Cyclic vomiting syndrome: Pathophysiology, comorbidities, and future research directions
Bibliographic record
Abstract
Cyclic vomiting syndrome (CVS) is characterized by severe episodic emesis in adults and children. Cannabinoid hyperemesis syndrome is an increasingly recognized CVS-like illness that has been associated with chronic cannabis use. There are significant gaps in our understanding of the pathophysiology, clinical features, comorbidities, and effective management options of CVS. Recommendations for treating CVS are based on limited clinical data, as no placebo-controlled, randomized trials have yet been conducted. Diseases associated with CVS, including migraine, mitochondrial disorders, autonomic dysfunction, and psychiatric comorbidities, provide clues about pathophysiologic mechanisms and suggest potential therapies. We review our current understanding of CVS and propose future research directions with the aim of developing effective therapy. Establishing a multicenter, standardized registry of CVS patients could drive research on multiple fronts including developing CVS-specific outcome measures to broaden our understanding of clinical profiles, to serve as treatment end points in clinical trials, and to provide a platform for patient recruitment for randomized clinical trials. Such a robust database would also facilitate conduct of research that aims to determine the underlying pathophysiological mechanisms and genetic basis for CVS, as well as identifying potential biomarkers for the disorder. Soliciting government and industry support is crucial to establishing the necessary infrastructure and achieving these goals. Patient advocacy groups such as the Cyclic Vomiting Syndrome Association (CVSA), which partner with clinicians and researchers to disseminate new information, to promote ongoing interactions between patients, their families, clinicians, investigators, to support ongoing CVS research and education, must be an integral part of this endeavor.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".