Health Improvements by Understanding the Determinants of Residual Risk in Coronary Artery Disease and New Targets for Prevention and Treatment

Condition(s) studied

Investigational drug(s) / intervention(s)

Cardiac CT: Cardiac CT to characterize coronary atherosclerosis

Study summary

Current medical treatments, in patients with stable coronary artery disease (CAD), mainly target established risk factors and are able to reduce morbidity and mortality but still leave a substantial residual risk of coronary artery disease progression and events. The main hypothesis of this study is that metabolic derangement, including pre-diabetes, elevated levels of triglycerides, low levels and functionality of high-density lipoprotein cholesterol, often associated with a chronic inflammatory state, is a currently unrecognized and undertreated conditon which could be the most relevant determinant of residual risk.

The goal of HURRICANE observational study is to discover specific individual genetic/molecular profiles subtending emerging cardiometabolic and vascular risk patterns and associating with a more severe and progressive coronary artery disease. We will thus develop and preliminary validate new predictive models for the recognition of high-risk patients and explore possible new targets for individualized preventive treatment.

The severity, extent and progression of coronary plaques will be assessed by qualitative and quantitative analysis of cardiac computed tomography (CCT) performed in retrospective and prospective cohorts of patients with stable coronary disease.

Eligibility

Primary outcome measure(s)

• Primary Objective — In the prospective Study patients will be evaluated at baseline and follow-up within a18 months time frame.
  The primary objective is the development (retrospective study) and validation (prospective study) of new integrated clinical and molecular/genetic predictive models of severity and extent of CAD defined by CCT in patients with stable disease. Developed models will be extended (prospective study) to the prediction of progression (at 1-year follow-up) of CAD phenotypes occurring despite OMT. The hypothesis is that these models, including specific molecular markers (assessed by traditional laboratory as well as by "omics" approaches) of emerging cardiometabolic and vascular risk, could predict CAD severity/extent and progression more accurately than other traditional risk models.

Trial sites (2)

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