Clinical Impact of Multimarker Diagnostics on Risk Stratification and Management of Chronic Heart Failure

Background: Chronic heart failure (CHF) is a progressive clinical syndrome associated with high morbidity, mortality, and healthcare burden worldwide. Accurate risk stratification remains a cornerstone for optimizing therapeutic strategies and improving outcomes. Traditional diagnostic approaches relying on single biomarkers are limited in their ability to reflect the complex and multifactorial pathophysiology of CHF. Objective: This study aimed to evaluate the clinical impact of a multimarker diagnostic strategy on risk stratification and management of patients with chronic heart failure. Methods: A prospective observational study included 180 patients diagnosed with CHF (NYHA II–IV). Serum concentrations of key biomarkers representing myocardial stress, fibrosis, and inflammation were measured, including NT-proBNP, Galectin-3, and soluble ST2. Patients were followed for 12 months to assess major adverse cardiovascular events (MACE), including all-cause mortality and heart failure–related hospitalization. Results: The multimarker model demonstrated significantly improved predictive performance compared with single biomarker assessment (AUC 0.88 vs 0.74, p<0.001). Patients with elevated levels of all three biomarkers had a threefold higher risk of adverse outcomes. Integration of multimarker data into clinical decision-making resulted in earlier therapy escalation and reduced rehospitalization rates. Conclusion: Multimarker diagnostics substantially enhance risk stratification and support more individualized management in chronic heart failure, potentially leading to improved clinical outcomes.

Hali tarjima qilinmagan