Application of a Quantitative Vascular Severity Score in Retinopathy of Prematurity in the United States and India: New Insights Into Disease Epidemiology and Pathophysiology.

Abstract

To compare the epidemiology and phenotypic characteristics of 2 populations of patients with retinopathy of prematurity (ROP) using a quantitative artificial intelligence (AI)-derived vascular severity score (VSS). We retrospectively analyzed 2 data sets of ROP images: (1) The iROP data set including 1019 babies and 6552 eye-level examinations developed as part of a large US multicenter cohort study from 2012 to 2020. (2) 8281 consecutive ROP telemedicine examinations from 2363 babies in the Indian Aravind Eye Care System (AECS), from 2019 to 2020. We analyzed all eye examinations using the iROP DL system, which outputs a VSS from 1 to 9. The main outcome was the relationship between the VSS and the zone, stage, and extent of stage 3 in each data set, assessed using generalized estimating equations to account for the correlation from bilateral and repeated examinations. In both data sets, higher VSS was associated with higher stage (P < .001 for all stages in both data sets), higher extent of stage 3 (i-ROP, P =.004, and AECS, P < .001), and a more posterior zone for a given stage of ROP (i-ROP: stage 1, P = .04, stage 2, P < .001, and stage 3, P < .001; AECS: stage 1, P < .001, and stage 3, P < .001). For any given stage, the VSS was lower in the AECS data set than in the i-ROP data set (all P < .001). In both populations, the VSS was associated with more posterior zone and higher ROP stage/extent, though on average the VSS was lower in the AECS population. A correlation between measured VSS and intraocular vascular endothelial growth factor concentration might explain both findings.