The “weekend warrior”: Fact or fiction for major trauma?
Bibliographic record
Abstract
BACKGROUND: The "weekend warrior" engages in demanding recreational sporting activities on weekends despite minimal physical activity during the week. We sought to identify the incidence and injury patterns of major trauma from recreational sporting activities on weekends versus weekdays. METHODS: We performed a retrospective cohort study using the Alberta Trauma Registry comparing all adults who were severely injured (injury severity score [ISS] ≥ 12) while engaging in physical activity on weekends versus weekdays between 1995 and 2009. RESULTS: Among the 351 identified patients (median ISS 18; median hospital stay 6 d; mortality 6.6%), significantly more were injured on the weekend than during the week (54.8% v. 45.2%, p = 0.016). Common mechanisms were motocross (23.6%), hiking or mountain/rock climbing (15.4%), skateboarding or rollerblading (12.3%), hockey/ice-skating (10.3%) and aircraft- (9.9%) and water-related (7.7%) activities. This distribution was similar regardless of the day of the week. Most patients were injured as a result of a ground-level (21.9%) or higher fall while hiking, mountain climbing or rock climbing (25.9%); motocross-related incidents (24.2%); or collision with a tree, person, man-made object or moving vehicle (14.0%). Injury patterns were similar across both groups (all p > 0.05): head (55.8%), spine (35.1%), chest (35.0%), extremities (31.1%), face (17.4%), abdomen (13.1%). Surgical intervention was required in 41% of patients: 15.1% required open reduction and internal fixation, 8.3% spinal fixation, 7.4% craniotomy, 5.1% facial repair and 4.3% laparotomy. CONCLUSION: The weekend warrior concept may be a validated entity for major trauma.
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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 | 0.007 |
| 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 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".