Abstract
BackgroundAcute kidney injury (AKI) is a major global health concern, particularly in individuals with diabetes or prediabetes. While insulin resistance (IR) is implicated in AKI pathogenesis, the relationship between comprehensive IR measures - particularly the estimated glucose disposal rate (eGDR) - and AKI risk remains unclear.MethodsThis prospective cohort study analyzed 60,149 UK Biobank participants with diabetes or prediabetes. eGDR was calculated using waist circumference, hypertension status, and HbA1c. The primary outcome was incident AKI. Multivariable Cox models assessed the eGDR-AKI risk relationship. Predictive performance was compared against conventional IR indices using C-index, net reclassification improvement (NRI), and integrated discrimination improvement (IDI).ResultsOver a median follow-up duration of 13.4 years, 6,259 participants developed AKI. Higher eGDR showed a strong inverse association with AKI risk (per SD increment, adjusted HR: 0.64; 95%CI: 0.61-0.66), with a 62% lower risk in the highest vs. lowest quartile (adjusted HR: 0.38, 95%CI: 0.34-0.43). The eGDR showed superior discriminative ability (C-index 0.709, 95%CI: 0.702-0.715) compared to other IR indices - including the triglyceride-glucose index (TyG, 0.665, 0.658-0.672), TyG-waist circumference (0.693, 0.686-0.700), triglyceride-to-HDL cholesterol ratio (0.661, 0.654-0.668), C-reactive protein-triglyceride-glucose index (0.679, 0.672-0.686), single-point insulin sensitivity estimator index (SPISE, 0.680, 0.673-0.687), metabolic score for insulin resistance (METS-IR, 0.694, 0.687-0.700), and lipid accumulation product (LAP, 0.669, 0.662-0.676) - while also demonstrating clinically meaningful improvements in risk reclassification (NRI 0.063-0.196; IDI 0.003-0.018).ConclusionLower eGDR, indicating severe IR, independently predicts higher AKI risk in dysglycemic individuals. As a composite measure integrating metabolic and vascular components, eGDR outperforms conventional IR indices in AKI risk stratification, suggesting its clinical utility for identifying high-risk patients who may benefit from targeted interventions.</p>