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The Efficacy of 5-HT3 Receptor Antagonists for the Prevention of Postoperative Nausea and Vomiting After Craniotomy: A Meta-Analysis

2006· review· en· W2019486723 on OpenAlexafffund
Susan Neufeld, Christine Newburn‐Cook

Bibliographic record

VenueJournal of Neurosurgical Anesthesiology · 2006
Typereview
Languageen
FieldMedicine
TopicNausea and vomiting management
Canadian institutionsStollery Children's HospitalUniversity of Alberta
FundersUniversity of Alberta
KeywordsMedicineNauseaOndansetronVomitingGranisetronTropisetronAnesthesiaPostoperative nausea and vomitingCumulative incidencePlaceboIncidence (geometry)PalonosetronCraniotomyMeta-analysisPopulationAntiemeticInternal medicineAntagonistCohort

Abstract

fetched live from OpenAlex

The purpose of this meta-analysis was to assess the efficacy of prophylactic administration of 5-HT3 receptor antagonists for postoperative nausea and vomiting in neurosurgical patients at 24 and 48+ hours. After a systematic search, 7 published randomized placebo controlled trials involving 448 craniotomy patients (222 treatment, 226 control) were included in the meta-analysis. Study drugs included ondansetron, granisetron, and tropisetron. The cumulative incidence of emesis was significantly reduced in the treatment group at 24 hours [relative risk (RR)=0.50, 95% confidence interval (CI): 0.38-0.66] and 48+ hours (RR=0.52, 95% CI: 0.36-0.75). There were no differences between the treatment and control groups in the cumulative incidence of nausea at 24 hours (RR=0.76, 95% CI: 0.54-1.06) and 48+ hours (RR=0.81, 95% CI: 0.62-1.06). The cumulative incidence of both nausea and vomiting continued to increase after 24 hours in both groups. Despite the ability of 5-HT3 receptor antagonists to reduce emetic episodes, future investigations should seek to address the control of postoperative nausea and to reduce further postoperative emesis in this population.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.014
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.016
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0140.026
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.097
GPT teacher head0.377
Teacher spread0.281 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations46
Published2006
Admission routes2
Has abstractyes

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