Estimating the risk of gestational diabetes mellitus based on the 2013 WHO criteria: a prediction model based on clinical and biochemical variables in early pregnancy

• Published in: Acta diabetologica Vol. 57; no. 6; pp. 661 - 671
• Main Authors: Benhalima, Katrien, Van Crombrugge, Paul, Moyson, Carolien, Verhaeghe, Johan, Vandeginste, Sofie, Verlaenen, Hilde, Vercammen, Chris, Maes, Toon, Dufraimont, Els, De Block, Christophe, Jacquemyn, Yves, Mekahli, Farah, De Clippel, Katrien, Van Den Bruel, Annick, Loccufier, Anne, Laenen, Annouschka, Minschart, Caro, Devlieger, Roland, Mathieu, Chantal
• Format: Journal Article
• Language: English
• Published: Milan Springer Milan 01.06.2020; Springer Nature B.V
• Subjects: Adult; Belgium - epidemiology; Biomarkers - analysis; Biomarkers - blood; Blood Glucose - analysis; Blood Glucose - metabolism; Body Mass Index; Cohort Studies; Diabetes; Diabetes mellitus; Diabetes, Gestational - blood; Diabetes, Gestational - diagnosis; Diabetes, Gestational - epidemiology; Diabetes, Gestational - etiology; Female; Gestational Age; Glucose Tolerance Test; Glycated Hemoglobin A - analysis; Glycated Hemoglobin A - metabolism; Health risk assessment; Humans; Internal Medicine; Medicine; Medicine & Public Health; Metabolic Diseases; Models, Statistical; Original Article; Prediction models; Pregnancy; Pregnancy and diabetes; Pregnancy Trimester, First - blood; Prenatal Diagnosis - methods; Prenatal Diagnosis - standards; Prognosis; Prospective Studies; Risk Factors; Triglycerides; Triglycerides - blood; World Health Organization; Young Adult; Belgium; Gestational diabetes mellitus; 2013 WHO criteria; Risk factors; Prediction
• ISSN: 0940-5429; 1432-5233
• DOI: 10.1007/s00592-019-01469-5

Aims We aimed to develop a prediction model based on clinical and biochemical variables for gestational diabetes mellitus (GDM) based on the 2013 World Health Organization (WHO) criteria. Methods A total of 1843 women from a Belgian multi-centric prospective cohort study underwent universal screening for GDM. Using multivariable logistic regression analysis, a model to predict GDM was developed based on variables from early pregnancy. The performance of the model was assessed by receiver-operating characteristic (AUC) analysis. To account for over-optimism, an eightfold cross-validation was performed. The accuracy was compared with two validated models (van Leeuwen and Teede). Results A history with a first degree relative with diabetes, a history of smoking before pregnancy, a history of GDM, Asian origin, age, height and BMI were independent predictors for GDM with an AUC of 0.72 [95% confidence interval (CI) 0.69–0.76)]; after cross-validation, the AUC was 0.68 (95% CI 0.64–0.72). Adding biochemical variables, a history of a first degree relative with diabetes, a history of GDM, non-Caucasian origin, age, height, weight, fasting plasma glucose, triglycerides and HbA 1c were independent predictors for GDM, with an AUC of the model of 0.76 (95% CI 0.72–0.79); after cross-validation, the AUC was 0.72 (95% CI 0.66–0.78), compared to an AUC of 0.67 (95% CI 0.63–0.71) using the van Leeuwen model and an AUC of 0.66 (95% CI 0.62–0.70) using the Teede model. Conclusions A model based on easy to use variables in early pregnancy has a moderate accuracy to predict GDM based on the 2013 WHO criteria.