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Record W2140913933 · doi:10.3109/01443615.2014.941342

Assessment of fetal and neonatal outcomes in the offspring of women who had been treated with dried ginger (<i>Zingiberis rhizoma siccus</i>) for a variety of illnesses during pregnancy

2014· article· en· W2140913933 on OpenAlexaff
June Seek Choi, J. Y. Han, Hyun Kyong Ahn, Seung Won Lee, Mi Kyoung Koong, E. Yadira Velázquez-Armenta, Alejandro A. Nava‐Ocampo

Bibliographic record

VenueJournal of Obstetrics and Gynaecology · 2014
Typearticle
Languageen
FieldMedicine
TopicPregnancy and Medication Impact
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
FundersWorld Health Organization
KeywordsMedicineIncidence (geometry)OffspringTeratologyPregnancyFetusConcomitantObstetricsCohortCohort studyPopulationInternal medicine

Abstract

fetched live from OpenAlex

The present study was designed to investigate if exposure to dried ginger during pregnancy would increase the risk of adverse fetal and neonatal outcomes. Participants consisted of 159 singleton pregnant women who received dried ginger as a herbal medication. We also included a control group of 306 pregnant women who had not been exposed to any herbal medication or any known teratogen. No increased risk of major malformations was detected in exposed women (OR = 4.9; 95% CI 0.9-25.5; p = 0.051). The incidence of stillbirths in the exposed group was marginally higher than in the controls (OR = 7.8; 95% CI 0.9-70.3; p = 0.05). The risk was more evident when the exposed group was compared with the general population in the Republic of Korea (OR = 7.9; 95% CI 2.9-21.4; p < 0.0001). Other fetal and neonatal study outcomes investigated in the exposed group were similar (p > 0.05) to the controls. In conclusion, dried ginger does not appear to be a major teratogen. However, due to the limitations of the study, e.g. the large variability in the dose of dried ginger in the exposed group, as well as the concomitant exposure to other herbal medications, the increased incidence of stillbirths requires confirmation in larger cohort studies.

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)0.002
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 score0.043
Threshold uncertainty score0.276

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
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 head0.010
GPT teacher head0.265
Teacher spread0.255 · 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

Citations17
Published2014
Admission routes1
Has abstractyes

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