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Risk prediction model of gestational diabetes mellitus based on nomogram in a Chinese population cohort study by Zhang, Xiaomei; Zhao, Xin; Huo, Lili; Yuan, Ning; Sun, Jianbin; Du, Jing; Nan, Min; Ji, Linong is a Biochemistry, Genetics and Molecular Biology article available to read on EtoBox.
What is Risk prediction model of gestational diabetes mellitus based on nomogram in a Chinese population cohort study about?
## Abstract To build a risk prediction model of gestational diabetes mellitus using nomogram to provide a simple-to-use clinical basis for the early prediction of gestational diabetes mellitus (GDM). This study is a prospective cohort study including 1385 pregnant women. (1) It is showed that the risk of GDM in women aged ≥ 35 years was 5.5 times higher than that in women aged < 25 years (95% CI: 1.27–23.73, p < 0.05). In the first trimester, the risk of GDM in women with abnormal triglyceride who were in their first trimester was 2.1 times higher than that of lipid normal women (95% CI: 1.12–3.91, p < 0.05). The area under the ROC curve of the nomogram of was 0.728 (95% CI: 0.683–0.772), the sensitivity and specificity of the model were 0.716 and 0.652, respectively. This study provides a simple and economic nomogram for the early prediction of GDM risk in the first trimester, and it has certain accuracy.
Who reads Risk prediction model of gestational diabetes mellitus based on nomogram in a Chinese population cohort study?
It is typically read by researchers, students, and practitioners in Biochemistry, Genetics and Molecular Biology.
- Author
- Zhang, Xiaomei; Zhao, Xin; Huo, Lili; Yuan, Ning; Sun, Jianbin; Du, Jing; Nan, Min; Ji, Linong
- Publisher
- Springer Science and Business Media LLC; London: Nature Publishing Group; [London]: Springer Nature; Nature Publishing Group; Society for Mining, Metallurgy and Exploration Inc.; Research Square; Springer Nature; Island Press (ISSN 2045-2322)
- Published
- 2020
- Language
- EN
- Field
- Biochemistry, Genetics and Molecular Biology (Life Sciences)