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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:
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