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Record W2019238637 · doi:10.2174/157340410790979789

Antipsychotic Medication (Safety/Risk) during Pregnancy and Breastfeeding

2010· article· en· W2019238637 on OpenAlexaff
Adrienne Einarson

Bibliographic record

VenueCurrent Women s Health Reviews · 2010
Typearticle
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsUniversity of TorontoHospital for Sick ChildrenSickKids Foundation
Fundersnot available
KeywordsQuetiapineMedicineRisperidoneOlanzapineZiprasidoneAntipsychoticPregnancyClozapineAripiprazoleHyperprolactinaemiaFluphenazinePromethazineAdverse effectBreastfeedingPsychiatrySchizophrenia (object-oriented programming)HaloperidolPediatricsPharmacologyInternal medicine

Abstract

fetched live from OpenAlex

It is important to evaluate the safety of antipsychotic drugs in pregnancy and the postpartum, especially as most women with schizophrenia need to continue their treatment during pregnancy and breastfeeding. With the increasing use of second generation antipsychotics, which cause less hyperprolactinemia-induced infertility than was the case with older drugs, the number of women with schizophrenia becoming pregnant will likely increase. In this review, I discuss the current available, evidenced-based information regarding the safety of antipsychotic drugs used in pregnancy. These include the first generation (chlorpromazine, fluphenazine, haloperidol, loxapine, perphenazine, prochlorperazine, promethazine, thioridazine, trifluoperazine) and second generation (aripiprazole, clozapine, olanzapine, quetiapine, risperidone, ziprasidone). To date, there has been no definitive association between use of these agents and an increased risk of birth defects or other adverse outcomes. Women who are pregnant or breastfeeding and require treatment should always discuss the risks/benefits of pharmacotherapy with their own physician. The evidenced-based information contained in this paper will be of use in their joint decision. Keywords: Pregnancy, breastfeeding, antipsychotic drugs

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.870
Threshold uncertainty score0.753

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.035
GPT teacher head0.364
Teacher spread0.328 · 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 designOther design
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

Citations8
Published2010
Admission routes1
Has abstractyes

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