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Retinopathy of prematurity: Accuracy of ROPScore and WINROP algorithms in a Brazilian population
Amanda F L Morais1, Luisa M Hopker2, Nilva S B Moraes1
1Department of Ophthalmology and Visual Sciences, Escola Paulista de Medicina, Universidade Federal de São Paulo, São Paulo, SP, Brazil.
Insights
The ROPScore accurately identified all infants at risk for severe retinopathy of prematurity. This score should be integrated into Brazilian guidelines for retinopathy of prematurity screening.
Area of Science:
- Neonatology
- Ophthalmology
- Pediatrics
Background:
- Retinopathy of prematurity (ROP) is a significant cause of visual impairment in preterm infants.
- Early detection and treatment are crucial to prevent severe visual outcomes.
- Predictive tools are needed to optimize screening protocols for preterm infants.
Purpose of the Study:
- To evaluate the sensitivity and specificity of the Retinopathy of Prematurity Score (ROPScore) and the weight, insulin-like growth factor-1, retinopathy of prematurity algorithm.
- To assess their ability to predict severe retinopathy of prematurity (prethreshold type 1) in Brazilian preterm infants.
Main Methods:
- Retrospective analysis of 288 preterm infants (birth weight ≤1500 g and/or gestational age 23-32 weeks).
- Data collected from a neonatal unit in Southern Brazil between May 2013 and December 2020.
- Comparison of ROPScore and weight, insulin-like growth factor-1, retinopathy of prematurity algorithm performance.
Main Results:
- The incidence of severe ROP was 6.6%.
- ROPScore demonstrated 100% sensitivity and 44.6% specificity for severe ROP.
- The weight, insulin-like growth factor-1, retinopathy of prematurity algorithm showed 78.9% sensitivity and 51.3% specificity.
Conclusions:
- ROPScore effectively identified all infants at risk for severe ROP.
- Incorporating ROPScore into Brazilian guidelines could optimize ROP screening.
- The weight, insulin-like growth factor-1, retinopathy of prematurity algorithm requires adjustments for the Brazilian population.
Purpose:
To assess the sensitivity and specificity of the retinopathy of prematurity score (ROPScore) and weight, insulin-like growth factor-1, retinopathy of prematurity algorithm in predicting the risk of developing severe retinopathy of prematurity (prethreshold type 1) in a sample of preterm infants in Brazil.
Methods:
Retrospective analysis of medical records of preterm infants (n=288) with birth weight of ≤1500 g and/or gestational age of 23-32 weeks in a neonatal unit in Southern Brazil from May 2013 to December 2020 (92 months).
Results:
The incidence of confirmed severe retinopathy of prematurity was 6.6%. ROPScore showed a 100% sensitivity, 44.6% specificity (95% confidence interval [CI] 38.7-50.6), 11.3% positive predictive value (95% CI 6.5-16.1), and 100% negative predictive value in predicting severe retinopathy of prematurity. The weight, insulin-like growth factor-1, retinopathy of prematurity algorithm demonstrated a 78.9% sensitivity (95% CI 60.6-97.3), 51.3% specificity (95% CI 45.3-57.3), 10.3% positive predictive value (95% CI 5.3-15.2), and 97.2% negative predictive value (95% CI 94.5-99.9).
Conclusion:
ROPScore identified all patients at risk for severe retinopathy of prematurity. These findings support incorporating ROPScore into Brazilian guidelines to optimize retinopathy of prematurity screening and reduce unnecessary ophthalmologic examinations. Weight, insulin-like growth factor-1, retinopathy of prematurity's suboptimal performance in this Brazilian sample highlights the need for country-specific algorithm adjustments.
