Diabetic nephropathy nomogram construction based on optical coherence tomography angiography variables

We developed a prediction model for DN with relatively good performance using OCTA-derived variables. DCP density and the FD-300 area were identified as key predictors. The resulting nomogram may serve as a useful diagnostic tool for DN and support future advances in OCTA-based artificial intelligence diagnostic systems. However, as external validation datasets are still missing, the results of this study should still be considered somewhat preliminary.