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Lookup NU author(s): Professor Judith RankinORCiD, Dr Ruth Bell
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
Copyright © 2024 Sobngwi, Sobngwi-Tambekou, Katte, Echouffo-Tcheugui, Balti, Kengne, Fezeu, Ditah, Tchatchoua, Dehayem, Unwin, Rankin, Mbanya and Bell.Background: The burden of gestational diabetes (GDM) and the optimal screening strategies in African populations are yet to be determined. We assessed the prevalence of GDM and the performance of various screening tests in a Cameroonian population. Methods: We carried out a cross-sectional study involving the screening of 983 women at 24-28 weeks of pregnancy for GDM using serial tests, including fasting plasma (FPG), random blood glucose (RBG), a 1-hour 50g glucose challenge test (GCT), and standard 2-hour oral glucose tolerance test (OGTT). GDM was defined using the World Health Organization (WHO 1999), International Association of Diabetes and Pregnancy Special Group (IADPSG 2010), and National Institute for Health Care Excellence (NICE 2015) criteria. GDM correlates were assessed using logistic regressions, and c-statistics were used to assess the performance of screening strategies. Findings: GDM prevalence was 5·9%, 17·7%, and 11·0% using WHO, IADPSG, and NICE criteria, respectively. Previous stillbirth [odds ratio: 3·14, 95%CI: 1·27-7·76)] was the main correlate of GDM. The optimal cut-points to diagnose WHO-defined GDM were 5·9 mmol/L for RPG (c-statistic 0·62) and 7·1 mmol/L for 1-hour 50g GCT (c-statistic 0·76). The same cut-off value for RPG was applicable for IADPSG-diagnosed GDM while the threshold was 6·5 mmol/L (c-statistic 0·61) for NICE-diagnosed GDM. The optimal cut-off of 1-hour 50g GCT was similar for IADPSG and NICE-diagnosed GDM. WHO-defined GDM was always confirmed by another diagnosis strategy while IADPSG and GCT independently identified at least 66·9 and 41·0% of the cases. Interpretation: GDM is common among Cameroonian women. Effective detection of GDM in under-resourced settings may require simpler algorithms including the initial use of FPG, which could substantially increase screening yield.
Author(s): Sobngwi E, Sobngwi-Tambekou J, Katte JC, Echouffo-Tcheugui JB, Balti EV, Kengne A-P, Fezeu L, Ditah CM, Tchatchoua A-P, Dehayem M, Unwin NC, Rankin J, Mbanya JC, Bell R
Publication type: Article
Publication status: Published
Journal: Frontiers in Clinical Diabetes and Healthcare
Year: 2024
Volume: 4
Online publication date: 09/01/2024
Acceptance date: 07/12/2023
Date deposited: 05/02/2024
ISSN (electronic): 2673-6616
Publisher: Frontiers Media SA
URL: https://doi.org/10.3389/fcdhc.2023.1272333
DOI: 10.3389/fcdhc.2023.1272333
Data Access Statement: The raw data supporting the conclusions of this article is available upon reasonable request to the corresponding author, sobngwieugene@yahoo.fr.
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