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Validation of a screening score model to predict the development of retinopathy of prematurity
Johanes E Siswanto1,2, Asri C Adisasmita3, Sudarto Ronoatmodjo3
1Neonatology Working Group, Department of Pediatrics, Harapan Kita National Women and Children Health Centre, Jakarta, Indonesia. edyjo15@yahoo.com.
Insights
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.
Abstract:
Retinopathy of prematurity (ROP) is a leading cause of preventable blindness in preterm infants, with a disproportionate burden in low- and middle-income countries. Screening criteria from high-income settings may not be directly applicable in these contexts. We developed and validated two pragmatic risk-based screening models using multicenter Indonesian neonatal data: Model A (FiO₂-based) and Model B (SpO₂-based). Significant predictors included intrauterine growth restriction, oxygen exposure, exchange transfusion, and socioeconomic status. Internal validation showed moderate discrimination (AUC 0.719-0.732) with sensitivities of 77-86% and specificities of 44-58%. The bedside operational score form is presented for clinical use. External validation in 163 infants (gestational age 25-37 weeks, birth weight 600-2000 g) confirmed robust performance, with the combined rule (positive if either model was positive) achieving a sensitivity 84%, a specificity 81%, positive predictive value 76%, and negative predictive value 87%. The pre-test probability of ROP was 0.42, increasing to 0.76 after a positive screen and decreasing to 0.13 after a negative result. These findings support the use of locally validated risk-based scores as a practical complement to gestational age and birth weight criteria, optimizing ROP case finding in resource-limited settings.
