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Cutoff Value of Phase Angle by Bioelectrical Impedance Analysis at Admission as a Prognostic Factor in Patients with Acute Heart Failure
Published on: June 10, 2025
Reasons why patients suffering from chronic heart failure at very high risk for death survive
Giovanni Cioffi1, Giovanni Pulignano2, Giulia Barbati3
1Cardiology Department, Villa Bianca Hospital Trento, Italy.
Insights
In chronic heart failure (CHF) patients with high risk scores, better renal function and higher body mass index predict survival. These factors help identify patients who may outlive expectations.
Area of Science:
- Cardiology
- Clinical Medicine
- Prognostics
Background:
- Accurate prognostic stratification is crucial for managing chronic heart failure (CHF).
- The Cardiac and Comorbid Conditions HF (3C-HF) Score aids in predicting mortality in CHF patients.
- Identifying high-risk patients optimizes clinical decisions.
Purpose of the Study:
- To characterize a subgroup of very high-risk CHF patients using the highest 3C-HF score decile.
- To identify predictors of survival in patients with an expected 1-year mortality rate near 45%.
Main Methods:
- Analysis of 1777 consecutive CHF patients from 3 Italian Cardiology Units.
- Focus on the 246 patients (13.8%) in the highest 3C-HF score decile.
- Cox regression multivariate analysis to determine survival predictors over a median 21-month follow-up.
Main Results:
- In the highest 3C-HF score decile, 55% of patients died within the follow-up period.
- Survival prediction was significantly influenced by a lower degree of renal dysfunction.
- Higher body mass index was also identified as a positive predictor of survival.
Conclusions:
- Prognostic stratification effectively selects high-risk CHF patients for targeted management.
- Lower renal dysfunction and higher body mass index are key factors for survival in high-risk CHF patients.
- These factors explain why some high-risk patients may have better outcomes than anticipated.
Background:
An accurate prognostic stratification is essential for optimizing the clinical management and treatment decision-making of patients with chronic heart failure (HF). Among the best available models, we used the Cardiac and Comorbid Conditions HF (3C-HF) Score, to predict all-cause mortality in patients with CHF.
Methods:
we selected and characterized the subgroup of patients at very high risk with the worst mid-term prognosis belonging to the highest decile of 3C-HF score with the aim to assess predictors of survival in subjects with an expected probability of 1-year mortality near to 45%.
Methods And Results:
We recruited 1777 consecutive chronic HF patients at 3 Italian Cardiology Units. Median age was 76 ± 10 years, 43% were female, and 32% had preserved ejection fraction. Subjects belonging to the highest decile of 3C-HF score were 246 (13.8% of total population). During a median follow-up of 21 [12-40] months, 110 of these patients (45%) survived and 136 (55%) died. The variables that contributed to survival prediction emerged by Cox regression multivariate analysis were the lower degree of renal dysfunction and higher body mass index.
Conclusions:
The prognostic stratification of chronic HF patients allows in daily practice to select patients at different risk for death and identify prognosticators of survival in outliers at very high risk of death. The reasons why these patients outlive the matching part of subjects who expectedly die are related to the maintenance of a satisfactory renal function and body mass index.
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