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Updated: Sep 26, 2025
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Lumped-Parameter and Finite Element Modeling of Heart Failure with Preserved Ejection Fraction
Published on: February 13, 2021
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Minimal subphenotyping model for acute heart failure with preserved ejection fraction
Yohei Sotomi1, Taiki Sato1, Shungo Hikoso1
1Department of Cardiovascular Medicine, Osaka University Graduate School of Medicine, Osaka, Japan.
ESC Heart Failure
|April 22, 2022
Summary
A simplified 16-variable model accurately classifies heart failure with preserved ejection fraction (HFpEF) phenotypes. This reduced model enhances clinical application of HFpEF subtyping for improved patient outcomes.
Area of Science:
- Cardiology
- Biostatistics
- Clinical Research
Background:
- Acute heart failure with preserved ejection fraction (HFpEF) is heterogeneous.
- Latent class analysis identified four distinct HFpEF phenotypes with varying outcomes.
- The original 32-variable model is too complex for routine clinical use.
Purpose of the Study:
- To identify a minimal set of variables for accurate HFpEF subphenotyping.
- To develop a simplified model for clinical application.
Main Methods:
- Post hoc analysis of the PURSUIT-HFpEF study (N=1095).
- Latent class analysis was previously applied to establish a 32-variable model.
- Cohen's kappa statistic was used to compare classification accuracy with reduced variable sets.
Main Results:
- A 16-variable model demonstrated high agreement (kappa >0.8) with the full 32-variable model.
- The 16 variables include biomarkers, clinical factors, and risk scores.
- The four identified phenotypes ('rhythm trouble', 'ventricular-arterial uncoupling', 'low output and systemic congestion', 'systemic failure') showed consistent characteristics and outcomes.
Conclusions:
- A 16-variable model provides accurate HFpEF phenotyping.
- This minimal model simplifies classification and enhances potential clinical utility.
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