ORIGINAL RESEARCH article
Front. Endocrinol.
Sec. Renal Endocrinology
Volume 16 - 2025 | doi: 10.3389/fendo.2025.1561228
This article is part of the Research TopicIs Insulin Resistance the Eminence Grise of Aging and Non-Communicable Chronic Diseases?View all 8 articles
Association between triglyceride glucose-body mass index and acute kidney injury and renal replacement therapy in critically ill patients with sepsis: analysis of the MIMIC-IV database
Provisionally accepted
- Nanjing University, Nanjing, China
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Background: Previous studies have linked kidney damage to insulin resistance (IR), yet the association between triglyceride glucose-body mass (TyG-BMI) index, a reliable marker of IR, and acute kidney injury (AKI) remains unclear.Methods: Patient data were collected from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. AKI was set as the primary endpoint and renal replacement therapy (RRT) was set as the secondary endpoint to represent the progression of AKI. TyG-BMI index and study endpoints were analyzed using cox regression and restricted cubic spline (RCS) analyses.Results: 1,117 patients with sepsis were enrolled, of whom 559 (50.0%) developed AKI. Cox regression revealed that TyG-BMI index was closely related to AKI (P = 0.032), and RCS analysis depicted a nonlinear correlation (P for nonlinear = 0.013). For RRT, similar results were observed. Compared with the simple severity of illness scores (SOFA, APSIII, SAPSII, and SIRS), when combined with the TyG-BMI index, their predictive ability for sepsis-related AKI significantly increased (AUCs: 0.745, 0.732, 0.708 and 0.566 vs 0.756, 0.747, 0.728 and 0.661; all P < 0.05).For critically ill patients with sepsis, an elevated TyG-BMI index implies a possible increased risk of AKI. TyG-BMI index has the potential to be a valuable predictor.
Keywords: Acute Kidney Injury, Sepsis, Triglyceride glucose-body mass index, predictor, Insulin Resistance
Received: 15 Jan 2025; Accepted: 26 Jun 2025.
Copyright: © 2025 Wang, Wang, Li, Zhang and Xie. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Xinying Wang, Nanjing University, Nanjing, China
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