What Do I Tell My Patient With IBD Who Is Asking About Cannabis as Therapy?
Bibliographic record
Abstract
Cannabis, colloquially referred to as marijuana, has become an increasingly frequent topic of discussion between patients with inflammatory bowel disease (IBD) and their providers in recent years. Cannabis has been classified into the category of complementary therapies, but unlike traditional complementary therapies, there are more robust data on the clinical effects in human disease states. Multiple studies have shown a high prevalence of cannabis use in IBD. In Canada, prior to national legalization in October 2018, up to 50% of patients with IBD reported current or past cannabis use to relieve abdominal pain or diarrhea and to improve appetite. 1 In the United States, data from 2013 showed 12% of patients with IBD report current use, with up to 40% with prior use. 2 One US-based study showed doubling rates of cannabis use in patients with IBD from 2012 to 2017, a period when cannabis decriminalization was widely adopted in the United States; however, the increased use appeared to wholly be for recreational use among patients with IBD. 3 A recent survey in pediatric patients (18 to 21 years old) showed 70% of pediatric IBD patients have used cannabis, and the majority (70%) of these patients did not discuss use with their provider. 4 It is important to recognize that a large fraction of patients with IBD are using or have used cannabis to treat IBD-related symptoms. As a provider, it is essential to not only ask your patient about cannabis use but to be prepared for the discussion. Following is an overview of cannabis and its potential application in patients with IBD.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.024 | 0.009 |
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".