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Record W4395070850 · doi:10.1136/bmj-2023-077664

Prenatal opioid exposure and subsequent risk of neuropsychiatric disorders in children: nationwide birth cohort study in South Korea

2024· article· en· W4395070850 on OpenAlexaff
Jiseung Kang, Hyeon Jin Kim, Tae Kim, Hyeri Lee, Minji Kim, Seung Won Lee, Min Seo Kim, Ai Koyanagi, Lee Smith, Guillaume Fond, Laurent Boyer, Masoud Rahmati, Guillermo F. López Sánchez, Elena Dragioti, Samuele Cortese, Jae Il Shin, Dong Keon Yon, Marco Solmi

Bibliographic record

VenueBMJ · 2024
Typearticle
Languageen
FieldMedicine
TopicPrenatal Substance Exposure Effects
Canadian institutionsOttawa HospitalUniversity of Ottawa
FundersResearch Executive AgencyMinistry of Science and ICT, South KoreaMinistry of Food and Drug SafetyNational Research FoundationDepartment of Health and Social CareNational Research Foundation of KoreaKorea Health Industry Development InstituteNational Institute for Health and Care Research
KeywordsMedicineCohortPediatricsCohort studyPregnancySiblingPsychiatryInternal medicinePsychology

Abstract

fetched live from OpenAlex

OBJECTIVE: To investigate the potential association between prenatal opioid exposure and the risk of neuropsychiatric disorders in children. DESIGN: Nationwide birth cohort study. SETTING: From 1 January 2009 to 31 December 2020, birth cohort data of pregnant women in South Korea linked to their liveborn infants from the National Health Insurance Service of South Korea were collected. PARTICIPANTS: All 3 251 594 infants (paired mothers, n=2 369 322; age 32.1 years (standard deviation 4.2)) in South Korea from the start of 2010 to the end of 2017, with follow-up from the date of birth until the date of death or 31 December 2020, were included. MAIN OUTCOME MEASURES: Diagnosis of neuropsychiatric disorders in liveborn infants with mental and behaviour disorders (International Classification of Diseases 10th edition codes F00-99). Follow-up continued until the first diagnosis of neuropsychiatric disorder, 31 December 2020 (end of the study period), or the date of death, whichever occurred first. Eight cohorts were created: three cohorts (full unmatched, propensity score matched, and child screening cohorts) were formed, all of which were paired with sibling comparison cohorts, in addition to two more propensity score groups. Multiple subgroup analyses were performed. RESULTS: Of the 3 128 571 infants included (from 2 299 664 mothers), we identified 2 912 559 (51.3% male, 48.7% female) infants with no prenatal opioid exposure and 216 012 (51.2% male, 48.8% female) infants with prenatal opioid exposure. The risk of neuropsychiatric disorders in the child with prenatal opioid exposure was 1.07 (95% confidence interval 1.05 to 1.10) for fully adjusted hazard ratio in the matched cohort, but no significant association was noted in the sibling comparison cohort (hazard ratio 1.00 (0.93 to 1.07)). Prenatal opioid exposure during the first trimester (1.11 (1.07 to 1.15)), higher opioid doses (1.15 (1.09 to 1.21)), and long term opioid use of 60 days or more (1.95 (1.24 to 3.06)) were associated with an increased risk of neuropsychiatric disorders in the child. Prenatal opioid exposure modestly increased the risk of severe neuropsychiatric disorders (1.30 (1.15 to 1.46)), mood disorders, attention deficit hyperactivity disorder, and intellectual disability in the child. CONCLUSIONS: Opioid use during pregnancy was not associated with a substantial increase in the risk of neuropsychiatric disorders in the offspring. A slightly increased risk of neuropsychiatric disorders was observed, but this should not be considered clinically meaningful given the observational nature of the study, and limited to high opioid dose, more than one opioid used, longer duration of exposure, opioid exposure during early pregnancy, and only to some neuropsychiatric disorders.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.662

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.005
GPT teacher head0.247
Teacher spread0.242 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations44
Published2024
Admission routes1
Has abstractyes

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