Evidence map›Paper›PMID 29739399›Full record

ArticleBiomedical engineering online2018

The roles of mid-myocardial and epicardial cells in T-wave alternans development: a simulation study.

D Janusek, J Svehlikova, J Zelinka, W Weigl, R Zaczek, G Opolski, M Tysler, R Maniewski

Open access · goldAbstract read
In one paragraph

Article in Biomedical engineering online, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.9field-weighted citation impact, top 24% 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

3 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Article
  3. Inhibition of CaPflugers Archiv : European journal of physiology · 2021
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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

8 authors at 4 institutions in 3 countries.

D JanusekNalecz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, 4 Ks Trojdena Str., 02-109, Warsaw, Poland. djanusek@ibib.waw.pl.ORCID http://orcid.org/0000-0001-9696-4127
J SvehlikovaInstitute of Measurement Science, Slovak Academy of Sciences, Bratislava, Slovakia.
J ZelinkaInstitute of Measurement Science, Slovak Academy of Sciences, Bratislava, Slovakia.
W WeiglDepartment of Surgical Sciences/Anaesthesiology and Intensive Care, Uppsala University, Akademiska Hospital, Uppsala, Sweden.
R ZaczekDepartment of Cardiology, Central Clinical Hospital of Medical University of Warsaw, Warsaw, Poland.
G OpolskiDepartment of Cardiology, Central Clinical Hospital of Medical University of Warsaw, Warsaw, Poland.
M TyslerInstitute of Measurement Science, Slovak Academy of Sciences, Bratislava, Slovakia.
R ManiewskiNalecz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, 4 Ks Trojdena Str., 02-109, Warsaw, Poland.
Slovak Academy of Sciences · SKInstitute of Biocybernetics and Biomedical Engineering · PLMedical University of Warsaw · PLUppsala University Hospital · SE

Funding

Polish National Science Centre DEC-2011/01/B/ST7/06801Slovak Research and Development Agency APVV-14-0875VEGA Grant Agency in Slovakia 2/0071/16
6 · The paper itself

Abstract

backgroundThe occurrence of T-wave alternans in electrocardiographic signals was recently linked to susceptibility to ventricular arrhythmias and sudden cardiac death. Thus, by detecting and comprehending the origins of T-wave alternans, it might be possible to prevent such events.

resultsHere, we simulated T-wave alternans in a computer-generated human heart model by modulating the action potential duration and amplitude during the first part of the repolarization phase. We hypothesized that changes in the intracardiac alternans patterns of action potential properties would differentially influence T-wave alternans measurements at the body surface. Specifically, changes were simulated globally in the whole left and right ventricles to simulate concordant T-wave alternans, and locally in selected regions to simulate discordant and regional discordant, hereinafter referred to as "regional", T-wave alternans. Body surface potential maps and 12-lead electrocardiographic signals were then computed. In depth discrimination, the influence of epicardial layers on T-wave alternans development was significantly higher than that of mid-myocardial cells. Meanwhile, spatial discrimination revealed that discordant and regional action potential property changes had a higher influence on T-wave alternans amplitude than concordant changes. Notably, varying T-wave alternans sources yielded distinct body surface potential map patterns for T-wave alternans amplitude, which can be used for location of regions within hearts exhibiting impaired repolarization. The highest ability for T-wave alternans detection was achieved in lead V1. Ultimately, we proposed new parameters Vector Magnitude Alternans and Vector Angle Alternans, with higher ability for T-wave alternans detection when using multi-lead electrocardiographic signals processing than for single leads. Finally, QT alternans was found to be associated with the process of T-wave alternans generation.

conclusionsThe distributions of the body surface T-wave alternans amplitude have been shown to have unique patterns depending on the type of alternans (concordant, discordant or regional) and the location of the disturbance in the heart. The influence of epicardial cells on T-wave alternans development is significantly higher than that of mid-myocardial cells, among which the sub-endocardial layer exerted the highest influence. QT interval alternans is identified as a phenomenon that correlate with T-wave alternans.

Indexed as

ElectrocardiographyModels, CardiovascularArrhythmias, CardiacMyocardiumPericardiumPulse Wave AnalysisECG signal simulationHeart modelT-wave alternans

Identifiers

PMID29739399
PMCPMC5941457
OpenAlexW2805233604

What OpenQuestion holds

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LicenceCC BY
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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.