ArticleThe Journal of clinical endocrinology and metabolism2021
Early Prediction of Gestational Diabetes Mellitus in the Chinese Population via Advanced Machine Learning.
Article in The Journal of clinical endocrinology and metabolism, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 101 papers, 3 of them syntheses that pooled it.
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Who cites it
101 citing papers in PubMed, 3 syntheses or guidelines pooled it, 192 citations in OpenAlex.
- Predictive Performance of Artificial Intelligence Algorithms for Gestational Diabetes Mellitus in Pregnant Women: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2026Pooled it
- The triglyceride glucose-body mass index and the risk of gestational diabetes mellitus: a systematic review and meta-analysis.Frontiers in nutrition · 2026Pooled it
- Machine Learning Prediction Models for Gestational Diabetes Mellitus: Meta-analysis.Journal of medical Internet research · 2022Pooled it
- Article
- Abdominal fat thickness predicts the risk of pregnancy-associated hypertension: A prospective cohort study.Asia Pacific journal of clinical nutrition · 2026Article
- Early prediction of gestational diabetes mellitus with clinical characteristics, cell-free DNA and genetic variants.Journal of translational medicine · 2026Article
- Predictive performance of artificial intelligence algorithms for gestational diabetes mellitus in pregnant women: a protocol for systematic review and meta-analysis.Systematic reviews · 2026Article
- First-Trimester Gestational Diabetes Mellitus Risk Prediction with Machine Learning Techniques: Results from the BORN2020 Cohort Study.Journal of clinical medicine · 2026Article
- Previous oral glucose tolerance test results as predictors of gestational diabetes mellitus in subsequent pregnancies: a retrospective cohort study.Nutrition & metabolism · 2026Article
- LASSO regression-derived first-trimester (9-14Archives of gynecology and obstetrics · 2026Article
- Effectiveness of a lifestyle intervention for pregnant women with abnormal glucose metabolism in early pregnancy (EAGM): protocol for a multicentre, open-labelled, two-arm, pragmatic randomised controlled trial.BMC pregnancy and childbirth · 2026Article
- Construction of an interpretable machine learning model for predicting gestational diabetes mellitus based on 45 dietary nutrients.BioData mining · 2026Article
- Comparative risk of gestational diabetes mellitus following fresh and frozen embryo transfers: a retrospective cohort study in Palestinian women undergoing in vitro fertilization.Diabetology & metabolic syndrome · 2026Article
- GraphRAG-Enabled Local Large Language Model for Gestational Diabetes Mellitus: Development of a Proof-of-Concept.JMIR diabetes · 2026Article
- Low early-pregnancy serum lipoprotein(a) as an independent associated factor for gestational diabetes mellitus: a retrospective cohort study.Frontiers in endocrinology · 2026Article
- Article
- Development and external validation of a non-invasive early gestational diabetes mellitus prediction model integrating social network variables: a machine learning-based prospective cohort study.BMC pregnancy and childbirth · 2025Article
- A Novel Single-Test Approach for GDM Diagnosis: Identification and Prediction of High-Risk Postprandial Hyperglycemia.Metabolites · 2025Article
- Associations of inflammation-related hematological profile with the early-stages of cardiovascular-kidney-metabolic syndrome and the mediating role of body composition: evidence from the China National Health Survey.Diabetology & metabolic syndrome · 2025Article
- The impact of early pregnancy uric acid on gestational diabetes risk: a prospective cohort study in Northwest China.BMC pregnancy and childbirth · 2025Article
41 more citing papers are in PubMed but not listed here.
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Authors and funding
11 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
contextAccurate methods for early gestational diabetes mellitus (GDM) (during the first trimester of pregnancy) prediction in Chinese and other populations are lacking.
objectivesThis work aimed to establish effective models to predict early GDM.
methodsPregnancy data for 73 variables during the first trimester were extracted from the electronic medical record system. Based on a machine learning (ML)-driven feature selection method, 17 variables were selected for early GDM prediction. To facilitate clinical application, 7 variables were selected from the 17-variable panel. Advanced ML approaches were then employed using the 7-variable data set and the 73-variable data set to build models predicting early GDM for different situations, respectively.
resultsA total of 16 819 and 14 992 cases were included in the training and testing sets, respectively. Using 73 variables, the deep neural network model achieved high discriminative power, with area under the curve (AUC) values of 0.80. The 7-variable logistic regression (LR) model also achieved effective discriminate power (AUC = 0.77). Low body mass index (BMI) (≤ 17) was related to an increased risk of GDM, compared to a BMI in the range of 17 to 18 (minimum risk interval) (11.8% vs 8.7%, P = .09). Total 3,3,5'-triiodothyronine (T3) and total thyroxin (T4) were superior to free T3 and free T4 in predicting GDM. Lipoprotein(a) was demonstrated a promising predictive value (AUC = 0.66).
conclusionsWe employed ML models that achieved high accuracy in predicting GDM in early pregnancy. A clinically cost-effective 7-variable LR model was simultaneously developed. The relationship of GDM with thyroxine and BMI was investigated in the Chinese population.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.