The association between early life antibiotic use and allergic disease in young children: recent insights and their implications
Bibliographic record
Abstract
INTRODUCTION: Greater prescribing of antibiotics to infants has coincided with an epidemic of allergic disease. Through meta-analytic synthesis, accumulating evidence from prospective or database cohorts suggests a link between infant antibiotic treatment and the development of atopy. Stronger associations seen with multiple course and broad-spectrum antibiotic treatment add to biological plausibility. A major bias, confounding by indication, has been addressed in studies on antibiotic treatment of conditions which do not precede allergic disease. Areas covered: Our review provides an up-to-date synthesis of the current literature on associations between infant antibiotic exposure and future allergic disease. We discuss methods that assist in reducing study bias and look at new insights from studies of the infant gut microbiome. Expert commentary: Large-scale profiling of the gut microbiome provides a new tool for disentangling biases found in observational studies of infant antibiotic use. To date, microbial dysbiosis of the infant gut has been reported to predict allergic disease independent of antibiotic exposure up to 3 months after birth. However, these studies have not accounted for antibiotic treatment in later infancy. Continued study of the infant gut microbiome, mycobiome, or resistome will provide a closer link to antibiotic treatment or refute it as a cause of allergic disease.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".