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Record W2981745666

Pharmacotherapy in perinatal mental health

2016· article· en· W2981745666 on OpenAlexaboutno aff
Megan Galbally

Bibliographic record

VenueMurdoch Research Repository (Murdoch University) · 2016
Typearticle
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePregnancyMental healthPsychiatryMoodPharmacotherapyMood disordersAnxiety
DOInot available

Abstract

fetched live from OpenAlex

Main Program Abstract
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\nWith the recognition of the importance of antenatal mental health for maternal and fetal outcomes there has followed an emphasis on the importance of adequate treatment of mental health in pregnancy. For some women, treatment may include the maintenance or commencement of psychotropic medications. This understanding by clinicians of the importance of maternal mental health may explain the significant rise in rates of use of these agents in pregnancy including rises in antidepressant rates in pregnancy across Australia, USA, Canada and the Netherlands. As rates of use of these agents rise it makes understanding the risks and benefits of these agents for women and offspring important information for all clinicians managing women in pregnancy.
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\nThis talk will give an overview of the indications, uses, risks and benefits of the key classes of psychotropic medications used to treat mental disorders in pregnancy, including antidepressants, mood stabilisers and antipsychotic agents. A discussion of where the use of these medications fit within an overall perinatal mental health management will be outlined as well as other treatment options for mental disorders. Finally, there will be a discussion of key recommendations for antenatal care monitoring for women who are either started or continue to be treated with these agents across pregnancy.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.617
Threshold uncertainty score0.651

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.053
GPT teacher head0.372
Teacher spread0.320 · 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 designNot applicable
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

Citations0
Published2016
Admission routes1
Has abstractyes

Explore more

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