assessment of dry eye severity using non-contact IDRA analyzer quantitative study

Authors: Adhitya ram Ganesh, Solasa Deepthi, Kirankumar Satti, B Chandrasekaran, SRI DIVYA DEGA

DOI: 10.18231/j.ijceo.11891.1761912783

Keywords: Dry Eye Disease, NIBUT, LLT, TMH, Meibography, Artificial Intelligence

Abstract: ABSTRACT Purpose: To evaluate ocular surface parameters using a non-contact dry eye analyzer (IDRA) across varying severities of dry eye disease. Methods: A retrospective analysis was conducted on 92 eyes stratified into normal, mild, moderate, and severe dry eye categories. Parameters assessed included NIBUT, LLT, TMH, and Meibomian gland loss (upper and lower lids). Data were analyzed using one-way ANOVA. Results: Statistically significant differences were observed for NIBUT (F = 15.01, p < 0.001), LLT (F = 10.36, p < 0.001), upper gland loss (F = 17.01, p < 0.001), and lower gland loss (F = 27.72, p < 0.001). TMH differences were not statistically significant (F = 0.53, p = 0.66). Conclusion: IDRA effectively differentiates severity levels of dry eye through objective, non-contact measurements of ocular surface parameters, supporting its utility in clinical practice.