Conceptio › Archive › ClinicalTrials.gov
ClinicalTrials.gov public full text Public Domain

'Understanding the Electrophysiological Substrate Underlying Persistent Atrial Fibrillation Study II (USURP AF- Study II)'

University of Leicester · 2019
ClinicalTrials.gov · Datasets · License: Public Domain · 2019
Open Source ↗
Atrial fibrillation (AF) is the most common type of chronic heart rhythm disease worldwide, with significant associated co-morbidities. Although there have been advances in understanding the mechanisms of AF, the underlying cause of AF and factors which perpetuate it remain incompletely understood. This is particularly the case for persistent AF (persAF). Drug treatments for persAF have a role but can have undesirable side effects with relatively limited efficacy. Furthermore, current invasive therapies for persAF remain suboptimal, requiring significant resources, and with potentially serious complications for patients. Catheter ablation is an effective treatment for paroxysmal AF. For persistent AF (persAF), however, catheter ablation does not provide similar results. This is because there remains a poor understanding of the electrophysiological mechanisms driving persAF. Part of this study aims to further explore the specific locations that represent important substrates which would guide more effective catheter ablation. There have been several different ablation approaches explored in the past (see below), however, these did not improve the outcome post procedure compared with pulmonary vein isolation alone. A pilot study has already been carried out and I aim to expand this further with a larger cohort of patients (10-20) over 2 years. In this study the investigators want to explore whether stable high dominant frequency (HDF) sites (with a high organisation index) act as potential drivers of Atrial Fibrillation. Thus, targeting these sites may results in prolongation of the cycle length and thus possible termination of the arrhythmia.
Conceptio Open Archive

Analyze & explore related research in Conceptio

Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.

This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗

Related documents

Record · ID 1352051
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive