Evidence map›Paper›PMID 35860652›Full record

ArticleFrontiers in physiology2022

A Poroelastic Approach for Modelling Myocardial Oedema in Acute Myocarditis.

Wesley de Jesus Lourenço, Ruy Freitas Reis, Ricardo Ruiz-Baier, Bernardo Martins Rocha, Rodrigo Weber Dos Santos, Marcelo Lobosco

Open access · goldAbstract read
In one paragraph

Article in Frontiers in physiology, 2022. 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
1.5field-weighted citation impact, top 17% 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, 9 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

6 authors at 2 institutions in 4 countries.

Wesley de Jesus LourençoGraduate Program on Computational Modelling, Federal University of Juiz de Fora, Juiz de Fora, Brazil.
Ruy Freitas ReisDepartment of Computer Science, Institute of Exact Sciences, Federal University of Juiz de Fora, Juiz de Fora, Brazil.
Ricardo Ruiz-BaierSchool of Mathematics and Victorian Heart Institute, Monash University, Melbourne, VIC, Australia.
Bernardo Martins RochaGraduate Program on Computational Modelling, Federal University of Juiz de Fora, Juiz de Fora, Brazil.
Rodrigo Weber Dos SantosGraduate Program on Computational Modelling, Federal University of Juiz de Fora, Juiz de Fora, Brazil.
Marcelo LoboscoGraduate Program on Computational Modelling, Federal University of Juiz de Fora, Juiz de Fora, Brazil.
Universidade Federal de Juiz de Fora · BRSechenov University · RU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Myocarditis is a general set of mechanisms that manifest themselves into the inflammation of the heart muscle. In 2017, more than 3 million people were affected by this disease worldwide, causing about 47,000 deaths. Many aspects of the origin of this disease are well known, but several important questions regarding the disease remain open. One of them is why some patients develop a significantly localised inflammation while others develop a much more diffuse inflammation, reaching across large portions of the heart. Furthermore, the specific role of the pathogenic agent that causes inflammation as well as the interaction with the immune system in the progression of the disease are still under discussion. Providing answers to these crucial questions can have an important impact on patient treatment. In this scenario, computational methods can aid specialists to understand better the relationships between pathogens and the immune system and elucidate why some patients develop diffuse myocarditis. This paper alters a recently developed model to study the myocardial oedema formation in acute infectious myocarditis. The model describes the finite deformation regime using partial differential equations to represent tissue displacement, fluid pressure, fluid phase, and the concentrations of pathogens and leukocytes. A sensitivity analysis was performed to understand better the influence of the most relevant model parameters on the disease dynamics. The results showed that the poroelastic model could reproduce local and diffuse myocarditis dynamics in simplified and complex geometrical domains.

Indexed as

computational immunologycomputational modellinglarge-strain poroelasticitymyocarditisoedema formation

Identifiers

PMID35860652
PMCPMC9289286
OpenAlexW4283793250

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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 OpenQuestion graph.