跳至主要内容
临床试验/NCT04127123
NCT04127123撤回不适用

Cloud-Based Mapping for Personalized Ablation

Stanford University1 个研究点 分布在 1 个国家开始时间: 2019年7月3日最近更新:
适应症

试验速览

阶段
不适用
状态
撤回
试验地点
1
主要终点
Mapping Accuracy

研究概览

简要总结

Atrial fibrillation is a serious public health issue that affects over 5 million Americans in whom it may cause skipped beats, dizziness, stroke and even death. This study seeks to improve our understanding of the causes of atrial fibrillation and to design new and more effective therapy for this heart rhythm disorder.

详细描述

This project will focus on the development of a novel paradigm for electrophysiologic data analysis and interpretation using cloud-based computing resources and mobile technology. Currently, electrophysiologic data gathered during a procedure is analyzed by the operator using multiple separate desk-based computer systems in the electrophysiology laboratory. The investigators propose that advances in cloud-based computing resources and network connectivity should apply a mobile paradigm to apply to invasive electrophysiologic procedures.

This project will provide proof-of-concept that open-access software the investigators have developed and made available online could be used, via a mobile phone interface, to identify sites in the heart where therapy is effective. At no time will patient therapy be guided by this system. The investigators will pursue therapy using only clinical means. In parallel, a double-blinded team will analyze data in real time using our online software visualized on a smartphone. Only when the case is concluded will the data be unblinded, to determine if the mobile system was accurate in real time.

Thus, development and testing of the cloud-based computing system is designed only to establish feasibility of the paradigm, followed by improvement of computational modeling algorithms. The data that is collected will add to the investigators' existing unique catalogue of multimodal (structural, clinical, and electrophysiologic) data.

The importance of this novel paradigm is to move from analyzing large volumes of data in isolation to creating a mobile platform, and to allow scalability to increase access, such as to underdeveloped medical centers.

研究设计

研究类型
Observational
观察模型
Cohort
时间视角
Prospective

入排标准

年龄范围
21 Years 至 80 Years(Adult, Older Adult)
性别
All
接受健康志愿者

入选标准

  • men and women of any ethnicity
  • aged 21-80 years
  • undergoing ablation of atrial fibrillation at Stanford University
  • failed or be intolerant of ≥ 1 anti-arrhythmic drug or not willing to accept antiarrhythmic drug therapy.

排除标准

  • active coronary ischemia or decompensated heart failure
  • atrial or ventricular clot on trans-esophageal echocardiography
  • pregnancy (to minimize fluoroscopic exposure)
  • inability or unwillingness to provide informed consent
  • rheumatic valve disease (because it results in a unique AF phenotype)
  • thrombotic disease or venous filters
  • significantly reduced kidney function

结局指标

主要结局

Mapping Accuracy

时间窗: During Procedure (Electrophysiology Study and Ablation)

Location of driver regions for AF

Termination of atrial fibrillation

时间窗: During Procedure (Electrophysiology Study and Ablation)

Does ablation at any driver region lead to AF termination

次要结局

未报告次要终点

研究者

申办方类型
Other
责任方
Principal Investigator
主要研究者

Sanjiv Narayan, MD, PhD

Professor of Medicine

Stanford University

研究点 (1)

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