Effect of predicted travel time to trauma care on mortality in major trauma patients in Nova Scotia
Bibliographic record
Abstract
Background: Trauma is a leading contributor to the burden of disease in Canada, accounting for more than 15 000 deaths annually. Although caring for injured patients at designated trauma centres (TCs) is consistently associated with survival benefits, it is unclear how travel time to definitive care influences outcomes. Using a population-based sample of trauma patients, we studied the association between predicted travel time (PTT) to TCs and mortality for patients assigned to ground transport. Methods: Victims of penetrating trauma or motor vehicle collisions (MVCs) in Nova Scotia between 2005 and 2014 were identified from a provincial trauma registry. We conducted cost distance analyses to quantify PTT for each injury location to the nearest TC. Adjusted associations between TC access and injury-related mortality were then estimated using logistic regression. Results: Greater than 30 minutes of PTT to a TC was associated with a 66% increased risk of death for MVC victims (p = 0.045). This association was lost when scene deaths were excluded from the analysis. Sustaining a penetrating trauma greater than 30 minutes from a TC was associated with a 3.4-fold increase in risk of death. Following the exclusion of scene deaths, this association remained and approached significance (odds ratio 3.48, 95% confidence interval 0.98–14.5, p = 0.053). Conclusion: Predicted travel times greater than 30 minutes were associated with worse outcomes for victims of MVCs and penetrating injuries. Improving communication across the trauma system and reducing prehospital times may help optimize outcomes for rural trauma patients.
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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 | 0.001 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".