The Role of Adjuvant Adenoidectomy and Tonsillectomy in the Outcome of the Insertion of Tympanostomy Tubes
Bibliographic record
Abstract
BACKGROUND: Otitis media is the most common medical problem in young children. The usual surgical treatment is myringotomy with insertion of tympanostomy tubes. There is debate about the usefulness of concomitant adenoidectomy or adenotonsillectomy. We examined the effects of these adjuvant procedures on the rates of reinsertion of tympanostomy tubes and rehospitalization for conditions related to otitis media. METHODS: Using hospital discharge records for the period 1995 through 1997, we examined the results of surgery for all 37,316 children (defined as persons 19 years of age or younger) in Ontario, Canada, who received tympanostomy tubes as their first surgical treatment for otitis media. We determined the time to the first readmission for conditions related to otitis media and the time to the first reinsertion of tympanostomy tubes. RESULTS: As compared with treatment involving the insertion of tympanostomy tubes alone, adjuvant adenoidectomy was associated with a reduction in the likelihood of reinsertion of tympanostomy tubes (relative risk, 0.5; 95 percent confidence interval, 0.5 to 0.6; P<0.001) and the likelihood of readmission for conditions related to otitis media (relative risk, 0.5; 95 percent confidence interval, 0.5 to 0.6; P<0.001). The risk of these outcomes was further reduced if an adjuvant adenotonsillectomy was performed. The effect was age-related. Children as young as one year appeared to benefit from adjuvant adenotonsillectomy; the benefit of an adjuvant adenoidectomy was apparent in two-year-olds and was greatest for children three years of age or older. CONCLUSIONS: Performing an adenoidectomy at the time of the initial insertion of tympanostomy tubes substantially reduces the likelihood of additional hospitalizations and operations related to otitis media among children two years of age or older.
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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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".