Exercise Volume and Coronary Artery Calcification: A Systematic Review
Bibliographic record
Abstract
Background: Exercise confers numerous health benefits, including a reduction in all-cause and cardiovascular (CV) mortality. However, conflicting evidence suggests that high-volume endurance exercise may increase coronary artery calcification, a robust predictor of CV events. This systematic review investigated the relationship between exercise volume and coronary artery calcium (CAC) scores. Methods: A systematic search of Medline, Embase, PubMed, and the Cochrane Library (1990 to November 26, 2025) was conducted. Studies reporting exercise volume and CAC scores were included. The methodological index for nonrandomized studies (MINORS) scale was implemented to test study quality. Exercise volume (minutes per week) was stratified into 4 categories: low; moderate; moderate-high; and high. Results: A total of 33 studies met the inclusion criteria: 15 reported higher CAC scores in their highest-volume groups; 8 showed no association or inverse associations; and 10 included single-cohort data. Nine of 12 comparative studies with participants exercising > 450 min/wk showed higher CAC scores in high-volume exercisers. The majority of the 9 studies reporting clinical outcomes showed no relationship or an inverse association between exercise volume and mortality or CV events. Among 5 studies assessing plaque composition, 4 reported a more benign, calcified plaque composition among their high-volume exercisers, representing a potential mechanism for the lower risk of CV events and mortality reported in this population, compared to that of less-active individuals with similar CAC scores. Conclusions: High-volume exercisers may have higher CAC scores compared to less-active cohorts. Despite elevated CAC scores, lower mortality and CV event rates observed in these groups challenge the clinical significance of this observation. Registration: PROSPERO CRD42024607693.
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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 | 0.005 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".