Intraoperative ice pack application for uvulopalatoplasty pain reduction: A randomized controlled trial
Bibliographic record
Abstract
OBJECTIVES/HYPOTHESIS: Pain after uvulopalatoplasty continues to cause patients significant morbidity, especially from the tonsillectomy portion. The literature describes multiple techniques to reduce post-tonsillectomy pain, none being definitive. The purpose of this study was to evaluate the effect of intraoperative ice pack application on post-uvulopalatoplasty pain. STUDY DESIGN: Single-blinded, randomized controlled trial. METHODS: After inclusion and exclusion criteria were met, patients were enrolled and randomized, and subsequently underwent standard electrocautery uvulopalatoplasty. Packs were placed into the tonsillar fossae immediately following tonsil removal and into the palate after the palatoplasty. Patients then completed a questionnaire that evaluated their experience for 10 days following surgery. The primary outcome was pain rated on a visual analog scale. Return to work and return to normal diet were also assessed. T test and Mann-Whitney statistical analyses, as well as routine descriptive statistics, were conducted. RESULTS: Eighteen subjects were recruited. Patients that received intraoperative cold packs experienced a statistically significant change in VAS average pain [3.4 ± 1.1 cm (p = 0.00001)] when compared with patients receiving room temperature packs. No difference in return to work (p = 0.16) and return to normal diet (p = 0.12) was identified. CONCLUSIONS: Intraoperative ice pack administration results in significantly reduced pain following electrocautery uvulopalatoplasty.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".