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Record W4404209101 · doi:10.1136/bmjopen-2024-086703

Combination of body mass index and body fat percentage in middle and late pregnancy to predict pregnancy outcomes in patients with gestational diabetes in Wenzhou, China: a single-centre retrospective cohort study

2024· article· en· W4404209101 on OpenAlexaff
B. Chen, L.-M. Chen, Tao You, Zhi Zheng, Yilin Chen, Shuoru Zhu

Bibliographic record

VenueBMJ Open · 2024
Typearticle
Languageen
FieldMedicine
TopicGestational Diabetes Research and Management
Canadian institutionsYork University
Fundersnot available
KeywordsMedicineGestational diabetesBody mass indexPregnancyRetrospective cohort studyObstetricsCohort studyReproductive medicineGestationDiabetes mellitusGynecologySurgeryInternal medicineEndocrinology

Abstract

fetched live from OpenAlex

OBJECTIVES: The present study aimed to evaluate whether body mass index (BMI) and body fat percentage (BFP) could be used to predict pregnancy outcomes in patients with gestational diabetes mellitus (GDM). DESIGN: Retrospective cohort study. SETTING: Wenzhou Medical University Affiliated Second Hospital (Zhejiang Province, China). Clinical data were collected from electronic medical records. PARTICIPANTS: Data from 683 patients with GDM admitted to the Wenzhou Medical University Affiliated Second Hospital between January 2019 and December 2021 were retrospectively analysed. OUTCOME MEASURES: Pregnancy outcomes. RESULTS: The results showed that pregnant women with BFP ≥33% were more prone to abnormal amniotic fluid volume, abnormal blood pressure and anaemia (p<0.05). Additionally, these patients were more likely to experience postpartum haemorrhage and macrosomia, as well as risk factors associated with caesarean section at labour (p<0.05). BMI exhibited a strong predictive value for abnormal blood pressure (OR 1.170; 95% CI 1.090 to 1.275), anaemia (OR 1.073; 95% CI 1.016 to 1.134), caesarean section (OR 1.150; 95% CI 1.096 to 1.208) and macrosomia (OR 1.169; 95% CI 1.063 to 1.285). Additionally, classified BFP had a predictive value for abnormal amniotic fluid volume (OR 3.196; 95% CI 1.294 to 7.894), abnormal blood pressure (OR 2.321; 95% CI 1.186 to 4.545), anaemia (OR 1.817; 95% CI 1.216 to 2.714), and caesarean section (OR 1.734; 95% CI 1.270 to 2.367). CONCLUSIONS: The results suggest that patients with GDM with BFP ≥33% were more likely to experience unfavourable pregnancy outcomes, undergo caesarean section and develop macrosomia. The combination of BMI with classified BFP could better predict abnormal blood pressure and caesarean section in patients with GDM during the middle and late stages of 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 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)0.001
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 score0.012
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.000
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 head0.019
GPT teacher head0.309
Teacher spread0.290 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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