Fig. 4: Progression of CKD in different pathological types and performance of Cox proportional hazards regression models in progression prediction. | Nature Communications

Fig. 4: Progression of CKD in different pathological types and performance of Cox proportional hazards regression models in progression prediction.

From: A noninvasive model for chronic kidney disease screening and common pathological type identification from retinal images

Fig. 4: Progression of CKD in different pathological types and performance of Cox proportional hazards regression models in progression prediction.The alternative text for this image may have been generated using AI.

a Kaplan−Meier curves for the progression of CKD according to different pathological types. IgAN IgA nephropathy, MN idiopathic membranous nephropathy, DN diabetic nephropathy, ANS arterionephrosclerosis, MCD/FSGS idiopathic minimal change disease and focal segmental glomerulosclerosis. b Kaplan−Meier curves for risk stratification from the Cox proportional hazards regression model with predicted pathological types from the image-only AI model. Survival curves represent the high-risk, medium-risk, and low-risk subgroups (risk score <Q1, Q1–Q3, >Q3), and 95% CI regions are represented as shaded areas around the curve. ROC curves showing the performance of Cox proportional hazards regression models at 1, 3, and 5 years with 10-fold cross-validation using c pathological types from renal biopsy and d predicted pathological types from the image-only AI model. The P value was calculated via the log-rank test among all groups. AUC area under the curve, CI confidence interval. Source data are provided as a Source Data file.

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