Outcomes of Multi-Trauma Road Traffic Crashes at a Tertiary Hospital in Oman: Does attendance by trauma surgeons versus non-trauma surgeons make a difference?
Bibliographic record
Abstract
Objectives: Trauma surgeons are essential in hospital-based trauma care systems. However, there are limited data regarding the impact of their presence on the outcome of multi-trauma patients. This study aimed to assess the outcomes of multi-trauma road traffic crash (RTC) cases attended by trauma surgeons versus those attended by non-trauma surgeons at a tertiary hospital in Oman. Methods: This retrospective study was conducted in December 2015. A previously published cohort of 821 multi-trauma RTC patients admitted between January and December 2011 to the Sultan Qaboos University Hospital, Muscat, Oman, were reviewed for demographic, injury and hospitalisation data. In-hospital mortality constituted the main outcome, with admission to the intensive care unit, operative management, intubation and length of stay constituting secondary outcomes. Results: A total of 821 multi-trauma RTC cases were identified; of these, 60 (7.3%) were attended by trauma surgeons. There was no significant difference in mortality between the two groups (P = 0.35). However, patients attended by trauma surgeons were significantly more likely to be intubated, admitted to the ICU and undergo operative interventions (P <0.01 each). The average length of hospital stay in both groups was similar (2.6 versus 2.8 days; P = 0.81). Conclusion: No difference in mortality was observed between multi-trauma RTC patients attended by trauma surgeons in comparison to those cared for by non-trauma surgeons at a tertiary centre in Oman.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".