The effect of ketamine on posttonsillectomy pain in children: a clinical trial.
Bibliographic record
Abstract
INTRODUCTION: Tonsillectomy is one of the most common surgical operations and has such complications as pain, hemorrhage and laryngospasm. Pain management is of vital importance in order to reduce the suffering and restlessness in children having undergone tonsillectomy. Different studies differ in their findings as to the use of ketamine for postoperative analgesia. The aim of this study was to investigate the effect of peritonsillar injection of ketamine preoperatively on postoperative pain relief. MATERIALS AND METHODS: This was a randomized controlled trial (RCT) on sixty 3-12-year-old children. Children were randomly assigned to the intervention and control groups. Peritonsillar injection consisted of 1 mg/kg ketamine in the intervention group and of normal saline in the control group. An injection of 1 cc was administered on each side five minutes prior to tonsillectomy. Pain assessment was performed using the self-report Oucher Scale and CHEOPS (Children's Hospital of Eastern Ontario Pain Scale) and sedative state assessment was performed using the Wilson Sedation Scale. Pain, medication and complications were studied for 24 hours. Data analysis was performed using chi-squared test and t-test. RESULTS: The ketamine group had a lower pain score compared with the control group (1.40±1.003 compared with 1.53±1.074). The average pain was less in the control group two hours after the surgery. The difference was statistically significant. There was no difference between the two groups in terms of nausea and vomiting incidence. CONCLUSION: The peritonsillar injection of ketamine five minutes prior to the surgery reduces the post-tonsillectomy pain without causing any complications.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".