Association Between Meconium Acetaminophen and Childhood Neurocognitive Development in GESTE, a Canadian Cohort Study
Bibliographic record
Abstract
Acetaminophen is the only over-the-counter pain reliever that is not contraindicated during pregnancy, but recent studies have questioned whether acetaminophen is safe for the fetus, particularly the developing brain. This prospective birth cohort study probed the previously observed association between in utero exposure to acetaminophen and neurodevelopment by using concentrations of acetaminophen measured in meconium, which more objectively captures exposure of the fetus than maternal report. Exposure, measured by liquid chromatography coupled with tandem mass spectrometry, was categorized into nondetection, low detection, and high detection levels. At age 6-8 years, children completed a set of subtests from the Wechsler Intelligence Scale for Children, 4th edition. Additionally, this study examined potential effect modification by child sex on the association between acetaminophen exposure and neurodevelopment. In fully adjusted models, in utero exposure to acetaminophen was not statistically significantly associated with decreased scores on any of the examined subtests in all children combined (n = 118). The effect of in utero acetaminophen exposure on the Coding subtest was marginally significantly different among boys and girls, with girls performing significantly better on the task with higher levels of acetaminophen compared with girls with undetectable levels of exposure (βgirls, low = 2.83 [0.97, 4.70], βgirls, high = 1.95 [-0.03, 3.93], βboys, low = .02 [-1.78, 1.81], βboys, high = -.39 [-2.09, 1.31], pinteraction = .06). Effect modification by child sex was not observed on other subtests. These results do not support prior reports of adverse neurodevelopmental effects of in utero exposure to acetaminophen.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".