# Triglyceride-glucose-body mass index predicts early-onset acute kidney injury in critically ill patients: a retrospective analysis using the MIMIC-IV database

## TL;DR

A new study finds that a metabolic marker called TyG-BMI can predict early-onset kidney injury in critically ill patients.

## Contribution

The study introduces TyG-BMI as a novel predictor of acute kidney injury in ICU patients and identifies an optimal cutoff for risk stratification.

## Key findings

- Higher TyG-BMI values are associated with increased risk of early-onset acute kidney injury.
- The optimal TyG-BMI cutoff for risk stratification is 252.50.
- Adding TyG-BMI to traditional models improves prediction accuracy for acute kidney injury.

## Abstract

Acute kidney injury (AKI) is a common and serious complication in critically ill patients, with metabolic dysfunction playing a crucial role in its pathogenesis. The triglyceride-glucose-body mass index (TyG-BMI) has emerged as a novel marker of insulin resistance and metabolic health. However, the relationship between TyG-BMI and early-onset AKI in critically ill patients remains unclear. The aim of this study was to evaluate the association between TyG-BMI and early-onset AKI in critically ill patients, and identify optimal cutoff thresholds for risk stratification.

This retrospective study analyzed 4,024 critically ill adults from the MIMIC-IV database. Patients were stratified according to TyG-BMI quartiles. Cox proportional hazards models, restricted cubic splines (RCS), and receiver operating characteristic (ROC) analyses were employed to examine associations between TyG-BMI and early-onset AKI. Optimal cutoff values were determined using the Youden index, while net reclassification improvement (NRI) assessed incremental predictive value.

Early-onset AKI developed in 2,535 patients (63.0%). Multivariable-adjusted hazard ratios increased across TyG-BMI quartiles, with the highest quartile showing significantly increased risk compared to the lowest (HR 1.40, 95% CI: 1.25–1.58). Risk increased approximately linearly when TyG-BMI exceeded 261.84. The optimal cutoff value was 252.50 (sensitivity 0.604, specificity 0.648). Adding TyG-BMI to traditional risk models improved prediction (NRI = 0.141, 95% CI: 0.024–0.207). Associations were stronger among males, younger patients, those with preserved eGFR, and patients with diabetes or sepsis.

Triglyceride-glucose-body mass index independently predicts early-onset AKI in critically ill patients. The threshold of 252.50 offers a reliable reference for risk stratification in ICU settings.