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Record W2160636027 · doi:10.3109/01443615.2011.641621

Pregnancy outcome after exposure to the probiotic Lactobacillus in early pregnancy

2012· article· en· W2160636027 on OpenAlexaff
J. E. Lee, Jung Yeol Han, June Seek Choi, Hyun Kyong Ahn, S. W. Lee, Melissa Kim, Hyun Mee Ryu, J. H. Yang, Alejandro A. Nava‐Ocampo, Gideon Koren

Bibliographic record

VenueJournal of Obstetrics and Gynaecology · 2012
Typearticle
Languageen
FieldNursing
TopicInfant Nutrition and Health
Canadian institutionsSickKids FoundationUniversity of TorontoHospital for Sick Children
Fundersnot available
KeywordsMedicinePregnancyObstetricsGestationLactobacillusAdverse effectEarly Pregnancy LossGestational ageBirth weightLive birthGynecologyInternal medicine

Abstract

fetched live from OpenAlex

The present study prospectively assessed pregnancy outcome of women taking probiotics during the periconceptional period. A group of 104 women who had taken Lactobacillus in early pregnancy and 200 age- and parity-matched control pregnant women exposed to non-teratogenic agents were also recruited into the study and followed-up prospectively. Median gestational age of women exposed to Lactobacillus was 5.2 (range: 1.9-17.6) weeks. Exposure was at a mean dose of 510 mg/day for a median of 4.0 days (range: 1-90 days). In the exposed group, pregnancy outcomes included 96 live births and eight spontaneous abortions versus 187 live births and 21 spontaneous abortions in the non-exposed group. There was no statistical difference in adverse pregnancy outcomes, including the number of spontaneous abortions, pre-term births as well as a low birth weight between the two groups (p > 0.05). In the exposed group, there were two (2.1%) major congenital malformations in comparison with five (2.7%) in the comparison group (p = 0.7). In conclusion, no association was identified between ingestion of Lactobacillus in early pregnancy for a limited period of time and adverse pregnancy outcomes. However, rare pregnancy outcomes may have been missed due to the limited sample size included in the study.

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)0.001
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 score0.051
Threshold uncertainty score0.337

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.027
GPT teacher head0.285
Teacher spread0.258 · 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

Citations14
Published2012
Admission routes1
Has abstractyes

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