Introduction of the Canadian CT Head Rule Reduces CT Scan Use in Minor Head Injury
Bibliographic record
Abstract
Background : The burden of traumatic brain injury (TBI) is rising in developing countries. Minor head injuries accounts for majority of non-fatal head injury and is associated with significant resource use. The utility of the CT scan in cases of mild head injury is undetermined although a big proportion of our patients are offered the investigation. We hypothesized that the introduction of the Canadian CT head rule (CCTHR) will reduce the utilization rate. Methods : Eighty four eligible patients diagnosed with minor head injury were recruited at the Accident and Emergency Department. The proportion of CT scan orders before (Group I-42 patients) and after (Group II- 42 patients) the introduction of the CCTHR was determined. Treatment in Group I patients followed the primary physician orders while group II patients were offered CT scans only if they presented with ‘high risk’ features of the CCTHR. Group II patients with ‘moderate’ risk factors were admitted for observation or discharged as appropriate to the rule. Results : The proportion of CT scans ordered in Group I was 95.2% while that in Group II was 21.4%. The proportion of patients with moderate risk factors Group I was 90.5%, representing the proportion of patients who did not require a CT scan. None of the patients required neurosurgical intervention and all had good recovery on follow up. Conclusion : The proportion of mild head injury patients requiring a CT scan at AKUH is 21.4%. Limiting CT scans to only this group was not associated with adverse outcomes. It is the recommended that CT scan rates for mild head injury be capped at 25% to save time and money currently being expended. Key Words : Canadian CT Head Rule, Minor Head Injury, Outcomes
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".