Validation of a screening score model to predict the development of retinopathy of prematurity
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View abstract on PubMed
Summary
This summary is machine-generated.Developing risk-based screening models for retinopathy of prematurity (ROP) in low-income countries is crucial. These validated models improve early detection of ROP, preventing blindness in premature infants.
Area Of Science
- Neonatal ophthalmology
- Public health
- Medical screening
Background
- Retinopathy of prematurity (ROP) is a major cause of preventable blindness in preterm infants, particularly in low- and middle-income countries.
- Existing screening criteria from high-income nations may not be suitable for resource-limited settings.
Purpose Of The Study
- To develop and validate pragmatic, risk-based screening models for ROP using Indonesian neonatal data.
- To provide a practical tool for optimizing ROP case finding in resource-limited environments.
Main Methods
- Development of two models (FiO₂-based and SpO₂-based) using multicenter Indonesian neonatal data.
- Internal validation assessing discrimination, sensitivity, and specificity.
- External validation in a separate cohort of preterm infants.
Main Results
- Significant predictors for ROP included intrauterine growth restriction, oxygen exposure, exchange transfusion, and socioeconomic status.
- Internal validation showed moderate discrimination (AUC 0.719-0.732).
- External validation of a combined rule demonstrated high sensitivity (84%) and specificity (81%), with strong predictive values.
Conclusions
- Locally validated, risk-based screening scores are a practical complement to existing ROP screening criteria.
- These models can optimize ROP case finding in resource-limited settings, aiding in the prevention of blindness.
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