Establishment of gestational diabetes risk prediction model and clinical verification

被引:4
|
作者
Niu, Z. -R [1 ]
Bai, L. -W [2 ]
Lu, Q. [1 ]
机构
[1] First Hosp Qinhuangdao, Dept Endocrinol, Qinhuangdao 066000, Hebei, Peoples R China
[2] Qinhuangdao Hosp Maternal & Child Hlth, Dept Obstet, Qinhuangdao 066000, Hebei, Peoples R China
关键词
Gestational diabetes mellitus; Predictive model; Body mass index; Uric acid; 1ST TRIMESTER PREDICTION; SERUM URIC-ACID; ASSOCIATION; PREGNANCY; MELLITUS;
D O I
10.1007/s40618-023-02249-3
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Objective The present study aimed to evaluate the risk factors for gestational diabetes mellitus (GDM) and build and validate an early risk prediction model of GDM by comparing the differences in the indicators of the first trimester of pregnancy between pregnant women with GDM and non-gestational diabetes mellitus (NGDM). Thus, this study provided a theoretical basis for early intervention of GDM.Methods A total of 6000 pregnant women who underwent a routine prenatal examination in Qinhuangdao Maternal and Child Health Hospital (Qinhuangdao City, Hebei Province, China) from January 2016-2022 were retrospectively selected and randomly divided into a modeling cohort (4200 cases) and validation cohort (1800 cases) at a ratio of 3:7. According to the results of oral glucose tolerance test (OGTT), they were divided into NGDM and GDM groups. The modeling cohort consisted of 2975 NGDM and 1225 GDM cases, while the validation cohort consisted of 1281 NGDM and 519 GDM cases. The differences in general conditions and laboratory indicators between different groups were compared, and logistic regression analysis was further used to establish a risk prediction model for GDM in the first trimester. The receiver operating characteristic curve (ROC) and Hosmer-Lemeshow (HL) tests were used to evaluate the prediction of the model efficacy.Results Age, pre-pregnancy body mass index (BMI), glycosylated hemoglobin (HbA1c), blood uric acid (UA), triglyceride (TG), and high-density lipoprotein cholesterol (HDL-C) in the first trimester were independent risk factors for GDM (P < 0.05). The model equation was Y = 1/{1 + exp[- (- 18.373 + age x 0.065 + BMI x 0.030 + first-trimester HbA1c x 2.519 + UA x 0.014 + TG x 0.224-HDL-C x 0.635)]}. The area under the ROC curve (AUC) of the model cohort was 0.803 (0.788-0.817), the sensitivity was 72.0%, and the specificity was 73.5%. The AUC of the validation cohort was 0.782 (0.759-0.806), the sensitivity was 68.6%, and the specificity was 73.8%. The P values of the HL test in both the training and validation sets were > 0.05, indicating a satisfactory model fit.Conclusion Age, pre-pregnancy BMI, HbA1C in early pregnancy, blood UA, TG, and HDL-C are independent risk factors for GDM. The risk prediction model established by combining age, pre-pregnancy BMI, and laboratory indicators in the first trimester can provide a theoretical basis for early screening, monitoring, and intervention of GDM high-risk pregnant women.
引用
收藏
页码:1281 / 1287
页数:7
相关论文
共 50 条
  • [1] Establishment of gestational diabetes risk prediction model and clinical verification
    Z.-R. Niu
    L.-W. Bai
    Q. Lu
    Journal of Endocrinological Investigation, 2024, 47 : 1281 - 1287
  • [2] Establishment and evaluation of a risk prediction model for gestational diabetes mellitus
    Lin, Qing
    Fang, Zhuan-Ji
    WORLD JOURNAL OF DIABETES, 2023, 14 (10) : 1541 - 1550
  • [3] Establishment and validation of a prediction model for gestational diabetes
    Wang, Xia
    He, Caidie
    Wu, Nian
    Tian, Yingkuan
    An, Songlin
    Chen, Wei
    Liu, Xiang
    Zhang, Haonan
    Xiong, Shimin
    Liu, Yijun
    Li, Quan
    Zhou, Yuanzhong
    Shen, Xubo
    DIABETES OBESITY & METABOLISM, 2024, 26 (02): : 663 - 672
  • [4] A clinical diabetes risk prediction model for prediabetic women with prior gestational diabetes
    Man, Bernice
    Schwartz, Alan
    Pugach, Oksana
    Xia, Yinglin
    Gerber, Ben
    PLOS ONE, 2021, 16 (06):
  • [5] Establishment and Verification of a Risk Prediction Model for Chronic Rhinosinusitis
    Cheng, Peng
    Zhou, Yinxin
    Li, Mingcai
    Wang, Yaowen
    Li, Yan
    ENT-EAR NOSE & THROAT JOURNAL, 2024,
  • [6] Establishment of a risk prediction model for large-for-gestational-age infants among Chinese women with gestational diabetes mellitus
    Guicun Yang
    Jing Wen
    Lina Si
    Nianrong Wang
    Yan Zhao
    Scientific Reports, 15 (1)
  • [7] Prediction of early gestational diabetes mellitus: A clinical model based on maternal demographic and clinical risk factors
    Feghali, Maisa
    Atlass, Jacqueline
    Catov, Janet
    Caritis, Steve
    Scifres, Christina
    AMERICAN JOURNAL OF OBSTETRICS AND GYNECOLOGY, 2018, 218 (01) : S580 - S580
  • [8] Establishment and verification of a nomogram prediction model of hypertension risk in Xinjiang Kazakhs
    Xu, Yuezhen
    Liu, Jinbao
    Wang, Jiawei
    Fan, Qiongling
    Luo, Yuanyuan
    Zhan, Huaifeng
    Tao, Ning
    You, Shuping
    MEDICINE, 2021, 100 (42)
  • [9] Establishment of a nomogram model to predict the risk of macrosomia in patients with gestational diabetes mellitus
    Sun, Pengyu
    Liu, Kang
    Cui, Xianmei
    Zhang, Liang
    Cao, Tao
    JOURNAL OF MATERNAL-FETAL & NEONATAL MEDICINE, 2023, 36 (02):
  • [10] Estimating the risk of gestational diabetes mellitus: a clinical prediction model based on patient characteristics and medical history
    van Leeuwen, M.
    Opmeer, B. C.
    Zweers, E. J. K.
    van Ballegooie, E.
    ter Brugge, H. G.
    de Valk, H. W.
    Visser, G. H. A.
    Mol, B. W. J.
    BJOG-AN INTERNATIONAL JOURNAL OF OBSTETRICS AND GYNAECOLOGY, 2010, 117 (01) : 69 - 75