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Project

Chronic inflammation and cardiovascular risk (INF-CVD)

Cardiovascular disease is the leading cause of death and illness globally. Preventive therapies can avoid or delay the occurrence of cardiovascular events, provided that one can identify individuals at risk and intervene before problems manifest. Recent scientific developments have established that inflammation has a prominent role in the development of cardiovascular diseases; but routine screening of inflammatory markers to assess cardiovascular risk in the general population is currently unfeasible. It is known however that certain diseases cause high and chronic inflammation, and patients affected by these conditions may be at increased risk of cardiovascular events. Yet, studies so far have been limited by the relatively modest absolute numbers of patients affected, so that for many of these conditions evidence is insufficient to guide clinical decisions.
The aim of this research proposal is to investigate the associations between a range of chronic inflammatory conditions and different types of cardiovascular disorders, by using one of the largest longitudinal healthcare datasets available for research purposes in the world. The study design leverages the potential of ‘big data’ to explore complex disease associations through a unique combination of skills – my own knowledge of epidemiology and experience with the studied data set; my host supervisor’s expertise in statistical models best suited for the analysis of longitudinal data; and interdisciplinary clinical expertise through an international network of collaborations.
A better understanding of cardiovascular risks associated with chronic inflammatory conditions may help guidelines and clinicians to focus on patients for which screening and treatments are more likely to have an effect, and improve the prevention of cardiovascular diseases. Differences between conditions may further point towards biological functions underlying these complications and inform the design of future research.

Date:2 Sep 2019 →  1 Sep 2021
Keywords:statistical models, inflammatory markers, cardiovascular risk
Disciplines:Cardiology, Biostatistics, Inflammation