Utility of computed tomographic imaging of the cervical spine in trauma evaluation of ground-level fall
Bibliographic record
Abstract
BACKGROUND: Computed tomography (CT) of the cervical spine (C-spine) is routinely ordered for low-risk mechanisms of injury, including ground-level fall. Two commonly used clinical decision rules (CDRs) to guide C-spine imaging in trauma are the National Emergency X-Radiography Utilization Study (NEXUS) and the Canadian Cervical Spine Rule for Radiography (CCR). METHODS: Retrospective cross-sectional study of 3,753 consecutive adult patients presenting to an urban Level I emergency department who received C-spine CT scans were obtained over a 6-month period. The primary outcome of interest was prevalence of C-spine fracture. Secondary outcomes included fracture stability, appropriateness of imaging by NEXUS and CCR criteria, and estimated radiation dose exposure and costs associated with C-spine imaging studies. RESULTS: Of the 760 patients meeting inclusion criteria, 7 C-spine fractures were identified (0.92% ± 0.68%). All fractures were identified by NEXUS and CCR criteria with 100% sensitivity. Of all these imaging studies performed, only 69% met NEXUS indications for imaging (50% met CCR indications). C-spine CT scans in patients not meeting CDR indications were associated with costs of $15,500 to $22,000 by NEXUS ($14,600-$25,600 by CCR) in this single center during the 6-month study period. CONCLUSION: For ground-level fall, C-spine CT is overused. The consistent application of CDR criteria would reduce annual nationwide imaging costs in the United States by $6.8 to $9.6 million based on NEXUS ($6.4-$15.6 million based on CCR) and would reduce population radiation dose exposure by 0.8 to 1.1 million mGy based on NEXUS (0.7-1.9 million mGy based on CCR) if applied across all Level I trauma centers. Greater use of evidence-based CDRs plays an important role in facilitating emergency department patient management and reducing systemwide radiation dose exposure and imaging expenditures. LEVEL OF EVIDENCE: Diagnostic study, level III.
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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 | 0.001 | 0.001 |
| 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 | 0.000 |
| 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".