Evidence map›Paper›PMID 42827523›Full record

ArticleFrontiers in endocrinology2026

Association between glycometabolic indicators and risk of early vascular aging and their predictive value.

Jinjin Wang, Yujiao Yang, Ruoling Teng, Yi Ding, Fenfen Liu

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In one paragraph

Article in Frontiers in endocrinology, 2026. 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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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Jinjin WangDepartment of Geriatrics, Mengcheng Second Peoples Hospital, Bozhou, China.
Yujiao YangDepartment of Geriatrics, The Third Affiliated Hospital of Soochow University, Changzhou, China.
Ruoling TengDepartment of Geriatrics, The Third Affiliated Hospital of Soochow University, Changzhou, China.
Yi DingDepartment of Geriatrics, The Third Affiliated Hospital of Soochow University, Changzhou, China.
Fenfen LiuDepartment of Geriatrics, The Third Affiliated Hospital of Soochow University, Changzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Early vascular aging (EVA) elevates cardiovascular risk, and glycometabolic dysfunction is closely associated with arterial stiffness. Seven markers including TyG, CHG and HOMA-series indices were compared to explore their independent correlations and discriminative value for prevalent EVA among physical examinees. Methods: This retrospective cross-sectional study enrolled 555 participants who underwent baPWV testing, identified from routine health-check records. Baseline data, biochemical indicators and seven glycometabolic indices were collected. Logistic regression, Spearman correlation and ROC analyses were performed to assess associations and diagnostic performance. Results: Totally 156 participants had prevalent EVA. All seven glycometabolic markers were independently associated with prevalent EVA after confounding adjustment. The CHG index showed strong correlation with mean baPWV (r=0.402, P<0.001). ROC analysis indicated modest discriminative performance for prevalent EVA across all markers; HbA1c yielded the highest observed AUC (0.690), while the TyG index achieved the highest observed discriminative sensitivity (70.51%). Conclusions: In this retrospective cross-sectional study, all seven glycometabolic indicators were independently associated with prevalent EVA and showed modest discriminative capacity for prevalent EVA within the study sample. The TyG index exhibited the highest observed discriminative sensitivity, while HbA1c showed the highest observed AUC. These two indices may be considered potential low-cost auxiliary markers for identifying prevalent EVA in health-check settings; bootstrap internal validation and prospective external validation are required before broad clinical application.

Indexed as

AgingBiomarkersBlood GlucoseCardiovascular DiseasesVascular StiffnessAgedCross-Sectional StudiesFemaleGlycated HemoglobinHumansMaleMiddle AgedPredictive Value of TestsRetrospective StudiesRisk FactorsBiomarkersBlood GlucoseGlycated Hemoglobinarterial stiffnessearly vascular agingglycometabolisminsulin resistancetriglyceride−glucose index

Identifiers

PMID42827523
PMCPMC13630510

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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.