| Autor: |
Yingdi Yuan, Qingyi Zhu, Xiaodie Yao, Zhonghua Shi, Juan Wen |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
BMC Pregnancy and Childbirth, Vol 23, Iss 1, Pp 1-10 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
1471-2393 |
| DOI: |
10.1186/s12884-023-05440-9 |
| Popis: |
Abstract Introduction Gestational diabetes mellitus (GDM), a metabolism-related pregnancy complication, is significantly associated with an increased risk of macrosomia. We hypothesized that maternal circulating metabolic biomarkers differed between women with GDM and macrosomia (GDM-M) and women with GDM and normal neonatal weight (GDM-N), and had good prediction performance for GDM-M. Methods Plasma samples from 44 GDM-M and 44 GDM-N were analyzed using Olink Proseek multiplex metabolism assay targeting 92 biomarkers. Combined different clinical characteristics and Olink markers, LASSO regression was used to optimize variable selection, and Logistic regression was applied to build a predictive model. Nomogram was developed based on the selected variables visually. Receiver operating characteristic (ROC) curve, calibration plot, and clinical impact curve were used to validate the model. Results We found 4 metabolism-related biomarkers differing between groups [CLUL1 (Clusterin-like protein 1), VCAN (Versican core protein), FCRL1 (Fc receptor-like protein 1), RNASE3 (Eosinophil cationic protein), FDR |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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