Predicting Osteoporotic Fracture in Patients With Early-Stage Diabetic Kidney Disease Using a Radiomic Model: A Longitudinal Cohort Study
作者全名:Gao, Youyuan; Gao, Jianya; Wang, Yunting; Gan, Hua
作者地址:[Gao, Youyuan; Gao, Jianya; Wang, Yunting; Gan, Hua] Chongqing Med Univ, Dept Nephrol, Affiliated Hosp 1, 1 Youyi Rd, Chongqing, Peoples R China; [Gao, Youyuan] Chongqing Univ, Fuling Hosp, Dept Neurol, Chongqing, Peoples R China
通信作者:Gan, H (通讯作者),Chongqing Med Univ, Dept Nephrol, Affiliated Hosp 1, 1 Youyi Rd, Chongqing, Peoples R China.
来源:ENDOCRINE PRACTICE
ESI学科分类:CLINICAL MEDICINE
WOS号:WOS:001219767700001
JCR分区:Q2
影响因子:3.7
年份:2024
卷号:30
期号:4
开始页:360
结束页:366
文献类型:Article
关键词:osteoporotic fracture; radiomics; diabetic kidney disease; dual-energy X-ray absorptiometry
摘要:Objective: There is an urgent need for effective predictive strategies to accurately evaluate the risk of fragility fractures in elderly patients in the early stages of diabetic kidney disease (DKD). Methods: This longitudinal cohort study included 715 older patients in the early stages of DKD diagnosed between January 2015 and August 2019. Patients were randomly allocated to a training cohort (n = 499) and a validation cohort (n = 216). The least absolute shrinkage and selection operator method was used to select key features for dual-energy x-ray absorptiometry-based radiomic analysis. A radiomic model was constructed using Cox proportional hazards regression. The performance of the radiomic model was compared with that of traditional fracture assessment tools through a receiver operating characteristic curve, calibration curve, and decision curve analysis. Results: Over a mean follow-up period of 4.72 +/- 1.60 years, 65 participants (9.09%) experienced incident fragility fractures. Seventeen features were ultimately selected to create the radiomic model. The calibration plots of this model demonstrated satisfactory agreement between the observed and predicted outcomes. Moreover, the radiomic model outperformed traditional fracture assessment tools in both the training and validation cohorts according to the area under the receiver operating characteristic curve and decision curve analysis. Conclusions: The novel radiomic model has demonstrated a more effective prediction of fragility fracture in elderly patients in the early stages of DKDcompared to traditional fracture assessment tools. (c) 2024 AACE. Published by Elsevier Inc. All rights reserved.
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