Evidence mapPaperPMID 41184346Full record

ArticleScientific reports2025

Age Stratified Analyses of TyG Index eGDR and Additive Effects on T2DM Outcomes in Prevalence and Mortality.

Xueyan Li, Jiwei Lin, Desheng Wang, Lei Su, Jialin He, Shaofeng Wei, Xueyun Li

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

1 citing paper in PubMed.

  1. Article
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.

Xueyan Li *The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of, Education, Guizhou Provincial Engineering Research Center of Ecological Food Innovation, Collaborative Innovation Center for Prevention and Control of Endemic and Ethnic Regional Diseases Co-Constructed By the Province and Ministry, School of Public Health, Guizhou Medical University, Guiyang, 561113, China.
Jiwei Lin *The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of, Education, Guizhou Provincial Engineering Research Center of Ecological Food Innovation, Collaborative Innovation Center for Prevention and Control of Endemic and Ethnic Regional Diseases Co-Constructed By the Province and Ministry, School of Public Health, Guizhou Medical University, Guiyang, 561113, China.
Desheng WangThe Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of, Education, Guizhou Provincial Engineering Research Center of Ecological Food Innovation, Collaborative Innovation Center for Prevention and Control of Endemic and Ethnic Regional Diseases Co-Constructed By the Province and Ministry, School of Public Health, Guizhou Medical University, Guiyang, 561113, China.
Lei SuDepartment of Chronic Non-Communicable Disease Prevention and Control, Huangpu District Center for Disease Control and Prevention of Guangzhou (Huangpu District Health Supervision Institute of Guangzhou), Guangzhou, Guangdong, China.
Jialin HeDepartment of Nutrition, Guangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health, Sun Yat-Sen University (Northern Campus), Guangzhou, Guangdong Province, China.
Shaofeng WeiThe Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of, Education, Guizhou Provincial Engineering Research Center of Ecological Food Innovation, Collaborative Innovation Center for Prevention and Control of Endemic and Ethnic Regional Diseases Co-Constructed By the Province and Ministry, School of Public Health, Guizhou Medical University, Guiyang, 561113, China. weishaofeng@gmc.edu.cn.
Xueyun LiDepartment of Healthcare-Associated Infection Management, Guizhou Provincial People's Hospital, Guiyang, 550000, People's Republic of China. lixy378@alumni.sysu.edu.cn.

Funding

High-level talent start-up fund NO. 2022071Science and Technology Fund of Guizhou Provincial Health Commission NO. gzwkj2025-507
6 · The paper itself

Abstract

Although the triglyceride-glucose (TyG) index and estimated glucose disposal rate (eGDR) have emerged as potential biomarkers, the age-specific predictive value of these markers for diabetes progression and long-term outcomes has not been clearly established. We sought to quantify the associations of TyG and eGDR with T2DM incident and all-cause mortality, and further examine whether these associations vary by age. In this cross-sectional and cohort study, a total of 15,457 eligible participants was included, among whom 2,328 had type 2 diabetes mellitus, participants were stratified into two age groups: Young (< 65 years) and old (≥ 65 years) adults. Logistic regression models to evaluate the associations between TyG index, eGDR index and their additive effect with the risk of type 2 diabetes incidence, Kaplan–Meier survival analysis and Cox proportional hazards regression models were utilized to assess the relationships between TyG/eGDR indices and all-cause mortality. TyG index was significantly positively correlated with the risk of type 2 diabetes across different ages. eGDR showed a significant inverse association with type 2 diabetes risk. High TyG and low eGDR were associated with the highest risk of type 2 diabetes. The restricted cubic spline analysis revealed a U-shaped relationship between TyG index and all-cause mortality, a L-shaped curve relationships between eGDR and all-cause mortality in the total and young type 2 diabetes, no significant association was found in the old type 2 diabetes subgroup. The High TyG and low eGDR demonstrated the highest risk of all-cause mortality in the younger type 2 diabetes, but no additive effect was observed in the older type 2 diabetes. TyG and eGDR positively correlated with the risk of type 2 diabetes, and the combination of TyG and eGDR indices improved the identification of the risk and adverse outcome of diabetes, whereas their association with mortality of type 2 diabetes is not significant in the elderly population even in an additive model.

Indexed as

Blood GlucoseDiabetes Mellitus, Type 2TriglyceridesAgedAge FactorsBiomarkersCross-Sectional StudiesFemaleHumansMaleMiddle AgedPrevalenceRisk FactorsBiomarkersBlood GlucoseTriglyceridesDifferent ageEstimated glucose disposal rateTriglyceride-glucose indexType 2 diabetes

Identifiers

PMID41184346
PMCPMC12583825

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.