Evidence map›Paper›PMID 34385893›Full record

ArticleJournal of interventional cardiology2021

Clinical Impact of Preprocedural CT-Based 3D Computational Simulation of Left Atrial Appendage Occlusion with Amulet.

Ian Buysschaert, Dries Viaene

Abstract read
In one paragraph

Article in Journal of interventional cardiology, 2021. 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
–field-weighted citation impact
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.

  1. Review
  2. Article
  3. 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

2 authors.

Ian BuysschaertAZ Sint-Jan Brugge-Oostende AV, Ruddershove 10, Brugge 8000, Belgium.ORCID https://orcid.org/0000-0003-1754-9334
Dries ViaeneASZ, Merestraat 80, Aalst 9300, Belgium.ORCID https://orcid.org/0000-0002-7889-0192

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimsStandard of care (SoC) device size selection with transoesophageal echocardiography (TOE) and computed tomography (CT) in LAAO can be challenging due to a certain degree of variability at both patient and device levels. The aim of this study was to prospectively evaluate the clinical impact of 3D computational modelling software in the decision-making of left atrial appendage occlusion (LAAO) with Amplatzer Amulet. METHODS AND

resultsSoC preprocedural assessments as well as CT-based 3D computational simulations (FEops) were performed in 15 consecutive patients scheduled for LAAO with Amulet. Preprocedural device size selection and degree of confidence were determined after SoC and after FEops-based assessments and compared to the implanted device. FEops-based preprocedural assessment correctly selected the implanted device size in 11 out of 15 patients (73.3%), compared to 7 patients (46.7%) for SoC-based assessment. In 4 patients (26.7%), FEops induced a change in device size initially selected by SoC. In the 7 patients (46.7%) in which FEops confirmed the SoC device size selection, the degree of confidence of the size selection increased from 6.4 ± 1.4 for SoC to 8.1 ± 0.7 for FEops. One patient (6.7%) could not be implanted for anatomical reason, as correctly identified by FEops.

conclusionsPreprocedural 3D computational simulation by FEops impacts Amulet size selection in LAAO compared to TOE and CT-based SoC assessment. Operators could consider FEops computational simulation in their preprocedural device size selection.

Indexed as

Atrial AppendageAtrial FibrillationAgedAged, 80 and overCardiac CatheterizationEchocardiography, TransesophagealFemaleHumansMaleTomography, X-Ray Computed

Identifiers

PMID34385893
PMCPMC8328713

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.