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Record W4398219324 · doi:10.1111/ppe.13086

Risks of congenital malformations and neonatal intensive care unit admissions with gabapentin use in pregnancy: A cohort study and scoping review with meta‐analysis

2024· review· en· W4398219324 on OpenAlexafffundabout
Brianne Desrochers, Alekhya Lavu, Eunice Valencia, Christine M. Vaccaro, Payam Peymani, Sherif Eltonsy

Bibliographic record

VenuePaediatric and Perinatal Epidemiology · 2024
Typereview
Languageen
FieldMedicine
TopicPregnancy and Medication Impact
Canadian institutionsChildren's Hospital Research Institute of ManitobaUniversity of Manitoba
FundersWinnipeg FoundationHealth Sciences Centre Foundation
KeywordsMedicineNeonatal intensive care unitRelative riskPregnancyCohort studyGabapentinCohortPopulationPediatricsConfidence intervalObstetricsMeta-analysisObservational studyCongenital malformationsInternal medicineEnvironmental healthPathology

Abstract

fetched live from OpenAlex

Abstract Background The increasing and prevalent use of gabapentin among pregnant people highlights the necessity to assess its neonatal safety. Objectives This study aimed to investigate the foetal safety of gabapentin during pregnancy using a cohort study and scoping review with a meta‐analysis of published evidence. Methods We conducted a population‐based cohort study using the Manitoba health databases between 1995 and 2019. We examined the association between gabapentin use during pregnancy and the prevalence of major congenital malformations, cardiac and orofacial malformations, and neonatal intensive care unit (NICU) admissions using multivariate regression models. We searched the literature in MEDLINE and EMBASE databases from inception to October 2022 to identify relevant observational studies and conducted a meta‐analysis using random‐effects models, including our cohort study results. Results Of the 289,227 included pregnancies, 870 pregnant people were exposed to gabapentin. Gabapentin exposure during the First trimester was not associated with an increased risk of any malformations (adjusted relative risk [aRR]) 1.16 (95% confidence interval [CI] 0.92, 1.46), cardiac malformations (aRR 1.29, 95% CI 0.72, 2.29), orofacial malformations (aRR 1.37, 95% CI 0.50, 3.75), and major congenital malformations (aRR 1.00, 95% CI 0.73, 1.36). whereas exposure during any trimester was associated with an increased NICU admission risk (aRR, 1.99, 95% CI 1.70, 2.32). The meta‐analysis of unadjusted results revealed an increased risk of major congenital malformations (RR 1.44, 95% CI 1.28, 1.61, I 2 = 0%), cardiac malformations (RR 1.66, 95% CI 1.11, 2.47, I 2 = 68%), and NICU admissions (RR 3.15, 95% CI 2.90, 3.41, I 2 = 10%), and increased trend of orofacial malformations (RR 1.98, 95% CI 0.79, 5.00, I 2 = 0%). Conclusions Gabapentin use was associated with an increased risk of NICU admissions in the cohort study and pooled meta‐analysis. Clinicians should prescribe gabapentin with caution during pregnancy and further studies are warranted.

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)0.018
metaresearch head score (Gemma)0.054
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: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.018
Threshold uncertainty score0.094

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.054
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0120.046
Bibliometrics0.0100.010
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.247
GPT teacher head0.460
Teacher spread0.212 · 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

Citations12
Published2024
Admission routes3
Has abstractyes

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