Evidence mapPaperPMID 40223076Full record

ArticleCardiovascular diabetology2025

Insulin resistance quantified by estimated glucose disposal rate predicts cardiovascular disease incidence: a nationwide prospective cohort study.

Shiyi Tao, Lintong Yu, Jun Li, Ji Wu, Xuanchun Huang, Zicong Xie, Tiantian Xue, Yonghao Li, Lilan Su

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Article in Cardiovascular diabetology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 2 pooled it
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

26 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Shiyi TaoDepartment of Cardiology, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, 100053, China.
Lintong YuGraduate School, Beijing University of Chinese Medicine, Beijing, 100029, China.
Jun LiDepartment of Cardiology, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, 100053, China. gamyylj@163.com.
Ji WuDepartment of Cardiology, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, 100053, China.
Xuanchun HuangDepartment of Cardiology, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, 100053, China.
Zicong XieDepartment of Cardiology, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, 100053, China.
Tiantian XueDepartment of Cardiology, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, 100053, China.
Yonghao LiDepartment of Cardiology, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, 100053, China.
Lilan SuDepartment of Cardiology, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, 100053, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundInsulin resistance (IR) is an important pathologic component in the occurrence and development of cardiovascular disease (CVD). The estimated glucose disposal rate (eGDR) is a measure of glucose handling capacity, that has demonstrated utility as a reliable marker of IR. The study aimed to determine the predictive utility of IR assessed by eGDR for CVD risk.

methodsThis nationwide prospective cohort study utilized data of 6416 participants from the China Health and Retirement Longitudinal Study (CHARLS) who were free of CVD but had complete data on eGDR at baseline. The Boruta algorithm was performed for feature selection. Multivariate Cox proportional hazards regression models and restricted cubic spline (RCS) analysis were conducted to examine the associations between eGDR and CVD, and the results were expressed with hazard ratio (HR) and 95% confidence interval (CI) values. The area under the receiver operating characteristic (ROC) curve (AUC), calibration curve, Hosmer-Lemeshow test, net reclassification improvement (NRI), and decision curve analysis (DCA) were employed to evaluate the clinical efficacy of eGDR in identifying CVD. Subgroup analysis was performed to explore the potential association of with CVD in different populations.

resultsDuring a median follow-up of 106.5 months, 1339 (20.87%) incident CVD cases, including 1025 (15.96%) heart disease and 439 (6.84%) stroke, were recorded from CHARLS. The RCS curves demonstrated a significant and linear relationship between eGDR and all endpoints (all P for nonlinear > 0.05). After multivariate adjustment, the lower eGDR levels were found to be significantly associated with a greater prevalence of CVD. Compared to the lowest quartile, the highest eGDR quartile was associated with a decreased risk of CVD (HR 0.686, 95% CI 0.545-0.862). When assessed as a continuous variable, individuals with a unit increasement in eGDR was related to a 21.2% (HR 0.788, 95% CI 0.669-0.929) lower risk of CVD, a 18.3% (HR 0.817, 95% CI 0.678-0.985) decreased risk of heart disease, and 39.5% (HR 0.705, 95% CI 0.539-0.923) lower risk of stroke. The eGDR had an excellent predictive performance according to the results of ROC (AUC = 0.712) and χ

conclusionA lower level of eGDR was found to be associated with increased risk of incident CVD, suggesting that eGDR may serve as a promising and preferable predictor for CVD.

Indexed as

Blood GlucoseCardiovascular DiseasesInsulinInsulin ResistanceAgedBiomarkersChinaFemaleHumansIncidenceLongitudinal StudiesMaleMiddle AgedPredictive Value of TestsPrognosisProspective StudiesBiomarkersBlood GlucoseInsulinCardiovascular diseaseCHARLSEstimated glucose disposal rateInsulin resistanceRisk factor

Identifiers

PMID40223076
PMCPMC11995552

What Socratic holds

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LicenceCC BY-NC-ND
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Registered trials

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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.