Canadian clinical practice guidelines for the use of plant-based cannabis and cannabinoid-based products in the management of chronic non-cancer pain and co-occurring conditions: protocol for a systematic literature review
Bibliographic record
Abstract
INTRODUCTION: Chronic pain and co-occurring disorders, such as sleep disorders, anxiety, depression, post-traumatic stress disorder and substance use disorders, are among the most common conditions for which cannabis and cannabinoid-based products derived from the cannabis plant (CBP) are used for therapeutic purposes. However, healthcare providers report that they lack sufficient information on the risks, benefits and appropriate use of cannabis and CBP derived from the cannabis plant for therapeutic purposes. METHODS AND ANALYSIS: We will conduct a systematic review of studies investigating the use of cannabis and CBP derived from the cannabis plant for the treatment of chronic pain and co-occurring conditions. Randomised controlled trials, meta-analyses and observational studies will be prioritised. We will exclude reviews of cannabinoid mechanisms of actions, commentary articles and narrative reviews. The primary outcome of interest will be efficacy in relieving chronic pain. Secondary outcomes will be efficacy in ameliorating conditions such as sleep disorders, anxiety, depression, post-traumatic stress disorder and substance use disorders. We will search electronic bibliographic databases including Academic Search Complete, Cochrane Database of Systematic Reviews, Evidence based Medicine Reviewes, OVID Medline, PsychINFO, PubMed, CINAHL and Web of Science. Two reviewers will conduct screening and data collection independently. Study level of bias will be assessed using the Cochrane Risk of Bias Assessment Tool for randomised controlled trials and non-randomised studies. Narrative analysis will be utilised to interpret the data. ETHICS AND DISSEMINATION: The results of this systematic review will inform guideline development for the use of cannabis and CBP derived from the cannabis plant in the management of chronic pain and co-occurring conditions. Areas requiring further study will also be highlighted. PROSPERO REGISTRATION NUMBER: CRD42020135886.
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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 | 0.082 | 0.117 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.013 | 0.019 |
| Bibliometrics | 0.022 | 0.025 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.008 | 0.007 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.049 | 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".