Prenatal antibiotic exposure, asthma, and the atopic march: A systematic review and meta‐analysis
Bibliographic record
Abstract
Antibiotic use during pregnancy may increase the risk for asthma in children. We performed a meta-analysis assessing prenatal antibiotic exposure and the risk for childhood wheeze or asthma, as well as for diseases associated with the atopic march. A systematic literature search protocol (PROSPERO-ID: CRD42020191940) was registered and searches were completed using Medline, Proquest, Embase, and the Cochrane central register of controlled trials. Screening for inclusion criteria: published in English, German, French, Dutch, or Arabic, intervention (use of any antibiotic at any time point during pregnancy), and disease (reporting atopic disease incidence in children with a primary outcome of asthma or wheeze), and exclusion criteria: reviews, preclinical data, and descriptive studies, yielded 27 studies. Study quality was assessed using the Newcastle-Ottawa Assessment Scale. Quality of the evidence was assessed using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach. Our meta-analysis demonstrates that antibiotic use during pregnancy is associated with an increased relative risk (RR) of developing wheeze RR 1.51 (95% CI: 1.17-1.94) or asthma RR 1.28 (95% CI 1.22-1.34) during childhood. Assessment of the atopic march in association with asthma or wheeze revealed that antibiotic use during pregnancy also increases the risk for eczema/dermatitis RR 1.28 (95% CI: 1.06-1.53) and allergic rhinitis RR 1.13 (95% CI: 1.02-1.25). One study found an increase in food allergy RR 1.81 (95% CI: 1.11-2.95). Maternal antibiotic use during pregnancy is associated with an increased risk for wheeze or asthma development in children, as well as for diseases involved in the atopic march. There was high heterogeneity in the data, and the certainty of the evidence was determined to be low quality, highlighting the need for more high-quality studies on this topic. These results have importance for antibiotic stewardship throughout the prenatal period. This work was supported by the Deutsche Forschungsgemeinschaft and the Konrad Adenauer Foundation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.007 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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".