Bibliographic record
Abstract
The overuse of computed tomographic (CT) scans for patients who present to the emergency department (ED) after mild traumatic brain injury (mTBI) has been well-documented. The Canadian Computed Tomography Head Rule (CCHR) is a validated tool to guide ED providers in determining the need for emergent CT of mTBI patients. The purpose of this project was to reduce radiation exposure and ED length of stay by using the CCHR to decrease unnecessary CT scans in adults with TBI. Cost of care was also estimated. The CCHR implementation strategy included an education program for ED staff. The use of the CCHR was promoted throughout the intervention period. The outcomes measured were the number of CT scans ordered, ED length of stay, and the cost of avoidable CT scans. Data were collected through medical record reviews completed by the project leader and were evaluated using the independent samples t test. A total of 600 medical records were reviewed. There was a significant difference between adherence to the CCHR before (M = 64.6%) and after provider education (M = 74.3%). The percentage of CT scans that could have been avoided significantly decreased from baseline (M = 0.63) after provider education (M = 0.46). Length of stay for mTBI patients who were managed based on the CCHR (M = 184.9) was significantly less than the length of stay for those who were not (M = 260.1). The cost of avoidable scans was decreased by 37% over the course of the project. There were no incidents of missed diagnosis found. By increasing awareness of the CCHR and promoting its use, the number of head CT scans ordered, cost of care, and ED length of stay for patients who present after mTBI were significantly improved.
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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 | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".