Evidence map›Paper›PMID 27477449›Full record

ArticleGenomics, proteomics & bioinformatics2016

Personalized Computer Simulation of Diastolic Function in Heart Failure.

Ali Amr, Elham Kayvanpour, Farbod Sedaghat-Hamedani, Tiziano Passerini, Viorel Mihalef, Alan Lai, Dominik Neumann, Bogdan Georgescu, Sebastian Buss, Derliz Mereles and 6 more

Abstract read
In one paragraph

Article in Genomics, proteomics & bioinformatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Review
  3. A Novel Nonlinear Parameter Estimation Method of Soft Tissues.Genomics, proteomics & bioinformatics · 2017
    Article
  4. 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

16 authors.

Ali AmrInstitute for Cardiomyopathies, Department of Medicine III, University of Heidelberg, 69120 Heidelberg, Germany; German Centre for Cardiovascular Research (DZHK), Heidelberg/Mannheim, Germany.
Elham KayvanpourInstitute for Cardiomyopathies, Department of Medicine III, University of Heidelberg, 69120 Heidelberg, Germany; German Centre for Cardiovascular Research (DZHK), Heidelberg/Mannheim, Germany.
Farbod Sedaghat-HamedaniInstitute for Cardiomyopathies, Department of Medicine III, University of Heidelberg, 69120 Heidelberg, Germany; German Centre for Cardiovascular Research (DZHK), Heidelberg/Mannheim, Germany.
Tiziano PasseriniSiemens Healthcare, Medical Imaging Technologies, Princeton, NJ 08540, USA.
Viorel MihalefSiemens Healthcare, Medical Imaging Technologies, Princeton, NJ 08540, USA.
Alan LaiInstitute for Cardiomyopathies, Department of Medicine III, University of Heidelberg, 69120 Heidelberg, Germany.
Dominik NeumannSiemens Healthcare, Medical Imaging Technologies, Princeton, NJ 08540, USA.
Bogdan GeorgescuSiemens Healthcare, Medical Imaging Technologies, Princeton, NJ 08540, USA.
Sebastian BussInstitute for Cardiomyopathies, Department of Medicine III, University of Heidelberg, 69120 Heidelberg, Germany.
Derliz MerelesInstitute for Cardiomyopathies, Department of Medicine III, University of Heidelberg, 69120 Heidelberg, Germany.
Edgar ZitronInstitute for Cardiomyopathies, Department of Medicine III, University of Heidelberg, 69120 Heidelberg, Germany.
Andreas E PoschSiemens Healthcare, Strategy and Innovation, 91052 Erlangen, Germany.
Maximilian WürstleSiemens Healthcare, Strategy and Innovation, 91052 Erlangen, Germany.
Tommaso MansiSiemens Healthcare, Medical Imaging Technologies, Princeton, NJ 08540, USA.
Hugo A KatusInstitute for Cardiomyopathies, Department of Medicine III, University of Heidelberg, 69120 Heidelberg, Germany; German Centre for Cardiovascular Research (DZHK), Heidelberg/Mannheim, Germany.
Benjamin MederInstitute for Cardiomyopathies, Department of Medicine III, University of Heidelberg, 69120 Heidelberg, Germany; German Centre for Cardiovascular Research (DZHK), Heidelberg/Mannheim, Germany. Electronic address: Benjamin.Meder@med.uni-heidelberg.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The search for a parameter representing left ventricular relaxation from non-invasive and invasive diagnostic tools has been extensive, since heart failure (HF) with preserved ejection fraction (HF-pEF) is a global health problem. We explore here the feasibility using patient-specific cardiac computer modeling to capture diastolic parameters in patients suffering from different degrees of systolic HF. Fifty eight patients with idiopathic dilated cardiomyopathy have undergone thorough clinical evaluation, including cardiac magnetic resonance imaging (MRI), heart catheterization, echocardiography, and cardiac biomarker assessment. A previously-introduced framework for creating multi-scale patient-specific cardiac models has been applied on all these patients. Novel parameters, such as global stiffness factor and maximum left ventricular active stress, representing cardiac active and passive tissue properties have been computed for all patients. Invasive pressure measurements from heart catheterization were then used to evaluate ventricular relaxation using the time constant of isovolumic relaxation Tau (τ). Parameters from heart catheterization and the multi-scale model have been evaluated and compared to patient clinical presentation. The model parameter global stiffness factor, representing diastolic passive tissue properties, is correlated significantly across the patient population with τ. This study shows that multi-modal cardiac models can successfully capture diastolic (dys) function, a prerequisite for future clinical trials on HF-pEF.

Indexed as

Computer SimulationAdultAgedAtrial Natriuretic FactorBiomarkersBlood PressureCardiac CatheterizationCardiomyopathy, DilatedEchocardiographyFemaleHeart FailureHeart RateHemodynamicsHumansMagnetic Resonance ImagingMaleAtrial Natriuretic FactorBiomarkersN-terminal proatrial natriuretic peptideProtein PrecursorsComputer-based 3D modelDiastolic functionDilated cardiomyopathyMyocardial stiffnessPersonalized medicineTau

Identifiers

PMID27477449
PMCPMC4996856

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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.