Introduction
Retinopathy of prematurity (ROP) is one of the major causes of preventable blindness in childhood period in both developed and developing countries over the world.(1-3) The main risk factors for the development of ROP are low gestational age (GA) and birth weight (BW). Another risk factors including oxygen therapy, septicemia, blood transfusion, bronchopulmonary dysplasia have found to be associated with the development of ROP.(4-7) Novel improvements in neonatal intensive care lead to an increase in the survival rate in preterm infants and even in very low and very low birth weight (VLBW) infants.(3) Timely screening, diagnose and intervention are very crucial to prevent permanent loss of vision in preterm infants with severe ROP.(8) The presence of ROP requires consecutive stressful eye examinations assisted with scleral indentation which may lead to clinical disturbance, apnea, arrhythmia. Therefore, using predictive algorithms designed for ROP may have a significant effect on decreasing the burden of eye examinations and might be beneficial for early prediction of severe ROP before reaching sight-threatening level.(1, 2)
The ROPScore is an algorithm that was first described by Eckert et al.(9) to predict severe ROP. The scores are calculated at once based on BW, GA, proportional weight gain at the sixth week of life, receiving oxygen therapy in mechanical ventilation and history of blood transfusions. This scoring system was found to be effective in predicting of severe ROP and decreasing the number of eye examinations in different population.(9-11)
In this study, we aimed to evaluate the validation and accuracy of the ROPScore scoring algorithm for predicting of ROP in VLBW infants in neonatal intensive care unit (NICU).