Diagnostic Accuracy of WINROP, CHOP-ROP and ROPScore in Detecting Type 1 Retinopathy of Prematurity.

BACKGROUND Algorithms for predicting retinopathy of prematurity (ROP) requiring treatment need to be validated in Indian settings to determine if the burden of screening can be reduced without compromising the sensitivity of existing gestation and weight-based cut offs. OBJECTIVE To evaluate the performance of the available algorithms namely, WINROP (Weight, Insulin-like growth factor I, Neonatal, ROP), CHOP-ROP (Children's Hospital of Philadelphia ROP) and ROPScore in predicting type 1 ROP and time from alarm to treatment by each algorithm. STUDY DESIGN Ambispective observational. SETTING Tertiary care neonatal intensive care unit in India. PARTICIPANTS Neonates less than 32 weeks or less than 1500 gm born between July 2013 to June 2019 (n=578) who underwent ROP screening. PRIMARY OUTCOME Sensitivity, specificity and time from alarm to treatment by each algorithm. RESULT The sensitivity and specificity of WINROP was 85% and 36%, CHOP-ROP was 54% and 71% and ROPScore was 73% and 67% respectively in detecting type 1 ROP. A total of 50/51 (98%) of neonates with type 1 ROP underwent treatment at median gestation of nine weeks and median time from alarm to treatment by WINROP, CHOP-ROP and ROPScore was seven, seven and three weeks respectively. CONCLUSION WINROP, CHOP-ROP and ROPScore were not sensitive enough to replace the gestational age, weight and risk factor-based screening criteria for type 1 ROP.