Prevention of Nausea and Vomiting after Middle Ear Surgery: Combination of Ondansetron and Dexamethasone Is the Right Choice
Bibliographic record
Abstract
OBJECTIVE: To determine the efficacy of a combination of ondansetron and dexamethasone in preventing postoperative nausea and vomiting after middle ear surgery compared with ondansetron alone. DESIGN: A prospective, randomized, double-blind study with prestudy power analysis performed to determine the sample size. SETTING: A tertiary teaching hospital. METHOD: One hundred patients undergoing tympanomastoidectomy under general anesthesia were included in the study. Patients in group O (n = 50) received ondansetron 4 mg and those in group OD (n = 50) received ondansetron 4 mg with dexamethasone 8 mg 30 minutes before the end of surgery. All patients were monitored for nausea score, episodes of vomiting, and rescue antiemetic requirement in 48 hours after surgery. The total number of complete responders was calculated. Patients' satisfaction at the end of the study period was also estimated. RESULTS: In patients receiving combination antiemetic (group OD), the nausea score was significantly less (p < .01) at 6, 12, and 24 hours after surgery. The total incidence of vomiting was reduced from 28% in group O to 6% in group OD. Rescue antiemetic requirement was significantly less (p < .01) in group OD. The number of complete responders significantly improved in the combination group (92% vs 62%). The patients were also found to be more satisfied in this group. CONCLUSION: Prophylaxis with a combination of ondansetron and dexamethasone decreased the incidence of nausea and vomiting after middle ear surgery to a minimum and improved patients' satisfaction significantly in the postoperative period.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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".