Hemoglobin A1c to Detect Prediabetes or Type 2 Diabetes Mellitus in a Rural Population of Wardha District in India

Abstract Background: Global diabetes prevalence has doubled since 1980; India has the second-largest diabetic population. Nearly half of type 2 diabetes mellitus (T2DM) cases go undiagnosed. This study assesses glycated hemoglobin A1c (HbA1c) for diagnosing T2DM and prediabetes in at-risk individual...

Full description

Saved in:
Bibliographic Details
Main Authors: Shilpa Gaidhane, Ranjit Sah, Quazi Syed Zahiruddin, Nazli Khatib, Shital Telrandhe, Sonali Choudhari, Abhay Gaidhane
Format: Article
Language:English
Published: Wolters Kluwer Medknow Publications 2024-04-01
Series:Journal of Diabetology
Subjects:
Online Access:https://doi.org/10.4103/jod.jod_122_23
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Abstract Background: Global diabetes prevalence has doubled since 1980; India has the second-largest diabetic population. Nearly half of type 2 diabetes mellitus (T2DM) cases go undiagnosed. This study assesses glycated hemoglobin A1c (HbA1c) for diagnosing T2DM and prediabetes in at-risk individuals. Materials and Methods: We conducted a community-based cross-sectional study in a rural area. We assessed glucose intolerance risk factors among 1353 individuals (age >20 years), categorizing participants into low and moderate–high risk using the Indian Diabetes Risk Score (IDRS). For 363 participants with moderate- or high-T2DM risk, we evaluated fasting plasma glucose, hemoglobin, and HbA1c. Receiver Operating Characteristics (ROC) were constructed for HbA1c against gold standard fasting plasma glucose and 2-h-postload glucose to determine diagnostic accuracy and cut-point values for prediabetes and T2DM. We used decision curve analysis (DCA) to assess the utility of the new HbA1c cut point for T2DM diagnosis. Results: The prevalence of newly diagnosed T2DM and prediabetes was 44.63% (95% CI: 39.44–49.91) and 48.48% (95% CI: 43.24–53.76), respectively in people with moderate to high risk of T2DM on IDRS. On ROC, the area under the curve was 90.36% and 79.18%, respectively, reflecting high diagnostic accuracy. The optimum cut point of HbA1c for diagnosis of T2DM was 6.34%, with sensitivity and specificity of 74% and 94%, respectively. The HbA1c cut point for prediabetes was 5.65%, with a sensitivity and specificity of 80% and 75%, respectively. The new cut point of 6.34% on DCA gives substantial net benefit at a 40% probability risk, identifying 31 additional cases per 100 individuals at risk of T2DM and reducing the false positive by 47%. Conclusion: Our findings offer potential for developing a diagnostic protocol for T2DM and prediabetes (impaired fasting glucose) using HbA1c cut-point in people with moderate- to high-T2DM risk in rural settings.
ISSN:2078-7685