Adherence to Brain Trauma Foundation Guidelines for Management of Traumatic Brain Injury Patients and Its Effect on Outcomes: Systematic Review
Bibliographic record
Abstract
Traumatic brain injury (TBI) management based on Brain Trauma Foundation (BTF) guidelines is widely accepted and thought to improve outcome. The objectives of this study are to provide an overview of adherence to BTF guidelines and to explore which factors influence adherence. We conducted a search of relevant electronic bibliographic databases. Twenty articles met inclusion/exclusion criteria out of 666 articles screened. All were cohort studies. Wide variation in adherence to BTF guidelines was observed with a median of 66.2% (range 0-100%). The lowest median adherence was observed with surgical management (14%), whereas the highest was observed with oxygenation (100%), steroid (97.8%), and blood pressure recommendation (92.3%). Variability was primarily explained by the variation in the strength of evidence of each recommendation. Treating patients with higher severity of injury as well as treatment in a Level I trauma center positively influenced adherence. Overall, adherence to BTF guidelines varies. Further research is required to strengthen the current evidence and to identify factors related to adherence to guidelines from a professional prospective.
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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 | 0.008 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".