Evidence map›Paper›PMID 36290541›Full record

ReviewBioengineering (Basel, Switzerland)2022

Evaluating the Haemodynamic Performance of Endografts for Complex Aortic Arch Repair.

Sampad Sengupta, Yu Zhu, Mohamad Hamady, Xiao Yun Xu

Open access · goldAbstract readReview
In one paragraph

Review in Bioengineering (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.0field-weighted citation impact, top 12% 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

9 citing papers in PubMed, 14 citations in OpenAlex.

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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

4 authors at 1 institution in 1 country.

Sampad SenguptaDepartment of Chemical Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, UK.ORCID 0000-0002-1691-1218
Yu ZhuDepartment of Chemical Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, UK.ORCID 0000-0003-1714-0408
Mohamad HamadyDepartment of Surgery & Cancer, Imperial College London, St. Mary's Campus, London W2 1NY, UK.ORCID 0000-0002-7512-1056
Xiao Yun XuDepartment of Chemical Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, UK.ORCID 0000-0002-8267-621X
Imperial College London · GB

Funding

Engineering and Physical Sciences Research Council EP/R513052/1
6 · The paper itself

Abstract

Thoracic endovascular aortic repair (TEVAR) of aortic aneurysms and dissections involving the arch has evolved over the last two decades. Compared to conventional surgical methods, endovascular repair offers a less invasive treatment option with lower risk and faster recovery. Endografts used in TEVAR vary in design depending on the procedure and application. Novel endografts (e.g., branched stent-graft) were developed to ensure perfusion of blood to the supra-aortic vessels, but their haemodynamic performance and long-term durability have not been adequately studied. This review focuses on the use of computational modelling to study haemodynamics in commercially available endografts designed for complex aortic arch repair. First, we summarise the currently adopted workflow for computational fluid dynamics (CFD) modelling, including geometry reconstruction, boundary conditions, flow models, and haemodynamic metrics of interest. This is followed by a review of recently (2010-present) published CFD studies on complex aortic arch repair, using both idealized and patient-specific models. Finally, we introduce some of the promising techniques that can be potentially applied to predict post-operative outcomes.

Indexed as

branched stent-graftcomputational fluid dynamicshaemodynamicthoracic endovascular aortic repair

Identifiers

PMID36290541
PMCPMC9598215
OpenAlexW4306736817

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.