Abstract
Background: In developing countries, data on the applicability of existing models to predict retinopathy of prematurity (ROP) are scarce. The study aimed to validate the Alexandria ROP (Alex-ROP) and high-grade Alex-ROP (Hg Alex-ROP) models retrospectively to identify treatable ROP in a cohort of preterm infants in Saudi Arabia. Materials and Methods: We reviewed and included the records of 281 infants born prematurely in 2015-2021. We recorded the infants' demographics, gestational age at birth (GA), birth weight (BW), and serial weight measurements (day 7, 14, 21, and 28). We determined whether the included met the Alex-ROP and Hg Alex-ROP detection criteria for treatable or any-stage ROP and calculated the specificity, sensitivity, negative and positive predictive values, and accuracy. Results: The median BW and GA was 1095 g (range: 426-1920 g) and 29 weeks (range: 23-36 weeks), respectively. ROP developed in 112 infants, of which 30 cases were treatable. The Alex-ROP sensitivity for correctly predicting any-stage ROP and treatable ROP was 77.7% and 80.0%, respectively, and its specificity for predicting any-stage ROP and treatable ROP was 49.7% and 41%, respectively. The Hg Alex-ROP had 36.6% and 50.0% sensitivity for detecting any-stage ROP and treatable ROP, respectively, and its specificity for detecting any-stage ROP and treatable ROP was 83.4% and 78.5%, respectively. Conclusion: Previously published accuracy parameters were not reproducible in this cohort and a significant number of children requiring treatment would have been missed if the Alex-ROP or Hg Alex-ROP were applied.