Emergence delirium and postoperative pain in children undergoing adenotonsillectomy: a comparison of propofol vs sevoflurane anesthesia
Bibliographic record
Abstract
BACKGROUND: Emergence delirium (ED) is a frequent postoperative complication in young children undergoing ENT procedures and it may be exacerbated by sevoflurane anesthesia whereas propofol maintenance has been suggested to decrease the incidence of ED. The aim of this randomized, prospective, double-blind study was to evaluate the effect of sevoflurane vs propofol anesthesia on the quality of recovery after adenotonsillectomy. METHODS: Forty-two patients were randomized to maintenance with either propofol or sevoflurane for adenotonsillectomy. At the conclusion of surgery, patients were extubated awake. ED and pain were assessed using the Pediatric Anesthesia Emergence Delirium (PAED) and the Children's Hospital of Eastern Ontario Scale (CHEOPS), respectively. Higher PAED scores (0-20) indicate greater severity of ED. Nursing and parental satisfaction, hospital length of stay, postoperative nausea and vomiting (PONV), anesthetic complications, and subsequent emergency room admissions were also assessed. RESULTS: Median PAED score was 14 in the propofol group and 17 in the sevoflurane group (NS). Propofol was associated with less pain medication required during recovery and a lower incidence of PONV (5.3% vs 36.8%, P < 0.05). Nursing and parental satisfaction as well as time spent in recovery room was similar for the two groups. CONCLUSION: Propofol anesthesia does not influence agitation after adenotonsillectomy, as measured by the PAED score. A PAED score of ≥ 10 was not useful in identifying patients with ED. However, propofol maintenance is associated with less need for pain medication in the recovery room and a lower incidence of PONV compared to sevoflurane anesthesia.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".