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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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Four-variable risk model in men and women with heart failure
Jennifer Chyu1, Gregg C Fonarow, Chi Hong Tseng
1Division of Cardiology, University of Washington, Seattle.
Circulation. Heart Failure
|November 28, 2013
Summary
A simple risk model using four key variables accurately predicts outcomes in advanced heart failure patients, regardless of sex. This model is effective for both men and women with heart failure (HF).
Area of Science:
- Cardiology
- Clinical Decision Making
- Prognostic Modeling
Background:
- Risk stratification is crucial for heart failure (HF) management.
- Unique characteristics of women with HF necessitate evaluating prognostic factors.
- The accuracy of sex-specific risk models in advanced HF is not well-established.
Purpose of the Study:
- To investigate if sex-specific risk models improve risk prediction in advanced HF patients.
- To identify key prognostic factors for outcomes in men and women with advanced HF.
Main Methods:
- Analysis of 2255 advanced HF patients from UCLA, divided into derivation and validation cohorts.
- Cox regression analysis to identify predictors of death/urgent transplantation/ventricular assist device.
- Comparison of the UCLA model with the Seattle Heart Failure Model (SHFM) and Heart Failure Survival Score (HFSS).
Main Results:
- Women with HF were younger, had higher ejection fraction, and better event-free survival.
- B-type natriuretic peptide, peak oxygen consumption (pkVO2), NYHA class, and ACE inhibitor/ARB use were strong predictors in both sexes.
- The UCLA model demonstrated superior performance (c-index 0.791) compared to SHFM (0.758) and HFSS (0.607-0.625).
Conclusions:
- A simple risk model incorporating B-type natriuretic peptide, pkVO2, NYHA class, and ACE inhibitor/ARB use provides prognostic information in advanced HF.
- This four-variable model is effective for both men and women with advanced heart failure.
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