Validation of weight, insulin like growth factor 1, neonatal retinopathy of prematurity for detecting retinopathy of prematurity among Indian preterm neonates

Abstract

Background: Among the premature infants, WINROP (weight, insulin like growth factor 1, neonatal retinopathy of prematurity), a web- based retinopathy of prematurity (ROP) risk algorithm, uses postnatal weight gain in predicting the risk of severe ROP. This retrospective study assess the sensitivity and specificity of WINROP algorithm to predict proliferative ROP (type 1, type 2).Methods: This was a tertiary hospital based retrospective study conducted in level 3 - NICU from February -November 2018. The data was entered in WINROP website. 45 neonates enrolled in the study, were classified as either alarm given (increased risk of severe ROP) or not given (no risk of severe ROP/ no ROP). Timing of alarm was also noted.Result: 10 neonates (22%) had severe ROP requiring treatment. The mean gestational age was 30 weeks and mean birth weight was 1275 grams. In this study, sensitivity to WINROP online system was found to be 90%, specificity of 48.6%, positive predictive value of 33.3% and negative predictive value of 94.4%. The median time from alarm to treatment was 6 weeks (3-8 weeks).Conclusion: WINROP algorithm has a good sensitivity in detection of treatable ROP.