Survival of the Fittest: The Hidden Cost of Undertriage of Major Trauma
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Injured patients cared for in trauma centers have a lower risk of death than those cared for in nontrauma centers. However, many patients are transported to a non-trauma center after injury (undertriaged) and require transfer to trauma center care. Previous analyses of undertriage focused only on survivors to trauma center care and were potentially subject to survivor bias. Using a novel population-based design, we evaluated the true mortality cost of undertriage. STUDY DESIGN: We used a retrospective cohort design and included all severely injured patients surviving to reach an emergency department within the province of Ontario, Canada. Those patients who were triaged to a non-trauma center as their first hospital exposure were the Undertriage cohort. Undertriage cohort patients were either transferred to a trauma center (Transfer cohort) or died before transfer could be accomplished (emergency department-death cohort). Patients that were transported directly from the scene of injury to a trauma center represented the Direct cohort. Thirty-day mortality in undertriaged patients was analyzed using two approaches: allowing for survivor bias (Transfer versus Direct) and without survivor bias (Undertriage versus Direct). RESULTS: Among 11,398 patients, 66% were transported directly to a trauma center and 30% were transferred. Four percent died before transfer (22% of all deaths). Reproducing approaches that ignore survivor bias, mortality in the Transfer and Direct cohorts was equivalent. However, unbiased assessment demonstrated that mortality was significantly higher in the Undertriage cohort than the Direct cohort (odds ratio = 1.24; 95% CI, 1.10-1.40). CONCLUSIONS: Undertriage after major trauma is associated with substantial mortality. These data suggest a need to design strategies to improve triage to trauma center.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it