Electrocardiographic changes following six months of long‐distance triathlon training in previously recreationally active individuals
Bibliographic record
Abstract
ABSTRACT Background : Clinical electrocardiographic (ECG) guidelines for athlete's heart are based upon cross‐sectional data. We aimed to longitudinally evaluate the influence of endurance training on the ECG and compare the prevalence of ECG abnormalities defined by contemporary criteria. Methods : A group of 66 training‐naïve individuals completed a six‐month training programme with resting ECGs and cardiopulmonary exercise tests performed at baseline, two and six months. Data were analysed using repeated measures analysis of variance and the prevalence of ECG abnormalities compared between proposed criteria. Results : Maximal oxygen consumption increased from 45.4 ± 7.1 to 50.3 ± 7.1 ml·kg −1 ·min −1 ( p < 0.05) pre‐to‐post training. ECG changes included, bradycardia (60 ± 12 vs. 53 ± 8 beats·min −1 ; p < 0.05), shorter P wave duration (106 ± 10 vs. 103 ± 11 ms; p < 0.05), reduced QTc (413 ± 27 vs. 405 ± 22 ms; p < 0.05), and increased left ventricular Sokolow‐Lyon index (2.45 ± 0.66 vs. 2.62 ± 0.78 mV; p < 0.05). 85% of individuals showed ≥1 ‘training‐related’ ECG finding at six months vs. 68% at baseline. Using the 2013 Seattle Criteria, 4 ECGs were ‘abnormal’ at baseline and 3 at month six vs. 2 at baseline and 1 at month six, using the 2017 International Consensus. Prevalence of ‘borderline’ findings did not increase with training (11% at baseline and six months). Conclusion : Six‐months endurance training leads to a greater prevalence of ‘training‐related’ but not ‘borderline’ or ‘training‐unrelated’ ECGs. ‘Borderline findings’ may not necessarily represent training‐related cardiac remodelling in novice athletes following a six‐month training intervention. KEY MESSAGES This study aimed to assess the longitudinal ECG changes following six months of endurance training, in training‐naïve individuals, and whether these ECG changes support the revisions made to the recent 2017 international consensus criteria. The prevalence of ‘training‐related’ findings were increased with six months of endurance training, however the prevalence of the revised ‘borderline’ criteria, according to the 2017 international consensus, did not increase and the associated quantitative ECG data (e.g. P‐wave amplitude, QRS axis and QRS duration) remained unchanged. Further clinical consideration may be warranted for individuals within the early phase of exercise engagement presenting with ‘borderline’ ECG abnormalities, defined by the International criteria.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".