Evidence map›Paper›PMID 32565583›Full record

ArticleComputer methods in applied mechanics and engineering2020

Sensitivity analysis of a strongly-coupled human-based electromechanical cardiac model: Effect of mechanical parameters on physiologically relevant biomarkers.

F Levrero-Florencio, F Margara, E Zacur, A Bueno-Orovio, Z J Wang, A Santiago, J Aguado-Sierra, G Houzeaux, V Grau, D Kay and 3 more

Open access · hybridAbstract read
In one paragraph

Article in Computer methods in applied mechanics and engineering, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
6.1field-weighted citation impact, top 3% 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

24 citing papers in PubMed, 76 citations in OpenAlex.

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  16. Bayesian optimisation for efficient parameter inference in a cardiac mechanics model of the left ventricle.International journal for numerical methods in biomedical engineering · 2022
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  20. Human biventricular electromechanical simulations on the progression of electrocardiographic and mechanical abnormalities in post-myocardial infarction.Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · 2021
    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

13 authors at 2 institutions in 3 countries.

F Levrero-FlorencioDepartment of Computer Science, University of Oxford, Oxford OX1 3QD, United Kingdom.
F MargaraDepartment of Computer Science, University of Oxford, Oxford OX1 3QD, United Kingdom.
E ZacurDepartment of Engineering Science, University of Oxford, Oxford OX3 7DQ, United Kingdom.
A Bueno-OrovioDepartment of Computer Science, University of Oxford, Oxford OX1 3QD, United Kingdom.
Z J WangDepartment of Computer Science, University of Oxford, Oxford OX1 3QD, United Kingdom.
A SantiagoBarcelona Supercomputing Center - Centro Nacional de Supercomputación, Barcelona 08034, Spain.
J Aguado-SierraBarcelona Supercomputing Center - Centro Nacional de Supercomputación, Barcelona 08034, Spain.
G HouzeauxBarcelona Supercomputing Center - Centro Nacional de Supercomputación, Barcelona 08034, Spain.
V GrauDepartment of Engineering Science, University of Oxford, Oxford OX3 7DQ, United Kingdom.
D KayDepartment of Computer Science, University of Oxford, Oxford OX1 3QD, United Kingdom.
M VázquezBarcelona Supercomputing Center - Centro Nacional de Supercomputación, Barcelona 08034, Spain.
R Ruiz-BaierMathematical Institute, University of Oxford, Oxford OX2 6GG, United Kingdom.
B RodriguezDepartment of Computer Science, University of Oxford, Oxford OX1 3QD, United Kingdom.
University of Oxford · GBBarcelona Supercomputing Center · ES

Funding

British Heart Foundation FS/17/22/32644National Centre for the Replacement, Refinement and Reduction of Animals in Research NC/P001076/1
6 · The paper itself

Abstract

The human heart beats as a result of multiscale nonlinear dynamics coupling subcellular to whole organ processes, achieving electrophysiologically-driven mechanical contraction. Computational cardiac modelling and simulation have achieved a great degree of maturity, both in terms of mathematical models of underlying biophysical processes and the development of simulation software. In this study, we present the detailed description of a human-based physiologically-based, and fully-coupled ventricular electromechanical modelling and simulation framework, and a sensitivity analysis focused on its mechanical properties. The biophysical detail of the model, from ionic to whole-organ, is crucial to enable future simulations of disease and drug action. Key novelties include the coupling of state-of-the-art human-based electrophysiology membrane kinetics, excitation-contraction and active contraction models, and the incorporation of a pre-stress model to allow for pre-stressing and pre-loading the ventricles in a dynamical regime. Through high performance computing simulations, we demonstrate that 50% to 200%

Indexed as

Cardiac electromechanicsFinite element methodHigh-performance computingMultiscale simulationsSensitivity analysis

Identifiers

PMID32565583
PMCPMC7299076
OpenAlexW2994823220

What OpenQuestion holds

Textmetadata
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.