Related Experiment Video

Updated: Oct 19, 2025

Cutoff Value of Phase Angle by Bioelectrical Impedance Analysis at Admission as a Prognostic Factor in Patients with Acute Heart Failure
05:16

Cutoff Value of Phase Angle by Bioelectrical Impedance Analysis at Admission as a Prognostic Factor in Patients with Acute Heart Failure

Published on: June 10, 2025

319

Head-to-head comparison of contemporary heart failure risk scores

Pau Codina1,2, Josep Lupón1,2,3, Andrea Borrellas1

  • 1Heart Failure Clinic and Cardiology Service, University Hospital Germans Trias i Pujol, Badalona, Spain.

European Journal of Heart Failure
|September 24, 2021
PubMed

Insights

Comparing heart failure risk scores, the Barcelona Bio-Heart Failure (BCN-Bio-HF) calculator showed the best performance, though it overestimated risk. Regular updates are needed for these clinical tools.

Area of Science:

  • Cardiology
  • Medical Informatics
  • Biostatistics

Background:

  • Several web-based risk scores exist for heart failure (HF) management.
  • A direct comparison of their accuracy and predictive performance is lacking.

Purpose of the Study:

  • To compare the accuracy and mortality prediction performance of four HF risk scores: MAGGIC-HF, SHFM, PREDICT-HF, and BCN-Bio-HF.
  • To assess the correlation between these risk scores.

Main Methods:

  • 1166 HF patients with NT-proBNP measurements were analyzed.
  • Mortality prediction was evaluated using Harrell's C-statistic (1-5 years).
  • Calibration and overall performance were assessed using calibration plots, Hosmer-Lemeshow test, and Nagelkerke's R².

Main Results:

  • Correlation between scores was relatively poor (Spearman's rho 0.66-0.79).
  • The Seattle Heart Failure Model (SHFM) demonstrated the highest discrimination for 1-year mortality (0.817).
  • The Barcelona Bio-Heart Failure (BCN-Bio-HF) calculator showed the best overall discrimination and performance across time points, despite overestimating risk.

Conclusions:

  • No single contemporary risk score demonstrated clear superiority.
  • The BCN-Bio-HF calculator offered the best discrimination and overall performance.
  • MAGGIC-HF exhibited the best calibration, while SHFM and PREDICT-HF tended to underestimate risk.
  • Periodic updates and recalibration of HF risk calculators are essential for maintaining accuracy.
Abstract

Keywords:
Heart failureMortalityRisk modelsRisk prediction

More Related Videos

An R-Based Landscape Validation of a Competing Risk Model05:37

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

2.3K
Lumped-Parameter and Finite Element Modeling of Heart Failure with Preserved Ejection Fraction09:20

Lumped-Parameter and Finite Element Modeling of Heart Failure with Preserved Ejection Fraction

Published on: February 13, 2021

6.7K

Related Concept Videos

Heart Failure IV: Classification and Diagnostic Evaluation01:30

Heart Failure IV: Classification and Diagnostic Evaluation

Heart failure can be classified in various ways, with the most common classifications based on physical activity limitations, disease progression, severity, and treatment strategies.The Functional Classification of Heart Failure divides patients into four categories based on physical activity limitation due to symptom burden.Class I: Patients in this class have cardiac disease but no physical activity limitations. Ordinary activities like walking, climbing stairs, or routine tasks do not cause...
74
Heart Failure I: Introduction01:27

Heart Failure I: Introduction

Heart failure refers to a clinical syndrome caused by structural or functional cardiac disorders that prevent the heart from pumping an adequate amount of blood to meet the body's metabolic needs. This condition often arises from myocardial infarction or ischemia, leading to decreased cardiac output, reduced tissue perfusion, impaired gas exchange, fluid volume imbalance, and decreased functional ability.Heart failure can result from disruptions in the mechanisms that regulate cardiac output...
157
Pathophysiology of Heart Failure01:17

Pathophysiology of Heart Failure

Heart failure (HF) is a progressive syndrome involving ventricles that leads to inadequate cardiac output. It can be classified based on location and output or ejection fraction. Ejection fraction (EF) is an essential measurement in the diagnosis and surveillance of HF. Reduced EF corresponds to systolic heart failure (HFrEF). However, HF with preserved ejection fraction (HFpEF) is becoming increasingly prevalent. Also known as diastolic HF, this form of HF is related to aging. The...
2.0K
Heart Failure II: Pathophysiology01:29

Heart Failure II: Pathophysiology

Systolic Heart Failure and Compensatory MechanismsSystolic heart failure (also termed HFrEF, Heart Failure with Reduced Ejection Fraction) is the most prevalent type of heart filure. It results in a decreased volume of blood being pumped from the ventricle. The aortic arch and carotid sinuses have baroreceptors that detect reduced blood pressure, triggering the sympathetic nervous system (SNS) to release epinephrine and norepinephrine. Initially, this response aims to boost heart rate and...
105
Relative Risk01:12

Relative Risk

Relative risk (RR) is a statistical measure commonly used in epidemiology to compare the likelihood of a particular event occurring between two groups. This metric is important for evaluating the relationship between exposure to a specific risk factor and the probability of a particular outcome. It plays a crucial role in medical research, public health studies, and risk assessment. Relative risk quantifies how much more (or less) likely an event is to occur in an exposed group compared to an...
550
Heart Failure V: Medical Management01:30

Heart Failure V: Medical Management

Medical Management of Acute Decompensated Heart Failure (ADHF)The primary goals of therapy for patients hospitalized with acute decompensated heart failure (ADHF) include:Relieving symptomsOptimizing volume statusSupporting oxygenation and ventilationMaintaining cardiac output (CO) and end-organ perfusionIdentifying and addressing the cause of ADHFPreventing complicationsProviding patient education on factors precipitating HF exacerbationPlanning for dischargeOngoing monitoring and assessment...
52