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Proof of Concept of Model Based Cardiovascular Prediction

NCT ID: NCT02591940

Last Updated: 2015-10-30

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

UNKNOWN

Total Enrollment

140 participants

Study Classification

OBSERVATIONAL

Study Start Date

2013-11-30

Study Completion Date

2016-12-31

Brief Summary

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CARDIOPROOF is a proof-of-concept project that consolidates the outcomes of previous virtual physiological human (VPH) projects and checks the applicability and effectiveness of available predictive modelling and simulation tools, validating them in interrelated clinical trials conducted in three European centres of excellence in cardiac treatment (from Germany, Italy and the UK). CARDIOPROOF focuses on patients with aortic valve disease and aortic coarctation, which, if left untreated, can ensue irreversible heart failure. As a result treatment becomes mandatory, but optimum timing and the best type of treatment still remain difficult to determine. With more than 50.000 interventions per year within the EU, the diseases addressed by CARDIOPROOF have a significant socio-economic impact. Present clinical guidelines are highly complex and rely mostly on imaging diagnostics and clinical parameters, without benefiting, as yet, from patient-specific disease modelling based prediction. CARDIOPROOF goes beyond the current state of the art by conducting validation trials aimed at covering and comparing the complete spectrum of cardiovascular treatment, predicting the evolution of the disease and the immediate and mid-term outcome of treatment. Operational clustering is going to provide a seamless clinical solution that applies different modeling methods to realize the potential of personalised medicine taking into account user-friendliness as a key component of clinical usability. CARDIOPROOF's goal is to provide first-hand data on comparative cost-effectiveness and clinical efficacy of the most advanced VPH approaches compared to conventional diagnostics and treatment algorithms, thus accelerating the deployment of VPH methods in clinical environments, and bring to maturity holistic patient-specific computer-based predictive models and simulations.

Detailed Description

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Conditions

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Cardiovascular Modeling Aortic Coarctation Aortic Valve Disease Cardiovascular MRI

Keywords

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cardiovascular modeling aortic coarctation aortic valve disease

Study Design

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Study Time Perspective

PROSPECTIVE

Study Groups

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Aortic Coarctation

interventional treatment in heart catheter (stenting/angioplasty) surgical repair of coarctation

Surgery or Treatment by Heart Catheter

Intervention Type PROCEDURE

Aortic Valve Disease

surgical repair in aortic valve disease (reconstruction/valve replacement)

Surgery or Treatment by Heart Catheter

Intervention Type PROCEDURE

Interventions

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Surgery or Treatment by Heart Catheter

Intervention Type PROCEDURE

Eligibility Criteria

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Inclusion Criteria

* patients with the need for surgical or interventional treatment with Aortic Coarctation
* patients with the need for aortic valve disease surgery

* both according to current treatment guidelines

Exclusion Criteria

* contraindications for MRI
Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Bambino Gesù Hospital and Research Institute

OTHER

Sponsor Role collaborator

University College, London

OTHER

Sponsor Role collaborator

German Heart Institute

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

References

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Runte K, Brosien K, Schubert C, Nordmeyer J, Kramer P, Schubert S, Berger F, Hennemuth A, Kuehne T, Kelm M, Goubergrits L. Image-Based Computational Model Predicts Dobutamine-Induced Hemodynamic Changes in Patients With Aortic Coarctation. Circ Cardiovasc Imaging. 2021 Feb;14(2):e011523. doi: 10.1161/CIRCIMAGING.120.011523. Epub 2021 Feb 16.

Reference Type DERIVED
PMID: 33591212 (View on PubMed)

Nordmeyer S, Hellmeier F, Yevtushenko P, Kelm M, Lee CB, Lehmann D, Kropf S, Berger F, Falk V, Knosalla C, Kuehne T, Goubergrits L. Abnormal aortic flow profiles persist after aortic valve replacement in the majority of patients with aortic valve disease: how model-based personalized therapy planning could improve results. A pilot study approach. Eur J Cardiothorac Surg. 2020 Jan 1;57(1):133-141. doi: 10.1093/ejcts/ezz149.

Reference Type DERIVED
PMID: 31131388 (View on PubMed)

Fernandes JF, Goubergrits L, Bruning J, Hellmeier F, Nordmeyer S, da Silva TF, Schubert S, Berger F, Kuehne T, Kelm M; CARDIOPROOF Consortium. Beyond Pressure Gradients: The Effects of Intervention on Heart Power in Aortic Coarctation. PLoS One. 2017 Jan 12;12(1):e0168487. doi: 10.1371/journal.pone.0168487. eCollection 2017.

Reference Type DERIVED
PMID: 28081162 (View on PubMed)

Other Identifiers

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Cardioproof

Identifier Type: -

Identifier Source: org_study_id