Evidence map›Paper›PMID 38753290›Full record

ReviewCurrent cardiology reports2024

The Role of Multimodality Imaging in Cardiomyopathy.

Jonathan A Pan, Amit R Patel

Abstract readReview
In one paragraph

Review in Current cardiology reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Review
  5. 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.

Jonathan A PanCardiovascular Division, Department of Medicine, University of Virginia Health System, 1215 Lee Street, Box 800158, Charlottesville, VA, 22908, USA.
Amit R PatelCardiovascular Division, Department of Medicine, University of Virginia Health System, 1215 Lee Street, Box 800158, Charlottesville, VA, 22908, USA. apatel@virginia.edu.

Funding

Training in Cardiovascular Imaging ResearchT32EB003841 · NIBIB · UNIVERSITY OF VIRGINIA CHARLOTTESVILLE · PI Jonathan R Lindner · 2004 to 2026
$4.4M
NIBIB NIH HHS T32 EB003841NIH HHS T32EB003841
6 · The paper itself

Abstract

purpose of reviewThere has been increasing use of multimodality imaging in the evaluation of cardiomyopathies. RECENT

findingsEchocardiography, cardiac magnetic resonance (CMR), cardiac nuclear imaging, and cardiac computed tomography (CCT) play an important role in the diagnosis, risk stratification, and management of patients with cardiomyopathies. Echocardiography is essential in the initial assessment of suspected cardiomyopathy, but a multimodality approach can improve diagnostics and management. CMR allows for accurate measurement of volumes and function, and can easily detect unique pathologic structures. In addition, contrast imaging and parametric mapping enable the characterization of tissue features such as scar, edema, infiltration, and deposition. In non-ischemic cardiomyopathies, metabolic and molecular nuclear imaging is used to diagnose rare but life-threatening conditions such amyloidosis and sarcoidosis. There is an expanding use of CCT for planning electrophysiology procedures such as cardioversion, ablations, and device placement. Furthermore, CCT can evaluate for complications associated with advanced heart failure therapies such as cardiac transplant and mechanical support devices. Innovations in multimodality cardiac imaging should lead to increased volumes and better outcomes.

Indexed as

CardiomyopathiesEchocardiographyMultimodal ImagingTomography, X-Ray ComputedHumansMagnetic Resonance ImagingSarcoidosisCardiomyopathyComputed TomographyEchocardiographyMagnetic ResonanceMultimodalityNuclear Imaging

Identifiers

PMID38753290
PMCPMC11236518

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.