- Complications
- Screening Tools Based on Nomogram for Diabetic Kidney Diseases in Chinese Type 2 Diabetes Mellitus Patients
-
Ganyi Wang, Biyao Wang, Gaoxing Qiao, Hao Lou, Fei Xu, Zhan Chen, Shiwei Chen
-
Diabetes Metab J. 2021;45(5):708-718. Published online April 13, 2021
-
DOI: https://doi.org/10.4093/dmj.2020.0117
-
-
8,038
View
-
152
Download
-
8
Web of Science
-
8
Crossref
-
Graphical Abstract
Abstract
PDFSupplementary MaterialPubReader ePub
- Background
The influencing factors of diabetic kidney disease (DKD) in Chinese patients with type 2 diabetes mellitus (T2DM) were explored to develop and validate a DKD diagnostic tool based on nomogram approach for patients with T2DM.
Methods A total of 2,163 in-hospital patients with diabetes diagnosed from March 2015 to March 2017 were enrolled. Specified logistic regression models were used to screen the factors and establish four different diagnostic tools based on nomogram according to the final included variables. Discrimination and calibration were used to assess the performance of screening tools.
Results Among the 2,163 participants with diabetes (1,227 men and 949 women), 313 patients (194 men and 120 women) were diagnosed with DKD. Four different screening equations (full model, laboratory-based model 1 [LBM1], laboratory-based model 2 [LBM2], and simplified model) showed good discriminations and calibrations. The C-indexes were 0.8450 (95% confidence interval [CI], 0.8202 to 0.8690) for full model, 0.8149 (95% CI, 0.7892 to 0.8405) for LBM1, 0.8171 (95% CI, 0.7912 to 0.8430) for LBM2, and 0.8083 (95% CI, 0.7824 to 0.8342) for simplified model. According to Hosmer-Lemeshow goodness-of-fit test, good agreement between the predicted and observed DKD events in patients with diabetes was observed for full model (χ2=3.2756, P=0.9159), LBM1 (χ2=7.749, P=0.4584), LBM2 (χ2=10.023, P=0.2634), and simplified model (χ2=12.294, P=0.1387).
Conclusion LBM1, LBM2, and simplified model exhibited excellent predictive performance and availability and could be recommended for screening DKD cases among Chinese patients with diabetes.
-
Citations
Citations to this article as recorded by
- Developing screening tools to estimate the risk of diabetic kidney disease in patients with type 2 diabetes mellitus
Xu Cao, Xiaomei Pei Technology and Health Care.2024; 32(3): 1807. CrossRef - Development of Serum Lactate Level-Based Nomograms for Predicting Diabetic Kidney Disease in Type 2 Diabetes Mellitus Patients
Chunxia Jiang, Xiumei Ma, Jiao Chen, Yan Zeng, Man Guo, Xiaozhen Tan, Yuping Wang, Peng Wang, Pijun Yan, Yi Lei, Yang Long, Betty Yuen Kwan Law, Yong Xu Diabetes, Metabolic Syndrome and Obesity.2024; Volume 17: 1051. CrossRef - Two-Dimensional Ultrasound-Based Radiomics Nomogram for Diabetic Kidney Disease: A Pilot Study
Xingyue Huang, Yugang Hu, Yao Zhang, Qing Zhou International Journal of General Medicine.2024; Volume 17: 1877. CrossRef - Risk prediction models for diabetic nephropathy among type 2 diabetes patients in China: a systematic review and meta-analysis
Wenbin Xu, Yanfei Zhou, Qian Jiang, Yiqian Fang, Qian Yang Frontiers in Endocrinology.2024;[Epub] CrossRef - Changes in urinary exosomal protein CALM1 may serve as an early noninvasive biomarker for diagnosing diabetic kidney disease
Tao Li, Tian ci Liu, Na Liu, Man Zhang Clinica Chimica Acta.2023; 547: 117466. CrossRef - Development and validation of a novel nomogram to predict diabetic kidney disease in patients with type 2 diabetic mellitus and proteinuric kidney disease
Hui Zhuan Tan, Jason Chon Jun Choo, Stephanie Fook-Chong, Yok Mooi Chin, Choong Meng Chan, Chieh Suai Tan, Keng Thye Woo, Jia Liang Kwek International Urology and Nephrology.2022; 55(1): 191. CrossRef - Nomogram-Based Chronic Kidney Disease Prediction Model for Type 1 Diabetes Mellitus Patients Using Routine Pathological Data
Nakib Hayat Chowdhury, Mamun Bin Ibne Reaz, Sawal Hamid Md Ali, Shamim Ahmad, María Liz Crespo, Andrés Cicuttin, Fahmida Haque, Ahmad Ashrif A. Bakar, Mohammad Arif Sobhan Bhuiyan Journal of Personalized Medicine.2022; 12(9): 1507. CrossRef - Development and assessment of diabetic nephropathy prediction model using hub genes identified by weighted correlation network analysis
Xuelian Zhang, Yao Wang, Zhaojun Yang, Xiaoping Chen, Jinping Zhang, Xin Wang, Xian Jin, Lili Wu, Xiaoyan Xing, Wenying Yang, Bo Zhang Aging.2022; 14(19): 8095. CrossRef
|