Canadian C-spine Rule versus NEXUS in Screening of Clinically Important Traumatic Cervical Spine Injuries; a systematic review and meta-analysis.
Bibliographic record
Abstract
Introduction: The Canadian C-spine Rule (CCR) and the National Emergency X-Radiography Utilization Study (NEXUS) are two criteria designed to rule-out clinically important traumatic cervical Spinal Cord Injury (SCI). In this systematic review and meta-analysis, we reviewed the articles comparing the performance of these two models. Methods: " package and applying weighted random effect model, area under the receiver operating characteristic (ROC) curve (AUC), sensitivity, specificity, negative likelihood ratio, positive likelihood ratio, and diagnostic odds ratio (DOR) were calculated with 95% confidence interval (95% CI). Results: We included 5 studies with direct comparison. Area under the ROC curve of NEXUS in screening of patients with clinically important cervical SCI was 0.708 (95% CI: 0.647 to 0.762). Pooled sensitivity and specificity of NEXUS criteria in screening of patients with clinically important cervical SCI were 0.899 (95% CI: 0.845 to 0.936) and 0.398 (95% CI: 0.315 to 0.488). The positive and negative likelihood ratios of NEXUS were 1.494 (95% CI: 1.146 to 1.949) and 0.254 (95% CI: 1.155 to 1.414), respectively. Diagnostic odds ratio of NEXUS was 5.894 (95% CI: 3.372 to 10.305). Furthermore, area under the ROC curve of CCR in screening of clinically important cervical SCI was 0.793 (95% CI: 0.657 to 0.884). Meta-analysis results showed that pooled sensitivity of CCR criteria in screening of patients with clinically important cervical SCI was 0.987 (95% CI: 0.957 to 0.996) and specificity was 0.167 (95% CI: 0.073 to 0.336). The positive and negative likelihood ratios of CCR were 1.184 (95% CI: 0.837 to 1.675) and 0.081 (95% CI: 0.021 to 0.308), respectively. Diagnostic odds ratio of CCR was 14.647 (95% CI: 3.678 to 58.336). Conclusion: Based on studies, both CCR and NEXUS were sensitive rules that have the potential to reduce unnecessary imaging in cervical spine trauma patients. However, the low specificity and false-positive results of both of these tools indicate that many people will continue to undergo unnecessary imaging after screening of cervical SCI using these tools. In this meta-analysis, CCR appeared to have better screening accuracy.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.012 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.000 | 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".