Evidence map›Paper›PMID 42009255›Full record

ArticleJournal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance

Cardiac magnetic resonance imaging diastolic function assessment in preserved ejection fraction and absence of late gadolinium enhancement.

Jonathan A Pan, Shuo Wang, Alper Turgot, Cristiane C Singulane, Deyu Sun, Yu Wang, Sivam Bhatt, Roberto M Lang, Christopher M Kramer, Amit R Patel

Abstract read
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In one paragraph

Article in Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
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0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

Jonathan A PanDivision of Cardiovascular Medicine, Department of Medicine, University of Virginia, Charlottesville, Virginia, USA.
Shuo WangDivision of Cardiovascular Medicine, Department of Medicine, University of Virginia, Charlottesville, Virginia, USA.
Alper TurgotSchool of Medicine, University of Virginia, Charlottesville, Virginia, USA.
Cristiane C SingulaneDivision of Cardiovascular Medicine, Department of Medicine, University of Virginia, Charlottesville, Virginia, USA.
Deyu SunDavid Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA.
Yu WangBiomedical Engineering, University of Virginia, Charlottesville, Virginia, USA.
Sivam BhattSchool of Medicine, University of Virginia, Charlottesville, Virginia, USA.
Roberto M LangSection of Cardiology, Department of Medicine, University of Chicago, Chicago, Illinois, USA.
Christopher M KramerDivision of Cardiovascular Medicine, Department of Medicine, University of Virginia, Charlottesville, Virginia, USA.
Amit R PatelDivision of Cardiovascular Medicine, Department of Medicine, University of Virginia, Charlottesville, Virginia, USA. Electronic address: 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 EB003841
6 · The paper itself

Abstract

backgroundCardiovascular magnetic resonance (CMR) accurately measures left ventricular (LV) ejection fraction (EF) and late gadolinium enhancement (LGE), but is not commonly used for diastolic function. This study combined unsupervised machine learning and diastolic function with cine imaging to identify prognostic groups.

methodsCMR studies from 391 patients with LVEF ≥50%, and no LGE were included. Using LV cine diastolic time-volume curves, early peak filling rate (E-PFR) indexed to stroke volume index (SVI), early to late diastolic filling ratio (E/A) ratio, and deceleration time (Decel

resultsMedian follow-up was 5 years with 30 events. Three clusters were identified with event rates of 2.6% (group 1), 8.5% (group 2), and 17.2% (group 3). Time-volume curves demonstrated a triphasic pattern with group 2 having lower E-PFR (6.5 vs 9.7 and 8.4 SVI/s for groups 1 and 3, respectively, p < 0.001), lower E/A (1.2 vs 2.4 and 1.9 for groups 1 and 3, respectively, p < 0.001), and longer Decel

conclusionCMR cine-derived diastolic parameters can add prognostic value despite normal EF and absence of LGE.

Indexed as

Contrast MediaHeart DiseasesMagnetic Resonance Imaging, CineStroke VolumeVentricular Function, LeftAgedClustering AlgorithmsDiastoleFemaleHumansImage Interpretation, Computer-AssistedMaleMiddle AgedPredictive Value of TestsPrognosisReproducibility of ResultsContrast MediaCardiac magnetic resonance imagingCine imagingDiastolic dysfunctionTime-volume curvesUnsupervised learning

Identifiers

PMID42009255
PMCPMC13253124

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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.