Proof of Concept of Model Based Cardiovascular Prediction

NCT02591940 | Unknown

• 1 other identifier: Cardioproof
• Study Type: observational
• Target: 140
• Locations: 0 countries
• Sites: N/A

Brief Summary

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.

Conditions

Cardiovascular Modeling; Aortic Coarctation; Aortic Valve Disease; Cardiovascular MRI

Keywords

cardiovascular modeling; aortic coarctation; aortic valve disease

Outcome Measures

Primary Outcomes (2)

• Comparative Cost effectiveness between regular treatment vs. simulated alternative treatment

  1 week up to 1 year

• Predicted (simulated) vs. real haemodynamic 4D flow profile (treatment outcome)

  1 week up to 1 year

Secondary Outcomes (3)

• Calculated Vessle comliance

  1 week up to 1 year

• Calculated External and Internal Heart Power

  1 week up to 1 year

• Number of Participants with Aortic Coarctation with Arterial Hypertension

  1 week up to 1 year

Study Arms (2)

Aortic Coarctation

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

Procedure: Surgery or Treatment by Heart Catheter

Aortic Valve Disease

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

Procedure: Surgery or Treatment by Heart Catheter

Interventions

Surgery or Treatment by Heart Catheter PROCEDURE

Aortic Coarctation; Aortic Valve Disease

Eligibility Criteria

• Sex: all
• Healthy Volunteers: No
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

Patients with the need for surgical or interventional treatment with Aortic Coarctation, as well as patients with the need for aortic valve disease surgery, both according to current treatment guidelines.

You may qualify if:

• 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

You may not qualify if:

• contraindications for MRI

Sponsors & Collaborators

• German Heart Institute: lead
• Bambino Gesù Hospital and Research Institute: collaborator
• University College, London: collaborator

Related Publications (3)

• 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.

  PMID: 33591212 DERIVED

• 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.

  PMID: 31131388 DERIVED

• 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.

  PMID: 28081162 DERIVED

MeSH Terms

Conditions

Aortic Coarctation; Aortic Valve Disease

Interventions

Surgical Procedures, Operative

Condition Hierarchy (Ancestors)

Heart Defects, Congenital; Cardiovascular Abnormalities; Cardiovascular Diseases; Heart Diseases; Congenital Abnormalities; Congenital, Hereditary, and Neonatal Diseases and Abnormalities; Heart Valve Diseases

Study Design

• Study Type: observational
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: October 27, 2015
• First Posted: October 30, 2015
• Study Start: November 1, 2013
• Primary Completion: December 1, 2015
• Study Completion: December 1, 2016
• Last Updated: October 30, 2015

Record last verified: 2015-10