Emergency department prediction of post-concussive syndrome following mild traumatic brain injury—an international cross-validation study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Between 20-50% of those suffering a mild traumatic brain injury (MTBI) will suffer symptoms beyond 3 months or post-concussive disorder (PCD). Researchers in Sydney conducted a prospective controlled study which identified that bedside recordings of memory impairment together with recordings of moderate or severe pain could predict those who would suffer PCS with 80% sensitivity and specificity of 76%. PRIMARY OBJECTIVE: This study is a cross-validation study of the Sydney predictive model conducted at Montreal General Hospital, Montreal, Canada. METHODS: One hundred and seven patients were assessed in the Emergency Department following a MTBI and followed up by phone at 3 months. The Rivermead Post-Concussive Questionnaire was the main outcome measure. RESULTS: Regression analysis showed that immediate verbal recall and quantitative recording of headache was able to predict PCD with a sensitivity of 71.4% and a specificity of 63.3%. In the combined MTBI groups from Sydney and Montreal the sensitivity was 70.2% and the specificity was 64.2%. CONCLUSION: This is the first study to compare populations from different countries with diverse language groups using a predictive model for identifying PCD following MTBI. The model may be able to identify an 'at risk' population to whom pre-emptive treatment can be offered.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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 it