Evidence map›Paper›PMID 41481542›Full record

ReviewThe Journal of physiology2026

Cardiac remodelling in type 2 diabetes: Pathophysiological mechanisms and opportunities for multiscale computational modelling and simulation.

Ambre Bertrand, Jakub Tomek, Blanca Rodriguez

Abstract readReview
In one paragraph

Review in The Journal of physiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

3 authors.

Ambre BertrandDepartment of Computer Science, University of Oxford, Oxford, UK.ORCID https://orcid.org/0000-0001-5116-6463
Jakub TomekDepartment of Physiology, Anatomy & Genetics, University of Oxford, Oxford, UK.ORCID https://orcid.org/0000-0002-0157-4386
Blanca RodriguezDepartment of Computer Science, University of Oxford, Oxford, UK.

Funding

Engineering and Physical Sciences Research Council EP/S02428X/1Engineering and Physical Sciences Research Council EP/X019446/1Sir Henry Wellcome Fellowship 222781/Z/21/ZWellcome Trust 214290/Z/18/Z
6 · The paper itself

Abstract

Type 2 diabetes is a highly prevalent metabolic disease that significantly impacts the heart and contributes to an increased risk of cardiac complications, notably heart failure with preserved ejection fraction and cardiac arrhythmias, which can cause sudden cardiac death. In type 2 diabetes chronic hyperglycaemia and insulin resistance lead to subcellular changes, including dysregulation of calcium/calmodulin-dependent protein kinase II (CaMKII), intracellular sodium and calcium handling and potassium currents, all of which impair cardiac contractility and repolarisation. Type 2 diabetes induces diffuse myocardial fibrosis and anatomical remodelling, which contribute to diastolic and systolic dysfunction, and the formation of a pro-arrhythmic substrate. Impaired connexin 43-mediated conduction and cardiac autonomic neuropathy further promote cardiac electrophysiological and mechanical dysfunction. Clinical studies using the ECG and cardiac imaging modalities have been successful in detecting some of these changes; however our mechanistic understanding of type 2 diabetes-driven cardiac disorders remains limited. Recent advances in multiscale computational modelling and simulation of human cardiac electrophysiology and mechanics provide new opportunities to study diabetes-induced cardiac remodelling in silico by unravelling disease mechanisms across different scales and assisting in the development of novel therapies. Here we review key pathophysiological mechanisms of electrophysiological, structural and nervous cardiac remodelling in type 2 diabetes; their clinical implications; and the cardiac effects of common glucose-lowering pharmacological agents commonly taken by diabetes patients. We discuss the potential of human-based computational cardiac modelling and simulation in this context to deepen our mechanistic understanding, and guide more precise prevention and treatment of diabetes-driven cardiac arrhythmias and diastolic dysfunction.

Indexed as

Diabetes Mellitus, Type 2Models, CardiovascularVentricular RemodelingAnimalsComputer SimulationHumanscardiac arrhythmiascardiac electrophysiologycardiac mechanicscomputational modelling and simulationdiabetic myocardial disorderin silico trialsprecision medicinetype 2 diabetes

Identifiers

PMID41481542
PMCPMC13327775

What Socratic 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 Socratic graph.