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Original Articles

Diagnostic accuracy of HbA1c in detecting gestational diabetes mellitus

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Pages 3497-3500 | Received 10 Nov 2018, Accepted 27 Jan 2019, Published online: 11 Feb 2019
 

Abstract

Objective: To investigate the diagnostic value of glycated hemoglobin A1c (HbA1c) in detecting gestational diabetes mellitus (GDM).

Methods: Pregnant women at gestational age 24 weeks or more, who had abnormal GDM screening test, were enrolled in this prospective study. A HbA1c assessment was performed at the same time of 3-h 100 g oral glucose tolerance test (OGTT). GDM was diagnosed according to the National Diabetes Data Group for a 3-h 100 g OGTT. Sensitivity and specificity of HbA1c were evaluated and pregnancy outcome were recorded in aspects of gestational age at delivery, preeclampsia, primary cesarean section rate, birth weight, fetal macrosomia, and neonatal intensive care unit admission.

Results: One hundred fourteen women were enrolled. There were 35 women with GDM using NDDG criteria. The area under the curve of the receiver operating characteristic curve for HbA1c detection of GDM was 0.725 (95% confidence interval 0.621–0.829). Cut-off value of HbA1c was 5.8%. Sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were 17.1, 100, 100, 73.2, and 74.6%, respectively. Pregnancy outcome in both groups in this study has no statistical significance.

Conclusions: HbA1c values cannot replace OGTT for the diagnosis of GDM. However, HbA1c might be a useful tool to reduce the number of OGTT, associated costs and patient inconvenience.

Acknowledgments

The authors acknowledge the assistance of medical and nursing staff of the antenatal care unit, Department of Obstetrics and Gynecology, Faculty of Medicine, Chulalongkorn University for their help in recruiting patients in the study.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This research was supported by the Ratchadapiseksompotch Fund, Faculty of Medicine, Chulalongkorn University, study grant number RA60/108.

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