Evidence mapPaperPMID 41310833Full record

ArticleDiabetology & metabolic syndrome2025

Association between changes in estimated glucose disposal rate and composite kidney outcome in middle-aged and elderly individuals: a national cohort study.

Weiyi Zhou, Guangdong Wang, Yaxin Zhang

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Article in Diabetology & metabolic syndrome, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

3 authors.

Weiyi ZhouGraduate School, Nanjing Medical University, Nanjing, Jiangsu, China.
Guangdong WangDepartment of Respiratory and Critical Care Medicine, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shanxi, China.
Yaxin ZhangDepartment of Neurology, Xiamen Humanity Hospital, Fujian Medical University, 3777 Xianyue Road, Huli District, Xiamen, Fujian, People's Republic of China. yaxin1996@qq.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimTo investigate the association between changes in estimated Glucose Disposal Rate (eGDR) and Composite Kidney Outcome (CKO) among middle-aged and older adults.

methodsThis study examined data from 4,007 individuals in the China Health and Retirement Longitudinal Study (CHARLS). The eGDR was estimated based on waist circumference, HbA1c, and hypertension status. Participants were stratified by cumulative eGDR quartiles and change patterns. The primary outcome was CKO, which included Chronic Kidney Disease (CKD)​ and rapid kidney function decline (RKFD). Logistic regression and restricted cubic spline (RCS) models were employed to assess the relationship between eGDR changes and outcomes, while receiver operating characteristic (ROC) curves evaluated the predictive performance of eGDR. Additionally, the Weighted Quantile Sum (WQS) regression model was used to quantify the contributions of eGDR components.

resultsCumulative eGDR exhibited a linear and inverse relationship with the risk of CKO (OR = 0.96 (0.94 ~ 0.99), P for nonlinear = 0.214), and the greatest cumulative eGDR group (Q4) had a 53% lower risk of CKO than the reference group (OR = 0.47 (0.28 ~ 0.79), P = 0.004). The predictive performance of cumulative eGDR surpassed both baseline eGDR and traditional insulin resistance indices. HbA1c and hypertension were the most influential components in the model.

conclusionLong-term declines in eGDR were significantly associated with an increased risk of CKO. Cumulative eGDR showed enhanced predictive value, underscoring its promise as a biomarker for early CKD risk assessment.

Indexed as

CHARLSChronic kidney diseaseEstimated glucose disposal rateInsulin resistance

Identifiers

PMID41310833
PMCPMC12866008

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.