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Record W2183904800 · doi:10.3109/00365521.2015.1115893

Pregnancy and childbirth in women with autoimmune hepatitis is safe, even in compensated cirrhosis

2015· article· en· W2183904800 on OpenAlexfundno aff
Åsa Danielsson Borssén, Sven Wallerstedt, Nils Nyhlin, Annika Bergquist, Stefan Lindgren, Sven Almér, Mårten Werner

Bibliographic record

VenueScandinavian Journal of Gastroenterology · 2015
Typearticle
Languageen
FieldMedicine
TopicLiver Diseases and Immunity
Canadian institutionsnot available
FundersUmeå UniversitetAlberta Innovates - Health Solutions
KeywordsMedicineAutoimmune hepatitisCirrhosisPregnancyChildbirthHepatitisObstetricsImmunologyInternal medicineBiology

Abstract

fetched live from OpenAlex

INTRODUCTION: Autoimmune hepatitis (AIH) is a liver disease that primarily affects women. Many become ill during childbearing age, and medication can be lifelong. Few studies exist on pregnancy outcome in women with AIH. Objectives The aim was to assess the outcome of women with AIH and their children during pregnancy and postpartum. MATERIALS AND METHODS: Sixty-four women from a well-characterised cohort with AIH filled out a questionnaire with information about their disease, miscarriage/abortion, pregnancies and potential birth defects in 2012. In 2004, 106 women answered the same questionnaire and their results were analysed along with the new questionnaires. RESULTS: One hundred and thirty-eight women have completed the questionnaire and 100 children have been born by 58 women. Fifty-seven women (41%) had cirrhosis. In 84% of the pregnancies, the AIH was stable or milder, 32% had an increase in activity postpartum. The proportion of preterm births (before week 38) was 22%, caesarean sections 17%, malformations 3%, and two children died. Twenty-three women with cirrhosis had children after diagnosis of cirrhosis but without more complications than for non-cirrhotic mothers. However, they did have a higher prevalence of caesarean sections. CONCLUSION: Pregnancy and childbirth in AIH appear to be safe for both child and mother, even in women with compensated liver cirrhosis.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.461

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.012
GPT teacher head0.236
Teacher spread0.224 · 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 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

Citations36
Published2015
Admission routes1
Has abstractyes

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