Comparison of TyG and Newly TyG Related Indicators for Chronic Kidney Diseases Estimation in a Chinese Population

Tong Chen,1– 4 Yu Liu,2,3 Shiquan Wu,2 Siyu Long,2 Ling Feng,4,5 Wenqian Lu,6 Wenya Chen,2 Guoai Hong,2 Li Zhou,2 Fang Wang,2 Yuechan Luo,2 Hequn Zou,2,4,6 Weihua Liu7 1Department of Nephrology, Chongqing Key Laboratory of Prevention and Treatment of Kidney Disease, Chongqing Clinical Research Center of Kidney and Urology Diseases, Xinqiao Hospital, Army Medical University (Third Military Medical University), Chongqing, 400037, People’s Republic of China; 2South China Hospital of Shenzhen University, Shenzhen, 518116, People’s Republic of China; 3Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, National Regional Key Technology Engineering Laboratory for Medical Ultrasound School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen, 518060, People’s Republic of China; 4Department of Nephrology, The Third Affiliated Hospital, Southern Medical University, Guangzhou, People’s Republic of China; 5Department of Nephrology, Shenzhen Hospital, Southern Medical University, Shenzhen, People’s Republic of China; 6School of Medicine, The Chinese University of Hong Kong, Shenzhen, People’s Republic of China; 7Department Nephrology of Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fujian, 350001, People’s Republic of ChinaCorrespondence: Weihua Liu, Department Nephrology of Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fujian, 350001, People’s Republic of China, Email lwh10280465@163.com Hequn Zou, School of Medicine, The Chinese University of Hong Kong, Shenzhen, People’s Republic of China, Email zouhequn@cuhk.edu.cnBackground: Obesity and insulin resistance (IR) are positively associated with chronic kidney disease (CKD). Previous studies have identified triglyceride-glucose index (TyG) as a valuable surrogate of insulin resistance. Recently, new indicators combining TyG and simple anthropometric indices have emerged, The objective of this study was to assess the diagnostic accuracy of TyG and newly TyG related indicators in detecting CKD and explore which indices were superior in associating with CKD in Chinese population.Methods: Correlation test, logistic regression analysis, and receiver operating characteristic (ROC) analyses were used to evaluate the optimal cut-off and value of TyG, TyG-body mass index (TyG-BMI), TyG-waist circumference (TyG-WC), TyG-waist to height ratio (TyG-WHtR) for predicting CKD.Results: TyG-WHtR, TyG-WC, and TyG-BMI correlated with several risk factors for CKD. After adjusting for confounders, TyG-WHtR and TyG-WC remained significantly associated with CKD, while TyG-BMI did not. The highest quartiles of TyG-WHtR and TyG-WC had 1.95- and 1.91-fold increased risk of CKD than the lowest quartiles (P< 0.05). TyG-WHtR had the largest AUC (0.687) for CKD detection, followed by TyG-WC (0.669), TyG (0.652), and TyG-BMI (0.648). A united model that involved TyG-WHtR and other risk variables had higher predictive performance (AUC=0.791) than a single TyG related indicator. However, TyG had the highest OR (2.713, 95% CI, 1.446– 5.090) for reduced eGFR in the fully adjusted model. A united model that involved TyG and WHtR separately had stronger predictive ability (AUC: 0.794) than the model that involved TyG-WHtR individually (AUC:0.791).Conclusion: This study found that TyG-WHtR had a better diagnostic value in the diagnosis of CKD, compared to other TyG related indicators, but none of the TyG related indicators showed a stronger association with CKD than TyG. Further research and more refined algorithms are needed to verify these new indicators.Keywords: chronic kidney disease, insulin resistance, obesity, TyG related indicators