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The MESA heart failure risk score: can't we do more?
  1. Jennifer E Ho1,2,
  2. Jared W Magnani1,2
  1. 1Department of National Heart, Lung and Blood Institute's and Boston University's Framingham Heart Study, Framingham, Massachusetts, USA
  2. 2Section of Cardiovascular Medicine, Department of Medicine, Boston University, Boston, Massachusetts, USA
  1. Correspondence to Dr Jared W Magnani, Section of Cardiovascular Medicine, Boston University School of Medicine, 88 E. Newton Street, Boston 02118, MA, USA; jmagnani{at}

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In 1987, Framingham Heart Study pioneer Dr William B Kannel1 wrote, ‘Epidemiologic data on incidence and prognosis of cardiac failure in the general population are actually quite sparse.’ Dr Kannel proceeded to report risk factors for heart failure identified in Framingham that included hypertension, ECG LV hypertrophy, obesity, diabetes, radiographic cardiac enlargement and cigarette use. Over the last decades heart failure epidemiology has been informed by advances in cardiac imaging, identification of novel biomarkers and refinements in pathophysiology and classification.

The exposures listed by Dr Kannel remain salient to heart failure risk. However, many individuals develop cardiovascular disease even in their absence. Risk assessment is refined by the integration of imaging, biomarkers and novel assessments. Risk scores are fundamental and essential for advancing risk prediction, and serve multiple functions to enhance epidemiological and clinical assessment. First, risk scores provide an avenue to integrate established exposures with novel, contemporary assessments in risk quantification. Second, risk scores may target at-risk populations and refine clinical definitions—such as ‘stage A’ and ‘stage B’ heart failure, for example—with the goal of disease prevention. Third, individualised risk scores can provide personal assessments of risk, be a tool for patient education or focus efforts to optimise prevention. Ultimately, the utility of a risk score is determined by its clinical relevance: can it be employed to target preventive strategies in heart failure, and ‘turn back the clock’ for a disease where the median survival upon diagnosis is as dismal as 5 years?2 Is it relevant to diverse populations? Can the addition of novel imaging or biomarkers be implemented in a cost-effective manner?

To our knowledge, three major, observational, community-based cohort studies have published heart failure risk scores. In 1999, Kannel et al3 described the probability of heart failure in Framingham participants with coronary disease, hypertension or …

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