ArticleLipids in health and disease2025
Comparing the impact of cumulative insulin resistance surrogates exposure on stroke: optimizing prevention strategies.
Article in Lipids in health and disease, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Predicting Stroke Incidence Using Estimated Glucose Disposal Rate Index in the Population with Cardiovascular-Kidney-Metabolic Syndrome Stage 0-3 in the Chinese Middle-Aged and Elderly Population.Cardiorenal medicine · 2026Observational
- Changes in the estimated glucose disposal rate and incident cardiovascular disease in patients with cardiovascular-kidney-metabolic syndrome stages 0-3: a prospective cohort study in China.BMC cardiovascular disorders · 2025Article
- Evaluation of four insulin resistance surrogate indicators for predicting short-term mortality in critically ill patients with ischemic stroke: a nationwide retrospective cohort study.Cardiovascular diabetology · 2025Article
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6 authors.
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Abstract
backgroundInsulin resistance (IR) plays a major role in increasing the risk of stroke. The objective of this research is to systematically evaluate and compare the impact of cumulative exposure over time to four commonly used IR surrogates-triglyceride-glucose (CumTyG) index, metabolic score for IR (CumMetS-IR), estimated glucose disposal rate (CumeGDR) and triglyceride to high-density lipoprotein cholesterol (CumTG/HDL-C) ratio-on stroke risk, providing insights for optimizing monitoring strategies for primary stroke prevention.
methodsThe study population was sourced from the China Health and Retirement Longitudinal Study (CHARLS2011-2018). Cumulative exposure to IR (CumIR) surrogates was calculated as the mean value of IR surrogates measured in the first and third waves of CHARLS, multiplied by the total exposure duration. The primary endpoint was incident stroke, determined through questionnaires in the third and fourth waves of CHARLS. Multivariable Cox regression models were applied to estimate and compare HRs and 95% CIs for stroke across quartiles of CumIR surrogates.
resultsA total of 4,669 participants with no history of stroke at baseline were included. During a median follow-up of 6 years, 347 new stroke events (7.43%) were recorded. The incidence rates of stroke in the highest quartiles of CumTyG index, CumTG/HDL-C ratio, and CumMetS-IR, as well as the lowest quartile of CumeGDR, were 9.67%, 9.93%, 10.45%, and 13.02%, respectively. In terms of risk assessment, the multivariable Cox regression analysis showed that the highest quartiles of CumTyG index, CumTG/HDL-C ratio, and CumMetS-IR and the lowest quartile of CumeGDR were associated with stroke risk, with corresponding HR (95% CI) of 1.48(1.05-2.10), 1.61(1.15-2.24), 1.72(1.21-2.43), and 3.57(2.25-5.68), respectively. In terms of event prediction, receiver operating characteristic analysis revealed that CumeGDR had the highest predictive accuracy for incident stroke compared with other common IR surrogates.
conclusionsIn assessing stroke risk and predicting events in middle-aged and elderly populations, cumulative exposure to eGDR demonstrates significant advantages over other common IR surrogates. Incorporating eGDR as an IR monitoring marker is recommended for primary stroke prevention.
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