Abstract 2803: Multiple Biomarkers For The Prediction Of Cardiac Events In Chronic Heart Failure Patients
Backgrounds: Chronic heart failure (CHF) still represents the major cause of death and hospitalization. Although there is substantial interest in the use of newer biomarkers to identify CHF patients (risk assessment and prevention for cardiac events) recently, few investigations have evaluated the incremental usefulness of combination of multiple biomarkers. Measurement of several biomarkers simultaneously could enhance risk stratification. We therefore evaluated the usefulness of 7 known biomarkers for predicting cardiac events.
Methods and Results: We analyzed 7 biomarkers (BNP, uric acid, Na, hemoglobin, creatinine, creatinine clearance, high sensitive CRP) which are known as established prognostic markers for CHF in consecutive 399 CHF patients. When there was an abnormal value, we scored it for one point to calculate multimarker score. Patients were categorized tertiles according to multimarker score. Patients with the high tertile were older and had more severe NYHA class and lower ejection fraction than those with low and intermediate tertiles. There were 135 cardiac events including cardiac deaths and readmissions for worsening CHF during follow-up period. A Cox proportional hazard model showed that patients with high tertile were associated with the highest risk of cardiac events compared with other two tertiles (Figure A⇓). Kaplan-Meier analysis revealed that tertile analysis effectively risk stratified CHF patients for cardiac events (Figure B⇓).
Conclusions: These findings suggest that the combination of the multi-biomarkers could potentially improve the risk stratification of CHF patiens for the prediction of cardiac events.