Evidence map›Paper›PMID 35155604›Full record

ArticleFrontiers in cardiovascular medicine2021

Acute Lesion Imaging in Predicting Chronic Tissue Injury in the Ventricles.

Abdel Hadi El Hajjar, Chao Huang, Yichi Zhang, Mario Mekhael, Charbel Noujaim, Lilas Dagher, Saihariharan Nedunchezhian, Christopher Pottle, Eugene Kholmovski, Tarek Ayoub and 5 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in cardiovascular medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.8field-weighted citation impact, top 28% 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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. 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

15 authors at 4 institutions in 2 countries.

Abdel Hadi El HajjarTulane Research Innovation for Arrhythmia Discoveries, Tulane University School of Medicine, New Orleans, LA, United States.
Chao HuangTulane Research Innovation for Arrhythmia Discoveries, Tulane University School of Medicine, New Orleans, LA, United States.
Yichi ZhangTulane Research Innovation for Arrhythmia Discoveries, Tulane University School of Medicine, New Orleans, LA, United States.
Mario MekhaelTulane Research Innovation for Arrhythmia Discoveries, Tulane University School of Medicine, New Orleans, LA, United States.
Charbel NoujaimTulane Research Innovation for Arrhythmia Discoveries, Tulane University School of Medicine, New Orleans, LA, United States.
Lilas DagherTulane Research Innovation for Arrhythmia Discoveries, Tulane University School of Medicine, New Orleans, LA, United States.
Saihariharan NedunchezhianTulane Research Innovation for Arrhythmia Discoveries, Tulane University School of Medicine, New Orleans, LA, United States.
Christopher PottleTulane Research Innovation for Arrhythmia Discoveries, Tulane University School of Medicine, New Orleans, LA, United States.
Eugene KholmovskiTulane Research Innovation for Arrhythmia Discoveries, Tulane University School of Medicine, New Orleans, LA, United States.
Tarek AyoubTulane Research Innovation for Arrhythmia Discoveries, Tulane University School of Medicine, New Orleans, LA, United States.
Aneesh DhorepatilTulane Research Innovation for Arrhythmia Discoveries, Tulane University School of Medicine, New Orleans, LA, United States.
Michel BarakatDepartment of Cardiology, PeaceHealth, Bellingham, WA, United States.
Takano YamaguchiDepartment of Cardiology, Saga University, Saga, Japan.
Mihail CheluBaylor Heart Clinic, Baylor College of Medicine, Houston, TX, United States.
Nassir MarroucheTulane Research Innovation for Arrhythmia Discoveries, Tulane University School of Medicine, New Orleans, LA, United States.
Tulane University · USBaylor College of Medicine · USPeaceHealth St. Joseph Medical Center · USSaga University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundChronic lesion formation after cardiac tissue ablation is an important indicator for procedural outcome. Moreover, there is a lack of knowledge regarding the features that predict chronic lesion formation.

objectiveThe aim of this study is to determine whether acute lesion visualization using late gadolinium enhanced magnetic resonance imaging (LGE-MRI) can reliably predict chronic lesion size.

methodsFocal lesions were created in left and right ventricles of canine models using either radiofrequency (RF) ablation or cryofocal ablation. Multiple ablation parameters were used. The first LGE-MRI was acquired within 1-5 h post-ablation and the second LGE-MRI was obtained 47-82 days later. Corview software was used to perform lesion segmentations and size calculations.

resultsFifty-Five lesions were created in different locations in the ventricles. Chronic volume size decreased by a mean of 62.5 % (95% CI 58.83-67.97,

conclusionChronic tissue injury related to catheter ablation can be reliably modeled as a linear function of the acute lesion volume as assessed by LGE-MRI, regardless of the ablation parameters.

Indexed as

animal modelarrhythmiacatheter ablationelectrophysiologyventricular ablation

Identifiers

PMID35155604
PMCPMC8831749
OpenAlexW4210533905

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.