Bibliographic record
Abstract
Background and aims: Currently there are no national guidelines in the UK for clearing the cervical spine (C-spine) of children following trauma. In children aged 0–3 years clinical examination is considered unreliable often leading to unnecessary cervical immobilisation and imaging. Aims: The aim of this study was to investigate the current practice of C-spine clearance at the major paediatric trauma centres across the UK. Methods: 144 consultants and registrars, including A&E doctors, orthopaedic surgeons, neurosurgeons, radiologists and paediatric intensivists at 16 major UK paediatric trauma centres were contacted to complete a 12 question survey. They were questioned on who was responsible for clearing C-spines in their hospital, the imaging they used, their level of paediatric experience, as well as the usage and presence of protocols in their hospital. Results: From 144 doctors contacted, 31 completed questionnaires were received from 6 different trauma centres. The results showed 82.1% of respondents used clinical judgement to clear the C-spine, the National Emergency X-Radiography Utilization Study (NEXUS) was used by 17.9% and the Canadian C-spine Rules (CCR) by 14.3%. The most frequently used imaging modality was CT (74.2%), with X-ray at 61.3%, MRI 41.9% and no imaging in 19.4% of cases. Only 22% of respondents reported having a local protocol. Conclusions: This study shows great diversity in current practice for clearance of the C-spine in young children following trauma. There were discrepancies between clinicians at the same hospital, as well as between different trauma centres, thus highlighting the need for consensus guidelines.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.748 | 0.612 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".