Injury Patterns and Discharge Dispositions in BC Motorcycle Accident Victims: A Retrospective Chart Analysis
Bibliographic record
Abstract
OBJECTIVE: Motorcycle ridership is rising in Canada. Though motorcycling injuries have been studied in the United States, Europe and Asia, there is a paucity of Canadian studies. We provide a descriptive analysis of injury patterns in motorcycle crash victims and their relationship to discharge disposition and length of hospital stay. METHODS: We performed a retrospective chart review of all patients involved in a motorcycle crash and admitted to Vancouver General Hospital between April 2001 and December 2009 (N = 567). We extracted data from the ICD-10 coded Discharge Abstract Database, and re-coded injuries into overarching anatomical categories. Discharge dispositions were recorded as they appeared in patient charts. RESULTS : Riders tended to be male (89.2%) and had a mean age of 37.2. The average length of stay was 14.4 days. The most common injuries were tibial fractures (N = 108, 19% of cases), forearm fractures (N = 105, 18.5%), and rib fractures (N=92%, 16.2%) . Most riders were discharged home (N=403, 70.0%), and these patients most commonly sustained tibial and forearm fractures (N=70, 17.4%, for each). Those who remained in hospital were most likely to have sustained injuries to the pelvis (N=43, 29.3%), cervical spine (N=38, 25.9%), or thoracic spine (N=37, 25.2%). Among the 14 patients (2.5%) who expired, the most common injuries were intracranial haemorrhage, rib fracture, haemothorax, liver injury, and cervical spine fracture (N=5, 35.7% each). CONCLUSION: The results provide a starting point to help physicians predict injuries in motorcycle crash victims as well as predict their dispositions.
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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 | 0.003 | 0.004 |
| 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) | 0.001 | 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".