IdeNtification of SPecific EleCTrophenotypes in Atrial Fibrillation

This study will investigate a common heart rhythm disturbance (arrhythmia), atrial fibrillation (AF), to improve understanding of how best to treat it in different patients. Direct current cardioversion (DCCV) is a procedure that can revert the heart to a normal rhythm, however almost all patients will only have a transient benefit, and their heart will return to the abnormal rhythm, AF. Ablation is an invasive procedure that creates scar tissue within the heart to reduce the arrhythmias, with a longer lasting effect than DCCV. It has been used with success in AF that occurs occasionally (paroxysmal) but is not as effective in AF that is more long-lasting, also known as persistent AF. Persistent AF is major cause of symptoms of breathlessness and palpitations and significantly increases the risk of stroke. Doctors are unable to accurately predict which patients will benefit most from an ablation, this can lead to as many as 50% of patients not benefitting from the procedure. The aim is to better predict which patients will benefit from an ablation. The study will include patients undergoing AF ablation or DCCV and perform additional tests including blood tests a heart MRI scan, a special type of heart tracing with up to 252 points and a short period of extra recordings from within the heart during the ablation procedure. Several techniques will be used to analyse this data, including machine learning, to develop a means predict which patients will benefit the most from the ablation procedure, without needing to use any recordings from within the heart.