Evidence map›Paper›PMID 40241989›Full record

ArticleFrontiers in endocrinology2025

Associations of Gla-rich protein and interleukin-1β with coronary artery calcification risk in patients with suspected coronary artery disease.

Cheng Zengwei, Gao Shiyi, Kang Pinfang, Gao Dasheng, Wang Jun, Hu Sigan

Abstract read
In one paragraph

Article in Frontiers in endocrinology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
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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

6 authors.

Cheng ZengweiDepartment of Cardiology, The First Affiliated Hospital of Bengbu Medical University, Bengbu, China.
Gao ShiyiDepartment of Cardiology, The First Affiliated Hospital of Bengbu Medical University, Bengbu, China.
Kang PinfangDepartment of Cardiology, The First Affiliated Hospital of Bengbu Medical University, Bengbu, China.
Gao DashengDepartment of Cardiology, The First Affiliated Hospital of Bengbu Medical University, Bengbu, China.
Wang JunDepartment of Cardiology, The First Affiliated Hospital of Bengbu Medical University, Bengbu, China.
Hu SiganDepartment of Cardiology, The First Affiliated Hospital of Bengbu Medical University, Bengbu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Gla-rich protein (GRP) and interleukin-1β (IL-1β) are recognized as reliable biomarkers for evaluating inflammation and are effective predictors of cardiovascular disease. However, the relationship between GRP, IL-1β, and coronary artery calcification (CAC) in patients with suspected coronary artery disease (CAD) remains unclear. Therefore, we investigated the association between these inflammatory biomarkers (GRP and IL-1β) and CAC in patients with suspected CAD. Methods: This prospective study included patients with suspected CAD who underwent coronary computed tomography angiography (CTA). Fasting venous blood samples were collected at admission, and GRP and IL-1β levels were quantified using enzyme-linked immunosorbent assays (ELISA). The Agatston score was calculated to assess coronary artery calcification (CAC) based on coronary CTA findings. Results: A total of 120 patients were included in this study. Multivariate logistic regression analysis revealed that GRP [odds ratio (OR), 1.202; 95% confidence interval (CI), 1.065-1.356; Conclusions: Elevated levels of GRP and IL-1β, as inflammatory biomarkers, were associated with CAC in patients with suspected CAD. These biomarkers may provide valuable insights into the pathophysiology of coronary artery calcification and contribute to improved risk stratification in this patient population.

Indexed as

Coronary Artery DiseaseInterleukin-1betaVascular CalcificationAgedBiomarkersComputed Tomography AngiographyFemaleHumansMaleMiddle AgedProspective StudiesRisk FactorsBiomarkersIL1B protein, humanInterleukin-1betaatherosclerosiscoronary artery calcium scorecoronary artery diseaseGla-rich proteininterleukin-1β

Identifiers

PMID40241989
PMCPMC11999850

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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.