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Fluconazole use during the first trimester of pregnancy was not associated with most major birth defects

2014· letter· en· W2079267049 on OpenAlexaffabout
Laura A. Magee

Bibliographic record

VenueAnnals of Internal Medicine · 2014
Typeletter
Languageen
FieldHealth Professions
TopicHealthcare cost, quality, practices
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineFluconazolePregnancyItraconazoleFirst trimesterPediatricsObstetricsGestationAntifungalDermatologyGenetics

Abstract

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ACP Journal Club21 January 2014Fluconazole use during the first trimester of pregnancy was not associated with most major birth defectsLaura A. Magee, MD, FRCPC, MSc, FACPLaura A. Magee, MD, FRCPC, MSc, FACPUniversity of British Columbia, Vancouver, British Columbia, Canada (L.A.M.)Search for more papers by this authorAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/0003-4819-160-2-201401210-02012 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail Source CitationMølgaard-Nielsen D, Pasternak B, Hviid A. Use of oral fluconazole during pregnancy and the risk of birth defects. N Engl J Med. 2013;369:830-9. https://pubmed.ncbi.nlm.nih.gov/23984730Clinical Impact RatingsGIM/FP/GP: Infectious Disease: References1 Lopez-Rangel E, Van Allen MI. Prenatal exposure to fluconazole: an identifiable dysmorphic phenotype. Birth Defects Res A Clin Mol Teratol. 2005;73:919-23. [PMID: 16265639] Google Scholar2 Tiboni GM, Marotta F, Del Corso A, Giampietro F. Defining critical periods for itraconazole-induced cleft palate, limb defects and axial skeletal malformations in the mouse. Toxicol Lett. 2006;167:8-18. [PMID: 16987620] Google Scholar3 Marotta F, Tiboni GM. Molecular aspects of azoles-induced teratogenesis. Expert Opin Drug Metab Toxicol. 2010;6:461-82. [PMID: 20102286] Google Scholar Author, Article, and Disclosure InformationAffiliations: University of British Columbia, Vancouver, British Columbia, Canada (L.A.M.)This article was published at Annals.org on 7 January 2014. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetails Metrics 21 January 2014Volume 160, Issue 2Page: JC12KeywordsAntifungalsCohort studiesCongenital disordersDrugsHeartInfantsPregnancyResearch fundingSafetyVentricular septal defects ePublished: 21 January 2014 Issue Published: 21 January 2014 Copyright & PermissionsCopyright © 2014 by American College of Physicians. All Rights Reserved.PDF downloadLoading ...

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: Observational
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0170.002

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 head0.443
GPT teacher head0.488
Teacher spread0.045 · 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
GenreCommentary

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".

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Citations0
Published2014
Admission routes2
Has abstractyes

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