Evaluation of Cannabis-Related Product Use Among Patients With Hidradenitis Suppurativa: A Narrative Review
Bibliographic record
Abstract
The use of cannabis and cannabis-related products among patients with hidradenitis suppurativa (HS) is increasing globally. Given the potential anti-inflammatory, therapeutic, and pain management benefits of cannabis-related products, we reviewed primary literature to evaluate the prevalence and possible purpose for cannabis use among patients with HS and to provide recommendations to patients and physicians. A narrative review of original studies was conducted using Embase and Ovid Medline databases. The search strategy was confirmed by a librarian and conducted on September 1, 2023, using a detailed list of subject headings and keywords tailored to cannabis, cannabis-related products, HS, and both adult and pediatric populations. Among 43 identified studies, 6 met the eligibility criteria and encompassed 34,435 patients. Patients were mostly female, and studies were conducted across the United States, Canada, and France. Findings show higher cannabis use among HS patients, demonstrating efficacy in pain management, sleep, anxiety relief, itch relief, and improved quality of life. Cannabis may play a role in analgesia, improved quality of life, pain, itch, and overall mental health in patients with HS and healthcare providers including dermatologists should increase their familiarity in appropriate use of cannabis-related products.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".