title: A simple clinically based predictive rule for heart failure in-hospital mortality.
abstract: BACKGROUND
  Scarce data are available to predict in-hospital mortality for decompensated heart failure (HF) in South American populations.
  
  
  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.
  
  
  CONCLUSIONS
  HF risk stratification can be accurately accomplished during the first day of admission with simple and easily obtained clinical variables.
authors.affiliation: Heart Failure and Cardiac Transplantation Unit, Cardiology Division at Hospital de Clínicas de Porto Alegre, Federal University of Rio Grande do Sul Medical School, Porto Alegre, Brazil.
authors.forename: Luis E
authors.initials: LE
authors.lastname: Rohde
authors.forename: Lívia
authors.initials: L
authors.lastname: Goldraich
authors.forename: Carisi A
authors.initials: CA
authors.lastname: Polanczyk
authors.forename: Aníbal Pires
authors.initials: AP
authors.lastname: Borges
authors.forename: Andréia
authors.initials: A
authors.lastname: Biolo
authors.forename: Eneida
authors.initials: E
authors.lastname: Rabelo
authors.forename: Luis
authors.initials: L
authors.lastname: Beck-Da-Silva
authors.forename: Nadine
authors.initials: N
authors.lastname: Clausell
mesh_terms: D000368:Aged; D000375:Aging; D001794:Blood Pressure; D001806:Blood Urea Nitrogen; D015331:Cohort Studies; D003404:Creatinine / Q000097:blood; D005260:Female; D006333:Heart Failure / Q000150:complications / Q000401:mortality* / Q000503:physiopathology*; D017052:Hospital Mortality; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D015999:Multivariate Analysis; D009369:Neoplasms / Q000150:complications; D011237:Predictive Value of Tests; D011379:Prognosis; D018570:Risk Assessment / Q000379:methods; D012964:Sodium / Q000097:blood
chemical_list: D012964:Sodium; D003404:Creatinine