Prenatal antibiotic exposure and risk of attention-deficit/hyperactivity disorder: a population-based cohort study
Bibliographic record
Abstract
BACKGROUND: Abnormal microbiota composition induced by prenatal exposure to antibiotics has been proposed as a potential contributor to the development of attention-deficit/hyperactivity disorder (ADHD). We examined the association between prenatal antibiotic exposure and risk of ADHD. METHODS: We conducted a population-based retrospective cohort study of children born in Manitoba, Canada, between 1998 and 2017 and their mothers. We defined exposure as the mother having filled 1 or more antibiotic prescriptions during pregnancy. The outcome was diagnosis of ADHD in the offspring, as identified in administrative databases. We estimated hazard ratios (HRs) using Cox proportional hazards regression in the overall cohort, in a separate cohort matched on high-dimensional propensity scores and in a sibling cohort. RESULTS: In the overall cohort, consisting of 187 605 children, prenatal antibiotic dispensation was associated with increased risk of ADHD (HR 1.22, 95% confidence interval [CI] 1.18-1.26). Similar results were observed in the matched cohort of 129 674 children (HR 1.20, 95% CI 1.15-1.24) but not in the sibling cohort (HR 1.06, 95% CI 0.99-1.13). Two negative-control analyses indicated a positive association with ADHD despite the lack of a reasonable biological mechanism, which suggested that the observed association between prenatal antibiotic dispensation and risk of ADHD was likely due to confounding. INTERPRETATION: In our study, prenatal antibiotic exposure was not associated with increased risk of ADHD in children. Although the risk was higher in the overall and matched cohorts, it was likely overestimated because of unmeasured confounding. Future studies are warranted to examine other factors affecting microbiota composition in association with risk of ADHD.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".