基于基线资料、维生素D和甲状腺功能状态构建妊娠期糖尿病的早期列线图预警模型与检验  

Construction and validation of an early warning model for gestational diabetes mellitus based on baseline data,vitamin D,and thyroid function status

作　　者：孙燕[1] 史少文 王佳盈 任倩 Sun Yan;Shi Shaowen;Wang Jiaying;Ren Qian(Department of Reproductive Medicine,First Hospital of Qinhuangdao;Department of Obstetrics,First Hospital of Qinhuangdao,Qinhuangdao 066000,China)

机构地区：[1]秦皇岛市第一医院生殖医学科,秦皇岛066000 [2]秦皇岛市第一医院产科,秦皇岛066000

出　　处：《中华内分泌外科杂志(中英文)》2025年第1期74-79,共6页Chinese Journal of Endocrine Surgery

基　　金：河北省秦皇岛市科技支撑项目(202101A126)。

摘　　要：目的:基于基线资料、维生素D(VitD)和甲状腺功能状态构建妊娠期糖尿病(GDM)的早期列线图预警模型。方法:选取2022年1月至2024年5月秦皇岛市第一医院产科收治的126例GDM患者(GDM组)及126例无GDM孕妇(对照组)。采用单因素、多因素LASSO Logistic回归分析GDM发病风险的影响因素,基于多因素结果构建GDM早期预警模型,并进行评价与验证。结果:两组年龄、孕前身体质量指数(BMI)、糖尿病家族史、甲状腺功能、低密度脂蛋白(LDL-C)、甘油三酯(TG)、VitD、空腹血糖(FPG)、糖化血红蛋白(HbA1c)、血尿酸比较,差异有统计学意义(P<0.05);经LASSO Logistic回归分析显示,糖尿病家族史、甲状腺功能减退、孕前BMI、TG、VitD、FPG、HbA1c、血尿酸与GDM发病风险独立相关(P<0.05);基于多因素结果构建GDM早期预警模型,该模型C-index为0.876,预测性能良好;模型评价与验证结果显示,该模型内、外部校准度较好,预测值与实际观测值一致性较高,且在外部数据集中仍具有良好的预测价值及区分度。结论:甲状腺功能减退、VitD及孕前BMI等基线资料均是GDM发生的独立影响因素,基于上述指标构建GDM早期列线图预警模型具有良好预测效能及临床适用性,可作为临床早期预测GDM的有效模型,并可指导临床防治工作。Objective:To construct an early warning model for gestational diabetes mellitus(GDM)based on baseline data,vitamin D(VitD),and thyroid function status.Methods:A prospective study was conducted to select 126 patients with GDM(GDM group)and 126 pregnant women without GDM(control group)admitted to the Obstetrics Department of Qinhuangdao First Hospital from Jan.2022 to May.2024.The single-factor and multi-factor LASSO Logistic regression analysis was used to analyze the influencing factors of the risk of GDM.Based on the results of the multi-factor analysis,an early warning model for GDM was constructed,evaluated,and validated.Results:Age,pre-pregnancy body mass index(BMI),family history of diabetes,thyroid function,low density lipoprotein(LDL-C),triglyceride(TG),VitD,fasting plasma glucose(FPG),glycated hemoglobin(HbA1c)and blood uric acid were compared,and the differences were statistically significant(P<0.05).LASSO Logistic regression analysis showed that family history of diabetes,hypothyroidism,pre-pregnancy BMI,TG,VitD,FPG,HbA1c and blood uric acid were independently correlated with the risk of GDM(P<0.05).A GDM early warning model was constructed based on the results of multiple factors,with a C-index of 0.876,indicating good predictive performance;The model evaluation and validation results show that the model has good internal and external calibration,high consistency between predicted values and actual observed values,and good predictive value and discrimination in external data sets.Conclusions:Baseline data such as hypothyroidism,VitD,and pre-pregnancy BMI are independent factors that affect the occurrence of GDM.The early warning model for GDM based on these indicators has good predictive performance and clinical applicability,and can be used as an effective model for early prediction of GDM in clinical practice,as well as guiding clinical prevention and treatment efforts.

关 键 词：甲状腺 维生素D 甲状腺功能减退 基线资料 妊娠期糖尿病 预警模型 

分 类 号：R714.256[医药卫生—妇产科学]