A Novel Approach to Identifying Atrial Fibrillation
Researchers in the UK have launched an innovative trial using artificial intelligence to identify individuals at risk of developing atrial fibrillation (AF) before symptoms manifest. This cutting-edge tool, developed by scientists and clinicians at the University of Leeds and Leeds Teaching Hospitals NHS Trust, scours GP records for potential risk factors associated with AF.
AF is a heart condition characterised by an irregular and often abnormally fast heart rate, significantly increasing the risk of stroke. With an estimated 1.6 million people diagnosed with AF across the UK, the British Heart Foundation (BHF) suggests thousands more may be living with the condition unaware.
How the AI Tool Works
The algorithm at the heart of this trial, named Find-AF, has been trained to recognise warning signs that could indicate a person's susceptibility to developing AF. It analyses GP records, considering factors such as age, sex, ethnicity, and the presence of other medical conditions including heart failure, high blood pressure, diabetes, ischaemic heart disease, and chronic obstructive pulmonary disease.
Currently being tested in several West Yorkshire GP surgeries, the tool aims to flag patients who may benefit from further cardiac assessment. This proactive approach could lead to earlier diagnosis and treatment, potentially reducing the risk of AF-related strokes.
Potential Impact on Public Health
The implications of this trial are significant. AF is believed to contribute to around 20,000 strokes annually in the UK. Professor Chris Gale, from the University of Leeds, emphasises that often, a stroke is the first indication that someone has undiagnosed AF, which can be devastating for patients and their families.
John Pengelly, a 74-year-old trial participant from Bradford, exemplifies the potential benefits of this technology. Despite having no symptoms, Pengelly was diagnosed with AF through the trial and now takes daily medication to manage his condition and reduce his stroke risk.
Dr Ramesh Nadarajah from Leeds Teaching Hospitals NHS Trust expresses hope that this study will pave the way for a nationwide trial, potentially preventing numerous avoidable strokes. The ultimate goal is to increase early AF diagnoses, ensuring more people receive timely treatment to mitigate their stroke risk.
As this AI-driven approach continues to evolve, it represents a promising step forward in preventative cardiac care, offering hope for improved outcomes for those at risk of AF and its associated complications.
