Natural Causes of Sports- and Recreation-Related Deaths in the General Population: A 14-Year Review in Québec, Canada
Bibliographic record
Abstract
Background: This study analyzed trends in the frequencies and rates of natural deaths associated with sport and recreation activities in Québec, Canada, from January 2006 to December 2019, and investigated their etiology and characteristics. Methods: (ÉBARS) and Canadian census population data. Results: A total of 297 natural deaths occurred, resulting in a population-based death rate of 0.26 per 100,000 person-years. The participation-based rate was 0.23 per 100,000 participant-years, focusing only on the 24 matching activities in both editions of the ÉBARS. Cycling (20.5%; n = 61), ice hockey (8.8%; n = 26), and hunting (8.1%; n = 24) were associated with the highest frequencies and rates of death. Most of the deaths (95.3%; n = 283) were of cardiac origin, with acute coronary syndrome and malignant cardiac arrhythmia identified as the most common causes. Automated external defibrillators were unavailable at 65% of death sites, and bystander cardiopulmonary resuscitation was performed in 60.9% of cases. Men accounted for the vast majority (92.6%; n = 275) of deaths. Death rates increased starting from age 35, peaking in males 45 and over. Conclusions: Efforts aimed at screening for cardiovascular risk factors and ensuring the widespread availability of automated external defibrillators at recreational sites, including remote areas such as hunting territories, could reduce the incidence of natural deaths associated with sport and recreation activities in Québec.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.020 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".