Early death in active professional athletes: Trends and causes
Bibliographic record
Abstract
The objective of the study was to examine mortality trends and causes of death among professional athletes from the four major sports in North America who died during their playing careers. 205 deceased athletes who were registered as active when they died from the National Basketball Association (NBA), National Football League (NFL), National Hockey League (NHL), and Major League Baseball (MLB) were examined. Results were compared with the Canadian and U.S. general population. The leading causes of death in players reflected the leading causes of death in the Canadian and U.S. general population (i.e., car accidents). Descriptively, NFL and NBA players had a higher likelihood of dying in a car accident (OR 1.75, 95% CI: 0.91-3.36) compared with NHL and MLB players. In addition, NFL and NBA players had a significantly higher likelihood of dying from a cardiac-related illness (OR 4.44, 95% CI: 1.59-12.43). Mortality trends were disproportionate to team size. Overall, death in active athletes is low. Out of 53 400 athletes who have historically played in the four leagues, only 205 died while active (0.38%). Future examinations into the trends and causes of mortality in elite athlete populations will create a better understanding of health-related risks in elite sport.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".