Evidence map›Paper›PMID 42517347›Full record

ArticleMediators of inflammation2026

Integrative Inflammation-Metabolism Indicator for Cardiovascular-Kidney-Metabolic Syndrome: Evaluating the C-Reactive Protein-Triglyceride Glucose Index for Risk Stratification and Progression Across Three National Cohorts.

Yupeng Zeng, Huhao Feng, Haiying Cheng, Weiqing Wu, Hui He, Lixin Cheng, Qingshan Geng

Abstract read
In one paragraph

Article in Mediators of inflammation, 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.

Yupeng ZengThe Second Clinical Medical College, Jinan University, Shenzhen 518020, China, jnu.edu.cn.
Huhao FengShenzhen People's Hospital (The Second Clinical Medical College, Jinan University; The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen 518020, China, szhospital.com.
Haiying ChengShenzhen People's Hospital (The Second Clinical Medical College, Jinan University; The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen 518020, China, szhospital.com.
Weiqing WuDepartment of Health Management, Shenzhen People's Hospital (The Second Clinical Medical College, Jinan University; The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen 518020, China, szhospital.com.
Hui HeDepartment of Health Management, Shenzhen People's Hospital (The Second Clinical Medical College, Jinan University; The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen 518020, China, szhospital.com.
Lixin ChengShenzhen People's Hospital (The Second Clinical Medical College, Jinan University; The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen 518020, China, szhospital.com.ORCID https://orcid.org/0000-0002-9427-383X
Qingshan GengThe Second Clinical Medical College, Jinan University, Shenzhen 518020, China, jnu.edu.cn.ORCID https://orcid.org/0000-0002-2588-1807

Funding

Major Science and Technology Special Project of Henan Province 241100310300National Natural Science Foundation of China 32370711National Natural Science Foundation of China 62472207Shenzhen Medical Research Fund A2303033
6 · The paper itself

Abstract

backgroundInflammation plays a critical role in the onset and progression of cardiovascular-kidney-metabolic (CKM) syndrome. However, the optimal inflammatory biomarker that simultaneously reflects disease severity and predicts future progression of CKM remains unexplored.

methodsThis study utilized data from three nationally representative cohorts: National Health and Nutrition Examination Survey (NHANES), UK Biobank (UKB), and China Health and Retirement Longitudinal Study (CHARLS). In NHANES, three machine learning approaches were applied to identify the inflammatory biomarker most strongly associated with CKM stages. The association between this biomarker and CKM severity was validated in UKB and CHARLS. Its predictive value for CKM progression was examined in UKB and CHARLS with Cox proportional hazard models. Multiple sensitivity analyses were conducted to ensure the robustness of the findings.

resultsAmong 15 circulating inflammatory biomarkers, the C-reactive protein-triglyceride glucose index (CTI) was identified as the most informative indicator of advanced CKM risk. In the cross-sectional analyses, 8959 participants from NHANES, 208,625 from UKB, and 8550 from CHARLS were included. After adjustment for potential confounders, higher CTI levels were consistently associated with advanced CKM across the three cohorts (NHANES: odds ratio [OR] = 1.35, 95% confidence interval (CI): 1.20-1.48; UKB: OR = 1.55, 95% CI: 1.46-1.64; CHARLS: OR = 1.42, 95% CI: 1.28-1.60). In longitudinal analyses including 186,753 participants from UKB and 3673 from CHARLS, elevated CTI levels predicted an increased risk of incident advanced CKM (UKB: HR = 1.22, 95% CI: 1.17-1.30; CHARLS: HR = 1.21, 95% CI: 1.01-1.46).

conclusionsCTI emerged as the most robust inflammatory biomarker for assessing disease severity and predicting CKM progression among multiple candidates. Its reproducible associations across national cohorts support its utility for early detection and risk stratification, offering a basis to refine CKM management.

Indexed as

Blood GlucoseCardiovascular DiseasesC-Reactive ProteinInflammationMetabolic SyndromeTriglyceridesAgedBiomarkersCohort StudiesCross-Sectional StudiesDisease ProgressionFemaleHumansLongitudinal StudiesMaleMiddle AgedBiomarkersBlood GlucoseC-Reactive ProteinTriglyceridescardiovascular–kidney–metabolic syndromeC-reactive protein–triglyceride glucose indexinflammationinsulin resistancemachine learningmulticenter cohort study

Identifiers

PMID42517347
PMCPMC13410279

What Socratic holds

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LicenceCC BY
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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.