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Influence of glycosylated hemoglobin on sight-threatening diabetic retinopathy: a population-based study

Rajiv Raman1, Aditya Verma, Swakshyar Saumya Pal

  • 1Shri Bhagwan Mahavir Vitreoretinal Services, 18 College Road, Sankara Nethralaya, Chennai 600 006, Tamil Nadu, India.

Diabetes Research and Clinical Practice
|February 8, 2011
PubMed

Insights

Elevated glycosylated hemoglobin (HbA1c) levels above 8.0% are significantly linked to sight-threatening diabetic retinopathy (STDR). This finding is crucial for identifying individuals at high risk during diabetes screening programs.

Area of Science:

  • Ophthalmology
  • Endocrinology
  • Public Health

Background:

  • Diabetic retinopathy (DR) is a leading cause of vision loss globally.
  • Glycosylated hemoglobin (HbA1c) is a key marker for long-term glycemic control in diabetes.
  • Identifying individuals at risk for sight-threatening diabetic retinopathy (STDR) is critical for timely intervention.

Purpose of the Study:

  • To investigate the association between HbA1c levels and the incidence of STDR in an urban Indian population.
  • To determine a potential HbA1c threshold for identifying STDR risk in screening programs.

Main Methods:

  • A cross-sectional study was conducted in Chennai, India, involving 1414 diabetic individuals.
  • HbA1c levels were measured using liquid chromatography.
  • Participants were categorized into no DR, non-STDR, and STDR groups based on fundus photography.

Main Results:

  • Statistically significant differences in diabetes duration, BMI, HbA1c, and albuminuria were observed between groups.
  • Multivariate analysis confirmed HbA1c as a significant predictor for both non-STDR (OR=1.23) and STDR (OR=1.31) compared to no DR.
  • Receiver Operating Characteristic analysis suggested an HbA1c cut-off of 8.0% for STDR detection, with 75.6% sensitivity and 58.2% specificity.

Conclusions:

  • An HbA1c level exceeding 8.0% is significantly associated with STDR.
  • An HbA1c cut-off of 8.0% demonstrates potential utility in maximizing STDR detection within screening programs.
Abstract

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