ArticleFrontiers in endocrinology2023
Integration of clinical demographics and routine laboratory analysis parameters for early prediction of gestational diabetes mellitus in the Chinese population.
Article in Frontiers in endocrinology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed, 9 citations in OpenAlex.
- A nomogram to predict gestational diabetes mellitus: a multicenter retrospective study.Journal of molecular cell biology · 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
- The early prediction of gestational diabetes mellitus by machine learning models.BMC pregnancy and childbirth · 2024Article
- Association and function analysis of genetic variants and the risk of gestational diabetes mellitus in a southern Chinese population.Frontiers in endocrinology · 2024Article
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8 authors at 3 institutions in 1 country.
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Abstract
Gestational diabetes mellitus (GDM) is one of the most common complications in pregnancy, impairing both maternal and fetal health in short and long term. As early interventions are considered desirable to prevent GDM, this study aims to develop a simple-to-use nomogram based on multiple common risk factors from electronic medical health records (EMHRs). A total of 924 pregnant women whose EMHRs were available at Peking University International Hospital from January 2022 to October 2022 were included. Clinical demographics and routine laboratory analysis parameters at 8-12 weeks of gestation were collected. A novel nomogram was established based on the outcomes of multivariate logistic regression. The nomogram demonstrated powerful discrimination (the area under the receiver operating characteristic curve = 0.7542), acceptable agreement (Hosmer-Lemeshow test,
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