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Introduction: Gestational diabetes mellitus (GDM) significantly affects pregnancy outcomes. Therefore, it is crucial to develop prediction models since they can guide timely interventions to reduce the incidence of GDM and its associated adverse effects.
Methods: A total of 554 pregnant women were selected and their sociodemographic characteristics, clinical data and dietary data were collected. Dietary data was investigated by a validated semi-quantitative food frequency questionnaire (FFQ). We applied random forest mean decrease impurity for feature selection and the models are built using Logistic Regression, XGBoost, and LightGBM algorithms. The prediction performance of different models was compared by Accuracy, Sensitivity, Specificity, Area Under Curve (AUC) and Hosmer-Lemeshow test.
Results: Blood glucose, age, pre-pregnancy body mass index (BMI), triglycerides and high-density lipoprotein cholesterol (HDL) were the top five features according to the feature selection. Among the three algorithms, XGBoost performed best with an AUC of 0.788, LightGBM came second (AUC = 0.749), and Logistic Regression performed the worst (AUC = 0.712). In addition, XGBoost and LightGBM both achieved a fairly good performance when dietary information was included, surpassing their performance on the non-dietary dataset (0.788 vs. 0.718 in XGBoost; 0.749 vs. 0.726 in LightGBM).
Conclusion: XGBoost and LightGBM algorithms outperform Logistic Regression in predicting GDM among the Chinese pregnant women. In addition, dietary data may have a positive effect on improving model performance, which deserves more in-depth investigation with larger sample size.
Chronic Disease Epidemiology Laboratory Pennington Biomedical Research Center, Baton Rouge, Louisiana, USA
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Introduction The worldwide rise in over-nutrition, sedentary life and obesity has resulted in a steep increase in the number of women who develop gestational diabetes mellitus (GDM) during pregnancy ( 1 ). Nearly 7% of pregnancies in the
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Center for Biochemistry, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
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Center for Biochemistry, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
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Center for Biochemistry, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
Center for Molecular Medicine Cologne (CMMC), University of Cologne, Cologne, Germany
Cologne Center for Musculoskeletal Biomechanics (CCMB), Cologne, Germany
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–30; overweight (OW)) and obese (BMI >30; obese (OB)) pregnant women. The classification of gestational diabetes mellitus (GDM) was based on the oral glucose tolerance test 50 and 75 or the clinical maternity log. The total patient collective is 247 patients
O&G ACP, Duke-NUS Graduate Medical School, Singapore, Singapore
Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
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Department of O&G, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
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Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
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O&G ACP, Duke-NUS Graduate Medical School, Singapore, Singapore
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Introduction Gestational diabetes mellitus (GDM) and hypertensive disorders of pregnancy (HDP) are two of the most commonly seen pregnancy complications that adversely affect both short-term and long-term maternal and fetal outcomes ( 1 , 2
PEDEGO Research Unit, MRC Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
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PEDEGO Research Unit, MRC Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
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Folkhälsan Research Centre, Helsinki, Finland
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Division of Family Medicine, Department of Neurobiology, Care Sciences and Society, Karolinska Institute, Stockholm, Sweden
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Department of Obstetrics and Gynaecology, Tampere University Hospital, Tampere, Finland
Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland
Institute for Molecular Medicine Finland, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
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PEDEGO Research Unit, MRC Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
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PEDEGO Research Unit, MRC Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
Children’s Hospital, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
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Introduction Gestational diabetes mellitus (GDM) and polycystic ovary syndrome (PCOS) are the most common endocrine disorders in women of reproductive age. The prevalence of GDM varies from 9% to 25% and the prevalence of PCOS varies from 5
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of a series of pregnancy complications and neonatal outcomes, including gestational diabetes mellitus, hypertensive disorders of pregnancy, preterm delivery, placenta previa, placenta abruption and neonatal weight-related outcomes. Subjects and
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Introduction Gestational diabetes mellitus (GDM) is a condition of glucose intolerance usually occurring during the late stage of pregnancy due to decreased maternal insulin sensitivity and increased glucose production, and often recovers
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Introduction Pancreas agenesis (PA) is a very rare condition that causes permanent neonatal diabetes mellitus (PNDM) and pancreatic exocrine insufficiency. It presents most commonly with neonatal hyperglycemia in small for gestational age
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expansion of pancreatic β-cell mass ( 1 , 2 ). However, when this adaptation fails to meet the increased insulin demand, the blood glucose level increases in pregnant women and this can lead to the development of gestational diabetes mellitus (GDM) ( 3
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Introduction Women with a history of gestational diabetes mellitus (GDM) are at an increased risk for the development of type 2 diabetes mellitus (T2DM) within 5 years following pregnancy (1, 2) with the reported incidence of T2DM ranging from
