Acute otitis media in Quebec's children : antibiotic prescribing patterns and outcomes
Bibliographic record
Abstract
Acute otitis media ( AOM) is one of the most common indications for antibiotic use in children. We used the Régie de l'assurance maladie du Québec databases to better understand the prescribing patterns of physicians and to assess the effectiveness of different antibiotics in the treatment of AOM. We selected a cohort of 60,513 children aged < 6 years with a first episode of AOM between June 1999 and June 2002. Failure was defined as either a new dispensation of antibiotic or a hospitalization or outpatient visit for complications related to AOM in the following 30 days. The antibiotic most widely used was amoxicillin (42.8%). Failure occurred in 12,693 (21%) children. Overall, azithromycin was the only antibiotic that was less associated with failure when compared to amoxicillin (odds ratio 0.88; 95% confidence interval 0.82, 0.94). In the first 3 days of treatment, a 50% increased risk of failure was seen when macrolides were initially given. However, azithromycin was associated with a 20% decrease in the risk of failure occurring > 14 days after the beginning of treatment. Other risk factors associated with treatment failure were age < 24 months, antibiotics or hospitalization in the preceding month, and otitis-prone conditions. Considering the results of the effectiveness study, the importance of macrolides resistance among pneumococci, and because there is no single factor or combination of factors that predict with certainty which child will develop early or late failure, amoxicillin should remain the first-line drug of choice.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".