Applying the Canadian Head <scp>CT</scp> Criteria to Older Adults Seen in the Emergency Department After a Fall
Bibliographic record
Abstract
BACKGROUND: The Canadian CT Head Rule (CCTHR) is validated in adults who hit their head and experience loss of consciousness, amnesia, or disorientation. There is less evidence to guide brain imaging when the fall history is unclear. METHODS: This is a secondary analysis of a prospective study on adults aged ≥ 65 who presented to 11 emergency departments across Canada and the United States after a ground level fall. We reported the prevalence of adjudicated clinically important intracranial bleeding within 42 days of the emergency department visit among (a) patients who hit their head and met the application criteria for the CCTHR (experienced loss of consciousness, amnesia, or disorientation), (b) patients who hit their head and did not meet the CCTHR application criteria, (c) patients with an unclear history of the CCTHR application criteria, (d) patients with an unclear head injury history, and (e) patients with no head injury. RESULTS: 4303 participants were analyzed. The prevalence of clinically important intracranial bleeding in the subgroups was (a) patients who fulfilled the CCTHR application criteria, 7.7% (54/703, 95% confidence interval [CI]: 5.9%-9.9%), (b) patients who hit their head but did not meet CCTHR application criteria, 2.5% (30/1204, 95% CI: 1.8%-3.5%), (c) patients with head injury but an unclear history of the CCTHR application criteria, 7.6% (19/251, 95% CI: 4.9%-12.0%), (d) patients with an unclear history of head injury, 4.6% (23/502, 95% CI: 3.2%-6.8%), and (e) patients who did not hit their head, 0.8% (13/1643, 95% CI: 0.5%-1.3%). CONCLUSIONS: Older adults presenting after a fall with an unclear history of head injury, or an unclear history of head injury-associated loss of consciousness, amnesia, or disorientation have an elevated risk for clinically important intracranial bleeding that merits emergency brain imaging.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".