Coronary Artery Disease Clinical Trial
Official title:
The Multicenter Cardiology Monitoring Platform Registry (mCMP-registry)
The multicenter Cardiology Monitoring Platform registry (mCMP-registry) is a prospective observational registry including multi-omics (diagnostic) measurements performed as part of routine clinical care, bio-banking (optional), and yearly questionnaires (optional). It's objective is to optimize (early) diagnosis and risk-stratification of (early) cardiovascular diseases, specifically cardiomyopathy phenotypes, arrhythmias, and coronary artery disease, and to create a better understanding of underlying pathophysiological processes.
Rationale: Heart failure (HF) represents a heterogeneous range of clinical overlapping cardiomyopathy phenotypes, resulting from multifactorial environmental insults in the presence or absence of a genetic predisposition. A better understanding of (early) cardiomyopathy phenotypes, related cardiovascular diseases, their underlying pathophysiological processes, and their related disease burden is key to pave the way for novel preventive and/or intervention studies. Objective: To optimize (early) diagnosis and risk-stratification of (early) cardiovascular diseases, specifically cardiomyopathy phenotypes, arrhythmias, and coronary artery disease, and to create a better understanding of underlying pathophysiological processes. Study design: The multicenter Cardiology Monitoring Platform registry (mCMP-registry) is an investigator-initiated multicentre prospective observational registry including multi-omics (diagnostic) measurements performed as part of routine clinical care, bio-banking (optional), and yearly questionnaires (optional). Study population: All subjects aged ≥16 years that have been referred to the cardiology or genetics department for cardiac symptoms, cardiac screening or cardiogenetic screening are eligible for inclusion. Main study parameters/endpoints: This is a prospective registry from which multiple research questions can be answered. In general, two main approaches will be used: (A) a data-driven (multi-)omics approach which aims to identify clusters of patients to predict clinical outcome, to improve (early) diagnosis, and/or to identify clusters of patients that share underlying pathophysiological processes; (B) a hypothesis-driven approach in which clinical parameters are tested for their (incremental) diagnostic and/or prognostic value. ;
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