MétaCan
Menu
Back to cohort
Record W2133363063

Perinatal exposure to maternal lamotrigine: clinical considerations for the mother and child.

2010· article· en· W2133363063 on OpenAlexaff
Parvaz Madadi, Shinya Ito

Bibliographic record

VenuePubMed · 2010
Typearticle
Languageen
FieldMedicine
TopicPharmacological Effects and Toxicity Studies
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsLamotrigineBreastfeedingMedicineBreast milkBreast feedingPregnancyIn uteroDrugPediatricsLactationObstetricsToxicityFetusIntensive care medicineEpilepsyPharmacologyPsychiatryInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

QUESTION: The question of neonatal safety during breastfeeding when mothers are taking lamotrigine (LTG) has become more prevalent in my practice. There are some theoretical concerns about breastfeeding while taking LTG, which have been compounded by a published case report of toxicity in the breastfed neonate of a mother taking LTG. How should I advise my patients who wish to breastfeed while taking LTG? ANSWER: Most neonates born to mothers taking LTG have already been exposed to the drug for 9 months in utero, given the chronic indications for which the drug is intended. Lamotrigine exposure via breast milk is considerably less than placental transfer, with serum LTG concentrations in neonates higher at birth than during lactation. While a single case of toxicity has been reported in a neonate exposed to LTG via breast milk, in most circumstances, breastfeeding can be initiated and maintained given the tremendous benefits of mothers' milk. On the other hand, toxicity during breastfeeding might occur more commonly in the mother, if sufficient and gradual dose readjustments are not undertaken in the weeks following delivery.

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)0.001
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0060.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.048
GPT teacher head0.338
Teacher spread0.291 · 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 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

Citations7
Published2010
Admission routes1
Has abstractyes

Explore more

Same venuePubMedSame topicPharmacological Effects and Toxicity StudiesFrench-language works237,207