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Record W4407489553 · doi:10.7759/cureus.78958

Cannabinoid Hyperemesis Syndrome: A Rising Complication

2025· review· en· W4407489553 on OpenAlexaff
Saar Peles, Roy Khalifé, Anthony M. Magliocco

Bibliographic record

VenueCureus · 2025
Typereview
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsNational Research Council Institute for Biodiagnostics
Fundersnot available
KeywordsNauseaMedicineCannabisCannabidiolVomitingTetrahydrocannabinolAbdominal painCannabinoidEndocannabinoid systemPsychiatryAnesthesiaInternal medicine

Abstract

fetched live from OpenAlex

Cannabis, commonly known as marijuana, is a psychoactive plant that has been used for both medicinal and recreational purposes for centuries. It contains over 100 biologically active compounds known as cannabinoids, the most notable of which are tetrahydrocannabinol (THC) and cannabidiol (CBD). THC is responsible for the euphoric and hallucinogenic effects associated with cannabis use, while CBD is often utilized for its potential therapeutic benefits, such as pain relief and anti-inflammatory properties. Despite its widespread reputation for alleviating nausea and stimulating appetite, chronic cannabis use has been linked to a paradoxical condition known as cannabinoid hyperemesis syndrome (CHS). CHS is a disorder that paradoxically causes abdominal pain, nausea, and uncontrollable vomiting in long-term cannabis users rather than alleviating pain and reducing nausea. Misdiagnosis of this condition is extremely common, and it is often confused with cyclic vomiting syndrome (CVS). The underlying pathogenesis of CHS is not completely understood, though several mechanisms have been proposed. Although considered rare, there has been a steady increase in CHS diagnoses in the Emergency Department (ED). This article summarizes the symptoms, pathogenesis, treatments for CHS, and differential diagnoses to further increase our understanding of this condition.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.052
GPT teacher head0.384
Teacher spread0.331 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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