Evidence mapPaperPMID 41816296Full record

ArticleiScience2026

TyG and RC combined with CVD risk in CKM syndrome: A national cohort study.

Hongtao Lan, Xu Jia, Zheng Zhao, Ruolan Chen, Banghui Wang, Changan Qu, Xianming Chu

Abstract read
In one paragraph

Article in iScience, 2026. 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.

Hongtao LanDepartment of Cardiology, The Affiliated Hospital of Qingdao University, No. 59 Haier Road, Qingdao 266100, China.
Xu JiaDepartment of Geriatric Medicine & Laboratory of Gerontology and Anti-Aging Research, Qilu Hospital of Shandong University, Jinan 250012, China.
Zheng ZhaoDepartment of Cardiology, The Affiliated Hospital of Qingdao University, No. 59 Haier Road, Qingdao 266100, China.
Ruolan ChenDepartment of Cardiology, The Affiliated Hospital of Qingdao University, No. 59 Haier Road, Qingdao 266100, China.
Banghui WangDepartment of Cardiology, The Affiliated Hospital of Qingdao University, No. 59 Haier Road, Qingdao 266100, China.
Changan QuDepartment of Cardiology, The Affiliated Hospital of Qingdao University, No. 59 Haier Road, Qingdao 266100, China.
Xianming ChuDepartment of Cardiology, The Affiliated Hospital of Qingdao University, No. 59 Haier Road, Qingdao 266100, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although the triglyceride-glucose index (TyG, insulin resistance) and remnant cholesterol (RC, lipid metabolism) are cardiovascular disease (CVD) risk factors in cardiovascular-kidney-metabolic (CKM) syndrome, their joint predictive power warrants further investigation. We utilized data from the China Health and Retirement Longitudinal Study (2020). Using participants with low TyG (<8.3) and low RC (<13.9) as the reference, individuals with both high TyG and high RC showed significantly elevated CVD risk. Over a median follow-up of 9.0 years, 1744 participants (23.2%) in CKM Stages 0-3 developed CVD. Participants with both high TyG and high RC had the highest risk (HR = 1.35). The TyG-RC index was created by multiplying TyG and RC. Each 1-SD increase in TyG-RC was associated with higher CVD risk, exhibiting an inverse J-shaped relationship. Time-independent ROC analysis demonstrated TyG-RC has superior predictive value compared to TyG-BMI, TyG-WC, TyG-WHtR, eGDR and METSIR. For enhanced CVD risk assessment, the joint assessment TyG-RC index offers a more effective tool than using TyG or RC individually.

Indexed as

Health sciences

Identifiers

PMID41816296
PMCPMC12972743

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.