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Record W2020723228 · doi:10.1016/s0020-7292(01)00496-9

Gestational diabetes mellitus: prevalence, risk factors, maternal and infant outcomes

2001· article· en· W2020723228 on OpenAlexaffabout
Xu Xiong, L. Duncan Saunders, F.L. Wang, Nestor Demianczuk

Bibliographic record

VenueInternational Journal of Gynecology & Obstetrics · 2001
Typearticle
Languageen
FieldMedicine
TopicGestational Diabetes Research and Management
Canadian institutionsUniversité LavalAlberta HealthUniversity of Alberta
Fundersnot available
KeywordsMedicineGestational diabetesObstetricsOdds ratioRetrospective cohort studyPregnancyConfoundingGestational ageCohort studyRisk factorLogistic regressionGestationInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: To study prevalence, risk factors, and maternal and infant outcomes of women with gestational diabetes mellitus (GDM). METHODS: A retrospective cohort study was performed based on 111563 pregnancies delivered between 1991 through 1997 in 39 hospitals in northern and central Alberta, Canada. Multivariate logistic regression was used to estimate the odds ratios with 95% confidence intervals, and to control for confounding variables. RESULTS: The prevalence of GDM was 2.5%. Risk factors for GDM included age >35 years, obesity, history of prior neonatal death, and prior cesarean section. Teenage mothers and women who drank alcohol were less likely to have GDM. Mothers with GDM were at increased risk of presenting with pre-eclampsia, premature rupture of membranes, cesarean section, and preterm delivery. Infants born to mothers with GDM were at higher risk of being macrosomic or large-for-gestational-age. CONCLUSIONS: Specific conditions predispose to GDM which itself is associated with a significantly increased risk of maternal and fetal morbidity.

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)0.000
metaresearch head score (Gemma)0.001
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.148
Threshold uncertainty score0.293

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.296
Teacher spread0.281 · 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
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

Citations412
Published2001
Admission routes2
Has abstractyes

Explore more

Same venueInternational Journal of Gynecology & ObstetricsSame topicGestational Diabetes Research and ManagementFrench-language works237,207