Abstract
PURPOSE: To assess the predictive performance of DIGIROP-v1.0 models in identifying treatment-requiring ROP among infants undergoing ROP screening at a tertiary neonatal intensive care unit in Greece. METHODS: Retrospective cohort analysis of 640 consecutive screened preterm infants with gestational age (GA) 24(0/7) to 30(6/7) weeks and known ROP outcome in the 2nd Neonatology Department of Aristotle University of Thessaloniki (2009-2021). The primary outcome was the development of type 1 ROP according to the Early Treatment of ROP criteria or treatment based on the ophthalmologist's judgement. Sensitivity, specificity, area under the curve (AUC) with corresponding 95% confidence intervals (CI) and calibration plots for the DIGIROP-v1.0 models were displayed. RESULTS: The DIGIROP-Birth-v1.0 model correctly identified 35/43 treated infants (sensitivity 81.4% [95% CI, 66.6%-91.6%], specificity 61.5% [95% CI, 57.4%-65.4%], AUC 0.82 [95% CI, 0.75-0.90]). During the postnatal weeks 6-14 the sensitivity of the DIGIROP-Screen-v1.0 model ranged from 82.6% to 100%. Eleven infants, all with severe comorbidities, that is, congenital malformation(s), syndrome(s), hydrocephalus or history of intestinal surgery, that were treated, were missed by the model, but met criteria for screening according to DIGIROP-v1.0 models' recommendations, and to our unit's routine standards. CONCLUSION: The DIGIROP-v1.0 models resulted in lower sensitivity and higher specificity in this Greek cohort compared with the Swedish development group. Despite higher GA and BW, infants in our cohort had higher incidence of treated ROP than in Sweden, resulting in an under-estimation of their risk for treatment-requiring ROP. Further validation of the DIGIROP-v2.0 models and potential adjusting are recommended to maximize generalizability in populations with different characteristics.