Clinical Prediction Model for Diabetic Kidney Disease Based on Optical Coherence Tomography Angiography / 中山大学学报(医学科学版)
Journal of Sun Yat-sen University(Medical Sciences)
;
(6): 253-260, 2024.
Artigo
em Chinês
| WPRIM
| ID: wpr-1016446
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.
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DisponíveL
Índice:
WPRIM (Pacífico Ocidental)
Idioma:
Chinês
Revista:
Journal of Sun Yat-sen University(Medical Sciences)
Ano de publicação:
2024
Tipo de documento:
Artigo
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