European Heart Journal Advance Access originally published online on October 11, 2005
European Heart Journal 2006 27(1):65-75; doi:10.1093/eurheartj/ehi555
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Predictors of mortality and morbidity in patients with chronic heart failure
1Medical Statistics Unit, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK
2Department of Medicine, Brigham and Women's Hospital, Boston, USA
3Hamilton Health Sciences and McMaster University, Hamilton, ON, Canada
4University of Glasgow, Glasgow, UK
5Sahlgrenska University Hospital, Ostra, Goteborg, Sweden
6Karolinska Hospital, Stockholm, Sweden
7AstraZeneca LP, Wilmington, DE, USA
8Duke Clinical Research Institute, Durham, NC, USA
Received 6 May 2005; revised 30 August 2005; accepted 8 September 2005; online publish-ahead-of-print 11 October 2005.
* Corresponding author. Tel: +44 207 927 2413; fax: +44 207 637 2853. E-mail address: stuart.pocock{at}lshtm.ac.uk
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.
Key Words: Chronic heart failure • Clinical trial database • Risk score • Prognostic models • Mortality • Hospitalization
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