Early Life Antibiotic Prescription for Upper Respiratory Tract Infection Is Associated With Higher Antibiotic Use in Childhood
Bibliographic record
Abstract
BACKGROUND: Antibiotic prescription for uncomplicated upper respiratory tract infection (URTI) in children is not recommended but remains common. The primary objective was to evaluate the relationship between antibiotic prescription for URTI prior to age 2 and antibiotic prescription for URTI after age 2. It was hypothesized that antibiotic prescription for URTI in early childhood may increase the risk of antibiotic use for subsequent URTIs. The secondary objective was to investigate whether this relationship was different for acute otitis media (AOM), for which antibiotics may be indicated. METHODS: A prospective cohort study was conducted between December 2008 and March 2016 at 9 primary care practices in Toronto, Canada. Healthy children aged 0-5 years that met TARGet Kids! cohort eligibility criteria were included if they had at least one sick visit prior to age 2 and least one sick visit after age 2. Generalized Estimating Equation (GEE) models were used to evaluate this relationship while considering within-subject correlation. RESULTS: Of 2380 participants followed for a mean duration of 4.6 years, children who received an antibiotic prescription for URTI prior to age 2 had higher odds of receiving an antibiotic prescription for URTI in later childhood (adjusted odds ratio: 1.39; 95% confidence interval: 1.19 to 1.63; P < .001). This relationship did not appear to be different for AOM compared to non-AOM URTI. CONCLUSION: Antibiotic prescription for URTI before age 2 was associated with antibiotic prescription for URTI in later childhood. Reducing early life antibiotic prescription for URTI may be associated with reduction in antibiotic prescription for subsequent URTIs.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".