Evidence map›Paper›PMID 36769762›Full record

ArticleJournal of clinical medicine2023

Comparative Cardiac Magnetic Resonance-Based Feature Tracking and Deep-Learning Strain Assessment in Patients Hospitalized for Acute Myocarditis.

Javier Urmeneta Ulloa, Vicente Martínez de Vega, Ana Álvarez Vázquez, Cristina Andreu-Vázquez, Israel John Thuissard-Vasallo, Manuel Recio Rodríguez, Gonzalo Pizarro, José Ángel Cabrera

Abstract read
In one paragraph

Article in Journal of clinical medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–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

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  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

8 authors.

Javier Urmeneta UlloaCardiology Department, Hospital Universitario Quirónsalud, 28223 Madrid, Spain.ORCID 0000-0001-6968-3741
Vicente Martínez de VegaRadiology Department, Hospital Universitario Quirónsalud, 28223 Madrid, Spain.
Ana Álvarez VázquezRadiology Department, Hospital Universitario Quirónsalud, 28223 Madrid, Spain.
Cristina Andreu-VázquezDepartment of Medicine, Faculty of Biomedical and Health Sciences, European University of Madrid, 28670 Madrid, Spain.ORCID 0000-0002-7558-4325
Israel John Thuissard-VasalloDepartment of Medicine, Faculty of Biomedical and Health Sciences, European University of Madrid, 28670 Madrid, Spain.
Manuel Recio RodríguezRadiology Department, Hospital Universitario Quirónsalud, 28223 Madrid, Spain.
Gonzalo PizarroCardiology Department, Hospital Universitario Quirónsalud, 28223 Madrid, Spain.ORCID 0000-0002-5082-3596
José Ángel CabreraCardiology Department, Hospital Universitario Quirónsalud, 28223 Madrid, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study sought to examine the correlation between left ventricular (LV) myocardial feature tracking (FT) and deep learning-based strain (DLS) analysis in the diagnostic (CMRd) and follow-up (CMRf) cardiac magnetic resonance imaging of patients with acute myocarditis. The retrospective study included 17 patients with acute myocarditis and 20 healthy controls. The CMRd took place within 14 days of symptom onset, while the CMRf took place at least 2 months after the event. The global-circumferential FT (FTc) and global-circumferential DLS (DLSc) were analyzed. The continuous variables were compared using paired

Indexed as

cardiac magnetic resonancedeep-learning strainfeature trackingmyocarditis

Identifiers

PMID36769762
PMCPMC9917983

What OpenQuestion holds

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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.