Assessment of Clinical Outcomes in Patients With Osteoarthritis: Analysis From the UK Medical Cannabis Registry
Bibliographic record
Abstract
Osteoarthritis accounts for 0.6% of disability-adjusted life years globally. There is a paucity of research focused on cannabis-based medicinal products (CBMPs) for osteoarthritic chronic pain management. This study aims to assess changes in validated patient-reported outcome measures (PROMs) and CBMP clinical safety in patients with osteoarthritis. A prospective case series from the UK Medical Cannabis Registry was analyzed. Primary outcomes were changes in the Brief Pain Inventory (BPI), McGill Pain Questionnaire (MPQ2), EQ-5D-5L, Generalized Anxiety Disorder-7 (GAD-7) questionnaire, and Single-Item Sleep Quality Scale (SQS) at 1-, 3-, 6-, and 12-month follow-ups from baseline. Common Terminology Criteria for Adverse Events v.4.0 was used for adverse event (AE) analysis. Statistical significance was defined as p < 0.050. Seventy-seven patients met inclusion criteria. CBMP initiation correlated with BPI pain severity (p = 0.004), pain interference (p = 0.005), and MPQ2 (p = 0.017) improvements at all follow-ups compared to baseline. There were improvements in the EQ-5D-5L index (p = 0.026), SQS (p < 0.001), and GAD-7 (p = 0.038) up to 6 and 3 months, respectively. Seventeen participants (22.08%) recorded 76 mild AEs (34.86%), 104 moderate AEs (47.71%), and 38 severe AEs (17.43%). Though causality cannot be assumed in this observational study, results support development of randomized control trials for osteoarthritis pain management with CBMPs.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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; a candidate call from one teacher head, 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".