Predictors of mortality and morbidity in patients with chronic heart failure.


Pocock, SJ; Wang, D; Pfeffer, MA; Yusuf, S; McMurray, JJ; Swedberg, KB; Ostergren, J; Michelson, EL; Pieper, KS; Granger, CB; (2006) Predictors of mortality and morbidity in patients with chronic heart failure. European heart journal, 27 (1). pp. 65-75. ISSN 0195-668X DOI: https://doi.org/10.1093/eurheartj/ehi555

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Abstract

AIMS: We aimed to develop prognostic models for patients with chronic heart failure (CHF). METHODS AND RESULTS: We evaluated data from 7599 patients in the CHARM programme with CHF with and without left ventricular systolic dysfunction. Multi-variable Cox regression models were developed using baseline candidate variables to predict all-cause mortality (n=1831 deaths) and the composite of cardiovascular (CV) death and heart failure (HF) hospitalization (n=2460 patients with events). Final models included 21 predictor variables for CV death/HF hospitalization and for death. The three most powerful predictors were older age (beginning >60 years), diabetes, and lower left ventricular ejection fraction (EF) (beginning <45%). Other independent predictors that increased risk included higher NYHA class, cardiomegaly, prior HF hospitalization, male sex, lower body mass index, and lower diastolic blood pressure. The model accurately stratified actual 2-year mortality from 2.5 to 44% for the lowest to highest deciles of predicted risk. CONCLUSION: In a large contemporary CHF population, including patients with preserved and decreased left ventricular systolic function, routine clinical variables can discriminate risk regardless of EF. Diabetes was found to be a surprisingly strong independent predictor. These models can stratify risk and help define how patient characteristics relate to clinical course.

Item Type: Article
Faculty and Department: Faculty of Epidemiology and Population Health > Dept of Medical Statistics
PubMed ID: 16219658
Web of Science ID: 233848200016
URI: http://researchonline.lshtm.ac.uk/id/eprint/12848

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