Drugs for preventing post-operative nausea and vomiting in patients undergoing laparoscopic cholecystectomy: Network meta-analysis of randomized clinical trials and trial sequential analysis
Bibliographic record
Abstract
BACKGROUND: Different categories of drugs are used to reduce the incidence of post-operative nausea and vomiting (PONV) following laparoscopic cholecystectomy (LC). This study is a network meta-analysis of randomized clinical trials with such drugs. METHODS: Electronic databases were searched for appropriate randomized clinical trials evaluating drugs reducing PONV in LC. Number of patients without PONV at 24 h was the primary outcome; and incidence of nausea and/or vomiting at 6 h and 24 h, and adverse events were the secondary outcome measures. Risk of bias was evaluated for each study. Mixed treatment comparison estimates were derived by random-effects modelling. Trial sequential analysis was carried out to assess the adequacy of evidence; and surface area under cumulative ranking curve was generated to identify the best intervention in the pool. Grading of the evidence for key comparisons was done. RESULTS: Ninety clinical trials were included. Metoclopramide, gabapentin, dixyrazine, ondansetron, granisetron, dexamethasone, tropisetron, droperidol, droperidol/dexamethasone, droperidol/metoclopramide, granisetron/droperidol and granisetron/dexamethasone, haloperidol, dexmedetomidine, palonosetron, droperidol/ondansetron, metoclopramide/dexamethasone, haloperidol/ondansetron, haloperidol/dexamethasone, palonosetron/dexamethasone and ramosetron/dexamethasone were observed with significant benefits compared to placebo. Corticosteroid/serotonin receptor antagonists was observed with the highest probability of being the 'best' in this pool. However, the moderate quality of evidence obtained was adequate to confirm the benefits of dexamethasone and ondansetron only. CONCLUSION: The relative effect sizes for various prophylactic anti-emetics for LC was modelled using the principles of network meta-analysis. Dexamethasone and ondansetron have the best evidence as stand-alone options and the combination is preferred in high-risk category. Caution should be exercised while interpreting the evidence as the estimates might change with head-to-head clinical trial data.
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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 | 0.040 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.018 | 0.012 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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; both teacher heads agree on what is shown here.
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".