Prognostic Models for People With Stable Coronary Artery Disease

There is currently no published algorithm for secondary prevention prognosis of CHD that is representative of the England GP-registered population and that includes both symptomatic and asymptomatic patients (as identified through primary care). In this paper the investigators will exploit routinely collected information in clinical practice to model CHD prognosis based on a large contemporary open cohort of stable CAD patients. Although the investigators model is based on data from GP practices in England only, the investigators believe that this population is sufficiently heterogeneous in terms of ethnic mix, socioeconomic background, predisposing characteristics and lifestyles to generate a prognostic model with good generalizing power to the wider population.

Among the research questions the investigators will try to answer is whether established risk factors for primary care prevention (smoking, hypertension, dyslipidaemia, diabetes) are also reliable for risk-stratification of patients who have already developed CAD. Similarly, the investigators will examine whether strong predictors of adverse outcomes in ACS patients in the short term, such as admission SBP and heart rate, are also associated with their long term prognosis.