Risk factors and prediction model for low-birth-weight infants born to women with gestational diabetes mellitus

• DOI: 10.3389/fpubh.2024.1432033
• Publication Date: 2024-10-10T13:33:04Z
• Authors: Yu-qing Pan; Xin-xin Huang; Xiu-min Jiang
• Keywords: Adult; China; Infant, Newborn; Infant, Low Birth Weight; gestational diabetes mellitus; nomogram; prediction model; Diabetes, Gestational; Nomograms; low birth weight infant; risk factor; Pregnancy; Risk Factors; Humans; Birth Weight; Female; Public Health; Public aspects of medicine; RA1-1270; Retrospective Studies

Aim To explore the risk factors for low-birth-weight infants born to pregnant women with GDM develop a prediction model and construct nomogram of low birth weight GDM. Methods The clinical data singleton diagnosed gestational diabetes mellitus in Southeast China 2019 were retrospectively reviewed. Gestational conditions neonatal assessed. Results A total 386 diabetic mothers enrolled, including 193 group normal group. statistically significant age over 36 years (OR = 1.916, 95% CI 1.048–3.505), junior high school education 4.454, 1.882–10.543), history fetal distress 0.120, 0.016–0.925), hypertension 3.681, 1.357–9.986), preeclampsia 24.652, 5.956–102.036), threatened preterm 18.393, 8.457–39.999), triglycerides 0.642, 0.485–0.850), inadequate gain 1.997, 1.162–3.432). area under receiver operating characteristic curve (AUC) was 0.834 (95% CI: 0.794–0.874, p < 0.001), sensitivity specificity 82.38 87.56%, respectively. goodness-of-fit test likelihood ratio 2 2.089 ( 0.978). comprehensive showed that discrimination mean absolute error 0.015, calibration curves acceptable agreement between predictions column line plots observations. DCA good positive net yields model. Discussion This study established score It helps pregnancy clinics identify newborns promptly, addition glycemic control management GDM, should improve appropriate treatment plan higher risk, provide personalized precise infant outcomes.