الفهرس | Only 14 pages are availabe for public view |
Abstract Retinopathy of prematurity is one of the avoidable leading causes of childhood blindness worldwide.Proper screening for ROP can prevent loss of vision. WINROP is an online surveillance system based on gestational age, birth weight and weekly weight gain that can predict infants at risk of sight-threatening retinopathy of prematurity. Aims:To evaluate diagnostic accuracy of WINROP algorithm in detecting sight threatening ROP in Egyptian preterm neonates. Methods: Birth weight, gestational age and weekly weight measurement of 365 preterm infants <32wk were prospectively entered into WINROP algorithm that give either high or low risk alarm based on weekly weight gain. Sensitivity, specificity and predictive values were calculated by comparing results of WINROP with ROP screening outcome. Results:This study showed that mean GA ± 31.24 and mean BW ± 1508.78. High risk WINROP alarm was triggered in 62 infants of whom 16 infants develop type 1, 2 ROP. These infants had associated comorbidities as sepsis, IVH, NEC, packed RBCS and PLT transfusion. Low risk WINROP alarm was triggered in 303 infants and only 15 infants were developed type 1, 2 ROP. WINROP showed sensitivity 51.6%, specificity 86.2%, PPV 25.8 % and NPV 95%. Conclusion: WINROP has low sensitivity and high specificity for detection of ROP. It may help in ROP prediction but can’t be used alone. Modification of WINROP algorithm with other risk factors may improve sensitivity and reduce number for ROP examination. |