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Cardiovascular Disease Risk Estimation in People with Severe Mental Illness

Vera Morgan
Professor Vera Morgan

Cardiovascular Disease (CVD) risk prediction helps identify individuals with high CVD risk and so provides opportunities for risk reduction treatments. Since the Framingham CVD risk equations were first developed many decades ago, a number of new equations have been constructed to better estimate risk for populations of different ethnicities, younger ages or with different lifestyle factors compared to the original Framingham sample.

People with psychotic illness are a distinct population that warrants special attention in this area as, on average, they have earlier disease onset compared to the general population and may be exposed to some unique risk factors such as antipsychotic medication.

This project will identify several existing predictive risk equations for CVD and establish how well they perform in predicting incident CVD amongst people with psychotic disorders in a representative Australian sample.  Further, we will explore whether any improvements in prediction can be achieved by incorporating additional risk predictors, including those specific to people with psychotic disorders.

We plan to publish our findings in an academic journal to highlight the best approach/es for estimating 5-year CVD risk for people with psychotic disorders.

Research Team:

Patsy Di Prinzio1, Anna Waterreus1, Taryn Ambrosi1, Lee Nedkoff2, Vicki Palmer3, Matthew Lewis3, Steve Kisely4, Amanda Neil5, Susie Hincks1, Vera Morgan1

1 – Neuropsychiatric Epidemiology Research Unit, School of Population and Global Health, The University of Western Australia

2 – Cardiovascular Disease Research Group, School of Population and Global Health, The University of Western Australia

3 – University of Melbourne

4 – University of Queensland

5 – University of Tasmania

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