Novel Risk Prediction Approaches for the Primary Prevention of Cardiovascular Diseases in Italy: the CVRISK-IT Trial (CVRISK-IT)

Recruiting now · Not applicable

Conditions studied: Cardiovascular Risk, Genetic Cardiovascular Risk

In brief

The CVRISK-IT study aims to evaluate the health benefit of measuring genetic and imaging risk information in men and women considered at 'low-to-moderate' or 'high' risk of developing cardiovascular diseases (CVD) in a randomized controlled trial in Italian primary care settings. Our primary objective is to answer a fundamental question in the prevention and prediction of CVD in Italy and globally: is there any benefit in including additional information (such as genetic and/or imaging data) in estimating risk, in conjunction with lifestyle advice and medical treatment for primary prevention of CVD? As a key secondary objective of the CVRISK-IT study, the goal is to build a large bioresource with clinical information and biological samples to facilitate a new generation of discovery and translational research that will advance understanding of the genetic, molecular and behavioural determinants as well as mechanisms of multiple chronic diseases in the Italian population. By contributing to the Rete Cardiologica database and the BBDCARDIO biobank, the CVRISK-IT study will also serve as a cornerstone for future investigations into the development and testing of early diagnostic technologies and preventive (or 'personalised precision health') interventions for chronic diseases.

Key facts

Study ID
NCT06832644
Run by
IRCCS Policlinico S. Donato
People needed
30000
Starts
2025-01-22
Expected to finish
2030-01-01
Last updated by the study team
2026-01-14

Who can join

Age: 40 and older, up to 80. Sex: any. Healthy volunteers: accepted.

You may qualify if…

You may not qualify if…

Where it is running

Full record on ClinicalTrials.gov

Trial information comes from ClinicalTrials.gov and is refreshed daily. TrialsForMe does not provide medical care and does not run the studies it lists.