Impact of trauma centre designation level on outcomes following hemorrhagic shock: a multicentre cohort study
Bibliographic record
Abstract
BACKGROUND: Hemorrhagic shock is responsible for 45% of injury fatalities in North America, and 50% of these occur within 2 h of injury. There is currently a lack of evidence regarding the trajectories of patients in hemorrhagic shock and the potential benefit of level I/II care for these patients. We aimed to compare mortality across trauma centre designation levels for patients in hemorrhagic shock. Secondary objectives were to compare surgical delays, complications and hospital length of stay (LOS). METHODS: We performed a retrospective cohort study based on a Canadian inclusive trauma system (1999-2012), including adults with systolic blood pressure (SBP) < 90 mm Hg on arrival who required urgent surgical care (< 6 h). Logistic regression was used to examine the influence of trauma centre designation level on risk-adjusted surgical delays, mortality and complications. Linear regression was used to examine LOS. RESULTS: Compared with level I centres, adjusted odds ratios (and 95% confidence intervals [CI]) of mortality for level III and IV centres were 1.71 (1.03-2.85) and 2.25 (1.08-4.73), respectively. Surgical delays did not vary across designation levels, but mean LOS and complications were lower in level II-IV centres than level I centres. CONCLUSION: Level I/II centres may offer a survival advantage over level III/IV centres for patients requiring emergency intervention for hemorrhagic shock. Further research with larger sample sizes is required to confirm these results and to identify optimal transport time thresholds for bypassing level III/IV centres in favour of level I/II centres.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".