Evidence map›Paper›PMID 30535300›Full record

ArticleEuropean heart journal. Cardiovascular Imaging2019

Metabolic pathways associated with right ventricular adaptation to pulmonary hypertension: 3D analysis of cardiac magnetic resonance imaging.

Mark I Attard, Timothy J W Dawes, Antonio de Marvao, Carlo Biffi, Wenzhe Shi, John Wharton, Christopher J Rhodes, Pavandeep Ghataorhe, J Simon R Gibbs, Luke S G E Howard and 3 more

Open access · hybridAbstract read
In one paragraph

Article in European heart journal. Cardiovascular Imaging, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 2 pooled it
1.6field-weighted citation impact, top 15% 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

19 citing papers in PubMed, 2 syntheses or guidelines pooled it, 21 citations in OpenAlex.

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  13. Right ventricular myocardial deoxygenation in patients with pulmonary artery hypertension.Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance · 2021
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  17. Artificial Intelligence for Cardiac Imaging-Genetics Research.Frontiers in cardiovascular medicine · 2019
    Review
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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

13 authors at 4 institutions in 1 country.

Mark I AttardMRC London Institute of Medical Sciences, Du Cane Road, London, UK.
Timothy J W DawesMRC London Institute of Medical Sciences, Du Cane Road, London, UK.
Antonio de MarvaoMRC London Institute of Medical Sciences, Du Cane Road, London, UK.
Carlo BiffiMRC London Institute of Medical Sciences, Du Cane Road, London, UK.
Wenzhe ShiMRC London Institute of Medical Sciences, Du Cane Road, London, UK.
John WhartonDivision of Experimental Medicine, Department of Medicine, Imperial College London, Du Cane Road, London, UK.
Christopher J RhodesDivision of Experimental Medicine, Department of Medicine, Imperial College London, Du Cane Road, London, UK.
Pavandeep GhataorheDivision of Experimental Medicine, Department of Medicine, Imperial College London, Du Cane Road, London, UK.
J Simon R GibbsRoyal Brompton Cardiovascular Research Centre, National Heart & Lung Institute, Imperial College London, Dovehouse Street, London, UK.
Luke S G E HowardImperial College Healthcare NHS Trust, Du Cane Road, London, UK.
Daniel RueckertDepartment of Computing, Imperial College London, South Kensington Campus, Queen's Gate, London, UK.
Martin R WilkinsDivision of Experimental Medicine, Department of Medicine, Imperial College London, Du Cane Road, London, UK.
Declan P O'ReganMRC London Institute of Medical Sciences, Du Cane Road, London, UK.
MRC London Institute of Medical Sciences · GBImperial College London · GBImperial College Healthcare NHS Trust · GBNIHR Royal Brompton Cardiovascular Biomedical Research Unit · GB

Funding

British Heart Foundation FS/15/59/31839British Heart Foundation NH/17/1/32725British Heart Foundation RE/13/4/30184Medical Research Council MC_UP_1102/19Wellcome Trust
6 · The paper itself

Abstract

aimsWe sought to identify metabolic pathways associated with right ventricular (RV) adaptation to pulmonary hypertension (PH). We evaluated candidate metabolites, previously associated with survival in pulmonary arterial hypertension, and used automated image segmentation and parametric mapping to model their relationship to adverse patterns of remodelling and wall stress. METHODS AND

resultsIn 312 PH subjects (47.1% female, mean age 60.8 ± 15.9 years), of which 182 (50.5% female, mean age 58.6 ± 16.8 years) had metabolomics, we modelled the relationship between the RV phenotype, haemodynamic state, and metabolite levels. Atlas-based segmentation and co-registration of cardiac magnetic resonance imaging was used to create a quantitative 3D model of RV geometry and function-including maps of regional wall stress. Increasing mean pulmonary artery pressure was associated with hypertrophy of the basal free wall (β = 0.29) and reduced relative wall thickness (β = -0.38), indicative of eccentric remodelling. Wall stress was an independent predictor of all-cause mortality (hazard ratio = 1.27, P = 0.04). Six metabolites were significantly associated with elevated wall stress (β = 0.28-0.34) including increased levels of tRNA-specific modified nucleosides and fatty acid acylcarnitines, and decreased levels (β = -0.40) of sulfated androgen.

conclusionUsing computational image phenotyping, we identify metabolic profiles, reporting on energy metabolism and cellular stress-response, which are associated with adaptive RV mechanisms to PH.

Indexed as

Imaging, Three-DimensionalAdaptation, PhysiologicalAdultAgedCase-Control StudiesFemaleHumansHypertension, PulmonaryMagnetic Resonance Imaging, CineMaleMetabolic Networks and PathwaysMiddle AgedMultivariate AnalysisReference ValuesRegression AnalysisRetrospective Studiescardiac magnetic resonance imagingimage segmentationmachine learningmetabolomicspulmonary hypertensionwall stress

Identifiers

PMID30535300
PMCPMC6529902
OpenAlexW2905245788

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.