Risk stratification after hospitalization for decompensated heart failure.

Published

Journal Article

BACKGROUND: Decompensated heart failure (HF) is among the most common indications for hospitalization in the United States, but little is known about features on admission that predict adverse events. We used data from the Outcomes of a Prospective Trial of Intravenous Milrinone for Exacerbations of Chronic Heart Failure (OPTIME-CHF) study to develop a model that would predict outcomes in patients with decompensated HF. METHODS AND RESULTS: OPTIME-CHF randomized 949 patients hospitalized with decompensated HF for 48 to 72 hours of infusion of either milrinone or placebo. We used multivariable modeling to evaluate variables on admission that would be predictive of 60-day mortality or the composite of death or rehospitalization at 60 days. Variables at presentation that predicted death at 60 days were increased age, lower systolic blood pressure, New York Heart Association class IV symptoms, elevated blood urea nitrogen (BUN), and decreased sodium. Predictors of the composite of death or rehospitalization within 60 days were the number of HF hospitalizations in the preceding 12 months, elevated BUN, lower systolic blood pressure, decreased hemoglobin, and a history of percutaneous coronary intervention (PCI). The discriminatory power of the model was substantial for the mortality model (c-index .77) but less for the composite endpoint (c-index .69). CONCLUSIONS: Risk stratification of patients with decompensated HF may be accomplished using easily assessed clinical variables. Further research into the validity of this model in independent samples will potentially aid in the development of risk stratification strategies.

Full Text

Duke Authors

Cited Authors

  • Felker, GM; Leimberger, JD; Califf, RM; Cuffe, MS; Massie, BM; Adams, KF; Gheorghiade, M; O'Connor, CM

Published Date

  • December 2004

Published In

Volume / Issue

  • 10 / 6

Start / End Page

  • 460 - 466

PubMed ID

  • 15599835

Pubmed Central ID

  • 15599835

Electronic International Standard Serial Number (EISSN)

  • 1532-8414

International Standard Serial Number (ISSN)

  • 1071-9164

Digital Object Identifier (DOI)

  • 10.1016/j.cardfail.2004.02.011

Language

  • eng