Establishment of gestational diabetes risk prediction model and clinical verification

• DOI: 10.1007/s40618-023-02249-3
• Publication Date: 2023-12-12T09:14:42Z
• Authors: Z.-R. Niu; L.-W. Bai; Q. Lu

Abstract Objective The present study aimed to evaluate the risk factors for gestational diabetes mellitus (GDM) and build validate an early prediction model of GDM by comparing differences in indicators first trimester pregnancy between pregnant women with non-gestational (NGDM). Thus, this provided a theoretical basis intervention GDM. Methods A total 6000 who underwent routine prenatal examination Qinhuangdao Maternal Child Health Hospital (Qinhuangdao City, Hebei Province, China) from January 2016–2022 were retrospectively selected randomly divided into modeling cohort (4200 cases) validation (1800 at ratio 3:7. According results oral glucose tolerance test (OGTT), they NGDM groups. consisted 2975 1225 cases, while 1281 519 cases. general conditions laboratory different groups compared, logistic regression analysis was further used establish trimester. receiver operating characteristic curve (ROC) Hosmer–Lemeshow (HL) tests efficacy. Results Age, pre-pregnancy body mass index (BMI), glycosylated hemoglobin (HbA1c), blood uric acid (UA), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C) independent ( P < 0.05). equation Y = 1/{1 + exp[− (− 18.373 age × 0.065 BMI 0.030 first-trimester HbA1c 2.519 UA 0.014 TG 0.224-HDL-C 0.635)]}. area under ROC (AUC) 0.803 (0.788–0.817), sensitivity 72.0%, specificity 73.5%. AUC 0.782 (0.759–0.806), 68.6%, 73.8%. values HL both training sets > 0.05, indicating satisfactory fit. Conclusion BMI, HbA1C pregnancy, UA, TG, HDL-C are established combining age, can provide screening, monitoring, high-risk women.