Evidence map›Paper›PMID 32042382›Full record

ArticleCaspian journal of internal medicine2020

Assessment of left ventricular torsion in long axis view in patients with chronic stenosis of coronary arteries.

Ali Jabari, Manijeh Mokhtari-Dizaji, Zahra Arab-Bafrani, Elham Mosavi, Leili Mahani, Mohammad Mostakhdem Hashemi

Open access · greenAbstract read
In one paragraph

Article in Caspian journal of internal medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.3field-weighted citation impact, top 42% of its field
1 · What the graph read from it

What it found

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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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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

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

6 authors at 4 institutions in 1 country.

Ali JabariIschemic Disorders Research Center, Golestan University of Medical Sciences, Gorgan, Iran.
Manijeh Mokhtari-DizajiIschemic Disorders Research Center, Golestan University of Medical Sciences, Gorgan, Iran.
Zahra Arab-BafraniIschemic Disorders Research Center, Golestan University of Medical Sciences, Gorgan, Iran.
Elham MosaviDepartment of Medical Physics, Tarbiat Modares University, Tehran, Iran.
Leili MahaniIschemic Disorders Research Center, Golestan University of Medical Sciences, Gorgan, Iran.
Mohammad Mostakhdem HashemiMetabolic Disorders Research Center, Golestan University of Medical Sciences, Gorgan, Iran.
Golestan University · IRGolestan University of Medical Sciences · IRIsfahan University of Medical Sciences · IRTarbiat Modares University · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLeft ventricular torsion is one of the most important biomechanical parameters of heart that routinely is measured in short axis view. A review of the literature has indicated that assessment of left ventricular torsion in short axis view has some limitations. In the present study, we evaluated whether torsion angle assessment in long axis view can be used as a diagnostic biomechanical marker in patients with coronary artery disease (CAD).

methodsWe assessed 20 males and 15 females who suffered from CAD and 24 healthy males and females. Two dimensional echocardiography images were scanned in cine loop format position throughout four cardiac cycles at basal and apical levels in the long axis view (4CH). Peak torsion angle in long axis view was obtained by speckle tracking method under block matching algorithm.

resultsIn long axis view, peak torsion angle and time of peak torsion angle were similar in female (34.87±5.8˚, 287±18ms) and males (33.26±5.60˚, 295 22ms) while they were significantly decreased and increased in CAD patients (female: 24.91±3.5˚, 345±26ms and male: 24.15±2.16˚, 358±24 ms) in comparison to healthy subjects. The peak torsion angle reduction in CAD patients was a subsequent of reduced rotation angle of basal and apical levels (P<0.001).

conclusionThe results showed that sex difference did not influence torsion angle of the left ventricle. It is concluded that left ventricular torsion assessment in long axis view has the potential to distinct patients with CAD from healthy subjects in routine echocardiography evaluation.

Indexed as

Block matching algorithm.Coronary artery diseaseEchocardiographyLeft ventricular torsionSpeckle tracking

Identifiers

PMID32042382
PMCPMC6992717
OpenAlexW2998612939

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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.