Clinics: elderly, men, high BMI. Biomarkers: brain natriuretic peptide and fibroblast growth factor-23
University of Birmingham
Researchers at the University of Birmingham have discovered two biomarkers that could be used to identify atrial fibrillation in patients with three "clinical risks."
Atrial fibrillation is the most common heart rhythm disorder and affects about 1.6 million people in the UK. Those with atrial fibrillation may be on alert for noticeable heart palpitations when the heart feels as if it is beating, throbbing or beating irregularly. Sometimes, atrial fibrillation does not cause symptoms and a person who is completely unaware that their heart rhythm is irregular.
Scientists have now identified that patients have an increased risk of atrial fibrillation if they have three "clinical risks":
- Old man
- High BMI Index
These patients, scientists say, could be examined for atrial fibrillation by testing their blood to see if they have elevated levels of two biomarkers:
- Brain natriuretic peptide (BNP)
- Phosphate regulation protein called fibroblast growth factor-23 (FGF-23).
The research was conducted by scientists at the Institute of Cardiovascular Sciences and the Institute of Cancer and Genomic Sciences at the College of Medical and Dental Sciences at the University of Birmingham and published in the European Heart Journal.
The first author, Dr. Winnie Chua, said: "People with atrial fibrillation are much more likely to develop blood clots and suffer strokes.
To prevent spills, it is important that they take anticoagulant medications to prevent blood clotting. However, atrial fibrillation is often diagnosed only after a patient has had a stroke.
"It is important that patients at risk be evaluated so they can start taking anticoagulants to avoid potentially fatal complications."
"An electrocardiogram (ECG), a test that measures the electrical activity of your heart to show whether it is working normally or not, is commonly used to detect atrial fibrillation in patients.
"Selecting ECGs requires a lot of resources and is a burden on patients, so it is important that appropriate patients be selected for this type of assessment.
"The biomarkers we identified have the potential to be used in blood tests in community settings, such as general practice, to simplify patient selection for ECG examination."
So far, most studies that have identified biomarkers in patients with atrial fibrillation have been hypothesized and included analysis of a single or small selection of blood biomarkers. In this study, the scientists analyzed 40 common cardiovascular biomarkers in a cohort of 638 hospitalized patients who were recruited between September 2014 and August 2016.
To get the results, the scientists combined traditional statistical analysis with completely new and innovative machine learning techniques.
Principal author Dr. Larissa Fabritz said: "The results of the research were surprising, although BNP is already a known biomarker and widely used in clinical practice, the results regarding the efficacy of the FGF-23 biomarker were an unexpected discovery and FGF-23 is currently only used in a research-based scenario, but we have demonstrated how its use can be invaluable in a clinical setting. "
Corresponding author Professor Paulus Kirchhof, director of the Institute of Cardiovascular Sciences at the University of Birmingham, said: "We hope that as a result of our findings, more people will be diagnosed with what can often be a silent disease to prevent any complications. "
Funded by the University of Birmingham, the research was supported by CATCH ME, a consortium funded by the European Union, led by the University of Birmingham, the British Heart Foundation and the Leducq Foundation.
The research was conducted in collaboration with Sandwell and West Birmingham Hospitals NHS Trust, University Hospital Birmingham NHS Foundation Trust, European Society of Cardiology, German Network for Atrial Fibrillation (AFNET) and Health Data Research UK.
Professor Metin Avkiran, Associate Medical Director of the British Heart Foundation (BHF), added: "Atrial fibrillation increases the risk of stroke, a serious condition that causes more than 36,000 deaths in the UK every year but is often Detect too late
This research used sophisticated machine learning and statistical methods to analyze patient data and provides encouraging evidence that a combination of easy-to-measure indices can be used to predict atrial fibrillation.
"The study may pave the way for better detection of people with AF and their targeted treatment with anticoagulant drugs for stroke prevention and its devastating consequences."
The research, which began in 2013, is under way and the next steps will include patient follow-up evaluations.