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Record W2015371581 · doi:10.1055/s-0029-1241736

The Association between Prepregnancy Maternal Body Mass Index and Preterm Delivery

2009· article· en· W2015371581 on OpenAlexaff
Yan Zhong, Alison G. Cahill, George A. Macones, Fufan Zhu, Anthony Odibo

Bibliographic record

VenueAmerican Journal of Perinatology · 2009
Typearticle
Languageen
FieldMedicine
TopicGestational Diabetes Research and Management
Canadian institutionsWomen's Health Research Institute
Fundersnot available
KeywordsMedicineUnderweightBody mass indexConfidence intervalGestationObstetricsOverweightPremature rupture of membranesGynecologyPregnancyInternal medicine

Abstract

fetched live from OpenAlex

We investigated the association between prepregnancy maternal body mass index (BMI) and preterm delivery (PTD). The study included 44,421 American women presenting for care in Saint Louis, Missouri between 1990 and 2006. Only singleton gestations were included. The authors examined the associations between categories of BMI with PTD <37 and <34 weeks, respectively. A stratified analysis by subtypes of PTD was also performed. The subtypes of PTD evaluated included spontaneous PTD without preterm premature rupture of membranes (PPROM), PPROM, and indicated PTD. Univariate and multivariable analyses were used to estimate the association between maternal BMI categories and PTD <37 weeks, PTD <34 weeks, and subtypes of PTD. Among women meeting the inclusion criteria, PTD <37 occurred in 4783 (10.8%) and PTD <34 weeks in 1132 (2.5%). Being underweight was associated with increased risks of PTD <37 weeks (adjusted odd ratio [OR] = 1.3, 95% confidence interval [CI]: 1.2, 1.5). Being obese was associated with decreased risks of spontaneous PTD without PPROM <37 weeks (adjusted OR = 0.8, 95% CI: 0.7, 0.9) and increased risk of PPROM <37 weeks (adjusted OR = 1.3, 95% CI: 1.1, 1.6) and PPROM <34 weeks (adjusted OR = 1.4, 95% CI: 1.0, 2.0). Prepregnancy obesity increases the risk of PPROM and decreases risk of spontaneous PTD without PPROM.

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 score0.300
Threshold uncertainty score0.189

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.006
GPT teacher head0.277
Teacher spread0.270 · 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

Citations105
Published2009
Admission routes1
Has abstractyes

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