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Published on: June 10, 2025
Risk score model for predicting mortality in advanced heart failure patients followed in a heart failure clinic
Barak Zafrir1, Yaron Goren, Hagar Paz
1Department of Cardiovascular Medicine, Lady Davis Carmel Medical Center and the Ruth and Bruce Rappaport School of Medicine, Technion-Israel Institute of Technology, Haifa, Israel. barakz@bezeqint.net
Insights
A new risk score model accurately predicts mortality in chronic heart failure (HF) patients using simple, noninvasive factors. This tool aids therapeutic decisions for better HF management and improved patient outcomes.
Area of Science:
- Cardiology
- Clinical Medicine
- Health Services Research
Background:
- Increasing prevalence of heart failure (HF) contributes to high rehospitalization and mortality rates.
- Effective prognostic tools are crucial for managing chronic HF and guiding treatment decisions.
Purpose of the Study:
- To develop and validate a prognostic risk score model for patients with chronic heart failure (HF).
- To identify key clinical, functional, laboratory, and therapeutic variables associated with mortality in HF patients.
Main Methods:
- A cohort of 500 chronic HF patients was followed for 25 months.
- Multivariate analysis was used to develop a risk score model based on predictors of mortality.
- The model's predictive performance was compared to the Seattle Heart Failure Model.
Main Results:
- Key predictors of mortality included low systolic blood pressure, male sex, advanced age, reduced 6-minute walk distance, lack of beta-blocker therapy, hyperuricemia, hyponatremia, and prolonged QTc interval.
- The developed risk score (0-55) stratified patients into low, moderate, high, and very high-risk groups with distinct 2-year mortality rates (9% to 62%).
- The new model demonstrated superior discrimination (concordance index 0.75) compared to the Seattle Heart Failure Model (0.69).
Conclusions:
- Simple, noninvasive factors assessed at initial HF clinic admission can serve as effective prognostic markers.
- This risk score model can aid in therapeutic decision-making for patients with chronic heart failure.
- The model offers a valuable tool for risk stratification and personalized management of HF.
Abstract:
The prevalence of heart failure (HF) in the population is increasing, concomitant with high incidence of rehospitalizations and mortality. The aim of this study was to characterize a prognostic risk score model for patients with chronic HF. A total of 500 patients followed at the HF clinic were evaluated by clinical, functional, laboratory, imaging, and therapeutic variables that were correlated to mortality during a follow-up period of 25 months. Risk stratification was carried out by applying a risk score model based on multivariate analysis. Predictors correlated with mortality during follow-up were systolic blood pressure <110 mm Hg, male sex, age older than 70 years, 6-minute walk distance <300 m, lack of β-blocker therapy, hyperuricemia (>7.5 mg/dL), hyponatremia, and prolonged QTc interval (>450 ms). Based on these variables, a risk score model (score 0-55) was established and included low risk, score <21 (9% mortality during 2-year follow-up); moderate risk, 21 to 29 (22%); high risk, 30 to 35 (35%), and very high risk: ≥36 points (62% 2-year mortality). The risk model had good discrimination ability (concordance index 0.75), which was better than the performance of the Seattle Heart Failure Model on our cohort (0.69). Simple noninvasive characteristics examined during the initial admission to the HF clinic can serve as prognostic markers for mortality and may help in the process of therapeutic decision-making in patients with HF.
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