F. Y. EYE

Deep-learning systems utilizing retinal imaging have previously been developed and shown to accurately predict chronological age. They have also generated the concept of a retinal age gap, the difference between predicted age from retinal imaging and actual chronological age, which has been used as a potential predictor of mortality and proposed as a more accurate measure of biological aging. Researchers used the concept of retinal age gap to investigate whether it could be used as a predictor of developing end stage kidney disease. The study utilized retinal imaging of 35 864 individuals who participated in the UK Biobank Study, following the participants for a median of 11 years of follow-up. Over the course of the study, 115 individuals (0.32%) developed end stage kidney disease. The study found that the risk of end stage kidney disease increased by 10% for each 1-year increase in retinal age gap (hazard ratio 1.10, 95% confidence interval 1.03-1.17, p=0.03). When the results were stratified by retinal age, those in the highest quartile had an increased risk that was almost three times higher (hazard ratio 2.77, p=0.009) than those in the lowest quartile. The risk was higher in females (hazard ratio 4.73, p=0.03) compared to males (hazard ratio 2.23, p=0.08). The authors concluded that retinal age gap is a potential predictor of end stage kidney disease.Zhang S, Chen R, Wang Y, Hu W, Kiburg KV, Zhang J, Yang X, Yu H, He M, Wang W, Zhu Z, Association of Retinal Age Gap and Risk of Kidney Failure: A UK Biobank Study, American Journal of Kidney Diseases (2023), doi: https://doi.org/10.1053/j.ajkd.2022.09.018.