A descriptive analysis of pediatric post-tonsillectomy pain and recovery outcomes over a 10-day recovery period from 2 randomized, controlled trials
Bibliographic record
Abstract
Pediatric tonsillectomy involves an often painful and lengthy recovery period, yet the extended recovery process is largely unknown. This article describes postoperative recovery outcomes for 121 children aged 4 to 15 (mean 6.6 years, SD = 2.3) years enrolled in 1 of 2 clinical trials of analgesia safety and efficacy after tonsillectomy. Postoperative analgesia included scheduled opioid analgesic plus acetaminophen/ibuprofen medication use (first 5 days) and "as-needed" use (last 5 days). Clinical recovery as measured daily by the Parents' Postoperative Pain Measure (PPPM; an observational/behavioral pain measure), children's self-reported pain scores, side-effect assessments, need for unanticipated medical care, and satisfaction with recovery over 10 days was assessed. Higher Parents' Postoperative Pain Measure scores were correlated with poorer sleep, receipt of breakthrough analgesics, distressing side effects, higher self-reported pain scores, and need for unanticipated medical care. Higher self-reported pain scores were associated with more distressing adverse events, including nausea, vomiting, insomnia, lower parent satisfaction, and unplanned medical visits and hospitalizations. Pain and symptoms improved over time, although 24% of the children were still experiencing clinically significant pain on day 10. Scheduled, multimodal analgesia and discharge education that sets realistic expectations is important. This study adds to the emerging body of literature that some children experience significant postoperative pain for an extended period after 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 | 0.033 | 0.086 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.008 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".