Cannabis-Induced Gastrointestinal Tract Symptoms in the Adult Population: A Systematic Review
Bibliographic record
Abstract
OBJECTIVE: Cannabinoid usage is widespread in the self-management of various medical ailments. However, adverse effects have been reported with use, especially pertaining to the gastrointestinal system in adults and aged patients. These range from nausea, vomiting, bloating, or abdominal pain. This systematic review of previously reported cannabis-induced gastrointestinal symptoms in the adult population from the literature provides an analysis of relevant data to enhance knowledge and awareness of this topic. METHODS: PubMed, Ovid MEDLINE, Cochrane Central, EMBASE, and Google Scholar databases were searched for relevant studies published from inception to March 2023. RESULTS: The search yielded 598 results, of which 13 were deemed relevant and underwent further review. These included two systematic reviews, one retrospective cohort study, one retrospective chart review, two cross-sectional studies, one survey, and six case reports. The Cochrane Risk Tool for bias analysis was applied where relevant. The total number of people in the studies selected for analysis was 79, 779. Twelve out of the thirteen included studies reported some type of gastrointestinal tract symptoms experienced in medical and/or recreational cannabis users ranging from nausea, vomiting, diarrhoea, abdominal pain to adult intussusception. CONCLUSION: Potential limitations include small sample sizes, variation in research methodologies, varied studied designs, and limited availability of data on specific populations such as geriatric users. Further research is warranted to add to current evidence pertaining to this emerging topic of significance, fill the broad knowledge gaps and contribute to evidence-based guidelines for healthcare professionals, ensuring safe prescribing practices and provision of quality care.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".