Management of opioid use disorder: 2024 update to the national clinical practice guideline
Bibliographic record
Abstract
BACKGROUND: In an evolving landscape of practices and policies, reviewing and incorporating the latest scientific evidence is necessary to ensure optimal clinical management for people with opioid use disorder. We provide a synopsis of the 2024 update of the 2018 National Guideline for the Clinical Management of Opioid Use Disorder, from the Canadian Research Initiative in Substance Matters. METHODS: For this update, we followed the United States Institute of Medicine's Standards for Developing Trustworthy Clinical Practice Guidelines and used the Appraisal of Guidelines Research and Evaluation-Recommendation Excellence tool to ensure guideline quality. We carried out a comprehensive systematic literature review, capturing the relevant literature from Jan. 1, 2017, to Sept. 14, 2023. We drafted and graded recommendations according to the Grading of Recommendations, Assessments, Development and Evaluation approach. A multidisciplinary external national committee, which included people with living or lived experience of opioid use disorder, provided input that was incorporated into the guideline. RECOMMENDATIONS: From the initial 11 recommendations in the 2018 guideline, 3 remained unchanged, and 8 were updated. Specifically, 4 recommendations were consolidated into a single revised recommendation; 1 recommendation was split into 2; another recommendation was moved to become a special consideration; and 2 recommendations were revised. Key changes have arisen from substantial evidence supporting that methadone and buprenorphine are similarly effective, particularly in reducing opioid use and adverse events, and both are now considered preferred first-line treatment options. Slow-release oral morphine is recommended as a second-line option. Psychosocial interventions can be offered as adjunctive treatment but should not be mandatory. The guideline reaffirms the importance of avoiding withdrawal management as a standalone intervention and of incorporating evidence-based harm reduction services along the continuum of care. INTERPRETATION: This guideline update presents new recommendations based on the latest literature for standardized management of opioid use disorder. The aim is to establish a robust foundation upon which provincial and territorial bodies can develop guidance for optimal care.
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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 | 0.034 | 0.121 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.008 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.007 | 0.005 |
| Research integrity | 0.012 | 0.012 |
| Insufficient payload (model declined to judge) | 0.008 | 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".