Cannabinoid Hyperemesis Syndrome Survey and Genomic Investigation
Bibliographic record
Abstract
Background: Cannabinoid hyperemesis syndrome (CHS) is a diagnosis of exclusion with intractable nausea, cyclic vomiting, abdominal pain, and hot bathing behavior associated with ongoing tetrahydrocannabinol (THC) exposure. Increasing cannabis use may elevate CHS prevalence, exacerbating a public health issue with attendant costs and morbidity. Objective, Design, and Data Source: This study, the largest contemporaneous database, investigated genetic mutations underlying CHS. Patients with CHS diagnosis and ongoing symptoms were compared with current cannabis users lacking symptoms. Target Population: A screening questionnaire was posted online. Of 585 respondents, 205 qualified as the CHS pool and 54 as controls; a reduced pool of 28 patients and 12 controls ultimately completed genomic testing. Results: Patients and controls were high-frequency users of cannabis flower or concentrates (93%), using multiple grams/day of THC-predominant material. Among patients, 15.6% carried diagnoses of cannabis dependency or addiction, and 56.6% experienced withdrawal symptoms. About 87.7% of patients improved after cannabis cessation, most suffering recurrence rapidly after resumption. Findings in patients included mutations in genes COMT {odds ratio, 12 (95% confidence limit [CL], 1.3–88.1) p =0.012}, transient receptor potential vanilloid receptor 1 ( TRPV1 ) (odds ratio, 5.8 [95% CL, 1.2–28.4] p =0.015), CYP2C9 (odds ratio, 7.8 [95% CL, 1.1–70.1] p =0.043), gene coding dopamine-2 receptor ( DRD2 ) (odds ratio, 6.2 [95% CL, 1.1–34.7] p =0.031), and ATP-binding cassette transporter gene ( ABCA1 ) (odds ratio, 8.4 [95% CL, 1.5–48.1] p =0.012). Limitations: Some participants were reluctant to undergo genetic testing; only 28 of 99 CHS patients who agreed to testing ultimately returned a kit. Conclusion: This is the largest patient cohort of CHS examined to date, and first to note associated mutations in genes affecting neurotransmitters, the endocannabinoid system, and the cytochrome P450 complex associated with cannabinoid metabolism. Although the sample size was smaller than desired, these preliminary findings may contribute to the growing body of knowledge, stimulate additional investigation, help elucidate the pathophysiology of CHS, and, ultimately, direct future treatment.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".