Clinical Prediction Model for Diabetic Kidney Disease Based on Optical Coherence Tomography Angiography
[Objective]To construct and validate a clinical prediction model for diabetic kidney disease(DKD)based on optical coherence tomography angiography(OCTA).[Methods]This study enrolled 567 diabetes patients.The random forest algorithm as well as logistic regression analysis were applied to construct the prediction model.The model discrimina-tion and clinical usefulness were evaluated by receiver operating characteristic curve(ROC)and decision curve analysis(DCA),respectively.[Results]The clinical prediction model for DKD based on OCTA was constructed with area under the curve(AUC)of 0.878 and Brier score of 0.11.[Conclusions]Through multidimensional verification,the clinical pre-diction nomogram model based on OCTA allowed for early warning and advanced intervention of DKD.
万方数据
维普
