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The burden of cardiovascular disease (CVD) is considerable, despite many advances in diagnosis, clinical management and drug therapy. The World Health Organization estimates 30% of global deaths are attributable to CVD and whilst mortality rates in developed countries are falling, it remains the largest single cause of death (WHO, 2007). Nineteen out of every 100 deaths in Australia are attributed to CVD, with an annual cost of $1.47 billion (AIHW, 2006).
Assessing the risk of future cardiovascular events is traditionally based on a number of 'risk-factors' determined by observational clinical studies such as the Framingham cohort. Recent evidence however invalidates their use in both the highest and lowest risk groups and raises questions about applying such methods in changing risk-behaviour. A considerable number of new risk markers have surfaced in recent years (including various biomarkers, pulse wave velocity and measures of arterial function). Unfortunately their long-term predictive capacity is largely unknown, particularly when compared with existing risk factors.
The aims of this study are to provide objective longitudinal data for a wide variety of risk markers both in current use and in development. Participants of current on-going clinical studies at will be approached to lengthen their observation period for the purposes of determining long-term clinical outcomes.
Standard clinical observations and data obtained within the participant's enrolled studies will be collated into an electronic database. All existing and future studies must have individual approval from an appropriate ethics committee with signed consent. The baseline studies and follow-up assessments of this cohort will be correlated with cardiovascular events, hospitalizations and mortality. In addition, volunteers can be directed to appropriate clinical studies in CVD, thereby enhancing recruitment, encouraging good quality clinical studies and advancing knowledge of cardiovascular disease prevention.
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Design: Longitudinal cohort study
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Data sourced from clinicaltrials.gov
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