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Intrauterine insulin resistance in fetuses of overweight mothers

2012· article· en· W1739325004 on OpenAlexaff
Bin Liu, Yun Xu, Jian‐ming Liang, Courtney Voss, Xiao Huan-yu, Wei‐yang Sheng, Yanhong Sun, Zilian Wang

Bibliographic record

VenueJournal of obstetrics and gynaecology research · 2012
Typearticle
Languageen
FieldMedicine
TopicGestational Diabetes Research and Management
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicineOverweightInsulin resistanceBirth weightPregnancyFetusEndocrinologyBody mass indexObstetricsInternal medicineGestational ageGestational diabetesInsulinGestationBiology

Abstract

fetched live from OpenAlex

AIM: To investigate the relationship between maternal overweight and fetal insulin resistance. MATERIAL AND METHODS: Nineteen overweight and 30 lean pregnant women were recruited in the present study. Maternal and fetal insulin resistance were determined by measuring sex hormone binding globulin (SHBG) concentrations in maternal venous or umbilical cord serum, respectively. Maternal age, gestational age, height, pre-gravidity weight, pre-partum weight, as well as fetal gender, birth weight, birth height, and head circumference were collected as clinical data. RESULTS: Fetuses of overweight mothers had larger birth weight (3.58±0.55kg vs 3.32±0.42, adjusted P=0.006) and lower SHBG concentrations (26.64±3.65 vs 34.36±7.84, adjusted P=0.007) than those of lean mothers after values were adjusted for potential cofactors. Fetal SHBG level was negatively correlated with pre-gravidity body mass index (R=-0.392, adjusted P=0.025) and weight gain during pregnancy (R=-0.332, adjusted P=0.026) even with adjustment for potential cofactors. Among the 29 pregnant women with gestational diabetes mellitus, the overweight mothers had higher H1AC levels than their lean counterparts (6.47±0.44 vs 5.74±0.52, adjusted P=0.004). CONCLUSION: Intrauterine insulin resistance is more prominent in fetuses of overweight mothers, an effect that is decreased by weight gain control during pregnancy.

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)0.002
metaresearch head score (Gemma)0.007
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 score0.129
Threshold uncertainty score0.844

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.007
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)0.0000.000

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 head0.052
GPT teacher head0.363
Teacher spread0.310 · 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

Citations8
Published2012
Admission routes1
Has abstractyes

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