Evaluation of Pre-Participation Screening and Risk Assessment in Masters Athletes in British Columbia
Bibliographic record
Abstract
BACKGROUND: There has been increased participation in recreational and competitive athletics by middle-aged individuals. Although routine physical activity is associated with health benefits, vigorous physical activity can transiently increase the risk of myocardial infarction or sudden cardiac death in those with unidentified cardiovascular disease. Pre-participation screening (PPS) may be a way to detect underlying disease and mitigate the risk. PURPOSE: To evaluate the prevalence of cardiovascular disease (CVD) and risk factors amongst British Columbia Masters athletes (>35 years). METHODS: Masters athletes from a wide range of sporting activities living in British Columbia, Canada were invited to participate. Athletes were eligible if they participated in sport >3 times per week at a moderate to vigorous intensity. RESULTS: 185 athletes were screened; 60%, 29% and 11% had low, intermediate, and high Framingham Scores (FRS), respectively. A new cardiovascular abnormality was discovered in 14% of the participants with 38 cases pending investigations. CONCLUSION: Given the significant amount of CVD detected in this population, PPS may be warranted amongst Masters athletes. Further study is required in order to determine whether this strategy reduces adverse cardiovascular events and is cost-effective.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".