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Record W2028129034 · doi:10.11622/smedj.2013148

A prospective study of risk factors for first trimester miscarriage in Asian women with threatened miscarriage

2013· article· en· W2028129034 on OpenAlexaff
LJ Kouk, GH Neo, Rahul Malhotra, John Carson Allen, S.M. Beh, TC Tan, Truls Østbye

Bibliographic record

VenueSingapore Medical Journal · 2013
Typearticle
Languageen
FieldPsychology
TopicGrief, Bereavement, and Mental Health
Canadian institutionsInstitute of Health Services and Policy Research
Fundersnot available
KeywordsMiscarriageMedicineObstetricsHazard ratioProspective cohort studyPregnancyProportional hazards modelGynecologyGestationAbortionInternal medicineConfidence interval

Abstract

fetched live from OpenAlex

INTRODUCTION: The present study aimed to assess the demographic, socioeconomic, medical and lifestyle factors associated with the progression of a threatened miscarriage to a complete miscarriage in the first trimester. METHODS: A prospective cohort study was conducted on 157 women who presented with vaginal bleeding in the fifth to tenth week of gestation. Cox regression analysis was used to determine the risk factors for progression to a complete miscarriage within 16 weeks of gestation. RESULTS: Of the 139 women included for data analysis, 36 (25.9%) had a miscarriage, mostly within two weeks of presentation. The results of our study showed that women aged ≥ 34 years were more likely to miscarry (hazard ratio [HR] = 1.95). Compared to women whose partner was 20-30 years of age, women whose partner was ≥ 41 years of age also had a higher likelihood of experiencing a miscarriage (HR = 8.33). However, the presence of nausea (HR = 0.33) and a high stress score (i.e. ≥ 17) on the Perceived Stress Scale (HR = 0.49) were associated with a reduced likelihood of miscarriage. CONCLUSION: Older pregnant women experiencing a threatened miscarriage should be counselled about their higher risk of miscarriage, especially if they have an older partner.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.021
GPT teacher head0.318
Teacher spread0.297 · 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.

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

Citations28
Published2013
Admission routes1
Has abstractyes

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