Clinical Research Center, Shanghai General Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
Department of Obstetrics and Gynecology, Shanghai General Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
Front Endocrinol (Lausanne). 2021 Dec 9;12:779210. doi: 10.3389/fendo.2021.779210. eCollection 2021.
Gestational diabetes mellitus (GDM) is a serious threat to maternal and child health. However, there isn't a standard predictive model for the disorder in early pregnancy. This study is to investigate the association of blood indexes with GDM and establishes a practical predictive model in early pregnancy for GDM.
This is a prospective cohort study enrolling 413 pregnant women in the department of Obstetrics and Gynecology in Shanghai General Hospital from July 2020 to April 2021.A total of 116pregnantwomen were diagnosed with GDM during the follow-up. Blood samples were collected at early trimester (gestational weeks 12-16) and second trimester(gestational weeks 24-26 weeks). A predictive nomogram was established based on results of the multivariate logistic model and 5-fold cross validation. We evaluate the nomogram by the area under the receiver operating characteristic curve (AUC), calibration curves and decision curve analysis (DCAs).
Significant differences were observed between the GDM and normal controls among age, pre-pregnancy BMI, whether the pregnant women with complications, the percentage of B lymphocytes, fasting plasma glucose (FPG), HbA1c, triglyceride and the level of progesterone in early trimester. Risk factors used in nomogram included age, pre-pregnancy BMI, FPG, HbA1c, the level of IgA, the level of triglyceride, the percentage of B lymphocytes, the level of progesterone and TPOAb in early pregnancy. The AUC value was 0.772, 95%CI (0.602,0.942). The calibration curves for the probability of GDM demonstrated acceptable agreement between the predicted outcomes by the nomogram and the observed values. DCA curves showed good positive net benefits in the predictive model.
A novel predictive nomogram was developed for GDM in our study, which could do help to patient counseling and management during early pregnancy in clinical practice.
妊娠期糖尿病（GDM）严重威胁母婴健康。然而，目前尚缺乏早孕期 GDM 的标准预测模型。本研究旨在探讨早孕期血指标与 GDM 的相关性，并建立一种实用的早孕期 GDM 预测模型。
这是一项前瞻性队列研究，纳入 2020 年 7 月至 2021 年 4 月在上海交通大学附属第一人民医院妇产科就诊的 413 名孕妇。随访期间共有 116 例孕妇被诊断为 GDM。在早孕期（妊娠 12-16 周）和中孕期（妊娠 24-26 周）采集血样。基于多变量逻辑回归模型和 5 折交叉验证结果建立预测列线图。通过受试者工作特征曲线（ROC）下面积（AUC）、校准曲线和决策曲线分析（DCA）评估列线图的性能。
GDM 组与正常对照组在年龄、孕前 BMI、是否合并妊娠并发症、B 淋巴细胞百分比、空腹血糖（FPG）、糖化血红蛋白（HbA1c）、三酰甘油、孕激素水平等方面存在显著差异。列线图的预测因素包括年龄、孕前 BMI、FPG、HbA1c、IgA 水平、三酰甘油水平、B 淋巴细胞百分比、孕激素水平和 TPOAb。AUC 值为 0.772，95%CI（0.602，0.942）。列线图预测 GDM 的概率与实际观察值的校准曲线显示出较好的一致性。DCA 曲线显示该预测模型具有良好的净获益。
本研究建立了一种新的 GDM 预测列线图，有助于临床实践中对早孕期患者进行咨询和管理。
