Vol. 2, Issue 6 (2013)

Background: Gestational diabetes mellitus (GDM) is a prevalent complication during pregnancy, increasing health risks for both mother and child. Accurate, rapid screening for GDM is essential for effective management. This study aimed to evaluate the reliability of glucometer readings as a diagnostic tool compared to venous glucose (VG) sampling in 1200 pregnant women and identify demographic and clinical factors associated with GDM.

Materials and Methods: A cross-sectional study was conducted with 1200 pregnant women. Both glucometer (CG) readings and venous sampling were used to measure blood glucose levels. Demographic data, obstetric and medical history, and clinical characteristics, including age, locality, socio-economic status, polycystic ovarian disease (PCOD), family history of diabetes, gestational age, parity, hypothyroidism, and glycosuria, were analyzed for associations with GDM. Statistical analyses, including ROC curve assessment, were performed to evaluate the diagnostic accuracy of glucometers.

Results: The glucometer demonstrated excellent diagnostic performance, with sensitivity and specificity of 100% and 99.4%, respectively, and an AUC of 0.998 (p=0.0005). Significant associations with GDM were found for age (p=0.0024), PCOD (p=0.0027), family history of diabetes (p=0.0014), gestational age at presentation (p=0.014), and glycosuria (p=0.00014). No significant associations were observed with locality, socio-economic status, parity, or hypothyroidism. These results suggest glucometers are highly accurate for GDM detection and suitable for use in resource-limited settings.

Conclusion: Glucometer readings closely align with venous glucose sampling, demonstrating high accuracy in diagnosing GDM. Significant demographic and clinical factors, such as age, PCOD, family diabetes history, and glycosuria, are predictive of GDM, supporting their consideration in screening protocols. These findings highlight the potential of glucometers for efficient GDM detection, particularly in rural and resource-limited healthcare environments. Further studies should examine socio-economic and geographic factors influencing GDM prevalence