Efficacy, Tolerability, and Safety of Cannabinoid Treatments in the Rheumatic Diseases: A Systematic Review of Randomized Controlled Trials
Bibliographic record
Abstract
OBJECTIVE: To assess the efficacy, tolerability, and safety of cannabinoids (phyto- and syntheto-) in the management of rheumatic diseases. METHODS: Multiple databases, including Medline, Embase, and CENTRAL, were searched. Randomized controlled trials with outcomes of pain, sleep, quality of life, tolerability (dropouts due to adverse events), and safety (serious adverse events), with comparison of cannabinoids with any type of control, were included. Study methodology quality was evaluated with the Cochrane risk of bias tool. RESULTS: In 4 short-term studies comprising 203 patients (58 with rheumatoid arthritis, 71 with fibromyalgia, and 74 with osteoarthritis [OA]), cannabinoids had a statistically significant effect on pain in 2, sleep in 2, and improved quality of life in 1, with the OA study prematurely terminated due to futility. The risk of bias was high for all 3 completed studies. Dizziness, cognitive problems, and drowsiness, as well as nausea, were reported for almost half of the patients. No serious adverse events were reported for cannabinoids during the study duration. No studies of herbal cannabis were identified. CONCLUSION: Extremely small sample sizes, short study duration, heterogeneity of rheumatic conditions and products, and absence of studies of herbal cannabis allow for only limited conclusions for the effects of cannabinoids in rheumatic conditions. Pain relief and effect on sleep may have some potential therapeutic benefit, but with considerable mild to moderate adverse events. There is currently insufficient evidence to recommend cannabinoid treatments for management of rheumatic diseases pending further study.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.066 | 0.068 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.038 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".