Emergence delirium in children: a randomized trial to compare total intravenous anesthesia with propofol and remifentanil to inhalational sevoflurane anesthesia
Bibliographic record
Abstract
BACKGROUND: Emergence delirium (ED) refers to a variety of behavioral disturbances commonly seen in children following emergence from anesthesia. Vapor-based anesthesia with sevoflurane, the most common pediatric anesthetic technique, is associated with the highest incidence of ED. Propofol has been shown to reduce ED, but these studies have been methodologically limited. OBJECTIVE: To conduct a randomized-controlled trial comparing the incidence of ED in children following sevoflurane (SEVO) anesthesia and propofol-remifentanil total intravenous anesthesia (TIVA). METHODS: One hundred and twelve children, ASA I-II, aged ≥ 2 and ≤ 6 years, undergoing strabismus repair, were assigned to receive TIVA (intravenous induction and maintenance of anesthesia with propofol and remifentanil) or SEVO (inhalational induction and maintenance of anesthesia with sevoflurane). Parent-child induction behavior was scored using the Perioperative Adult Child Behavior Interaction Scale (PACBIS). Postoperatively, ED was assessed by a masked investigator using the Pediatric Anesthesia Emergence Delirium (PAED) Scale and pain using the Face, Legs, Activity, Cry, Consolability (FLACC) Scale every 5 min. RESULTS: Data are reported for 94 subjects. Incidence of ED was higher with SEVO (38.3% vs 14.9%, P = 0.018). There was no difference in the median PACBIS score. A higher FLACC score was seen with SEVO (median 3 vs 1, P = 0.033). Subjects experiencing ED had higher FLACC scores vs those unaffected by ED (median 7 vs 1, P < 0.0001). CONCLUSION: There was a lower incidence of ED after TIVA. Both intravenous and inhalational inductions were similarly well-tolerated. The use of TIVA was associated with reduced postoperative pain as measured using FLACC scores.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".