Clinical predictors of multiple tympanostomy tube placements in Ontario children
Bibliographic record
Abstract
OBJECTIVES: To characterize risk factors that predict the need for multiple tympanostomy tube (TT) procedures. STUDY DESIGN: Retrospective population-based cohort study of children aged 18 years and younger in Ontario, Canada, who underwent at least one TT placement between January 1, 1994, and October 31, 2013. METHODS: The relative risk (RR) of need for multiple TT procedures was determined using log-binomial regression. RESULTS: There were 193,880 children who underwent TT insertion included in this cohort. Of these, 28.58% underwent at least two separate TT procedures. Over time, the RR of undergoing multiple TT procedures is decreasing for all children. In general, the younger the child was at the first TT procedure, the more likely the child was to undergo multiple TT procedures. Significantly higher RR for multiple TT procedures also was associated with male sex, the second-highest neighborhood income quintile, asthma or reactive airways, gastrointestinal disease, prematurity, or cleft lip and/or palate. Significantly lower RR for multiple TT procedures was associated with adenoidectomy or tonsillectomy (with or without adenoidectomy) at first TT placement or within 3 years prior. Furthermore, the benefit of adjuvant adenoidectomy or tonsillectomy was present for children aged under 4 years, in addition to those aged 4 years and older. CONCLUSION: Among Ontario children who have had TT placement, more than one in four will have multiple sets placed. These identified risk factors permit improved preoperative counseling and enable identification of children who need closer follow-up. LEVEL OF EVIDENCE: 2b. Laryngoscope, 128:991-997, 2018.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".