<scp>UK</scp> Medical Cannabis Registry: An Analysis of Outcomes of Medical Cannabis Therapy for Hypermobility‐Associated Chronic Pain
Bibliographic record
Abstract
OBJECTIVE: The study aims to evaluate the clinical outcomes in patients with hypermobility spectrum disorder (HSD) and hypermobile Ehlers-Danlos syndrome (hEDS) with chronic pain following treatment with cannabis-based medicinal products (CBMPs). METHODS: This was a case series conducted with the UK Medical Cannabis Registry. The primary outcomes were changes in the following validated patient-reported outcome measures at 1, 3, 6, 12, and 18 months compared with baseline: Short-Form McGill Pain Questionnaire 2 (SF-MPQ-2), pain visual analog scale score (Pain-VAS), Brief Pain Inventory (BPI), five-level EQ-5D (EQ-5D-5L), Single-Item Sleep Quality Scale (SQS), General Anxiety Disorder Seven-Item Scale (GAD-7), and Patient Global Impression of Change. The incidence of adverse events was analyzed as secondary outcomes. Statistical significance was defined as P <0.050. RESULTS: A total of 161 patients met inclusion criteria. Improvements were observed in BPI severity and interference subscales, SF-MPQ-2, and Pain-VAS (P < 0.001). Changes were also seen in the EQ-5D-5L index value, SQS, and GAD-7 (P < 0.001). A total of 50 patients (31.06%) reported one or more adverse event with a total incidence of 601 (373.29%). The most frequent rating for adverse events was moderate (n = 258; 160.25%), with headache being the most common (n = 44; 27.33%). CONCLUSION: An association was identified between patients with HSD/hEDS with chronic pain and improvements in pain-specific and general health-related quality of life following the commencement of CBMPs. CBMPs were also well tolerated at 18 months. These findings must be interpreted within the context of the limitations of study design but add further weight to calls for randomized controlled trials.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".