Predicting Retinopathy of Prematurity in Thailand: A Practical Model for Risk-Based Screening

Background/Objectives: Retinopathy of prematurity (ROP) screening must balance timely detection with feasibility, particularly in resource-limited settings. We aimed to develop a pragmatic, locally derived prediction model to support prioritization of ophthalmologic assessment among Thai neonates already eligible for ROP screening.

Methods

We conducted a retrospective cohort study of neonates undergoing their first planned ROP screening examination at Chiang Rai Prachanukroh Hospital (2011–2015) and Lampang Hospital (2021–2022). Prespecified predictors included gestational age, birth weight, multiple pregnancy, respiratory distress syndrome, neonatal anemia, neonatal sepsis, necrotizing enterocolitis, bronchopulmonary dysplasia, duration of oxygen exposure, and duration of mechanical ventilation. A multivariable logistic regression model was developed. Performance was evaluated using discrimination, calibration, decision curve analysis, and bootstrap internal validation with 1000 resamples.