OBJECTIVE: This study aimed to assess the predictive value of risk factors (RFs) for gestational diabetes mellitus (GDM) established by selective screening (SS) and to identify subgroups of women at a higher risk of developing GDM. DESIGN: A retrospective, single-center study design was employed. METHODS: Data of 1015 women screened for GDM at 24-28 weeks of gestation and diagnosed according to the International Association of Diabetes and Pregnancy Study Groups criteria were evaluated. Information on RFs established by SS was also collected and their association with GDM was determined. To identify distinct and homogeneous subgroups of patients at a higher risk, the RECursive Partitioning and AMalgamation (RECPAM) method was used. RESULTS: Overall, 113 (11.1%) women were diagnosed as having GDM. The application of the SS criteria would result in the execution of an oral glucose tolerance test (OGTT) in 58.3% of women and 26 (23.0%) cases of GDM would not be detected due to the absence of any RF. The RECPAM analysis identified high-risk subgroups characterized by fasting plasma glucose values >5.1 mmol/l (odds ratio (OR)=26.5; 95% CI 14.3-49.0) and pre-pregnancy BMI (OR=7.0; 95% CI 3.9-12.8 for overweight women). In a final logistic model including RECPAM classes, previous macrosomia (OR=3.6; 95% CI 1.1-11.6), and family history of diabetes (OR=1.8; 95% CI 1.1-2.8), but not maternal age, were also found to be associated with an increased risk of developing GDM. A screening approach based on the RECPAM model would reduce by over 50% (23.0 vs 10.6%) the number of undiagnosed GDM cases when compared with the current SS approach, at the expense of 50 additional OGTTs required. CONCLUSIONS: A screening approach based on our RECPAM model results in a significant reduction in the number of undetected GDM cases compared with the current SS procedure.
OBJECTIVE: This study aimed to assess the predictive value of risk factors (RFs) for gestational diabetes mellitus (GDM) established by selective screening (SS) and to identify subgroups of women at a higher risk of developing GDM. DESIGN: A retrospective, single-center study design was employed. METHODS: Data of 1015 women screened for GDM at 24-28 weeks of gestation and diagnosed according to the International Association of Diabetes and Pregnancy Study Groups criteria were evaluated. Information on RFs established by SS was also collected and their association with GDM was determined. To identify distinct and homogeneous subgroups of patients at a higher risk, the RECursive Partitioning and AMalgamation (RECPAM) method was used. RESULTS: Overall, 113 (11.1%) women were diagnosed as having GDM. The application of the SS criteria would result in the execution of an oral glucose tolerance test (OGTT) in 58.3% of women and 26 (23.0%) cases of GDM would not be detected due to the absence of any RF. The RECPAM analysis identified high-risk subgroups characterized by fasting plasma glucose values >5.1 mmol/l (odds ratio (OR)=26.5; 95% CI 14.3-49.0) and pre-pregnancy BMI (OR=7.0; 95% CI 3.9-12.8 for overweight women). In a final logistic model including RECPAM classes, previous macrosomia (OR=3.6; 95% CI 1.1-11.6), and family history of diabetes (OR=1.8; 95% CI 1.1-2.8), but not maternal age, were also found to be associated with an increased risk of developing GDM. A screening approach based on the RECPAM model would reduce by over 50% (23.0 vs 10.6%) the number of undiagnosed GDM cases when compared with the current SS approach, at the expense of 50 additional OGTTs required. CONCLUSIONS: A screening approach based on our RECPAM model results in a significant reduction in the number of undetected GDM cases compared with the current SS procedure.
Authors: Kaat Beunen; Astrid Neys; Paul Van Crombrugge; Carolien Moyson; Johan Verhaeghe; Sofie Vandeginste; Hilde Verlaenen; Chris Vercammen; Toon Maes; Els Dufraimont; Nele Roggen; Christophe De Block; Yves Jacquemyn; Farah Mekahli; Katrien De Clippel; Annick Van Den Bruel; Anne Loccufier; Annouschka Laenen; Roland Devlieger; Chantal Mathieu; Katrien Benhalima Journal: Acta Diabetol Date: 2021-11-01 Impact factor: 4.280
Authors: Diane Farrar; Mark Simmonds; Maria Bryant; Debbie A Lawlor; Fidelma Dunne; Derek Tuffnell; Trevor A Sheldon Journal: PLoS One Date: 2017-04-06 Impact factor: 3.240
Authors: Marije Lamain-de Ruiter; Anneke Kwee; Christiana A Naaktgeboren; Arie Franx; Karel G M Moons; Maria P H Koster Journal: Diagn Progn Res Date: 2017-02-08
Authors: Grammata Kotzaeridi; Julia Blätter; Daniel Eppel; Ingo Rosicky; Martina Mittlböck; Gülen Yerlikaya-Schatten; Christian Schatten; Peter Husslein; Wolfgang Eppel; Evelyn A Huhn; Andrea Tura; Christian S Göbl Journal: Eur J Clin Invest Date: 2021-06-18 Impact factor: 5.722