Evidence map›Paper›PMID 37122522›Full record

ArticleWorld journal of clinical cases2023

Interaction between the left ventricular ejection fraction and left ventricular strain and its relationship with coronary stenosis.

Hai-Yan Gui, Shu-Wen Liu, Dong-Fang Zhu

Open access · diamondAbstract read
In one paragraph

Article in World journal of clinical cases, 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
–field-weighted citation impact, top 95% 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

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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, 0 citations in OpenAlex.

  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

3 authors at 1 institution in 1 country.

Hai-Yan GuiMRI Room, Harbin No. 4 Hospital, Harbin 150026, Heilongjiang Province, China.
Shu-Wen LiuDepartment of Cardiology, Harbin No. 4 Hospital, Harbin 150026, Heilongjiang Province, China. shuwenl007@yeah.net.
Dong-Fang ZhuDepartment of Cardiology, Harbin No. 4 Hospital, Harbin 150026, Heilongjiang Province, China.
Heilongjiang Provincial Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCoronary artery stenosis (CAS) is the most common type of heart disease and the leading cause of death in both men and women globally. CAS occurs when the arteries that supply blood to the heart muscle harden and become narrower due to plaque buildup - cholesterol and other material - on their inner walls. As a result, the heart muscle cannot receive the blood or oxygen it needs. Most heart attacks happen when a blood clot suddenly cuts off the hearts' blood supply, causing permanent heart damage.

aimTo analyze the relationship between the left ventricular ejection fraction (LVEF), left ventricular strain (LVS), and coronary stenosis.

methodsA total of 190 participants were enrolled in this trail. The control group comprised 93 healthy individuals, and observation group comprised 97 patients with coronary heart disease who were hospitalized between July 2020 and September 2021. Coronary lesions were assessed using the Gensini score, and the LVEF and LVS were measured using magnetic resonance imaging (MRI). The interaction between the LVEF and LVS was examined using a linear regression model. The relationship between LVEF and coronary stenosis was examined using Spearman's correlation.

resultsThe LVEF of the observation group was lower than that of the control group. The left ventricular end-systolic volume (LVESV) and left ventricular end-diastolic volume (LVEDV) of the observation group were significantly higher than those of the control group (

conclusionThe LVEF measured using MRI is significantly linearly correlated with LVS and negatively correlated with coronary stenosis.

Indexed as

Coronary stenosisLeft ventricular ejection fractionLeft ventricular end-diastolic volumeLeft ventricular end-systolic volumeLeft ventricular strainMagnetic resonance imaging

Identifiers

PMID37122522
PMCPMC10131022
OpenAlexW4361278417

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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.