Canadian C-spine Audit: Appropriateness of C-spine Radiograph Requests in Adult Spinal Injury Assessment ID 10371
Bibliographic record
Abstract
Aims and Objectives: To establish whether a newly instituted head and neck care bundle (a checklist document), following recommendations by the initial audit appropriateness of C-spine Radiograph Requests in Spinal Injury or direct CT C-spine in accordance to NICE guidance NG41 showed an improvement in the use of the correct first time modality (X-ray or CT). Methodology: This was a retrospective study using the CRIS system to evaluate all patients that attended accident and emergency in the months of January and February 2019. Thirty-five patients had C-spine radiographs and 127 patients had C-spine CT scans. The patient were categorised into high and low risk based on NICE guidance NG41 and the use of patient notes via Patient First. Results: Data was collected and compared with the first audit (ID1614). 74.4% of patients received the appropriate first line radiological modality, compared with 90.7% of patients after the newly instituted head and neck bundle. Discussion: High risk patients were supposed to have a CT first line while low risk patients were supposed to have plain films as a first line modality. The increase in percentage of patients receiving the correct first line modality was thought to be as a result of the newly instituted head and neck care bundle. Whilst this is an improvement, there were still 15 patients who were at high risk of c-spine fracture who did not receive the appropriate first line modality (CT) and therefore could have been missed.
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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 | 0.004 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".