Updated Canadian Clinical Practice Guideline for the Rehabilitation of Adults With Moderate to Severe Traumatic Brain Injury: Behavioral Recommendations
Bibliographic record
Abstract
OBJECTIVE: Behavioral changes following moderate to severe traumatic brain injury (MSTBI) are common and can include agitation or aggression, reduced arousal or apathy, and inappropriate sexual behavior. These changes can negatively affect recovery, function, and quality of life. Pharmacological and nonpharmacological interventions are often used to address these challenges; however, there is limited evidence regarding the effectiveness of these treatments. This article will summarize the updated recommendations for the assessment and management of behavioral changes in adults after MSTBI. DESIGN: A systematic search was conducted by the evidence-based review of moderate to severe acquired brain injury to identify new and relevant articles. Expert panels reviewed and discussed the new and existing evidence, evaluated its quality, and added, removed, or modified recommendations and tools as needed. A consensus process was followed to achieve agreement on recommendations. RESULTS: The 2023 Canadian Clinical Practice Guideline for the Rehabilitation of Adults with Moderate to Severe Traumatic Brain Injury (CAN-TBI 2023) includes 21 recommendations regarding best practices for the assessment and management of behavioral disorders post-MSTBI. Fifteen recommendations remained unchanged, and 6 recommendations were updated. Eight recommendations are based on level B evidence and 13 on level C evidence. There are no recommendations based on level A evidence. The guideline also includes a step-by-step algorithm for clinicians to follow outlining an approach to the assessment and management of agitation and aggression. CONCLUSION: CAN-TBI 2023 will assist clinicians in the assessment and safe and effective management of behavioral changes post-MSTBI. The guideline is informed by a growing scientific database although there is a need for additional high-quality research to better guide the assessment and management of this complex patient population.
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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 | 0.012 | 0.065 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.008 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.007 | 0.003 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.015 | 0.006 |
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".