Evidence map›Paper›PMID 36837892›Full record

ArticleMetabolites2023

Alterations of NMR-Based Lipoprotein Profile Distinguish Unstable Angina Patients with Different Severity of Coronary Lesions.

Yongxin Ye, Jiahua Fan, Zhiteng Chen, Xiuwen Li, Maoxiong Wu, Wenhao Liu, Shiyi Zhou, Morten Arendt Rasmussen, Søren Balling Engelsen, Yangxin Chen and 2 more

Open access · goldAbstract read
In one paragraph

Article in Metabolites, 2023. 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
0.5field-weighted citation impact, top 36% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Trial
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

12 authors at 2 institutions in 2 countries.

Yongxin YeDepartment of Nutrition, School of Public Health, Sun Yat-sen University (Northern Campus), Guangzhou 510080, China.ORCID 0000-0002-4982-0814
Jiahua FanDepartment of Nutrition, School of Public Health, Sun Yat-sen University (Northern Campus), Guangzhou 510080, China.
Zhiteng ChenDepartment of Cardiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China.ORCID 0000-0002-7891-5783
Xiuwen LiDepartment of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China.
Maoxiong WuDepartment of Cardiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China.
Wenhao LiuDepartment of Cardiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China.
Shiyi ZhouDepartment of Nutrition, School of Public Health, Sun Yat-sen University (Northern Campus), Guangzhou 510080, China.ORCID 0000-0002-2113-0192
Morten Arendt RasmussenDepartment of Food Science, University of Copenhagen, 1958 Frederiksberg C, Denmark.
Søren Balling EngelsenDepartment of Food Science, University of Copenhagen, 1958 Frederiksberg C, Denmark.ORCID 0000-0003-4124-4338
Yangxin ChenDepartment of Cardiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China.
Bekzod KhakimovDepartment of Food Science, University of Copenhagen, 1958 Frederiksberg C, Denmark.ORCID 0000-0002-6580-2034
Min XiaDepartment of Nutrition, School of Public Health, Sun Yat-sen University (Northern Campus), Guangzhou 510080, China.ORCID 0000-0001-5330-6466
Sun Yat-sen University · CNUniversity of Copenhagen · DK

Funding

the China Scholarship Council 201906380062the National Natural Science Foundation-Guangdong Joint Fund U1801281
6 · The paper itself

Abstract

Non-invasive detection of unstable angina (UA) patients with different severity of coronary lesions remains challenging. This study aimed to identify plasma lipoproteins (LPs) that can be used as potential biomarkers for assessing the severity of coronary lesions, determined by the Gensini score (GS), in UA patients. We collected blood plasma from 67 inpatients with angiographically normal coronary arteries (NCA) and 230 UA patients, 155 of them with lowGS (GS ≤ 25.4) and 75 with highGS (GS > 25.4), and analyzed it using proton nuclear magnetic resonance spectroscopy to quantify 112 lipoprotein variables. In a logistic regression model adjusted for four well-known risk factors (age, sex, body mass index and use of lipid-lowering drugs), we tested the association between each lipoprotein and the risk of UA. Combined with the result of LASSO and PLS-DA models, ten of them were identified as important LPs. The discrimination with the addition of selected LPs was evaluated. Compared with the basic logistic model that includes four risk factors, the addition of these ten LPs concentrations did not significantly improve UA versus NCA discrimination. However, thirty-two selected LPs showed notable discrimination power in logistic regression modeling distinguishing highGS UA patients from NCA with a 14.9% increase of the area under the receiver operating characteristics curve. Among these LPs, plasma from highGS patients was enriched with LDL and VLDL subfractions, but lacked HDL subfractions. In summary, we conclude that blood plasma lipoproteins can be used as biomarkers to distinguish UA patients with severe coronary lesions from NCA patients.

Indexed as

cardiovascular diseasescoronary lesionsGensini scorelipoproteinsNMRunstable angina

Identifiers

PMID36837892
PMCPMC9958945
OpenAlexW4320919176

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.