Management of cyclic vomiting syndrome in adults: Evidence review
Bibliographic record
Abstract
BACKGROUND: This evidence review was conducted to inform the accompanying clinical practice guideline on the management of cyclic vomiting syndrome (CVS) in adults. METHODS: We followed the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) framework and focused on interventions aimed at prophylactic management and abortive treatment of adults with CVS. Specifically, this evidence review addresses the following clinical questions: (a) Should the following pharmacologic agents be used for prophylaxis of CVS: amitriptyline, topiramate, aprepitant, zonisamide/levetiracetam, or mitochondrial supplements? (b) Should the following pharmacologic agents be used for abortive treatment: triptans or aprepitant? RESULTS: We found very low-quality evidence to support the use of the following agents for prophylactic and abortive treatment of CVS: amitriptyline, topiramate, aprepitant, zonisamide/levetiracetam, and mitochondrial supplements. We have moderate certainty of evidence for the use of triptans as abortive therapy. We found limited evidence to support the use of ondansetron and the treatment of co-morbid conditions and complementary therapies. CONCLUSIONS: This evidence review helps inform the accompanying guideline for the management of adults with CVS which is aimed at helping clinicians, patients, and policymakers, and should improve patient outcomes.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".