Journal of cardiothoracic surgery · 2025
The application of the triglyceride-glucose-body mass index (TyG-BMI) in predicting acute kidney injury in diabetic patients following coronary artery bypass grafting surgery.
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Li Chen, Liu Xiaobin, Lv Xingping, Zhou Wei, Fan Guoliang, Zhu Feng
Аннотация
BACKGROUND: The triglyceride-glucose-body mass index (TyG-BMI), a marker for insulin resistance, is recognized for its predictive role in cardiovascular and metabolic diseases, including kidney disease. we explored the TyG-BMI index's association with postoperative kidney injury in coronary artery bypass grafting (CABG) patients, who are at an elevated risk for such complications, underscoring its potential as a predictor for acute kidney injury (AKI).
METHODS: This single-center, retrospective study included 126 patients. Patients were divided into AKI and non-AKI groups postoperatively according to the KDIGO classification criteria. Univariate logistic regression was used to screen for variables with significant differences (P < 0.01), and multiple multivariate regression models were constructed to analyze independent risk factors in the multivariate regression model and to analyze the value of TyG-BMI in predicting AKI in diabetic patients after CABG.
RESULTS: Compared to the non-AKI group, the AKI group had statistically significant differences in preoperative fasting triglycerides, preoperative fasting glucose, preoperative and postoperative creatinine levels, ICU stay duration, and TyG-BMI levels (P < 0.05). Based on the results of univariate regression analysis, a multivariate logistic regression model A was constructed using all significant variables, and a multivariate logistic regression model 2 was constructed using significant variables other than TyG-BMI. ROC analysis showed that model 2 had better predictive performance than model 1 (AUC = 0.836 vs. 0.766). A positive correlation was observed between TyG-BMI and AKI occurrence (Spearman's correlation coefficient: R = 0.33, P = 0.00019).
CONCLUSION: Elevated TyG-BMI levels are closely associated with AKI in diabetic patients after CABG. TyG-BMI has potentially predictive value for AKI in diabetic patients after CABG and may play a crucial role in risk stratification in clinical practice.
METHODS: This single-center, retrospective study included 126 patients. Patients were divided into AKI and non-AKI groups postoperatively according to the KDIGO classification criteria. Univariate logistic regression was used to screen for variables with significant differences (P < 0.01), and multiple multivariate regression models were constructed to analyze independent risk factors in the multivariate regression model and to analyze the value of TyG-BMI in predicting AKI in diabetic patients after CABG.
RESULTS: Compared to the non-AKI group, the AKI group had statistically significant differences in preoperative fasting triglycerides, preoperative fasting glucose, preoperative and postoperative creatinine levels, ICU stay duration, and TyG-BMI levels (P < 0.05). Based on the results of univariate regression analysis, a multivariate logistic regression model A was constructed using all significant variables, and a multivariate logistic regression model 2 was constructed using significant variables other than TyG-BMI. ROC analysis showed that model 2 had better predictive performance than model 1 (AUC = 0.836 vs. 0.766). A positive correlation was observed between TyG-BMI and AKI occurrence (Spearman's correlation coefficient: R = 0.33, P = 0.00019).
CONCLUSION: Elevated TyG-BMI levels are closely associated with AKI in diabetic patients after CABG. TyG-BMI has potentially predictive value for AKI in diabetic patients after CABG and may play a crucial role in risk stratification in clinical practice.