Evidence map›Paper›PMID 39806389›Full record

ArticleCardiovascular diabetology2025

Association between estimated glucose disposal rate and cardiovascular diseases in patients with diabetes or prediabetes: a cross-sectional study.

Jinhao Liao, Linjie Wang, Lian Duan, Fengying Gong, Huijuan Zhu, Hui Pan, Hongbo Yang

Abstract read
In one paragraph

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 59 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
59citing papers in PubMed, 1 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

59 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Association between metal co-exposure and frailty: exploring the potential explanatory pathway of inflammation.Biometals : an international journal on the role of metal ions in biology, biochemistry, and medicine · 2026
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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

7 authors.

Jinhao LiaoKey Laboratory of Endocrinology of National Health Commission, Department of Endocrinology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, No. 1 Shuaifuyuan, Dongcheng District, Beijing, 100730, China.
Linjie WangKey Laboratory of Endocrinology of National Health Commission, Department of Endocrinology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, No. 1 Shuaifuyuan, Dongcheng District, Beijing, 100730, China.
Lian DuanKey Laboratory of Endocrinology of National Health Commission, Department of Endocrinology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, No. 1 Shuaifuyuan, Dongcheng District, Beijing, 100730, China.
Fengying GongKey Laboratory of Endocrinology of National Health Commission, Department of Endocrinology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, No. 1 Shuaifuyuan, Dongcheng District, Beijing, 100730, China.
Huijuan ZhuKey Laboratory of Endocrinology of National Health Commission, Department of Endocrinology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, No. 1 Shuaifuyuan, Dongcheng District, Beijing, 100730, China.
Hui PanKey Laboratory of Endocrinology of National Health Commission, Department of Endocrinology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, No. 1 Shuaifuyuan, Dongcheng District, Beijing, 100730, China.
Hongbo YangKey Laboratory of Endocrinology of National Health Commission, Department of Endocrinology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, No. 1 Shuaifuyuan, Dongcheng District, Beijing, 100730, China. yanghb@pumch.cn.ORCID 0000-0003-2985-8265

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundInsulin resistance proxy indicators are significantly associated with cardiovascular disease (CVD) and diabetes. However, the correlations between the estimated glucose disposal rate (eGDR) index and CVD and its subtypes have yet to be thoroughly researched.

methods10,690 respondents with diabetes and prediabetes from the NHANES 1999-2016 were enrolled in the study. Three machine learning methods (SVM-RFE, XGBoost, and Boruta algorithms) were employed to select the most critical variables. Logistic regression models were established to evaluate the association between eGDR and CVD. We applied ROC curves, C-statistics, NRI, IDI, calibration curves, and DCA curves to assess model performance. Subgroup analyses were conducted to investigate the association among different subgroups.

resultsParticipants in the higher quartile showed a decreased prevalence of CVD. Multivariate logistic regression models and RCS curves demonstrated that eGDR had an independently negative linear correlation with the likelihood of CVD[Q4 vs. Q1: OR 0.24(0.18,0.32)], CAD[OR 0.81(0.78,0.85)], CHF[OR 0.81(0.76,0.86)], and stroke[0.85(0.80,0.90)]. Model evaluation showed better performance in fully adjusted models than basic models[C-statistics(Model 3 vs. Model 1): CVD(0.683 vs. 0.814), CAD(0.672 vs. 0.807), CHF(0.714 vs. 0.839) and stroke(0.660 vs. 0.790)]. The AUCs of eGDR were significantly higher than the values of other IR surrogates in the unadjusted models, and slightly higher in the fully adjusted models. Subgroup analyses indicated that the results were robust.

conclusionA lower eGDR was significantly associated with a heightened likelihood of CVD and its subtypes in diabetic and prediabetic populations. And eGDR exhibited better performance in evaluating the associations compared to other IR proxies encompassing TyG, HOMA-IR, QCUIKI, METS-IR, etc.

Indexed as

Blood GlucoseCardiovascular DiseasesDiabetes MellitusInsulin ResistancePrediabetic StateAdultAgedBiomarkersCross-Sectional StudiesFemaleHumansMachine LearningMaleMiddle AgedNutrition SurveysPredictive Value of TestsBiomarkersBlood GlucoseCardiovascular diseaseDiabetesEstimated glucose disposal rateInsulin resistancePrediabetes

Identifiers

PMID39806389
PMCPMC11730478

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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 OpenQuestion graph.