Cannabinoid Hyperemesis Syndrome: A Review of Potential Mechanisms
Bibliographic record
Abstract
Introduction: Cannabinoids have long been known for their ability to treat nausea and vomiting. Recent reports, however, have highlighted the paradoxical proemetic effects of cannabinoids. Cannabinoid hyperemesis syndrome (CHS) is characterized by cyclical episodes of nausea and vomiting, accompanied by abdominal pain following prolonged, high-dose cannabis use, which is alleviated by hot baths and showers. Little is known about the cause of this syndrome. Discussion: Cannabinoids produce a biphasic effect on nausea and vomiting, with low doses having an antiemetic effect and high doses producing emesis. Presentation and treatment of CHS are similar to cyclical vomiting syndrome as well as chemotherapy-related anticipatory nausea and vomiting, suggesting that these phenomena may share mechanisms. The prevalence of CHS is not known because of the symptomatic overlap with other disorders and the lack of knowledge of the syndrome by the public and physicians. Treatment with typical antiemetic drugs is ineffective for CHS, but anxiolytic and sedative drugs, along with hot showers, seem to be consistently effective at reducing symptoms. The only known way to permanently end CHS, however, is abstinence from cannabinoids. Case studies and limited pre-clinical data on CHS indicate that prolonged high doses of the main psychotropic compound in cannabis, Δ 9 -tetrahydrocannabinol (THC), result in changes to the endocannabinoid system by acting on the cannabinoid 1 (CB 1 ) receptor. These endocannabinoid system changes can dysregulate stress and anxiety responses, thermoregulation, the transient receptor potential vanilloid system, and several neurotransmitters systems, and are thus potential candidates for mediating the pathophysiology of CHS. Conclusions: Excessive cannabinoid administration disrupts the normal functioning of the endocannabinoid system, which may cause CHS. More clinical and pre-clinical research is needed to fully understand the underlying pathophysiology of this disorder and the negative consequences of prolonged high-dose cannabis use.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".