CT for all or selective approach? Who really needs a cervical spine CT after blunt trauma
Bibliographic record
Abstract
BACKGROUND: Computed tomography (CT) is the standard to screen blunt trauma patients for cervical spine (c-spine) fractures, yet there remains a reluctance to scan all trauma team activations because of radiation exposure and cost. The purpose of this study was to identify predictors of positive CT in an effort to decrease future CT use without compromising patient care. METHODS: We performed a prospective study in which we documented 18 combined NEXUS and Canadian c-spine criteria on 5,182 patients before CT comparing those with and without fractures to identify predictors of injury. Clinical examination was considered positive if any of the 18 criteria were positive. RESULTS: There were 324 patients with a fracture, for an incidence rate of 6.25%. Fracture patients were older (43.89 ± 18.83 years vs. 38.42 ± 17.45 years, p <; 0.0001), with a lower GCS (Glasgow Coma Scale) score (13.49 ± 3.49 vs. 14.32 ± 2.34, p < 0.0001), than nonfracture patients. Clinical examination had a 100% (324 of 324) sensitivity, 0.62% (30 of 4,858) specificity, 6.29% (324 of 5,152) positive predictive value, and 100% (30 of 30) negative predictive value. A total of 77.8% (14 of 18) criteria were significantly associated with fracture by univariate analysis, seven of which were independent predictors of fracture by logistic regression (midline tenderness, GCS score < 15, age ≥65 years, paresthesias, rollover motor vehicle collision, ejected, never in sitting position in emergency department). Evaluation of these seven factors demonstrated a sensitivity of 99.07% (321 of 324), positive predictive value of 6.95% (321 of 4,617), specificity of 11.57% (562 of 4,858), and negative predictive value of 99.47% (562 of 565). CONCLUSION: Although sensitive, the standard clinical criteria used to determine patients who need radiographs lack specificity. Based on these results, more narrow criteria should be validated in an effort to limit the number of c-spine CTs while not compromising patient care. LEVEL OF EVIDENCE: Prognostic study, level II; diagnostic study, level II.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".