The Use of the WINROP Screening Algorithm for the Prediction of Retinopathy of Prematurity in a Chinese Population

Abstract

Background: Retinopathy of prematurity (ROP) is a gestational age (GA)-related illness that can lead to blindness in premature infants. Timely screening of premature infants could improve visual prognosis. Objective: To evaluate the WINROP algorithm as a method of predicting severe ROP in a Chinese population. Methods: 590 infants with a GA <32 weeks were entered into an online surveillance system (www.winrop.com) that included ROP evaluations and weekly weight measurements from birth to a corrected GA of 40 weeks. If the rate of weight gain decreased to a certain degree, the algorithm signaled an alarm that the infant was at risk for developing sight-threatening ROP. Each infant was categorized as having no, mild, or severe ROP. Results: Among the 590 infants with a GA <32 weeks, an alarm was triggered in 85 infants (14.4%), 50 of which developed severe ROP and were identified in this alarm group. Twenty-seven infants triggered the alarm signal in the first week after birth and 7 infants triggered the alarm at birth. Seven of the infants developed proliferative ROP and the median GA at birth for these infants was 31 weeks. Conclusions: The WINROP system had a sensitivity of 87.5% in a Chinese population for the early identification of infants that developed severe ROP. Postnatal weight gain may help predict ROP in lower birth weight infants.