分患者消融后房颤复发的机制。我们将通过记录AF的详细地图和研究每个受试者AF的几个主要可能机制来实现这些目标。这些研究将包括详细的心房组织功能记录,AF的数学分析,消融后患者的详细随访以及可能复发的AF患者的重复研究。我们将在这个项目中进行的患者特异性分析将是该领域最详细和临床相关的分析之一,并将用于了解疾病并帮助设计更好的治疗方法。这个项目很重要,因为它将定义最近发现的房颤新机制治疗的成功,在这种治疗不成功的情况下,我们将研究原因。通过这种方式,我们将开发一种方法来更好地定义每个患者房颤的原因(机制)。本项目将在电生理研究期间对房颤患者进行研究,使其结果可以直接转化为实践。这种方法
英文摘要
DESCRIPTION (provided by applicant): Atrial fibrillation (AF) is the most common heart rhythm disorder, affecting 2-5 million Americans in whom it may cause skipped heart beats, dizziness, stroke and even death. Unfortunately, therapy for AF is limited. One of the major drawbacks in developing better therapy for AF is that our understanding of what causes AF (its 'mechanisms') is not clear. This renewal project builds on discoveries by this group in the last funding period that human AF is not random or chaotic, but instead is often maintained (driven) by a small number of 'sources' in the form of rotors (akin to electrical spinning tops) or focal beats, that are stable over time. Sources may lie in regions of the heart (the atria, or top chambers) that are different in each patient, often away from where physicians typically target cautery therapy (ablation). In this project, we will study 1) the effectiveness of ablation of rotos and focal sources alone (that drive AF); 2) how ablation alters rotors, trigger sites near the pulmonary veins, or other mechanisms; 3) the mechanisms for AF that may recur in some patients after ablation. We will pursue these aims by recording detailed maps of AF and studying several major possible mechanisms for AF in each subject. These studies will include detailed recordings of atrial tissue function, mathematical analyses of AF, detailed follow-up of patients after ablation and repeat study in patients in whom AF may recur. The patient-specific analyses that we will perform in this project will be among the most detailed and clinically-relevant in the field, and will be used to understand the disease and to help design better therapy. This project is significant because it will define the success of therapy at recently discovered novel mechanisms for AF and, in cases when such therapy is unsuccessful, we will study why. In this way, we will develop an approach to better define the causes (mechanisms) for AF in each patient. This project will be performed in patients with AF during electrophysiologic study, so that its results can be translated directly to practice. This approach may also allow a more rational general approach to drug development and gene therapy.
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Machine Learning for Ventricular Arrhythmias
  • 批准号:
    10658931
  • 项目类别:
  • 资助金额:
    $65.76万
  • 财政年份:
    2023
  • 负责人:
    Sanjiv M Narayan
  • 依托单位:
Machine Learning in Atrial Fibrillation
  • 批准号:
    10594043
  • 项目类别:
  • 资助金额:
    $74.22万
  • 财政年份:
    2020
  • 负责人:
    Sanjiv M Narayan
  • 依托单位:
Machine Learning in Atrial Fibrillation
  • 批准号:
    10347364
  • 项目类别:
  • 资助金额:
    $74.91万
  • 财政年份:
    2020
  • 负责人:
    Sanjiv M Narayan
  • 依托单位:
The Maintenance of Human Atrial Fibrillation
  • 批准号:
    9107482
  • 项目类别:
  • 资助金额:
    $18.33万
  • 财政年份:
    2010
  • 负责人:
    Sanjiv M Narayan
  • 依托单位:
海外基金