Cloud-Based Mapping for Personalized Ablation
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
- 否
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
Sanjiv Narayan, MD, PhD
Professor of Medicine
Stanford University
