Validation of three weight gain-based algorithms as a screening tool to detect retinopathy of prematurity: A
Lina Raffa1,2, Aliaa Alamri3, Amal Alosaimi4
1Department of Ophthalmology, King Abdulaziz University, Jeddah, Saudi Arabia.
Insights
WINROP and ROPScore achieved 100% sensitivity for detecting retinopathy of prematurity (ROP) in preterm infants. However, low specificity suggests a need for tailored algorithms to accurately identify infants at risk of sight-threatening ROP.
Area of Science:
- Ophthalmology
- Neonatology
- Medical Informatics
Background:
- Retinopathy of prematurity (ROP) screening guidelines are frequently updated.
- Accurate identification of infants at risk for type 1 ROP is crucial for timely intervention.
Purpose of the Study:
- To evaluate the diagnostic accuracy of three predictive algorithms: WINROP, ROPScore, and CO-ROP.
- To assess their effectiveness in detecting ROP in preterm infants within a developing country context.
Main Methods:
- Retrospective study of 386 preterm infants (gestational age ≤30 weeks and/or birth weight ≤1500 g).
- Data collected from two centers between 2015 and 2021.
- Analysis of ROP screening outcomes and algorithm performance.
Main Results:
- 123 neonates (31.9%) developed ROP.
- WINROP and ROPScore demonstrated 100% sensitivity for type 1 ROP.
- Specificity was low: WINROP (28%), ROPScore (1.4%), CO-ROP (19.3%).
- WINROP showed the best performance for type 1 ROP (AUC 0.61).
Conclusions:
- WINROP and ROPScore offer high sensitivity but lack specificity for type 1 ROP.
- Development of population-specific, highly specific algorithms is recommended.
- Such tools could aid in detecting preterm infants at risk for sight-threatening ROP.
Purpose:
Screening guidelines for retinopathy of prematurity (ROP) are updated frequently to help clinicians identify infants at risk of type 1 ROP. This study aims to evaluate the accuracy of three different predictive algorithms-WINROP, ROPScore, and CO-ROP-in detecting ROP in preterm infants in a developing country.
Methods:
This retrospective study was conducted on 386 preterm infants from two centers between 2015 and 2021. Neonates with gestational age ≤30 weeks and/or birth weight ≤1500 g who underwent ROP screening were included.
Results:
One hundred twenty-three neonates (31.9%) developed ROP. The sensitivity to identify type 1 ROP was as follows: WINROP, 100%; ROPScore, 100%; and CO-ROP, 92.3%. The specificity was 28% for WINROP, 1.4% for ROPScore, and 19.3% for CO-ROP. CO-ROP missed two neonates with type 1 ROP. WINROP provided the best performance for type 1 ROP with an area under the curve score at 0.61.
Conclusion:
The sensitivity was at 100% for WINROP and ROPScore for type 1 ROP; however, specificity was quite low for both algorithms. Highly specific algorithms tailored to our population may serve as a useful adjunctive tool to detect preterm infants at risk of sight-threatening ROP.
