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).