A 3-Biomarker 2-Point-Based Risk Stratification Strategy in Acute Heart Failure

Area of Science:

• Cardiology
• Biomarker Research
• Prognostic Modeling

Background:

• Single-point biomarker measurements limit prognostic accuracy in acute heart failure (HF).
• Evaluating dynamic changes and combinations of biomarkers is crucial for improved risk stratification.

Purpose of the Study:

• To assess the prognostic value of NT-proBNP, hsTnT, Cys-C, hs-CRP, GDF15, and GAL-3 in HF patients at admission and discharge.
• To determine if a multi-biomarker approach improves 12-month mortality prediction compared to clinical models and existing scores.

Main Methods:

• Prospective, multicenter registry of 830 acute HF patients.
• Primary outcome: 12-month mortality.
• Statistical analysis included C-index, calibration, Net Reclassification Improvement (NRI), and Integrated Discrimination Improvement (IDI) on top of clinical models and established scores.

Main Results:

• The combination of NT-proBNP, hs-CRP, and GDF-15 at admission and discharge significantly improved 12-month mortality prediction (C-index 0.782, IDI 5%, NRI 57%).
• This 3-biomarker panel successfully stratified patients into four distinct risk categories for 12-month mortality.
• The novel model outperformed both the best clinical model and four commonly used risk scores.

Conclusions:

• A multi-biomarker model incorporating NT-proBNP, hs-CRP, and GDF-15 measured dynamically (admission and discharge) offers superior prognostic prediction in acute HF.
• This approach provides a more accurate and refined risk stratification tool for 12-month mortality compared to current methods.