Topical losartan for established corneal fibrosis with machine learning-based predictors

Abstract

This study evaluated the effectiveness of topical losartan 1 mg/mL in reducing corneal fibrosis by inhibiting myofibroblast proliferation and improving corneal transparency, offering a potential therapeutic alternative. A prospective, interventional case series enrolled adults with corneal fibrosis. Participants administered topical losartan 1 mg/mL six times daily for 3 months. Visual acuity, slit-lamp examination, corneal tomography, and densitometry were used to assess outcomes. A Random Forest machine learning model identified key predictors of visual improvement. Nineteen eyes from seventeen patients were analyzed. Mean uncorrected distance visual acuity improved from 1.04 ± 0.62 to 0.74 ± 0.46 LogMAR (p = 0.007). Corneal densitometry significantly decreased, particularly in the midperipheral zone (p = 0.0184). Worse baseline visual acuity and longer leukoma duration correlated with greater improvement. The predictive model achieved an AUROC of 0.76, with 86.67% sensitivity, 75.00% specificity, and 84.21% accuracy, confirming its robustness. These findings suggest that topical losartan improves corneal transparency and functional vision in patients with corneal fibrosis. The predictive model provides a clinically useful scoring system to guide treatment selection. Further validation in larger clinical trials is warranted.