Time-to-Subsequent Head Injury From Sports and Recreation Activities
Bibliographic record
Abstract
OBJECTIVE: To provide population-based risk estimates for sustaining subsequent head injuries (HIs), which occur in sports and recreation (SR). DESIGN: Population-based, retrospective, cross-sectional study. SETTING: Retrospective review of data from 2 tertiary care and 3 community care emergency departments (EDs) in Edmonton, Alberta, Canada. PATIENTS: Individuals younger than 36 years presenting to an ED with an SR-related injury between April 1, 1997, and March 31, 2008. There were 9246 subsequent ED records identified for 8958 patients in the main analysis. MAIN OUTCOME MEASURES: Clinically diagnosed HI occurring in SR activities after an index presentation, and the number of days between ED presentations for diagnosed SR-HIs. RESULTS: Individuals with 1 and 2 previous SR-related HIs were 2.62 [95% confidence interval (CI), 2.23-3.07] and 5.94 times, respectively, more likely (95% CI, 3.43-10.29) to sustain a subsequent HI than those without a previous HI. The median time-to first HI was 758 days from an initial injury and decreased to 613 days and 303 days for those at risk of second and third SR-related HIs (P < 0.0001). Individuals aged 7 to 13 years were 4.29 times more likely (95% CI, 2.65-6.92) to sustain an HI when presenting with a subsequent SR injury, compared with those aged 30 to 35 years. CONCLUSIONS: The odds of sustaining a subsequent HI substantially increase with each successive HI. Time between SR-related HIs shortens as the number of HIs increases. Initial HI may be a key marker to institute high-risk injury prevention measures directed at young persons who present to EDs.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".