To Study the Neutrophil-to-lymphocyte Ratio as a Quick and Reliable Predictive Marker to Diagnose Diabetic Retinopathy Among Diabetes Patients: a Case–control Study
Year: 2025
Type: article
Study design: Observational Study
Abstract: Objectives: Diabetic retinopathy (DR) is a prevalent microvascular complication of diabetes mellitus (DM), and a leading cause of preventable blindness worldwide. Chronic hyperglycemia derives retinal neurovascular damage, and systemic inflammation contributes significantly to its pathogenesis. The neutrophil-to-lymphocyte ratio (NLR), a simple biomarker of inflammation, had shown promise in identifying DR risk. This study is to assess NLR levels in DM patients with and without DR, determine its association with DR presence and severity, and evaluate its diagnostic accuracy. Methods: This hospital-based case–control study enrolled 100 Type 2 DM (T2DM) patients (50 with clinically confirmed DR and 50 without DR) from September 2023 to February 2025 at a tertiary-care center in rural Pondicherry. All patients underwent fundoscopic examination, glycemic profiling, and complete blood counts to calculate NLR. Statistical analyses comprised an independent t-test, the Chi-square test, Cox regression, and diagnostic accuracy using the Statistical Package for the Social Sciences software. Results: The mean age of the participants was 57.4±10.8 years; 66% of them were males. Mean NLR was significantly higher in the DR group (3.33±0.59) than in controls (1.74±0.49; p<0.001). Each unit rise in NLR nearly tripled DR risk (Hazard ratio: 2.98; 95% confidence interval: 2.02–4.38; p<0.001). Receiver operating characteristics analysis yielded 96% for sensitivity, 92% for specificity with Youden’s index of 0.880. Conclusion: Thus, NLR is a robust, cost-effective biomarker for early DR detection in T2DM patients. Incorporating NLR into routine diabetes care may enhance screening, risk stratification, and timely intervention to prevent vision loss.
Authors: SALAIPUDHUR RAJENDRAN ELAKKIAN, VIGNESSH RAVEEKUMARAN, SETHURAJ SELVARAJ, CHENTHIL KS
Language: English
Subfield: Oncology
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4415026825