Aim: To test the effectiveness of WINROP software tool to screen retinopathy of prematurity (ROP) in Indian preterm infant population including twin neonates.
Materials and methods:In a retrospective single-center study, birth weight (BW), gestational age (GA), comorbidities, and weekly weight measurements (for 5 weeks) were retrieved from 63 preterm infants born between 01/2014 and 04/2015. The obtained data were entered into the WINROP algorithm to obtain ROP outcomes and WINROP alarm. Results: For a cohort of 63 patients together with twin neonates, the median BW was 1250 gm and GA was 30 weeks. Of the 63 infants, 22 infants developed type I ROP and 39 infants developed type II ROP. WINROP alarm was triggered in 33 (52.38%) infants. Comorbidities, such as malnutrition, respiratory distress syndrome (RDS), blood transfusion, anemia of prematurity, and pregnancy-induced hypertension (PIH) were associated with the development of ROP. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of WINROP to predict type I ROP were 63.6, 53.6, 42.4, and 73.3%, respectively. In twin neonates, WINROP predicted type I ROP with sensitivity, specificity, PPV, and NPV of 100, 60, 33.3, and 100%, respectively. Conclusion: This is the first WINROP validation study in twin neonates from Indian settings. The WINROP model was highly sensitive to detect type I ROP in twin neonates. However, due to low specificity and low PPV, the outcome of this study suggests the use of WINROP algorithm alongside standard ROP screening in infants including twin neonates with WINROP alarm.