Outcomes of Different Health Care Contexts for Direct Transport to a Trauma Center versus Initial Secondary Center Care: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
INTRODUCTION: Within a trauma system, pre-hospital care is the first step in managing the trauma patient. Timely and appropriate transport of the injured patient to the most appropriate facility is important. Many trauma systems mandate that serious trauma cases are transported directly to a level I trauma center unless transfer to a closer hospital is deemed necessary to resuscitate and stabilize the patient prior to onward transfer to definitive care. Statistical and clinical heterogeneity is often high and is likely to be influenced by the heath care context. METHODS: We conducted a systematic review and meta-analysis to compare patient outcomes for patients with serious trauma transported directly to a Level I/II trauma center ('direct' group) to those transported to a healthcare facility before transfer to the Level I/ II trauma center ('transfer' group). A search of bibliographic databases and secondary sources that focus on trauma was made. Studies were grouped by region: United States of America, Canada, Europe, Asia, Australia and New Zealand and South Africa. RESULTS: The review included 43,554 patients from the 30 studies that met the selection criteria. Heterogeneity of the studies was high (I(2) 71%) overall but low for European, Asian, and Australian and New Zealand studies. There was considerable variation between studies in the structure, policies and practices of the respective trauma systems. The effect of "directness" on patient outcomes was inconsistent. CONCLUSION: The current research evidence does not support nor refute a position that all serious trauma patients be routinely transported directly to a level I/II trauma center. As this is a complex issue, local health-care context and injury profile influence trauma policy and practice.
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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 | 0.019 | 0.060 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.057 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".