Dexamethasone and Risk of Bleeding in Children Undergoing Tonsillectomy
Bibliographic record
Abstract
OBJECTIVE: To determine whether dexamethasone use in children undergoing tonsillectomy is associated with increased risk of postoperative bleeding. STUDY DESIGN: Retrospective cohort study using a multihospital administrative database. SETTING: Thirty-six US children's hospitals. SUBJECTS: Children undergoing same-day tonsillectomy between the years 2004 and 2010. METHODS: We used discrete time failure models to estimate the daily hazards of revisits for bleeding (emergency department or hospital admission) up to 30 days after surgery as a function of dexamethasone use. Revisits were standardized for patient characteristics, antibiotic use, year of surgery, and hospital. RESULTS: Of 139,715 children who underwent same-day tonsillectomy, 97,242 (69.6%) received dexamethasone and 4182 (3.0%) had a 30-day revisit for bleeding. The 30-day cumulative standardized risk of revisits for bleeding was greater with dexamethasone use (3.11% vs 2.71%; standardized difference 0.40% [95% confidence interval, 0.13%-0.67%]; P = .003), and the increased risk was observed across all age strata. Dexamethasone use was associated with a higher standardized rate of revisits for bleeding in the postdischarge time periods of days 1 through 5 but not during the peak period for secondary bleeding, days 6 and 7. CONCLUSIONS: In a real-world practice setting, dexamethasone use was associated with a small absolute increased risk of revisits for bleeding. However, the upper bound of this risk increase does not cross published thresholds for a minimal clinically important difference. Given the benefits of dexamethasone in reducing postoperative nausea and vomiting and the larger body of evidence from trials, these results support guideline recommendations for the routine use of dexamethasone.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".