Bibliographic record
Abstract
Background: Masters athletes (MAs) (>35y) are a rapidly growing population. While exercise has tremendous health benefits, there is a small absolute risk of major adverse cardiac events (MACE) in those with underlying cardiovascular disease (CVD). Prevention strategies, such as cardiovascular screening aim to identify CVD that may cause a MACE; however, they have not systematically been evaluated. Purpose: To assess cardiovascular risk in MAs and to determine the incidence, cost, and psychological implications of a screening program to detect CVD and prevent MACE in MAs. Methods: MAs underwent cardiovascular screening for five years. The screen consisted of anthropometrics, blood pressure, resting electrocardiogram, questionnaire, physical examination, and Framingham Risk Score (FRS). Participants with an abnormal screen underwent further evaluations. Impact of event scale-revised (IES-R) was used to determine the psychological impact in those diagnosed with CVD. Results: In the first year of the study, 799 MAs (63% male, 54.6 ± 9.5 years) were screened; 91 (11%) of the cohort were found to have CVD. CAD was the most common diagnosis (69.2%). During the following four years, there were an additional 89 CVD diagnoses with an incidence rate of 3.58/100, 4.14/100, 3.74/100, 1.19/100, for years two to five, respectively. A total of 10 MACE (0.30/100 athletes per year) occurred. All MACE occurred in male athletes (63.6±12.5 years). Increasing age (OR=1.05, 95%CI 1.00-1.09; p=0.038), FRS (%) (OR=1.09, 95%CI 1.03-1.16; p=0.003), and LDL cholesterol (mmol/L) (OR=1.71, 95% CI 1.22-2.40; p=0.002) were statistically significant in predicting the presence of CAD, whereas physical activity intensity and volume were not. The overall cost of the screening program was $603,465 or $3,063 per diagnosis. The initial screening year was the most expensive, yet had the highest number of diagnoses, thereby, had the lowest cost per diagnosis ($2,778). The median IES-R scores were within normal ranges. Conclusion: Yearly cardiovascular screening of MAs identified approximately 3 new diagnoses per 100 athletes per year. Despite this, MACE still occurred in MAs. In assessing MAs at risk of CAD FRS, age, and LDL-cholesterol should be utilized. Screening is justifiable, however, further research is required to refine the tools to decrease the cost.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.000 | 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".