• heart failure
• risk prediction

Estimating prognosis is endorsed by recent clinical guidelines as a key element of the management of heart failure.^1,2 How this is to be done is less clear. Heart failure follows a variable clinical course, and as many as one half of patients will die suddenly rather than dying of progressive heart failure.³ The predictability of death may therefore be lower than in other conditions. The challenge of identifying clinical variables consistently associated with mortality has been summarised by Cowburn and colleagues.⁴ Many of the published studies are small, and include highly selected patient populations, with different variables recorded in each dataset. Differences in the way measurements are made—for example, in the assessment of left ventricular systolic function—and the close correlation between many variables add further complexity. Also, it should not be assumed that the same variables will be associated with mortality in the early phases of heart failure as well as in the later phases. The recent rise in the use of β blockade may make the conclusions drawn from earlier studies less relevant to modern practice. From the statistical viewpoint, the methodology of how best to use available data and to validate the derived risk equations is rapidly evolving.^5,6

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