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In the United States, 5 million individuals have heart failure. Each year, 550 000 new cases are diagnosed, and there are 1 million hospitalizations. The direct and indirect costs of heart failure are estimated at $29 billion per year. Although heart failure presents enormous healthcare burdens, outcomes in heart failure are highly variable, with annual mortality varying from 5% to 75%. Physicians need to counsel patients about prognosis to enable informed decisions about medications, devices, transplantation, and end-of-life care.

Previous heart failure (HF) risk models stratify patients into three risk groups using peak oxygen consumption (VO2). An individualized estimate of survival in HF has not been reported. The Seattle Heart Failure Model was derived by retrospectively investigating predictors of survival among 1,125 HF patients in PRAISE1 (NYHA 3B-4, EF<30%, ACEI, diuretics, 403 deaths). A stepwise Cox proportional hazard model was used to develop a multivariate risk model, which identified age, gender, ischemic etiology, NYHA, ejection fraction, systolic blood pressure, K-sparing diuretic use, statin use, allopurinol use, hemoglobin, % lymphocyte count, uric acid, sodium, cholesterol, and diuretic dose/kg as significant predictors of survival. The model was prospectively validated in 5 additional cohorts totaling 9942 heart failure patients and 17,307 person-years of follow-up. The Seattle Heart Failure Model provides an accurate estimate of 1-, 2-, and 3-year survival with the use of easily obtained clinical, pharmacological, device, and laboratory characteristics.

The model was developed by Drs. Wayne C. Levy, Dariush Mozaffarian, David T. Linker and co-authors as shown in the publication.

The Java applet to calculate the score was designed by Drs. Linker and Levy and programmed by Dr. David T. Linker.
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