WINROP algorithm for prediction of sight threatening retinopathy of prematurity: Initial experience in Indian preterm infants

Purpose: To determine the efficacy of the online monitoring tool, WINROP ( https://winrop.com/ ) in detecting sight-threatening type 1 retinopathy of prematurity (ROP) in Indian preterm infants. Methods: Birth weight, gestational age, and weekly weight measurements of seventy preterm infants ( Results: Of the seventy infants enrolled in the study, 31 (44.28%) developed Type 1 ROP. WINROP alarm was signaled in 74.28% (52/70) of all infants and 90.32% (28/31) of infants treated for Type 1 ROP. The specificity was 38.46% (15/39). The positive predictive value was 53.84% (95% CI: 39.59–67.53) and negative predictive value was 83.3% (95% CI: 57.73–95.59). Conclusion: This is the first study from India using a weight gain-based algorithm for prediction of ROP. Overall sensitivity of WINROP algorithm in detecting Type 1 ROP was 90.32%. The overall specificity was 38.46%. Population-specific tweaking of algorithm may improve the result and practical utility for ophthalmologists and neonatologists.