Evidence map›Paper›PMID 29769455›Full record

ArticleJournal of atherosclerosis and thrombosis2019

Tenascin C: A Potential Biomarker for Predicting the Severity of Coronary Atherosclerosis.

Wen Gao, Jian Li, Huanchun Ni, Haiming Shi, Zhiyong Qi, Shouguo Zhu, Chuanming Hao, Qionghong Xie, Xinping Luo, Kun Xie

Open access · diamondAbstract read
In one paragraph

Article in Journal of atherosclerosis and thrombosis, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
2.4field-weighted citation impact, top 11% of its field
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

17 citing papers in PubMed, 25 citations in OpenAlex.

  1. Review
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  5. The role of TNC in atherosclerosis and drug development opportunities.International journal of biological sciences · 2024
    Review
  6. Matricellular proteins in atherosclerosis development.Matrix biology : journal of the International Society for Matrix Biology · 2023
    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

10 authors at 3 institutions in 1 country.

Wen GaoDepartment of Cardiology, Huashan Hospital, Fudan University.
Jian LiDepartment of Cardiology, Huashan Hospital, Fudan University.
Huanchun NiDepartment of Cardiology, Huashan Hospital, Fudan University.
Haiming ShiDepartment of Cardiology, Huashan Hospital, Fudan University.
Zhiyong QiDepartment of Cardiology, Zhongshan Hospital, Fudan University.
Shouguo ZhuDepartment of Cardiology, Yunnan Kungang Hospital, Kunming.
Chuanming HaoDepartment of Nephrology, Huashan Hospital, Fudan University.
Qionghong XieDepartment of Nephrology, Huashan Hospital, Fudan University.
Xinping LuoDepartment of Cardiology, Huashan Hospital, Fudan University.
Kun XieDepartment of Cardiology, Huashan Hospital, Fudan University.
Fudan University · CNHuashan Hospital · CNThe First Affiliated Hospital, Sun Yat-sen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimsCoronary artery disease (CAD) is the leading cause of mortality and morbidity worldwide and one of the greatest threats to public health. Tenascin C (TNC) is an extracellular matrix glycoprotein that is found in low concentrations in normal tissues and is enhanced by a range of cardiovascular pathologies. This study aimed to evaluate the value of TNC in assessing the severity of atherosclerosis measured by the Gensini score.

methodsA total of 157 patients with chest pains who underwent selective coronary angiography for suspected coronary atherosclerosis were enrolled. The patients were divided into the CAD group and non-CAD group according to symptoms and angiography. Demographic data and laboratory analyses were collected.

resultsThe mean TNC level was significantly higher in the CAD group than in the non-CAD group (p<0.001). A significant positive correlation between TNC levels and Gensini score (p<0.01, r=0.672) was found. ROC curve analysis demonstrated that the cutoff value for TNC at 89.48 ng/mL was well differentiated in the CAD and non-CAD groups. Furthermore, TNC was also a good predictor for a higher Gensini score (the third tertile) in the ROC curve analysis. When the cutoff was accepted as 100.91 ng/mL, the sensitivity and specificity were 82.7% and 79%, respectively.

conclusionA significant relationship was found between the Gensini score and serum TNC level. TNC levels can be considered in risk assessments for CAD before angiography.

Indexed as

Severity of Illness IndexAgedBiomarkersCase-Control StudiesCoronary Artery DiseaseCross-Sectional StudiesFemaleHumansMaleMiddle AgedPrognosisROC CurveTenascinBiomarkersTenascinTNC protein, humanAtherosclerosisCoronary artery diseaseGensini scoreTenascin C

Identifiers

PMID29769455
PMCPMC6308263
OpenAlexW2967918028

What OpenQuestion holds

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LicenceCC BY-NC-SA
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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 OpenQuestion graph.