An evaluation of the use of whole-body computed tomography in trauma patients at a United Kingdom trauma centre
Bibliographic record
Abstract
We sought to identify the impact of whole-body computed tomography (WBCT) on working and suspected diagnoses in Emergency Department (ED) trauma patients and to determine the rate of WBCT scans with no detectable traumatic injuries. We performed a retrospective database analysis of all trauma patients who underwent WBCT in 2009, comparing pretest suspicion of specific injury to WBCT findings, looking for the rates of unexpected findings and the absence of traumatic injury in WBCT studies. Our results showed that of the 179 patients who underwent WBCT, no traumatic injury reported in 17 patients while 162 patients demonstrated pathology (47 confirming previously suspected or diagnosed injury and 115 with previously unexpected injury). Overall, WBCT results differed from clinical findings in 130 (72.6%) patients, a statistically significant difference (P<0.0001). In conclusion, WBCT identifies previously unexpected injuries in almost 66% of ED trauma patients, supporting its continued use in the initial assessment of trauma patients.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".