The impact of repeated marathon running on cardiovascular function in the aging population
Bibliographic record
Abstract
BACKGROUND: Several studies have correlated elevations in cardiac biomarkers of injury post marathon with transient and reversible right ventricular (RV) systolic dysfunction as assessed by both transthoracic echocardiography (TTE) and cardiovascular magnetic resonance (CMR). Whether or not permanent myocardial injury occurs due to repeated marathon running in the aging population remains controversial. OBJECTIVES: To assess the extent and severity of cardiac dysfunction after the completion of full marathon running in individuals greater than 50 years of age using cardiac biomarkers, TTE, cardiac computed tomography (CCT), and CMR. METHODS: A total of 25 healthy volunteers (21 males, 55 ± 4 years old) from the 2010 and 2011 Manitoba Full Marathons (26.2 miles) were included in the study. Cardiac biomarkers and TTE were performed one week prior to the marathon, immediately after completing the race and at one-week follow-up. CMR was performed at baseline and within 24 hours of completion of the marathon, followed by CCT within 3 months of the marathon. RESULTS: All participants demonstrated an elevated cTnT post marathon. Right atrial and ventricular volumes increased, while RV systolic function decreased significantly immediately post marathon, returning to baseline values one week later. Of the entire study population, only two individuals demonstrated late gadolinium enhancement of the subendocardium in the anterior wall of the left ventricle, with evidence of stenosis of the left anterior descending artery on CCT. CONCLUSIONS: Marathon running in individuals over the age of 50 is associated with a transient, yet reversible increase in cardiac biomarkers and RV systolic dysfunction. The presence of myocardial fibrosis in older marathon athletes is infrequent, but when present, may be due to underlying occult coronary artery disease.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".