Evidence Hub

Joint association of estimated glucose disposal rate and systemic inflammation response index with mortality in cardiovascular-kidney-metabolic syndrome stage 0–3: a nationwide prospective cohort study

Yuwen Chen, Wenbin Lian, Lun-Zhe Wu, An’an Huang, De-Lian Zhang, Bingchen Liu, Yuangang Qiu, Qu-Cheng Wei

Cardiovascular Diabetology, 2025

18,295 participants · 53 citations

Abstract

The Cardiovascular-Kidney-Metabolic (CKM) syndrome underscores the complex interactions among metabolic disorders, kidney disease, and cardiovascular conditions. Insulin resistance (IR) and inflammation are crucial in CKM syndrome development, but their combined effect in stages 0–3 remains unclear. Using data from the National Health and Nutrition Examination Survey (NHANES), we included 18,295 participants with CKM syndrome stages 0–3 from 10 cycles between 1999 and 2018. IR was assessed using the estimated glucose disposal rate (eGDR), and systemic inflammation was evaluated using the Systemic Inflammation Response Index (SIRI). The primary endpoint was all-cause mortality, and the secondary endpoint was cardiovascular disease (CVD) mortality. Over an average follow-up period of 121 months, we recorded 1,998 all-cause deaths and 539 CVD deaths. Both eGDR and SIRI were independent risk factors for mortality. The hazard ratios (HR) for eGDR were 0.90 (0.86, 0.94) for all-cause mortality and 0.85 (0.78, 0.93) for CVD mortality, per unit increase in eGDR. For SIRI, the HRs were 1.16 (1.11, 1.21) for all-cause mortality and 1.33 (1.19, 1.46) for CVD mortality, per unit increase in SIRI. Compared to individuals with high eGDR and low SIRI levels, those with low eGDR and high SIRI levels exhibited significantly higher mortality risks, with HRs of 1.97 (1.58, 2.44) for all-cause mortality and 2.35 (1.48, 3.73) for CVD mortality. Subgroup analysis revealed that the combined impact…

Read the paper

Related studies

Go deeper in Evidence Hub

Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.

Open this study Sign up free