Lässt sich die Canadian CT Head Rule für das leichte Schädel-Hirn-Trauma auf Deutschland übertragen?
Bibliographic record
Abstract
PURPOSE: To evaluate the applicability of the Canadian CT Head Rule (CCHR) on head trauma patients in a German university hospital. METHODS: 122 patients (m = 74; f = 48; 40 +/- 19 years) were examined with cranial CT due to minor head trauma. The need for cranial CT according to the CCHR was evaluated retrospectively. RESULTS: With a sensitivity of 98.9 % and a specificity of 46.6 % all patients with the need for neurosurgical intervention were detected by applying the major criteria of the CCHR. Also, every patient with severe brain injury was detected by the extended criteria with a sensitivity of 99.6 % and a specificity of 34.1 %. This would have led to a reduction in the rate of cranial CT examinations by 45.1 % for the major and 22.1 % for the extended criteria. No patient with severe brain injury would have been missed by application of the criteria. CONCLUSION: The Canadian CT Head Rule for patients with minor head trauma is applicable with a very high sensitivity and the potential of significantly reducing the rate of cranial CT examinations in these patients.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".