Cargando…
Risk prediction model of gestational diabetes mellitus based on nomogram in a Chinese population cohort study
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...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7718223/ https://www.ncbi.nlm.nih.gov/pubmed/33277541 http://dx.doi.org/10.1038/s41598-020-78164-x |
_version_ | 1783619469132693504 |
---|---|
author | Zhang, Xiaomei Zhao, Xin Huo, Lili Yuan, Ning Sun, Jianbin Du, Jing Nan, Min Ji, Linong |
author_facet | Zhang, Xiaomei Zhao, Xin Huo, Lili Yuan, Ning Sun, Jianbin Du, Jing Nan, Min Ji, Linong |
author_sort | Zhang, Xiaomei |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7718223 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-77182232020-12-08 Risk prediction model of gestational diabetes mellitus based on nomogram in a Chinese population cohort study Zhang, Xiaomei Zhao, Xin Huo, Lili Yuan, Ning Sun, Jianbin Du, Jing Nan, Min Ji, Linong Sci Rep Article 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. Nature Publishing Group UK 2020-12-04 /pmc/articles/PMC7718223/ /pubmed/33277541 http://dx.doi.org/10.1038/s41598-020-78164-x Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Zhang, Xiaomei Zhao, Xin Huo, Lili Yuan, Ning Sun, Jianbin Du, Jing Nan, Min Ji, Linong Risk prediction model of gestational diabetes mellitus based on nomogram in a Chinese population cohort study |
title | Risk prediction model of gestational diabetes mellitus based on nomogram in a Chinese population cohort study |
title_full | Risk prediction model of gestational diabetes mellitus based on nomogram in a Chinese population cohort study |
title_fullStr | Risk prediction model of gestational diabetes mellitus based on nomogram in a Chinese population cohort study |
title_full_unstemmed | Risk prediction model of gestational diabetes mellitus based on nomogram in a Chinese population cohort study |
title_short | Risk prediction model of gestational diabetes mellitus based on nomogram in a Chinese population cohort study |
title_sort | risk prediction model of gestational diabetes mellitus based on nomogram in a chinese population cohort study |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7718223/ https://www.ncbi.nlm.nih.gov/pubmed/33277541 http://dx.doi.org/10.1038/s41598-020-78164-x |
work_keys_str_mv | AT zhangxiaomei riskpredictionmodelofgestationaldiabetesmellitusbasedonnomograminachinesepopulationcohortstudy AT zhaoxin riskpredictionmodelofgestationaldiabetesmellitusbasedonnomograminachinesepopulationcohortstudy AT huolili riskpredictionmodelofgestationaldiabetesmellitusbasedonnomograminachinesepopulationcohortstudy AT yuanning riskpredictionmodelofgestationaldiabetesmellitusbasedonnomograminachinesepopulationcohortstudy AT sunjianbin riskpredictionmodelofgestationaldiabetesmellitusbasedonnomograminachinesepopulationcohortstudy AT dujing riskpredictionmodelofgestationaldiabetesmellitusbasedonnomograminachinesepopulationcohortstudy AT nanmin riskpredictionmodelofgestationaldiabetesmellitusbasedonnomograminachinesepopulationcohortstudy AT jilinong riskpredictionmodelofgestationaldiabetesmellitusbasedonnomograminachinesepopulationcohortstudy |