Research that we part-fund at the University of Birmingham could better identify people living with an undiagnosed abnormal heart rhythm.
Atrial fibrillation (AF) is one of the most common forms of abnormal heart rhythm. It has been diagnosed in 1.3 million people in the UK, but it is estimated that there are hundreds of thousands of people living with undiagnosed AF in the country. It is also a major cause of stroke, as it can increase the risk of a blood clot forming inside the heart, which can then travel in the bloodstream to the brain.
An electrocardiogram (ECG) – a test that measures the electrical activity in the heart - is usually used to screen people for AF, but this is resource-intensive and can be burdensome for some patients.
Now, researchers believe some patients could be tested for AF through simple blood tests.
Simplifying patient selection
Scientists have previously identified that patients are more at risk of AF if they have three ‘clinical risks’ – they are older aged, male and have a high Body Mass Index.
These patients, say the researchers at Birmingham, could be screened for AF by testing their blood to see if they have elevated levels of two substances - a hormone released from the heart called brain natriuretic peptide (BNP) and another protein called fibroblast growth factor-23 (FGF-23).
The research was carried out by scientists from the Institute of Cardiovascular Sciences and the Institute of Cancer and Genomic Sciences at the University of Birmingham’s College of Medical and Dental Sciences and has been published in European Heart Journal.
Dr Winnie Chua, one of the lead researchers on the project said: “People with AF are much more likely to develop blood clots and suffer from strokes. To avoid strokes it is important for them to take anticoagulant drugs to prevent blood clotting. However, AF is often only diagnosed after a patient has suffered a stroke.
“Therefore it is important that patients at risk are screened so that they can begin taking anticoagulants to prevent potentially life-threatening complications.”
Until now, studies attempting to identify new predictors of AF have looked at a narrower range of chemicals present in the blood. In this study, the scientists simultaneously analysed 40 common blood chemicals in 638 people.
The scientists combined traditional statistical analyses with innovative machine learning techniques in order to identify new predictors of AF.
Better detection of people with AF
Professor Metin Avkiran, our Associate Medical Director added: “AF increases the risk of stroke, a serious condition that causes over 36,000 deaths in the UK each year, but is often detected too late. This research has used sophisticated statistical and machine learning methods to analyse patient data and provides encouraging evidence that a combination of easy-to-measure indices may be used to predict AF.
"The study may pave the way towards better detection of people with AF and their targeted treatment with blood-thinning medicines for the prevention of stroke and its devastating consequences."
The research, which began in 2013, is ongoing and next steps will involve following up the patients recruited to the study in order to further understand health outcomes and improve the prevention and treatment of AF.
Find out more about atrial fibrillation