Performance of the Canadian CT Head Rule and the New Orleans Criteria for Predicting Any Traumatic Intracranial Injury on Computed Tomography in a United States Level I Trauma Center
Bibliographic record
Abstract
OBJECTIVES: This study compared the clinical performance of the Canadian CT Head Rule (CCHR) and the New Orleans Criteria (NOC) for detecting any traumatic intracranial lesion on computed tomography (CT) in patients with a Glasgow Coma Scale (GCS) score of 15. Also assessed were ability to detect patients with "clinically important" brain injury and patients requiring neurosurgical intervention. Additionally, the performance of the CCHR was assessed in a larger cohort of those presenting with GCS of 13 to 15. METHODS: This prospective cohort study was conducted in a U.S. Level I trauma center and enrolled a consecutive sample of mildly head-injured adults who presented to the emergency department (ED) with witnessed loss of consciousness, disorientation or amnesia, and GCS 13 to 15. The rules were compared in the group of patients with GCS 15. The primary outcome was prediction of "any traumatic intracranial injury" on CT. Secondary outcomes included "clinically important brain injury" on CT and need for neurosurgical intervention. RESULTS: Among the 431 enrolled patients, 314 patients (73%) had a GCS of 15, and 22 of the 314 (7%) had evidence of a traumatic intracranial lesion on CT. There were 11 of 314 (3.5%) who had "clinically important" brain injury, and 3 of 314 (1.0%) required neurosurgical intervention. The NOC and CCHR both had 100% sensitivity (95% confidence interval [CI] = 82% to 100%), but the CCHR was more specific for detecting any traumatic intracranial lesion on CT, with a specificity of 36.3% (95% CI = 31% to 42%) versus 10.2% (95% CI = 7% to 14%) for NOC. For "clinically important" brain lesions, the CCHR and the NOC had similar sensitivity (both 100%; 95% CI = 68% to 100%), but the specificity was 35% (95% CI = 30% to 41%) for CCHR and 9.9% (95% CI = 7% to 14%) for NOC. When the rules were compared for predicting need for neurosurgical intervention, the sensitivity was equivalent at 100% (95% CI = 31% to 100%) but the CCHR had a higher specificity at 80.7% (95% CI = 76% to 85%) versus 9.6% (95% CI = 7% to 14%) for NOC. Among all 431 patients with a GCS score 13 to 15, the CCHR had sensitivities of 100% (95% CI = 84% to 100%) for 27 patients with clinically important brain injury and 100% (95% CI = 46% to 100%) for five patients requiring neurosurgical intervention. CONCLUSIONS: In a U.S. sample of mildly head-injured patients, the CCHR and the NOC had equivalently high sensitivities for detecting any traumatic intracranial lesion on CT, clinically important brain injury, and neurosurgical intervention, but the CCHR was more specific. A larger cohort will be needed to validate these findings.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".