Evidence map›Paper›PMID 28327972›Full record

ArticleGigaScience2017

Orthogonal decomposition of left ventricular remodeling in myocardial infarction.

Xingyu Zhang, Pau Medrano-Gracia, Bharath Ambale-Venkatesh, David A Bluemke, Brett R Cowan, J Paul Finn, Alan H Kadish, Daniel C Lee, Joao A C Lima, Alistair A Young and 1 more

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PubMed Full text at PMC Publisher
In one paragraph

Article in GigaScience, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Xingyu ZhangDepartment of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand.
Pau Medrano-GraciaDepartment of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand.
Bharath Ambale-VenkateshThe Donald W. Reynolds Cardiovascular Clinical Research Center, The Johns Hopkins University, Baltimore, USA.
David A BluemkeNational Institute of Biomedical Imaging and Bioengineering, Bethesda, Maryland, USA.
Brett R CowanDepartment of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand.
J Paul FinnDepartment of Radiology, UCLA, Los Angeles, USA.
Alan H KadishFeinberg Cardiovascular Research Institute, Northwestern University Feinberg School of Medicine, Chicago, USA.
Daniel C LeeFeinberg Cardiovascular Research Institute, Northwestern University Feinberg School of Medicine, Chicago, USA.
Joao A C LimaThe Donald W. Reynolds Cardiovascular Clinical Research Center, The Johns Hopkins University, Baltimore, USA.
Alistair A YoungDepartment of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand.
Avan SuinesiaputraDepartment of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand.

Funding

The Cardiac Atlas ProjectR01HL121754 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI MCCULLOCH, ANDREW D., OMENS, JEFFREY H. · 2014 to 2023
$5.0M
Molecular Biomedical Imaging Laboratory (NIBIB)ZIAEB000072 · NIBIB · NATIONAL INSTITUTE OF BIOMEDICAL IMAGING AND BIOENGINEERING · PI BLUEMKE, DAVID · 2010 to 2017
$5.0M
The Cardiac Atlas Project: Establishment of a Cardiac MRI Database.R01HL087773 · NHLBI · UNIVERSITY OF AUCKLAND · PI YOUNG, ALISTAIR ANDREW · 2008 to 2010
$1.4M
NHLBI NIH HHS R01 HL087773NHLBI NIH HHS R01 HL121754
6 · The paper itself

Abstract

backgroundLeft ventricular size and shape are important for quantifying cardiac remodeling in response to cardiovascular disease. Geometric remodeling indices have been shown to have prognostic value in predicting adverse events in the clinical literature, but these often describe interrelated shape changes. We developed a novel method for deriving orthogonal remodeling components directly from any (moderately independent) set of clinical remodeling indices.

resultsSix clinical remodeling indices (end-diastolic volume index, sphericity, relative wall thickness, ejection fraction, apical conicity, and longitudinal shortening) were evaluated using cardiac magnetic resonance images of 300 patients with myocardial infarction, and 1991 asymptomatic subjects, obtained from the Cardiac Atlas Project. Partial least squares (PLS) regression of left ventricular shape models resulted in remodeling components that were optimally associated with each remodeling index. A Gram-Schmidt orthogonalization process, by which remodeling components were successively removed from the shape space in the order of shape variance explained, resulted in a set of orthonormal remodeling components. Remodeling scores could then be calculated that quantify the amount of each remodeling component present in each case. A one-factor PLS regression led to more decoupling between scores from the different remodeling components across the entire cohort, and zero correlation between clinical indices and subsequent scores.

conclusionsThe PLS orthogonal remodeling components had similar power to describe differences between myocardial infarction patients and asymptomatic subjects as principal component analysis, but were better associated with well-understood clinical indices of cardiac remodeling. The data and analyses are available from www.cardiacatlas.org.

Indexed as

Models, CardiovascularVentricular Function, LeftVentricular RemodelingAdultAgedAged, 80 and overAlgorithmsAsymptomatic DiseasesComputer SimulationFemaleHumansMaleMiddle AgedModels, StatisticalMyocardial InfarctionReproducibility of ResultsCardiac remodelingMagnetic resonance imagingPartial least squares regressionShape components

Identifiers

PMID28327972
PMCPMC5791439

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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.