Introduction: Symptomatic heart failure continues to confer a poor prognosis, with 1-year mortality averaging 50%. Risk or prognostic stratification is one of the pivotal activities in medical practice. Virtually all patient management decisions are driven by the clinician´s assessment of the patient´s prognosis.
Objectives: The purpose of the study was to develop the prognostic model to predict survival in elderly heart failure patients.
Material and Methods: 104 patients with CHF >74 years, average age 80±0,4 years, underwent diagnostic work-up, including medical history, physical examination, 6-min walking test, chest X-ray, ECG, echocardiography, blood test (including BNP) (in all 150 variables). A quality of life was assessed using a disease specific questionnaire - Minnesota Living with Heart Failure Questionnaire (MLHFQ). All patients were followed up for a median period of 2.5 years. Cox proportional hazards model was used to assess the association of variables with mortality.
Results: Within the 2.5 years follow-up period 70% of 104 CHF patients died. The strongest predictors were plasma BNP level and age. Age-BNP survival mathematical model is defined in the following way: S(t)=e(0,143*В+0,001*К)*Н(t), where S(t) is a survival function evaluated at time t, B is the age in years, K – plasma BNP level, H(t) is the basic risk function. The use of Age-BNP Survival Model based just of the determine plasma BNP level. Knowing patient´s age and his plasma BNP level we can define his 2.5-year survival probability (for each month) from day of BNP blood analysis.
Discussion: Patients 75 years and older are the majority of heart failure population. Patients of this age have two features: many co-diseases and low intensity of ambulatory care. An accurate prognosis estimating can help clinician´s to make optimal treatment decision.
Conclusions: The Age-BNP Survival Model provides accurate estimate of 2.5 years survival probability among elderly patients with heart failure.
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30 de Noviembre de 2009
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