Kulak burun boğaz cerrahisi geçiren pediatrik hastalarda intraoperatif uygulanan sıvı volümünün postoperatif kusmaya etkisi
Bibliographic record
Abstract
Aim: Intravenous fluid therapy is recommended in international guidelines to prevent the postoperative nause and vomiting in children. But the proper amount of fluid therapy is not clear yet. The aim of this observational study is to evaluate the effect of intraoperative intravenous fluid administration on postoperative vomiting in children after adenoidectomy, tonsillectomy and adenotonsillectomy . Material and Methods: 160 children, aged between 2-10 years, undergoing elective adenoidectomy, tonsillectomy and adenotonsillectomy under general anaesthesia were randomized to administration of intraoperative infusions of low-volume (group 1=10 ml/kg/h) or high volume (group 2=20/ml/kg/h) 0.9 % NaCl solution. A standardized anaesthesia protocol was performed. The vomiting and pain scores of all patients were evaluated. Results: The frequency of vomiting in patients who received limited fluid in group 1 was significantly higher than those in group 2 at first and 15 th minute in post-anesthesia care unit (PACU). The Children’s Hospital East Ontario Pain Scale (CHEOPS) scores at 1 st and 15 th minutes of PACU were significantly higher in group 2 than in group 1 (p = 0.021, p = 0.026) However, no significant difference was found between the two groups regarding CHEOPS scores at the further time-points . Conclusion: Our results suggest that intraoperative administration of 0.9% NaCl solution at a rate of 20 ml/kg/ h can be useful in reducing mild vomiting complaint in the postoperative first and 15 th minutes in children undergoing adenoidectomy, tonsillectomy, and adenotonsillectomy.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".