Evidence map›Paper›PMID 32286459›Full record

ArticleScientific reports2020

Epicardial adipose tissue thickness is not associated with adverse cardiovascular events in patients undergoing haemodialysis.

Ying-Chih Chen, Wen-Hsien Lee, Meng-Kuang Lee, Po-Chao Hsu, Wei-Chung Tsai, Chun-Yuan Chu, Chee-Siong Lee, Hsueh-Wei Yen, Tsung-Hsien Lin, Wen-Chol Voon and 3 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.4field-weighted citation impact, top 34% 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

8 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
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  4. Article
  5. Review
  6. Negative association of apelin plasma levels with epicardial fat thickness in patients with stable angina and acute myocardial infarction: A case-control study.Journal of research in medical sciences : the official journal of Isfahan University of Medical Sciences · 2024
    Article
  7. Review
  8. Review
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

13 authors at 1 institution in 1 country.

Ying-Chih ChenDepartment of Internal Medicine, Kaohsiung Municipal Siaogang Hospital, Kaohsiung, Taiwan.
Wen-Hsien LeeDepartment of Internal Medicine, Kaohsiung Municipal Siaogang Hospital, Kaohsiung, Taiwan.
Meng-Kuang LeeDivision of Cardiology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan.
Po-Chao HsuDivision of Cardiology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan.
Wei-Chung TsaiDivision of Cardiology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan.ORCID http://orcid.org/0000-0002-1123-6954
Chun-Yuan ChuDivision of Cardiology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan.
Chee-Siong LeeDivision of Cardiology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan.
Hsueh-Wei YenDivision of Cardiology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan.
Tsung-Hsien LinDivision of Cardiology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan.
Wen-Chol VoonDivision of Cardiology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan.
Wen-Ter LaiDivision of Cardiology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan.
Sheng-Hsiung SheuDivision of Cardiology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan.
Ho-Ming SuDepartment of Internal Medicine, Kaohsiung Municipal Siaogang Hospital, Kaohsiung, Taiwan. cobeshm@seed.net.tw.
Kaohsiung Medical University · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In non-haemodialysis (HD) patients, increased epicardial adipose tissue (EAT) thickness was significantly associated with adverse cardiovascular (CV) events. This study was designed to investigate whether EAT thickness was a useful parameter in the prediction of adverse CV events in HD patients. In addition, we also evaluated the major correlates of EAT thickness in these patients. In 189 routine HD patients, we performed a comprehensive transthoracic echocardiographic examination with assessment of EAT thickness. The definition of CV events included CV death, non-fatal stroke, non-fatal myocardial infarction, peripheral artery disease, and hospitalization for heart failure. The follow-up period for CV events was 2.5 ± 0.7 years. Thirty-one CV events were documented. The multivariable analysis demonstrated that older age, smoking status, the presence of diabetes mellitus and coronary artery disease, and low albumin levels were independently correlated with adverse CV events. However, increased EAT thickness was not associated with adverse CV events (P = 0.631). Additionally, older age, female sex, low haemoglobin, and low early diastolic mitral annular velocity were correlated with high EAT thickness in the univariable analysis. In the multivariable analysis, older age and female sex were still correlated with high EAT thickness. In conclusion, high EAT thickness was associated with older age and female sex in the multivariable analysis in our HD patients. However, EAT thickness was not helpful in predicting adverse CV events in such patients. Further large-scale studies are necessary to verify this finding.

Indexed as

Adipose TissueAgedCardiovascular DiseasesFemaleHumansMaleMiddle AgedPericardiumRenal DialysisRisk Factors

Identifiers

PMID32286459
PMCPMC7156515
OpenAlexW3015736171

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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 OpenQuestion graph.