Comparative Outcomes of Traumatic Brain Injury from Biking Accidents With or Without Helmet Use
Bibliographic record
Abstract
OBJECTIVE: To determine if health outcomes and demographics differ according to helmet status between persons with cycling-related traumatic brain injuries (TBI). METHODS: This is a retrospective study of 128 patients admitted to the Montreal General Hospital following a TBI that occurred while cycling from 2007-2011. Information was collected from the Quebec trauma registry and the coroner's office in cases of death from cycling accidents. The independent variables collected were socio-demographic, helmet status, clinical and neurological patient information. The dependent variables evaluated were length of stay (LOS), extended Glasgow outcome scale (GOS-E), injury severity scale (ISS), discharge destination and death. RESULTS: 25% of cyclists wore a helmet. The helmet group was older, more likely to be university educated, married and retired. Unemployment, longer intensive care unit (ICU) stay, severe intracranial bleeding and neurosurgical interventions were more common in the no helmet group. There was no significant association between the severity of the TBI, ISS scores, GOS-E or death and helmet wearing. The median age of the subjects who died was higher than those who survived. CONCLUSION: Cyclists without helmets were younger, less educated, single and unemployed. They had more severe TBIs on imaging, longer LOS in ICU and more neurosurgical interventions. Elderly cyclists admitted to the hospital appear to be at higher risk of dying in the event of a TBI.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".