META‐ANALYSIS OF THE DIFFERENCES IN THE TIME TO ONSET OF ACTION BETWEEN ROCURONIUM AND VECURONIUM
Bibliographic record
Abstract
1. The aim of the present study was to conduct a meta-analysis of the magnitude of differences in the onset of action (T(max)) between rocuronium and vecuronium. 2. A search was made in PubMed, EMBASE Drugs and Pharmacology, Cochrane Controlled Trials Register and Cochrane Database on Systematic Reviews. Studies comparing the T(max) at the adductor policies between rocuronium and vecuronium administered as an intravenous bolus were included in the study. Twenty-nine effect sizes obtained from 21 studies were included. 3. The result of the meta-analysis of differences was -57.9 s (95% confidence interval -71.4 to -44.3 s), favouring rocuronium over vecuronium. The smallest difference in T(max) between these neuromuscular-blocking agents was observed in children (-19.1 s). The difference in T(max) between rocuronium and vecuronium in female patients was -38.7 s. The difference in T(max) between rocuronium and vecuronium measured by electromyography was approximately 50% shorter than that determined by acceleromyography or mechanomyography. In a subanalysis between rocuronium 600 mg/kg versus vecuronium 100 mg/kg, the difference in T(max) between them was very similar to that obtained in the general meta-analysis. 4. According to subanalyses of patient age and sex, drug dose and neuromuscular monitoring systems, the T(max) of rocuronium was approximately 20-70 s faster than that of vecuronium.
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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 | 0.021 | 0.032 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.059 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".