Difference in trauma team activation criteria between hospitals within the same region
Bibliographic record
Abstract
OBJECTIVES: The present study was conducted to establish the current criteria for trauma team activation (TTA) in hospitals in the Metropolitan Sydney area, and examine the rationale behind their use. METHODS: A cross-sectional survey was undertaken of the seven hospitals in the Metropolitan Sydney area designated to receive adult major trauma in March 2004. Trauma coordinators in each hospital provided the criteria used for adult TTA within their hospital. RESULTS: All seven hospitals replied with their TTA criteria and completed the survey. The results show a wide variation in those criteria used by hospitals to activate their trauma team. Universally used criteria included penetrating injury to the head, neck or torso, limb amputation, spinal cord injury and systolic blood pressure <90 mmHg. Physiological limits for TTA varied between hospitals, with different limits for pulse rate and GCS used in different hospitals. All hospitals used mechanism of injury criteria alone as an activation prompt. CONCLUSIONS: The criteria for TTA differ between hospitals within the same region. The criteria currently used will result in over-triage of trauma patients, but this might be of benefit in training the trauma team in centres that do not see a large volume of trauma patients. There are several advantages in standardization of criteria including optimization of patient care, training, research and audit. Further work is needed to validate existing criteria for use throughout the region.
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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 | 0.006 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 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".