Comparison of Two Risk Calculators Based on Clinical Variables (MAGGIC and BCN Bio-HF) in Prediction of All-Cause Mortality After Acute Heart Failure Episode

Gallego-Cuenca, Alejandro ; Bueno-Juana, Esperanza ; Campos-Sáenz de Santamaría, Amelia (Universidad de Zaragoza) ; Garcés-Horna, Vanesa (Universidad de Zaragoza) ; Sánchez-Marteles, Marta (Universidad de Zaragoza) ; Pérez-Calvo, Juan I. ; Giménez-López, Ignacio ; Rubio-Gracia, Jorge (Universidad de Zaragoza)

Resumen: Background: Heart failure (HF) is common and deadly, affecting over 60 million people worldwide, and it remains a leading cause of hospitalization and post-discharge death. One-year mortality after an acute decompensated HF (ADHF) admission often approaches 40%. Prognostic models are critical for stratifying mortality risk in heart failure (HF) patients. This study compared the performance of the MAGGIC and BCN Bio-HF models in predicting 1-year and 3-year all-cause mortality (ACM) in patients discharged after acute decompensated HF (ADHF). Methods: A retrospective analysis was conducted on 229 patients hospitalized for ADHF at the Clinical University Hospital of Zaragoza. The required variables were extracted from medical records, and ACM risks were calculated using web-based tools. Calibration, discrimination (AUC), and Kaplan–Meier survival analysis and calibration curves assessed risk stratification and alignment with observed outcomes. Reclassification metrics (Net Reclassification Index [NRI], Integrated Discrimination Improvement [IDI]) were used to compare the models’ predictive performances. Results: Both of the models demonstrated robust discrimination for 1-year ACM (AUC: MAGGIC = 0.738, BCN Bio-HF = 0.769) but showed lower performance for 3-year predictions. Calibration was poor, with both models exhibiting significant risk underestimation at the individual level. MAGGIC achieved higher sensitivity (1-year: 0.911; 3-year: 0.685), favoring high-risk patient identification, whereas BCN Bio-HF offered superior specificity (1-year: 0.679; 3-year: 0.746) and a positive prediction value, reducing false positives. BCN Bio-HF showed a significant 12.7% reclassification improvement for 1-year mortality prediction. Conclusions: BCN Bio-HF did not outperform MAGGIC in our cohort. MAGGIC is preferable for the initial high-risk patient identification, requiring more intense short-term follow-up, while BCN Bio-HF’s higher specificity is best-suited to avoid overtreatment. Altogether, the clinical utility of both models was limited in our cohort by severe miscalibration, which may render adequate risk stratification difficult.

Idioma: Inglés

DOI: 10.3390/hearts6040026

Año: 2025

Publicado en: Hearts (Basel) 6, 4 (2025), 26 [17 pp.]
ISSN: 2673-3846

Financiación: info:eu-repo/grantAgreement/ES/DGA/B07-23R

Tipo y forma: Artículo (Versión definitiva)

Área (Departamento): Area Medicina (Dpto. Medicina, Psiqu. y Derm.)