Therapeutic Potential of Cannabidiol, Cannabidiolic Acid, and Cannabidiolic Acid Methyl Ester as Treatments for Nausea and Vomiting
Bibliographic record
Abstract
Introduction: Nausea and vomiting are the most distressing symptoms reported by oncology patients undergoing anticancer treatment. With the currently available treatments, vomiting and especially nausea remain problematic, highlighting the need for alternative treatments. Discussion: Here we review in vitro and in vivo evidence for the effectiveness of the nonpsychoactive cannabinoid cannabidiol (CBD) in managing nausea and vomiting. In addition, we also review the evidence for CBD's acidic precursor, cannabidiolic acid (CBDA), and a methylated version of CBDA (CBDA-ME) in these phenomena. Finally, we explore the potential role of CBD in the treatment of cannabinoid hyperemesis syndrome. Conclusions: CBD has demonstrated efficacy in reducing nausea and vomiting, with CBDA and CBDA-ME being more potent. The data suggest a need for these compounds to be evaluated in clinical trials for their ability to reduce nausea and/or vomiting.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".