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.