Analysis of risk factors and construction of a predictive model for macrosomia in deliveries with gestational diabetes

Article type: Research Article

Authors: Dou, Fengjiao^{a; *} | Tian, Qingxiu^b | Zhang, Ran^c

Affiliations: [a] Shaoxing University Yuanpei College, Shaoxing, China | [b] Department of Endocrinology, The First Affiliated Hospital of Shandong First Medical University, Shandong Provincial Qianfoshan Hospital, Jinan, China | [c] Department of Critical Care Medicine, Beijing Tiantan Hospital, Capital Medical University, Beijing, China

Correspondence: [*] Corresponding author: Fengjiao Dou, Shaoxing University Yuanpei College, No. 2799 Qunxian Middle Road, Yuecheng District, Shaoxing, Zhejiang 312000, China. Tel.: +86 15088635660; E-mail: [email protected].

Abstract: BACKGROUND: Gestational diabetes, a frequent pregnancy complication marked by elevated maternal blood glucose, can cause serious adverse effects for both mother and fetus, including increased amniotic fluid and risks of fetal asphyxia, hypoxia, and premature birth. OBJECTIVE:To construct a predictive model to analyze the risk factors for macrosomia in deliveries with gestational diabetes. METHODS:From January 2021 to February 2023, 362 pregnant women with gestational diabetes were selected for the study. They were followed up until delivery. Based on newborn birth weight, the participants were divided into the macrosomia group (birth weight ⩾ 4000 g) and the non-macrosomia group (birth weight < 4000 g). The data of the two groups of pregnant women were compared. ROC curves were plotted to analyze the predictive value of multiple factors for the delivery of macrosomic infants among pregnant women with gestational diabetes. A logistic regression model was constructed to identify the risk factors for delivering macrosomic infants and the model was tested. RESULTS:A total of 362 pregnant women with gestational diabetes were included, of which 58 (16.02%) had babies with macrosomia. The macrosomia group exhibited higher metrics in several areas compared to those without: pre-pregnancy BMI, fasting glucose, 1 h and 2 h OGTT sugar levels, weight gain during pregnancy, and levels of triglycerides, LDL-C, and HDL-C, all with significant differences (P< 0.05). ROC analysis revealed predictive value for macrosomia with AUCs of 0.761 (pre-pregnancy BMI), 0.710 (fasting glucose), 0.671 (1 h OGTT), 0.634 (2 h OGTT), 0.850 (weight gain), 0.837 (triglycerides), 0.742 (LDL-C), and 0.776 (HDL-C), indicating statistical significance (P< 0.05). Logistic regression identified high pre-pregnancy BMI, fasting glucose, weight gain, triglycerides, and LDL-C levels as independent risk factors for macrosomia, with odds ratios of 2.448, 2.730, 1.884, 16.919, and 5.667, respectively, and all were statistically significant (P< 0.05). The model’s AUC of 0.980 (P< 0.05) attests to its reliability and stability. CONCLUSION:The delivery of macrosomic infants in gestational diabetes may be related to factors such as body mass index before pregnancy, blood-glucose levels, gain weight during pregnancy, and lipid levels. Clinical interventions targeting these factors should be implemented to reduce the incidence of macrosomia.

Keywords: Gestational diabetes, delivery, macrosomia, risk factors, predictive model

DOI: 10.3233/THC-240679

Journal: Technology and Health Care, vol. 32, no. 5, pp. 3595-3604, 2024