Severe Traumatic Brain Injury in French-Speaking Pediatric Intensive Care Units: Study of Practices
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
Abstract Best strategies for managing severe pediatric traumatic brain injury (TBI) are not established, with wide variations among professional practices. The main objective of this study was to assess compliance with updated pediatric TBI management guidelines (2019). A survey was distributed among French-speaking pediatric intensive care physicians from April 1 to June 30, 2019. The survey was based on a clinical case with a total of 70 questions that cover the 15 items of the 2019 TBI guidelines. The questions evaluated the assessment and management of TBI during the acute and intensive care phases. Of 487 e-mails sent, 78 surveys were included. Guidelines were adhered to (> 60%) for 10 of 15 items in the guidelines. Strong adherence to recent guideline changes was achieved for seizure prophylaxis with levetiracetam (n = 21/33, 64%) and partial pressure of carbon dioxide threshold (n = 52, 67%). However, management of the sodium and glucose thresholds and the role of transcranial Doppler were not consistent with the guidelines. Assessment of brain tissue oxygenation (n = 12, 16%) and autoregulation (n = 35, 45%) was not a common practice. There was strong agreement among clinicians on the intracranial pressure (> 80%) and cerebral perfusion pressure (> 70%) thresholds used according to age. Overall, stated practices for the management of TBI appear to be relatively standardized among responders. Variations persist in areas with a lack of evidence and pediatric-specific recommendations.
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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 | 0.001 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it