Evidence map›Paper›PMID 31509951›Full record

ArticleJournal of clinical medicine2019

Assessment of Global Longitudinal and Circumferential Strain Using Computed Tomography Feature Tracking: Intra-Individual Comparison with CMR Feature Tracking and Myocardial Tagging in Patients with Severe Aortic Stenosis.

Emilija Miskinyte, Paulius Bucius, Jennifer Erley, Seyedeh Mahsa Zamani, Radu Tanacli, Christian Stehning, Christopher Schneeweis, Tomas Lapinskas, Burkert Pieske, Volkmar Falk and 4 more

Open access · goldAbstract read
In one paragraph

Article in Journal of clinical medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
3.1field-weighted citation impact, top 7% 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

10 citing papers in PubMed, 25 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

14 authors at 5 institutions in 3 countries.

Emilija MiskinyteDepartment of Internal Medicine/Cardiology, German Heart Center Berlin, 13353 Berlin, Germany.
Paulius BuciusDepartment of Internal Medicine/Cardiology, German Heart Center Berlin, 13353 Berlin, Germany.
Jennifer ErleyDepartment of Internal Medicine/Cardiology, German Heart Center Berlin, 13353 Berlin, Germany.
Seyedeh Mahsa ZamaniDepartment of Internal Medicine/Cardiology, German Heart Center Berlin, 13353 Berlin, Germany.
Radu TanacliDepartment of Internal Medicine/Cardiology, German Heart Center Berlin, 13353 Berlin, Germany.
Christian StehningPhilips Healthcare, 22335 Hamburg, Germany.
Christopher SchneeweisKlinik für Kardiologie und Internistische Intesivmedizin, Krankenhaus der Augustinerinnen, 50678 Köln, Germany.
Tomas LapinskasDepartment of Cardiology, Medical Academy, Lithuanian University of Health Sciences, 50161 Kaunas, Lithuania.ORCID 0000-0001-7726-6948
Burkert PieskeDepartment of Internal Medicine/Cardiology, German Heart Center Berlin, 13353 Berlin, Germany.
Volkmar FalkDZHK (German Centre for Cardiovascular Research), Partner Site Berlin, 10785 Berlin, Germany.
Rolf GebkerDepartment of Internal Medicine/Cardiology, German Heart Center Berlin, 13353 Berlin, Germany.
Gianni PedrizzettiDepartment of Engineering and Architecture, University of Trieste, 34127 Trieste, Italy.ORCID 0000-0003-2886-7653
Natalia SolowjowaDepartment of Cardiothoracic Surgery, German Heart Center Berlin, 13353 Berlin, Germany.
Sebastian KelleDepartment of Internal Medicine/Cardiology, German Heart Center Berlin, 13353 Berlin, Germany. kelle@dhzb.de.
Deutsches Herzzentrum der Charité · DELithuanian University of Health Sciences · LTKrankenhaus der Augustinerinnen · DEPhilips (Germany) · DEUniversity of Trieste · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this study, we used a single commercially available software solution to assess global longitudinal (GLS) and global circumferential strain (GCS) using cardiac computed tomography (CT) and cardiac magnetic resonance (CMR) feature tracking (FT). We compared agreement and reproducibility between these two methods and the reference standard, CMR tagging (TAG). Twenty-seven patients with severe aortic stenosis underwent CMR and cardiac CT examinations. FT analysis was performed using Medis suite version 3.0 (Leiden, The Netherlands) software. Segment (Medviso) software was used for GCS assessment from tagged images. There was a trend towards the underestimation of GLS by CT-FT when compared to CMR-FT (19.4 ± 5.04 vs. 22.40 ± 5.69, respectively;

Indexed as

cardiac computed tomographycardiac magnetic resonancefeature trackingmyocardial deformationstrainsystemic diseasetagging

Identifiers

PMID31509951
PMCPMC6780556
OpenAlexW2972370498

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.