Evidence map›Paper›PMID 41530580›Full record

ArticleBiomechanics and modeling in mechanobiology2026

Sensitivity analysis of factors in a microfluidics CFD model of coagulation and cardiac applications.

Paolo Melidoro, Ahmed Qureshi, Steven E Williams, Gregory Y H Lip, Magdalena Klis, Oleg Aslanidi, Adelaide De Vecchi

Abstract read
In one paragraph

Article in Biomechanics and modeling in mechanobiology, 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. Computational Modeling of Pro-inflammatory Cytokine-Enhanced Blood Coagulation.Computational and structural biotechnology journal · 2026
    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

7 authors.

Paolo MelidoroSchool of Biomedical Engineering and Imaging Sciences, King's College London, London, UK. paolo.melidoro@kcl.ac.uk.
Ahmed QureshiSchool of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
Steven E WilliamsSchool of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
Gregory Y H LipLiverpool Centre for Cardiovascular Science at University of Liverpool, Liverpool John Moore's University and Liverpool Heart & Chest Hospital, Liverpool, UK.
Magdalena KlisCardiovascular Directorate, Guy's and St Thomas' NHS Foundation Trust, London, UK.
Oleg AslanidiSchool of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
Adelaide De VecchiSchool of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.

Funding

British Heart Foundation FS/20/26/34952EPSRC CDT EP/R513064/1Wellcome/EPSRC Centre for Medical Engineering WT203148/Z/16/ZWellcome Trust
6 · The paper itself

Abstract

Coagulation is essential for haemostasis but can lead to harmful thrombus formation in conditions such as atrial fibrillation. Computational fluid dynamics (CFD) models that incorporate coagulation with blood flow can simulate this process, but their complexity often limits their use in clinical settings. This study focuses on fibrin formation during the peak thrombin phase, a brief but critical period in the thrombogram, and employs Gaussian Process Emulators to improve computational efficiency. A simplified coagulation model is integrated into a CFD framework and validated using data from an ex vivo experiment. Model inputs are varied within physiological ranges to train an emulator that predicts fibrin concentration and haemodynamic changes associated with thrombus development. A global sensitivity analysis (GSA) is performed to identify the relative influence of each input parameter. The model is then applied to a two-dimensional idealised representation of the left atrium (LA) to evaluate its suitability for cardiac simulations and to compare thrombus formation dynamics between small vessel and atrial flow. The model accurately captures fibrin formation in microchannels and the GSA and reveals potential mechanisms underlying thrombus growth in vessels while the LA simulation simulated various stages of thrombogenesis in the LA. The use of emulators enables efficient and precise predictions, enhancing the clinical feasibility of thrombosis modelling. These findings provide a foundation for the development of predictive tools to assess thrombus formation and stroke risk in patients.

Indexed as

Blood CoagulationHydrodynamicsMicrofluidicsModels, CardiovascularComputer SimulationFibrinHeart AtriaHumansThrombosisFibrinCoagulationComputational fluid dynamicsLeft atriumMicrofluidicsThrombus formation

Identifiers

PMID41530580
PMCPMC12799656

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.