Exercise-Induced Cardiac Troponin Elevations: From Underlying Mechanisms to Clinical Relevance
Bibliographic record
Abstract
Serological assessment of cardiac troponins (cTn) is the gold standard to assess myocardial injury in clinical practice. A greater magnitude of acutely or chronically elevated cTn concentrations is associated with lower event-free survival in patients and the general population. Exercise training is known to improve cardiovascular function and promote longevity, but exercise can produce an acute rise in cTn concentrations, which may exceed the upper reference limit in a substantial number of individuals. Whether exercise-induced cTn elevations are attributable to a physiological or pathological response and if they are clinically relevant has been debated for decades. Thus far, exercise-induced cTn elevations have been viewed as the only benign form of cTn elevations. However, recent studies report intriguing findings that shed new light on the underlying mechanisms and clinical relevance of exercise-induced cTn elevations. We will review the biochemical characteristics of cTn assays, key factors determining the magnitude of postexercise cTn concentrations, the release kinetics, underlying mechanisms causing and contributing to exercise-induced cTn release, and the clinical relevance of exercise-induced cTn elevations. We will also explain the association with cardiac function, correlates with (subclinical) cardiovascular diseases and exercise-induced cTn elevations predictive value for future cardiovascular events. Last, we will provide recommendations for interpretation of these findings and provide direction for future research in this field.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".