Exercise is beneficial to heart health, however, there appears to be a 'U' shaped relationship where too much exercise may increase the risk of an irregular heart rhythm, called atrial fibrillation. Endurance athletes may have up to a 2.5-fold higher risk of developing atrial fibrillation than non-athletic controls.
The mechanisms behind this increased risk of atrial fibrillation are not the well understood. It is thought to be a mixture of enlarged heart chambers, low resting heart rate, genetic predisposition and possibly scarring in the heart. In this study, the investigators will investigate the electrical activity changes in the heart, using a high-quality electrocardiogram (ECG) and relate this to changes in the heart size measured by ultrasound and MRI. Cardiopulmonary exercise testing will determine fitness (V̇O2 max) and assess the heart's electrical activity during exercise.
This will be a case-control study where athletes with and without atrial fibrillation will be recruited. The investigators hope the results of this study can improve our understanding of atrial fibrillation in athletes by associating atrial fibrillation with structural and electrical differences which may aid the prediction of future atrial fibrillation development and help guide more athlete-specific treatment pathways.
≥18 years of age at the time of enrolment, male and female.
History of atrial fibrillation confirmed on ECG - either paroxysmal or persistent.
Competed in endurance sports with a total cumulative moderate to high intensity of > 1500 hours.
Have participated in at least one competitive event in the last 10 years.
Permanent atrial fibrillation.
Atherosclerotic disease: previous myocardial infarction, symptomatic coronary artery disease or Peripheral peripheral arterial disease
Left ventricular systolic dysfunction (EF < 45%)
Heart muscle disease: cardiomyopathies, Infiltrative diseases of the heart
Endurance athletes with and without atrial fibrillation from across the United Kingdom. Recruitment through social media, sports clubs, and word of mouth.
Case-control
Cross-sectional
Not listed
High-resolution ECG
Using high quality ECG, assess whether subtle differences can be detected in athletes with AF, compared to athletes without AF, and whether machine learning could predict new-onset AF. Detection of subtle differences in p wave parameters (duration, amplitude, dispersion, PTFV1) in athletes with AF compared to athletes without AF. AUC, specificity and sensitivity.
AI classification and prediction
Assess the accuracy of using machine learning to identify athletes with AF using ECG data. AUC, specificity and sensitivity of machine learning identification of AF.
72hr heart rate monitoring
Compare autonomic tone via heart rate variability from 72-hour continuous ECG monitoring in athletes with and without AF. Analysis of RR intervals from heart rate variability.
Electronic stethoscope recording
Compare the heart sounds using electronic stethoscope in athletes with and without AF. S1 and S2 sounds of heart valves.
Cardiac imaging
Left ventricular mass
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