Effect of propofol on emergence behavior in children after sevoflurane general anesthesia
Bibliographic record
Abstract
BACKGROUND: Emergence agitation (EA) is a postoperative behavior that may occur in children undergoing general anesthesia with inhaled agents. OBJECTIVES: The aim of the present study was to assess the effect of propofol administered at the end of sevoflurane anesthesia on the incidence and severity of EA in children undergoing magnetic resonance imaging (MRI). METHODS: Eighty-four children, 2-7 years old, undergoing MRI were enrolled in this randomized double-blind study. No sedative premedication was administered prior to anesthesia induction. Anesthesia was induced and maintained with sevoflurane in N(2)O/O(2). Group P received propofol 1 mg.kg(-1) and group S received saline. Pediatric Anesthesia Emergence Delirium scale (PAEDs) was used to evaluate recovery characteristics upon awakening and during the first 30 min after emergence from anesthesia. Children with PAEDs >16 were considered agitated. EA was analyzed using the Mann-Whitney U-test. Demographic data and other side effects were analyzed using the Student's t-test. RESULTS: Eighty-three children completed the study. There were 42 children in group P. EA was diagnosed in two children in the propofol group (4.8%) and in 11 children in the placebo group (26.8%, P < 0.05). Time to achieving postanesthesia care unit discharge criteria was not different between the two groups. CONCLUSIONS: The addition of propofol 1 mg.kg(-1) can significantly decrease the incidence of EA after sevoflurane general anesthesia in children undergoing nonpainful procedures.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".