Multicentre prospective validation of use of the Canadian C-Spine Rule by triage nurses in the emergency department
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVES: The Canadian C-Spine Rule for imaging of the cervical spine was developed for use by physicians. We believe that nurses in the emergency department could use this rule to clinically clear the cervical spine. We prospectively evaluated the accuracy, reliability and acceptability of the Canadian C-Spine Rule when used by nurses. METHODS: We conducted this three-year prospective cohort study in six Canadian emergency departments. The study involved adult trauma patients who were alert and whose condition was stable. We provided two hours of training to 191 triage nurses. The nurses then assessed patients using the Canadian C-Spine Rule, including determination of neck tenderness and range of motion, reapplied immobilization and completed a data form. RESULTS: Of the 3633 study patients, 42 (1.2%) had clinically important injuries of the cervical spine. The kappa value for interobserver assessments of 498 patients with the Canadian C-Spine Rule was 0.78. We calculated sensitivity of 100.0% (95% confidence interval [CI] 91.0%-100.0%) and specificity of 43.4% (95% CI 42.0%-45.0%) for the Canadian C-Spine Rule as interpreted by the investigators. The nurses classified patients with a sensitivity of 90.2% (95% CI 76.0%-95.0%) and a specificity of 43.9% (95% CI 42.0%-46.0%). Early in the study, nurses failed to identify four cases of injury, despite the presence of clear high-risk factors. None of these patients suffered sequelae, and after retraining there were no further missed cases. We estimated that for 40.7% of patients, the cervical spine could be cleared clinically by nurses. Nurses reported discomfort in applying the Canadian C-Spine Rule in only 4.8% of cases. CONCLUSION: Use of the Canadian C-Spine Rule by nurses was accurate, reliable and clinically acceptable. Widespread implementation by nurses throughout Canada and elsewhere would diminish patient discomfort and improve patient flow in overcrowded emergency departments.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it