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Published on: June 10, 2025
A simple clinically based predictive rule for heart failure in-hospital mortality
Luis E Rohde1, Lívia Goldraich, Carisi A Polanczyk
1Heart Failure and Cardiac Transplantation Unit, Cardiology Division at Hospital de Clínicas de Porto Alegre, Federal University of Rio Grande do Sul Medical School, Porto Alegre, Brazil.
Journal of Cardiac Failure
|October 19, 2006
Summary
A new clinical score accurately predicts in-hospital mortality for decompensated heart failure (HF) patients in South America using simple admission data. This HF Revised Score identifies low-risk individuals, improving patient care.
Area of Science:
- Cardiology
- Clinical Medicine
- Public Health
Background:
- Limited data exist for predicting in-hospital mortality in South American decompensated heart failure (HF) populations.
- Accurate risk stratification is crucial for managing HF admissions.
Purpose of the Study:
- To develop and validate a clinical score for predicting in-hospital mortality in decompensated HF patients.
- To identify simple, readily available clinical variables for early risk assessment.
Main Methods:
- A cohort of 779 consecutive HF admissions was evaluated.
- Stepwise logistic regression identified independent predictors of mortality from 83 variables.
- The HF Revised Score was developed using regression coefficients.
Main Results:
- In-hospital mortality was 10% (77 deaths).
- Six independent predictors of mortality were identified: cancer, low systolic blood pressure, elevated serum creatinine, elevated blood urea nitrogen, low serum sodium, and age >70.
- The HF Revised Score (c-statistic=0.76) demonstrated adequate predictive performance, outperforming the ADHERE algorithm (c-statistic=0.71) and identifying a low-risk group.
Conclusions:
- HF risk stratification is feasible on the first day of admission using simple clinical variables.
- The HF Revised Score offers an accurate and accessible tool for predicting mortality in HF patients.
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