Effect of Desflurane versus Sevoflurane in Pediatric Anesthesia: A Meta-Analysis
Bibliographic record
Abstract
PURPOSE: To compare the effect of desflurane versus sevoflurane in pediatric anesthesia by conducting meta-analysis. METHODS: Studies were searched from PubMed, Medline, Springer, Elsevier Science Direct, Cochrane Library and Google Scholar up to July 2014. Weighted mean difference (WMD) or risk ratio (RR) and 95% confidence intervals (CIs) were considered as effect sizes. Heterogeneity across studies was assessed by Cochran Q test and I2 statistic. The random effects model was performed in the meta-analysis when heterogeneity was observed, or the fixed effect model was used. Review Manager 5.1 software was applied for the meta-analysis. RESULTS: A total of 11 studies (13 comparisons) involving 1,273 objects were included in this meta-analysis. No heterogeneity was observed between studies for any comparison but for postoperative extubation time. The results showed significant differences between desflurane and sevoflurane groups for postoperative extubation time (WMD = -3.87, 95%CI = -6.14 to -1.60, P < 0.01), eye opening time (WMD = -1.11, 95%CI = -1.49 to -0.72, P < 0.01), awakening time (WMD = -4.27, 95%CI = -5.28 to -3.26, P < 0.01) and agitation (RR = 1.44, 95%CI = 1.05 to 1.96, P = 0.02). No significant differences (P > 0.05) were detected for discharge from the recovery room, oculocardiac reflex, nausea and vomiting and severe pain. CONCLUSIONS: Desflurane may have less adverse effects than sevoflurane when used in pediatric anesthesia with significantly shorter postoperative extubation time, eye opening time and awakening time as well as slighter agitation.
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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 | 0.014 | 0.026 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.025 | 0.064 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 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".