Evidence mapPaperPMID 40662214Full record

ArticleEuropean journal of heart failure2025

Computational modelling of myocardial metabolism in patients with advanced heart failure.

Niklas Beyhoff, Vera M Braun, Marieluise Kirchner, Lucy E M Finnigan, Christoph Knosalla, István Baczkó, Evgenij Potapov, Ulrich Kintscher, Tilman Grune, Titus Kuehne and 8 more

Abstract read
In one paragraph

Article in European journal of heart failure, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Why the septum thickens in hypertrophic cardiomyopathy.Journal of molecular and cellular cardiology plus · 2026
    Review
  2. 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

18 authors.

Niklas BeyhoffDivision of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK.
Vera M BraunInstitute of Pharmacology, Max Rubner Center for Cardiovascular Metabolic Renal Research, Charité - Universitätsmedizin Berlin, Berlin, Germany.
Marieluise KirchnerBerlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany.
Lucy E M FinniganDivision of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK.
Christoph KnosallaCharité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
István BaczkóDepartment of Pharmacology and Pharmacotherapy, Albert Szent-Györgyi Medical School, University of Szeged, Szeged, Hungary.
Evgenij PotapovCharité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
Ulrich KintscherInstitute of Pharmacology, Max Rubner Center for Cardiovascular Metabolic Renal Research, Charité - Universitätsmedizin Berlin, Berlin, Germany.
Tilman GruneInstitute of Pharmacology, Max Rubner Center for Cardiovascular Metabolic Renal Research, Charité - Universitätsmedizin Berlin, Berlin, Germany.
Titus KuehneCharité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
Hermann-Georg HolzhütterInstitute of Biochemistry, Charité - Universitätsmedizin Berlin, Berlin, Germany.
Philipp MertinsBerlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany.
Damian J TylerDivision of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK.
Hendrik MiltingErich and Hanna Klessmann Institute for Cardiovascular Research and Development, Clinic for Thoracic and Cardiovascular Surgery, Heart and Diabetes Center NRW, Bad Oeynhausen, Germany.
Betty RamanDivision of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK.
Oliver J RiderDivision of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK.
Stefan NeubauerDivision of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK.
Nikolaus BerndtCharité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.

Funding

Deutsche Gesellschaft für Kardiologie-Herz und Kreislaufforschung DGK07/2021Deutsches Zentrum für Herz-Kreislaufforschung 81Z0100212
6 · The paper itself

Abstract

aimsPerturbations of myocardial metabolism and energy depletion are well-established hallmarks of heart failure (HF), yet methods for their systematic assessment remain limited in humans. This study aimed to determine the ability of computational modelling of patient-specific myocardial metabolism to assess individual bioenergetic phenotypes and their clinical implications in HF. METHODS AND

resultsBased on proteomics-derived enzyme quantities in 136 cardiac biopsies, personalised computational models of myocardial metabolism were generated in two independent cohorts of advanced HF patients together with sex- and body mass index-matched non-failing controls. The bioenergetic impact of dynamic changes in substrate availability and myocardial workload were simulated, and the models' ability to predict the myocardial response following left ventricular assist device (LVAD) implantation was assessed. Compared to controls, HF patients had a reduced ATP production capacity (p < 0.01), although there was remarkable interindividual variance. Utilisation of glucose relative to fatty acids was generally higher in HF patients, depending on substrate availability and myocardial workload. The ratio of fatty acid to glucose utilisation was associated with reverse cardiac remodelling after LVAD implantation and highly predictive of an improvement in left ventricular ejection fraction ≥10% (C-index 0.94 [0.81-1.00], p < 0.01). System-level simulations identified fatty acid administration and carnitine supplementation in those with low mitochondrial carnitine content as potential pharmacological interventions to restore myocardial substrate utilisation.

conclusionsComputational modelling identified a subset of advanced HF patients with preserved myocardial metabolism despite a similar degree of systolic dysfunction. Substrate preference was associated with the myocardial response after LVAD implantation, which suggests a role for substrate manipulation as a therapeutic approach. Computational assessment of myocardial metabolism in HF may improve understanding of disease heterogeneity, individual risk stratification, and guidance of personalised clinical decision-making in the future.

Indexed as

Computer SimulationEnergy MetabolismHeart FailureMyocardiumAgedFemaleHeart-Assist DevicesHumansMaleMiddle AgedStroke VolumeVentricular Function, LeftVentricular RemodelingCardiomyopathyComputational modellingHeart failureMetabolismPrecision medicineProteomicsVentricular assist device

Identifiers

PMID40662214
PMCPMC12803576

What Socratic 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 Socratic graph.