Ketamine Does Not Reduce Postoperative Morphine Consumption After Tonsillectomy in Children
Bibliographic record
Abstract
BACKGROUND: Tonsillectomy is one of the most frequently performed operations in children and frequently associated with moderate-to-severe pain. OBJECTIVES: The aim of the present study was to assess the effect of a subhypnotic dose of ketamine on postoperative pain and morphine consumption after tonsillectomy in children. METHODS: This randomized double-blind study involved 84 children, 2 to 12-year-olds, undergoing elective outpatient tonsillectomy. Children were assigned to 2 groups. Group K received morphine and ketamine, 0.25 mg/kg, at induction and Group M received morphine. Modified Children's Hospital of Eastern Ontario (mCHEOP) scale was used to evaluate postoperative pain. Pain, morphine consumption, and unwanted side effects were recorded for a 24-hour period. One-way analysis of variance and chi2 tests were used for statistical analysis. RESULTS: Pain scores and adverse events were similar between the 2 groups. Although morphine consumption was less in the ketamine group during the immediate postoperative period, total morphine consumption over the course of the study was not significantly different between the 2 groups. Fewer patients in the ketamine group required supplementary oral analgesia in the postoperative surgical unit. CONCLUSIONS: The addition of ketamine 0.25 mg/kg at induction of anesthesia did not decrease postoperative morphine consumption in children undergoing tonsillectomy.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".