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This study aimed to identify risk factors for predicting gestational diabetes mellitus (GDM) in order to reduce the risk of pre-eclampsia and preterm birth. Prospective data from 489 patients between 2019-2021 were analyzed using logistic regression and random forest methods. The identified risk factors for GDM included age, body mass index, hemoglobin A1c level, fasting blood sugar level, physical activity in the first trimester, gravidity, triglycerides, and high-density lipoprotein cholesterol. Logistic regression had a sensitivity of 90% and specificity of 75%, while random forest had a sensitivity of 71% and specificity of 90%.
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