Evaluation of Postoperative Efficacy and Safety of Celecoxib in Children Hospitalized After Adenotonsillectomy
Bibliographic record
Abstract
OBJECTIVE: The choice of optimal analgesia following an adenotonsillectomy is a clinical issue because of the risk of respiratory depression and bleeding. The objective of this study was to assess the effect of celecoxib on opioid use and pain scores in children hospitalized after adenotonsillectomy and to document its adverse effects. METHODS: This retrospective study was conducted in a tertiary care pediatric hospital. We compared a group of subjects aged 1 to 17 years who were prescribed celecoxib and opioids between January 2017 and June 2020 following an adenotonsillectomy during a 3-day or less hospitalization to a group of matched controls for sex, age, and length of stay who were prescribed opioids. RESULTS: A total of 228 patients were identified (76 in the celecoxib + opioids group, 152 in the control group). Opioid use, in oral morphine equivalent daily dose, was lower in the celecoxib + opioids group at 0 to 24 hours of hospitalization (0.15 vs 0.20 mg/kg/day, p = 0.05). Initiating celecoxib within 24 hours of surgery (n = 60) significantly reduced opioid requirement for up to 48 hours compared with controls (0-24 hours: 0.12 vs 0.20 mg/kg/day, p = 0.002; 25-48 hours: 0.02 vs 0.09 mg/kg/day, p = 0.001). A shorter length of stay was observed for patients receiving celecoxib + opioids during the first 24-hour post--operative period (27 vs 32 hours, p = 0.01). With celecoxib use, no significant change in pain scores and occurrence of adverse effects including bleeding was found. CONCLUSIONS: Using celecoxib early after an adenotonsillectomy has reduced both opioid use and duration of hospital stay without increasing adverse effects or bleeding.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".