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SMART - Systems Medicine of Heart Failure

Conditions
Aortic Valve Disease
Registration Number
NCT03172338
Lead Sponsor
German Heart Institute
Brief Summary

The onset and course of heart failure (HF) is triggered by a complex regulatory network that includes stressors (pressure overload by individual anatomic hemodynamic settings), intrinsic (genes), environmental (regulating epigenetics), and modifying factors (such as hor-mones and the immune system). SMART aims to establish individualized strategies for the prevention and management of HF by early detection of the physiological, genomic, proteo-mic and hemodynamic mechanisms that lead from onecommon cause of ventricular dysfunction (pressure overload) to maladaptive remodelling and irreversible HF. To cope with the complexity of HF, SMART will interrelate models describing the interplay between ge-nome, proteome and cell function, regulating hormones, tissue composition and hemody-namic whole organ function up to a whole body description of a patient and patient cohorts. The ultimate goal is to demonstrate proof-of-concept tools for predicting disease evolution and efficacy of treatment in a given patient. To achieve this task SMART will apply

* A modelling framework that couples multi-scale mechanistic models with in-depth genome/proteome, cell physiology and whole organ (biomechanical and fluid dynamic) models

* Subsequently, investigate methods validity and relevance for "quantitative prediction" of treatment outcome in a clinical proof-of-concept trial (demonstrator) of patients with aortic valve desieases.

Detailed Description

Not available

Recruitment & Eligibility

Status
UNKNOWN
Sex
All
Target Recruitment
60
Inclusion Criteria
  • Aortic Valve Stenosis
Exclusion Criteria
  • coronary heart disease

Study & Design

Study Type
OBSERVATIONAL
Study Design
Not specified
Primary Outcome Measures
NameTimeMethod
Hypertrophy3 months

Muscle Mass and Fibrosis

Secondary Outcome Measures
NameTimeMethod

Trial Locations

Locations (1)

German Heart Center Berlin

🇩🇪

Berlin, Germany

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