Antibiotics for nonspecific upper respiratory tract infections and exacerbation risk in children with asthma
Bibliographic record
Abstract
<bold>Background:</bold> While the gut microbiome plays an important role in asthma, it is unclear if interventions that cause gut dysbiosis, like antibiotics, will increase exacerbation risk in children with asthma. <bold>Objectives:</bold> To assess if treating a nonspecific upper respiratory tract infection (NURTI) with broad-spectrum or narrow-spectrum antibiotics vs. no antibiotics increases 6-month exacerbation risk in children with asthma. <bold>Methods:</bold> We emulated a target trial to inform the decision to treat children with asthma visiting an outpatient physician for a NURTI using Quebec administrative data. Children <18 years old with asthma were eligible for the trial if they did not recently use antibiotics or had an exacerbation at the physician visit. Children were followed from 14 days after the visit for 6 months. Treatment strategies evaluated were: 1) broad-spectrum antibiotics, 2) narrow-spectrum antibiotics, or 3) no treatment, defined with drug claims filled within 3 days of the visit. Exacerbation was defined as any oral corticosteroid, emergency department visit, or hospitalization for asthma. We used inverse probability weighting to emulate randomization and estimated marginal HRs of exacerbation for antibiotic treatment strategies vs. no treatment with marginal structural Cox models. <bold>Results:</bold> Of the 24437 included person-trials, 3688 (15.1%) and 2613 (10.7%) were treated with broad-spectrum and narrow-spectrum antibiotics, respectively. Broad-spectrum antibiotics (HR 1.15 95%CI 1.00,1.34), but not narrow spectrum (HR 1.08; 0.93,1.31), vs. no antibiotics increased exacerbation risk. <bold>Conclusion:</bold> Broad-spectrum antibiotics increased short-term exacerbation risk in children with asthma.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".