NCT04127123

Cloud-Based Mapping for Personalized Ablation

• Status: Withdrawn
• Phase: —
• Study type: Observational
• Enrollment: 0 (actual)
• Sponsor: Stanford University · Academic / Other
• Sex: All
• Age: 21 Years – 80 Years
• Healthy volunteers: Not accepted

Summary

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.

Detailed description

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.

Conditions

• Atrial Fibrillation
• Arrhythmias, Cardiac

Timeline

• Start date: 2019-07-03
• Primary completion: 2020-12-30
• Completion: 2021-01-11
• First posted: 2019-10-15
• Last updated: 2021-05-07

Locations

1 site across 1 country: United States