Community Risk-based monitoring for Atrial Fibrillation Trial (CRAFT)

Atrial fibrillation, an irregular heart-beat, is common, affecting ~7% of people over 65 years of age. It is a major cause of stroke, increasing the risk of stroke 5-fold, and about one-third of patients with acute stroke have atrial fibrillation. Once detected, there are very effective treatments to prevent stroke - oral anticoagulant therapy (e.g. warfarin or newer anticoagulants) reduces the risk of stroke by about 80% in people who take these medications. However, atrial fibrillation is frequently silent (no symptoms) and often intermittent, and can be difficult to detect. In many cases, the first diagnosis of atrial fibrillation happens when people present to hospital with disabling stroke, even though it could have been prevented if atrial fibrillation was detected. One of the most important challenges in stroke prevention is to find better ways of detecting atrial fibrillation in people who are unaware they have it. Previous studies have shown that a pulse check by a General Practitioner picks-up atrial fibrillation in about 1 in 120 people over 65 years. However, this approach is not sufficient for finding atrial fibrillation when it 'comes and goes' (a single pulse check is likely to miss it). What is required is continuous measurement of the heart rhythm, but until recently, technology to measure continuous heart rhythm has been inadequate. In this trial, we evaluate a novel approach to screening high-risk people, with extended heart monitoring, and compare this to standard care in general practice. We will also evaluate whether self-screening for atrial fibrillation, by regular pulse checks by themselves and/or family members, can pick-up atrial fibrillation. Improving our ability to detect atrial fibrillation will have a major impact on stroke prevention; for every 30 new cases of atrial fibrillation identified, we will prevent one stroke each year.  

Award Date

24 February 2017

Award Value

€886525

Principal Investigator

Professor Martin O'Donnell

Host Institution

National University of Ireland, Galway

Scheme

DIFA 2017