Clinical Prediction Model for Diabetic Kidney Disease Based on Optical Coherence Tomography Angiography
10.13471/j.cnki.j.sun.yat-sen.univ（med.sci）.20240319.002
- VernacularTitle:基于OCTA构建糖尿病肾脏病临床预测模型
- Author:
Lijiao LU
1
;
Nan XU
1
;
Xinxin LIU
1
;
Fangfang DU
1
;
Cong ZHENG
1
;
Hongjun PENG
1
;
Mingzhe CAO
1
;
Shibei AI
1
Author Information
1. Department of Ophthalmology， The Seventh Affiliated Hospital of Sun Yat-sen University， Shenzhen 518000， China
- Publication Type:Journal Article
- Keywords:
optical coherence tomography angiography （OCTA）;
diabetic kidney disease （DKD）;
clinical prediction model;
receiver operating characteristic curve （ROC）;
decision curve analysis （DCA）
- From:
Journal of Sun Yat-sen University(Medical Sciences)
2024;45(2):253-260
- CountryChina
- Language:Chinese
-
Abstract:
ObjectiveTo construct and validate a clinical prediction model for diabetic kidney disease （DKD） based on optical coherence tomography angiography （OCTA）. MethodsThis study enrolled 567 diabetes patients. The random forest algorithm as well as logistic regression analysis were applied to construct the prediction model. The model discrimination and clinical usefulness were evaluated by receiver operating characteristic curve （ROC） and decision curve analysis （DCA）， respectively. ResultsThe 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. ConclusionsThrough multidimensional verification， the clinical prediction nomogram model based on OCTA allowed for early warning and advanced intervention of DKD.
