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Studies of the Epidemiology and Prognosis of Patients with Heart Failure in Leicestershire

By James Douglas Newton


Background - Heart failure (HF) is a major disease with high mortality despite many therapeutic options. Little is known on the epidemiology and prognosis of HF in Leicestershire, which includes a large proportion of South Asians. \ud Hypotheses - The epidemiology of heart failure in Leicestershire is different to that of published national and international cohorts. South Asians have more severe coronary disease compared to Caucasians, and will have more severe HF and increased mortality. Simple clinical data on admission can be used to predict survival. \ud Methods - Matched cohort design with retrospective data collection on 528 patients - 176 South Asians age and sex matched to 352 Caucasians admitted with a validated new diagnosis of HF between April 1998 and March 2001. Cox proportional hazards modelling to test variables associated with outcome and develop a prognostic model. \ud Results - The majority of HF is secondary to ischaemic heart disease or hypertension. Two-thirds of patients undergo echocardiography. Only 60% of patients are discharged with an ACE inhibitor, just 17% receive a beta blocker. 11% died during admission, and by the end of follow up 45% had died. South Asians have higher rates of hypertension and diabetes and present earlier with less severe impairment of systolic function. South Asians have lower mortality - odds ratio of 0.71 (95% CI 0.53 – 0.96, p=0.02) compared to Caucasians. A prognostic score based on five simple variables stratifies patients into low or high risk with a sensitivity 78% of and specificity of 57%. \ud Conclusion - The epidemiology of patients admitted with HF in Leicestershire is not significantly different to published cohorts. South Asian patients present with less severe ventricular dysfunction and survive for longer with no differences in the investigations or treatment given compared to Caucasians. A pragmatic risk prediction model using easily available clinical variables can identify high risk individuals

Publisher: University of Leicester
Year: 2009
OAI identifier: oai:lra.le.ac.uk:2381/8263

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