Role of chronic cannabis use: Cyclic vomiting syndrome vs cannabinoid hyperemesis syndrome
Bibliographic record
Abstract
Cannabis is commonly used in cyclic vomiting syndrome (CVS) due to its antiemetic and anxiolytic properties. Paradoxically, chronic cannabis use in the context of cyclic vomiting has led to the recognition of a putative new disorder called cannabinoid hyperemesis syndrome (CHS). Since its first description in 2004, numerous case series and case reports have emerged describing this phenomenon. Although not pathognomonic, a patient behavior called "compulsive hot water bathing" has been associated with CHS. There is considerable controversy about how CHS is defined. Most of the data remain heterogenous with limited follow-up, making it difficult to ascertain whether chronic cannabis use is causal, merely a clinical association with CVS, or unmasks or triggers symptoms in patients inherently predisposed to develop CVS. This article will discuss the role of cannabis in the regulation of nausea and vomiting, specifically focusing on both CVS and CHS, in order to address controversies in this context. To this objective, we have collated and analyzed published case series and case reports on CHS in order to determine the number of reported cases that meet current Rome IV criteria for CHS. We have also identified limitations in the existing diagnostic framework and propose revised criteria to diagnose CHS. Future research in this area should improve our understanding of the role of cannabis use in cyclic vomiting and help us better understand and manage this disorder.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".