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Record W4327902022 · doi:10.1111/ppe.12963

In utero acetaminophen exposure and child neurodevelopmental outcomes: Systematic review and meta‐analysis

2023· review· en· W4327902022 on OpenAlexafffund
Christina Ricci, Carmela Melina Albanese, Lesley A. Pablo, Jiaying Li, Maryam Fatima, Kathryn Barrett, Brooke Levis, Hilary K. Brown

Bibliographic record

VenuePaediatric and Perinatal Epidemiology · 2023
Typereview
Languageen
FieldMedicine
TopicPregnancy and Medication Impact
Canadian institutionsWomen's College HospitalPublic Health OntarioThe Scarborough HospitalJewish General HospitalUniversity of TorontoPublic Health Agency of Canada
FundersCanada Research Chairs
KeywordsMedicineAcetaminophenCINAHLIn uteroMEDLINEMeta-analysisConfoundingCohort studyObservational studyProspective cohort studyPediatricsPregnancyInternal medicinePsychiatryAnesthesiaPsychological interventionFetus

Abstract

fetched live from OpenAlex

Abstract Background Acetaminophen is a frequently used analgesic for pain and fever. There have been reports of adverse neurodevelopmental outcomes associated with in utero acetaminophen exposure. However, it is unclear whether this association is related directly to acetaminophen use, or the reasons for use. Objectives To summarise the literature on the association between in utero acetaminophen exposure and child neurodevelopmental outcomes, and assess the extent to which the association is due to confounding by indication. Data Sources OVID for Medline, Embase, and PsycINFO, and EBSCO for CINAHL, from inception to August 18, 2022. Study Selection and Data Extraction We searched for peer‐reviewed, English‐language studies on in utero acetaminophen exposure and child neurodevelopmental outcomes. Data were extracted using a standardised form created a priori, and quality was assessed using the Systematic Assessment of Quality in Observational Research. Synthesis We generated pooled risk ratios (RR) for outcomes examined by ≥3 studies using random‐effects models; outcomes that could not be meta‐analysed were narratively summarised following Synthesis Without Meta‐Analysis guidelines. Results Twenty‐two studies including 23 cohorts were eligible (n = 367,775 total participants; median: 51.7% with acetaminophen exposure). Studies were primarily prospective cohort studies from Europe and the US, with attention deficit/hyperactivity disorder (ADHD) being the most common outcome. Quality assessments resulted in 13.6% of studies being classified as high, 59.1% as medium, 22.7% as low, and 4.5% as very low quality. In utero acetaminophen exposure was associated with an elevated risk of ADHD (unadjusted pooled RR 1.32, 95% confidence interval [CI] 1.20, 1.44; I2 = 47%, n = 7 studies), with little difference after adjusting for confounders, including indications for acetaminophen use (adjusted pooled RR 1.34, 95% CI 1.15, 1.55; I2 = 50%, n = 4 studies). Conclusions Confounding by indication did not explain the association between in utero acetaminophen exposure and child ADHD. Further, high‐quality research is needed on this and other neurodevelopmental outcomes.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.021
metaresearch head score (Gemma)0.063
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.021
Threshold uncertainty score0.108

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.063
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0190.032
Bibliometrics0.0080.010
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0030.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0060.000

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.

Opus teacher head0.114
GPT teacher head0.398
Teacher spread0.284 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations21
Published2023
Admission routes2
Has abstractyes

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