Association between the triglyceride-glucose index and all-cause mortality in critically ill patients with acute kidney injury

Background: The triglyceride-glucose (TyG) Index is a reliable alternative biomarker of insulin resistance, but the association between the TyG Index and acute kidney injury(AKI) in critically ill patients remains unclear. Methods: The data for the study was extracted from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Cox regression and restricted cubic spline(RCS) analysis were performed to analyze the association between the TyG index and all cause mortality. Besides, cox regression was carried out in subgroups of age, gender, BMI, diabetes history and dialysis status. Results: A total of 7508 critically ill participants with AKI from the MIMIC-IV database were included in study, with 3688(49.12%) participants failed to survive. In cox regression, after confounder adjustment, patients with a higher TyG Index had a higher risk of all cause mortality (HR = 1.845, 95% CI =1.49-2.285, p <0.001). In RCS, after confounder adjustment, the risk of death was positively correlated with the increased value of the TyG index when TyG index surpassed 10.014. This relationship was validated in age, gender, BMI and diabetes subgroups but not in the dialysis subgroup. Interestingly, RCS analysis demonstrated that, in patients undertaking dialysis, there is a “U” shape curve for the value of TyG index and risk of all cause mortality. When TyG index is less than 10.460, the risk of all cause mortality would decrease with the increase value of TyG index, while when TyG index is higher than 11.180, the risk of all cause mortality would increase firmly with the increase value of TyG index. Conclusion: Overall, higher TyG index is associated with higher risk of all-cause mortality in critically ill AKI. Interestingly, the relationship in dialysis subgroup follows a "U"-shaped curve, indicating the importance of a properly clinical blood glucose and lipid management of this particular population.