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. Results: Among 681 infants, 50 (7.3%) had any ROP detected at the index examination. The apparent area under the receiver operating characteristic curve was 0.901 (95% CI, 0.856-0.946), and the optimism-corrected estimate was 0.883 (bootstrap 95% CI, 0.841-0.928). Optimism-corrected calibration-in-the-large was 0.008, the expected-to-observed ratio was 1.005, and the calibration slope was 0.866. At the sensitivity-constrained exploratory cut-off of 1.5%, sensitivity was 96.0% and specificity was 53.4%. The observed ROP risk was 14.0% in the higher-risk group and 0.6% in the lower-risk group. Decision curve analysis suggested net benefit across threshold probabilities up to 0.20. Conclusions: The model showed good discrimination and may support risk stratification and prioritization among infants already eligible for ROP screening. The 1.5% cut-off remains exploratory, and independent external validation, preferably in prospective contemporary cohorts, is required before clinical implementation.