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Updated: Aug 26, 2026

Lumped-Parameter and Finite Element Modeling of Heart Failure with Preserved Ejection Fraction
Published on: February 13, 2021
A multivariate model for predicting mortality in patients with heart failure and systolic dysfunction
James M Brophy1, Gilles R Dagenais, Frances McSherry
1Division of Cardiology and Clinical Epidemiology, McGill University Health Center, Montréal, Quebec, Canada. jbroph@po-box.mcgill.ca
Background:
Heart failure is a leading cause of morbidity and mortality, but there are no reliable models based on readily available clinical variables to predict outcomes in patients taking angiotensin-converting enzyme (ACE) inhibitors.
Methods:
A multivariate statistical model to predict mortality was developed in a random sample (n = 4277 patients [67%]) of the 6422 patients enrolled in the Digitalis Investigation Group trial who had a depressed ejection fraction (
Results:
Total mortality in the derivation sample was 11.2% (n = 480) at 12 months and 29.9% (n = 1277) at 36 months. Lower ejection fraction, worse renal function, cardiomegaly, worse functional class, signs or symptoms of heart failure, lower blood pressure, and lower body mass index were associated with reduced 12-month survival. This model provided good predictions of mortality in the verification sample. The same variables, along with age and the baseline use of nitrates, were also predictive of 36-month mortality.
Conclusion:
Routine clinical variables can be used to predict short- and long-term mortality in patients with heart failure and systolic dysfunction who are treated with ACE inhibitors.
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