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Predictors of mortality and morbidity in patients with chronic heart failure
Stuart J Pocock1, Duolao Wang, Marc A Pfeffer
1Medical Statistics Unit, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK. stuart.pocock@lshtm.ac.uk
European Heart Journal
|October 13, 2005
Summary
Prognostic models for chronic heart failure (CHF) identify key risk factors like age, diabetes, and low ejection fraction. These models accurately predict mortality and hospitalizations in diverse CHF patients.
Area of Science:
- Cardiology
- Clinical Research
- Predictive Modeling
Background:
- Chronic heart failure (CHF) affects millions globally, necessitating accurate risk stratification.
- Existing prognostic models may not fully capture risk across the spectrum of left ventricular systolic function.
Purpose of the Study:
- To develop and validate robust prognostic models for predicting mortality and cardiovascular events in a large chronic heart failure population.
- To identify key clinical predictors of adverse outcomes in patients with CHF, irrespective of ejection fraction.
Main Methods:
- Utilized data from 7599 patients in the CHARM program with varying degrees of left ventricular systolic function.
- Employed multi-variable Cox regression to build models predicting all-cause mortality and the composite of cardiovascular death/heart failure hospitalization.
- Identified 21 independent predictor variables for the final prognostic models.
Main Results:
- Older age (>60 years), diabetes, and lower left ventricular ejection fraction (<45%) were the strongest predictors of adverse outcomes.
- Other significant risk factors included higher NYHA class, cardiomegaly, prior heart failure hospitalization, male sex, lower BMI, and lower diastolic blood pressure.
- The developed models accurately stratified 2-year mortality risk across deciles, from 2.5% to 44%.
Conclusions:
- Routine clinical variables effectively stratify risk in chronic heart failure patients, regardless of ejection fraction.
- Diabetes emerged as a potent independent predictor of adverse outcomes in this CHF cohort.
- These validated models provide valuable tools for risk assessment and understanding the clinical course of chronic heart failure.
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