Infant antibiotic use and wheeze and asthma risk: a systematic review and
Bibliographic record
Abstract
Our aim was to systematically review and meta-analyse longitudinal studies on antibiotic use and subsequent development of wheeze and/or asthma with regards to study quality, outcome measurement, reverse causation (RC; wheezing/asthma symptoms have caused prescription of antibiotics) and confounding by indication (CbI; respiratory tract infections leading to antibiotic use may be the underlying cause triggering asthma symptom development). English-language papers and studies published before November 1, 2010 with longitudinal observational design were included. Study quality was assessed using the Newcastle-Ottawa scale. We identified 21 longitudinal studies. The effect of antibiotic use on wheeze/asthma risk varied between studies. 18 studies were eligible for meta-analysis showing pooled OR 1.27 (95% CI 1.12- 1.43) for wheeze/asthma. When we eliminated studies with possible RC and CbI, the pooled risk estimate in the nine remaining studies was attenuated to OR 1.12 (95% CI 0.98-1.26). Definition of wheeze/asthma and age at follow-up differed between studies. Three studies focused on wheeze/ asthma beyond 5-6 yrs of age with the presence of active symptoms and/or medication (pooled OR 1.08, 95% CI 0.93-1.23; dominated by one study). RC and CbI lead to overestimation of the association between antibiotic use and subsequent development of wheeze/asthma. Association was weak when fully adjusted for these types of bias. Heterogeneity of disease definition between studies could affect the results.
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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 | 0.016 | 0.040 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.019 |
| Bibliometrics | 0.012 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 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".