Arrhythmias & electrophysiologyResearch article
Using Atrial Cardiomyopathy Metrics to Characterize Atrial Fibrillation in Endurance Athletes
- Development of an atrial fibrillation (AF) probability model (logistic regression) in endurance athletes and nonathletic control subjects
Authors' conclusion
A combination of atrial cardiomyopathy markers was associated with high AF prevalence in EAs. A resulting quantitative AF risk identification tool provides promise for interventions aimed at preventing AF and thromboembolic complications in EAs.
Study context
- Population
- Endurance athletes and nonathletic control subjectsEndurance athletes (EAs) 353 · NAs 97
- Participants
- 353 vs 97
- Comparison
- EAs with prevalent AF vs EAs without AF
- EAsn = 353
- NAsn = 97
Main finding
As reported in the abstract
40% larger; P < 0.001
Further findings
Atrial cardiomyopathy markers, EAs with AF vs EAs without AF
LA volume EAs with AF 46.2 mL/m² · EAs without AF 41.9 mL/m²
LA strain (reservoir)
P-wave duration EAs with AF 124 ms · EAs without AF 111 ms
Abnormal P-wave terminal force velocity in lead V1
PACs EAs with AF 118 PACs/24 h · EAs without AF 15 PACs/24 h
- Atrial cardiomyopathy markers, EAs with AF vs EAs without AF: all P < 0.001
Prevalent AF among EAs
- EAs with prevalent AF
- 96 (27%)
Clinical risk model discrimination
- AUC
- 0.84
High AF-PRS and AF odds
- High AF-PRS increased AF odds
- 2.56-fold
- Contributed little additional predictive value
AF prevalence by model risk category
- Low risk athletes
- 4%
- Very high risk athletes
- 86%
Original publication
Summarised from the published abstract; every number is checked against it