A simple clinically based predictive rule for heart failure in-hospital mortality

J Card Fail. 2006 Oct;12(8):587-93. doi: 10.1016/j.cardfail.2006.06.475.

Abstract

Background: Scarce data are available to predict in-hospital mortality for decompensated heart failure (HF) in South American populations.

Methods and results: We evaluated 779 consecutive HF admissions defined by the Boston criteria in a tertiary care hospital. Stepwise logistic regression was used to determine independent correlates of in-hospital mortality, derived from 83 potential predictors collected on hospital admission. A clinical score rule (HF Revised Score) was created using the regression coefficient estimates derived from multivariate modeling. During hospital stay, 77 (10%) deaths occurred and 6 clinical characteristics were independently associated with in-hospital mortality: presence of cancer (P < .001), systolic blood pressure < or =124 mm Hg (P < .001), serum creatinine >1.4 mg/dL (P = .02), blood urea nitrogen >37 mg/dL (P = .03), serum sodium <136 mEq/L (P = .03), and age >70 years old (P = .03). Both the Acute Decompensated Heart Failure National Registry stratification algorithm and the proposed HF Revised Score performed adequately to predict in-hospital mortality ("c" statistics = 0.71 and 0.76, respectively). The newly proposed score, however, discriminated a very low-risk group (101 [13%]) in whom all patients were discharged home, representing patients admitted with none of the 6 predictors of risk.

Conclusion: HF risk stratification can be accurately accomplished during the first day of admission with simple and easily obtained clinical variables.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Aging
  • Blood Pressure
  • Blood Urea Nitrogen
  • Cohort Studies
  • Creatinine / blood
  • Female
  • Heart Failure / complications
  • Heart Failure / mortality*
  • Heart Failure / physiopathology*
  • Hospital Mortality*
  • Humans
  • Logistic Models
  • Male
  • Middle Aged
  • Models, Theoretical
  • Multivariate Analysis
  • Neoplasms / complications
  • Predictive Value of Tests
  • Prognosis
  • Risk Assessment / methods
  • Sodium / blood

Substances

  • Sodium
  • Creatinine