Clinical practice guidelines for mild traumatic brain injury and persistent symptoms.
Bibliographic record
Abstract
OBJECTIVE: To outline new guidelines for the management of mild traumatic brain injury (MTBI) and persistent postconcussive symptoms (PPCS) in order to provide information and direction to physicians managing patients’ recovery from MTBI. QUALITY OF EVIDENCE: A search for existing clinical practice guidelines addressing MTBI and a systematic review of the literature evaluating treatment of PPCS were conducted. Because little guidance on the management of PPCS was found within the traumatic brain injury field, a second search was completed for clinical practice guidelines and systematic reviews that addressed management of these common symptoms in the general population. Health care professionals representing a range of disciplines from across Canada and abroad were brought together at an expert consensus conference to review the existing guidelines and evidence and to attempt to develop a comprehensive guideline for the management of MTBI and PPCS. MAIN MESSAGE: A modified Delphi process was used to create 71 recommendations that address the diagnosis and management of MTBI and PPCS. In addition, numerous resources and tools were included in the guideline to aid in the implementation of the recommendations. CONCLUSION: A clinical practice guideline was developed to aid health care professionals in implementing evidencebased, best-practice care for the challenging population of individuals who experience PPCS following MTBI.
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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 | 0.035 | 0.107 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.011 | 0.008 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.007 | 0.005 |
| Research integrity | 0.011 | 0.009 |
| Insufficient payload (model declined to judge) | 0.010 | 0.008 |
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".