The evaluation of a patient would be incomplete without an initial and periodic assessment of short- and long-term prognosis. However, the likelihood of survival can be determined reliably only in populations and not in individual patients. Numerous factors have been used as prognostic indicators including demographics (age, sex, race), symptoms (New York Heart Association [NYHA] classification), comorbidities (hypertension, diabetes, cachexia, anemia, and renal and hepatic dysfunction), and objective clinical parameters (e.g., ejection fraction, left ventricular size, volume, mass and shape, exercise capacity, and serum levels of sodium, norepinephrine, renin, B-type natriuretic peptide, uric acid, angiotensin II, aldosterone, tumor necrosis factor-alfa, endothilin). Multivariate analysis of these variables has helped to identify the most significant predictors of survival, and prognostic models have been developed and validated. However, all existing models to predict the risk of death or need for urgent transplantation have features that may limit their applicability. Hemoglobin A1c was also found to be an independent progressive risk factor for cardiovascular death, hospitalization, and mortality, even in nondiabetic patients.
The most comprehensive prognostic model is the Seattle Heart Failure Model. The Seattle Heart Failure Model external link opens in a new window This model has been implemented as an interactive program that employs the Seattle Heart Failure Score to estimate mean, 1-, 2-, and 5-year survival and the benefit of adding medications and/or devices for an individual patient.
Despite standard medical therapy the survival for patients with end-stage heart failure is poor.
Despite optimal medical therapy including cardiac resynchronization therapy, only 65% of patients in NYHA class 4 are alive at a mean follow-up of 17 months.
The 5-year survival in patients with stage D heart failure is only 20%.
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