Antibiotic use in children and youths with asthma: a population-based case-control study
Bibliographic record
Abstract
RATIONALE: Antibiotics are among the most common medications dispensed to children and youths. The objective of this study was to characterise and compare antibiotic use patterns between children and youths with and without asthma. METHODS: We conducted a population-based nested case-control study using health administrative data from Ontario, Canada, in 2018. All Ontario residents aged 5-24 years with asthma were included as cases. Cases were matched to controls with a 1:1 ratio based on age (within 0.5 year), sex and location of residence. Multivariable conditional logistic regression was used to obtain an odds ratio and 95% confidence interval for having filled at least one antibiotic prescription, adjusted for socioeconomic status, rurality, and presence of common infections, allergic conditions and complex chronic conditions. RESULTS: The study population included 1 174 424 Ontario children and youths aged 5-24 years. 31% of individuals with asthma and 23% of individuals without asthma filled at least one antibiotic prescription. The odds of having filled at least one antibiotic prescription were 34% higher among individuals with asthma compared to those without asthma (OR 1.34, 95% CI 1.32-1.35). In the stratified analysis, the odds ratios were highest in the youngest group of children studied, aged 5-9 years (OR 1.45, 95% CI 1.41-1.48), and in females (OR 1.36, 95% CI 1.34-1.38). CONCLUSION: Asthma is significantly associated with increased antibiotic use in children and youths. This association is the strongest in younger children and in females.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.000 | 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 teacher head, 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".