ArticleBMJ open diabetes research & care2020
Development and validation of an early pregnancy risk score for the prediction of gestational diabetes mellitus in Chinese pregnant women.
Article in BMJ open diabetes research & care, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 3 of them syntheses that pooled it.
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Who cites it
20 citing papers in PubMed, 3 syntheses or guidelines pooled it, 43 citations in OpenAlex.
- Liver Enzyme Biomarkers Before or in Early Pregnancy as Predictors for Gestational Diabetes Mellitus: A Systematic Review and Meta-Analysis.Journal of the ASEAN Federation of Endocrine Societies · 2026Pooled it
- Maternal metabolic factors and the association with gestational diabetes: A systematic review and meta-analysis.Diabetes/metabolism research and reviews · 2022Pooled it
- Machine Learning Prediction Models for Gestational Diabetes Mellitus: Meta-analysis.Journal of medical Internet research · 2022Pooled it
- Development and multicenter validation of a novel model for selective screening of gestational diabetes mellitus: the Vietnam gestational diabetes mellitus study.BMC pregnancy and childbirth · 2025Article
- Development and validation of a prediction model for gestational diabetes mellitus risk among women from 8 to 14 weeks of gestation in Western China.BMC pregnancy and childbirth · 2025Article
- Nonlinear association between alanine aminotransferase to high-density lipoprotein cholesterol ratio and risk of gestational diabetes mellitus.Scientific reports · 2024Article
- Identifying Predictor Variables for a Composite Risk Prediction Tool for Gestational Diabetes and Hypertensive Disorders of Pregnancy: A Modified Delphi Study.Healthcare (Basel, Switzerland) · 2024Article
- Development and validation of a Non-INvaSive Pregnancy RIsk ScoRE (INSPIRE) for the screening of high-risk pregnant women for gestational diabetes mellitus in Pakistan.BMJ public health · 2024Article
- A nested case-control study on the association of gut virome in early pregnancy and gestational diabetes mellitus.Frontiers in microbiology · 2024Article
- A Simplified Screening Model to Predict the Risk of Gestational Diabetes Mellitus in Pregnant Chinese Women.Diabetes therapy : research, treatment and education of diabetes and related disorders · 2023Article
- Development and validation of a screening questionnaire for early identification of pregnant women at risk for excessive gestational weight gain.BMC pregnancy and childbirth · 2023Article
- Development and validation of a multivariable genotype-informed gestational diabetes prediction algorithm for clinical use in the Mexican population: insights into susceptibility mechanisms.BMJ open diabetes research & care · 2023Article
- Passive smoking and risk of gestational diabetes mellitus: A systematic review and meta-analysis.Tobacco induced diseases · 2023Review
- Assessing Healthy Aging Score and Its Association With All-Cause Mortality: Findings From the China Health and Retirement Longitudinal Study.Innovation in aging · 2023Article
- Optimising Cardiometabolic Risk Factors in Pregnancy: A Review of Risk Prediction Models Targeting Gestational Diabetes and Hypertensive Disorders.Journal of cardiovascular development and disease · 2022Review
- Association between body mass index in the first half of pregnancy and gestational diabetes: A systematic review.SAGE open medicine · 2022Review
- Stacking Ensemble Method for Gestational Diabetes Mellitus Prediction in Chinese Pregnant Women: A Prospective Cohort Study.Journal of healthcare engineering · 2022Article
- Development of Clinical Risk Scores for Detection of COVID-19 in Suspected Patients During a Local Outbreak in China: A Retrospective Cohort Study.International journal of public health · 2022Article
- Extracellular vesicle-associated miRNAs are an adaptive response to gestational diabetes mellitus.Journal of translational medicine · 2021Article
- FGF21 Serum Levels in the Early Second Trimester Are Positively Correlated With the Risk of Subsequent Gestational Diabetes Mellitus: A Propensity-Matched Nested Case-Control Study.Frontiers in endocrinology · 2021Article
Corrections and comments
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Authors and funding
11 authors at 5 institutions in 6 countries.
Funding
Abstract
objectiveTo develop and validate a set of risk scores for the prediction of gestational diabetes mellitus (GDM) before the 15th gestational week using an established population-based prospective cohort.
methodsFrom October 2010 to August 2012, 19 331 eligible pregnant women were registered in the three-tiered antenatal care network in Tianjin, China, to receive their antenatal care and a two-step GDM screening. The whole dataset was randomly divided into a training dataset (for development of the risk score) and a test dataset (for validation of performance of the risk score). Logistic regression was performed to obtain coefficients of selected predictors for GDM in the training dataset. Calibration was estimated using Hosmer-Lemeshow test, while discrimination was checked using area under the receiver operating characteristic curve (AUC) in the test dataset.
resultsIn the training dataset (total=12 887, GDM=979 or 7.6%), two risk scores were developed, one only including predictors collected at the first antenatal care visit for early prediction of GDM, like maternal age, body mass index, height, family history of diabetes, systolic blood pressure, and alanine aminotransferase; and the other also including predictors collected during pregnancy, that is, at the time of GDM screening, like physical activity, sitting time at home, passive smoking, and weight gain, for maximum performance. In the test dataset (total=6444, GDM=506 or 7.9%), the calibrations of both risk scores were acceptable (both p for Hosmer-Lemeshow test >0.25). The AUCs of the first and second risk scores were 0.710 (95% CI: 0.680 to 0.741) and 0.712 (95% CI: 0.682 to 0.743), respectively (p for difference: 0.9273).
conclusionBoth developed risk scores had adequate performance for the prediction of GDM in Chinese pregnant women in Tianjin, China. Further validations are needed to evaluate their performance in other populations and using different methods to identify GDM cases.
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