From statistical significance to clinical relevance: A simple algorithm to integrate brain natriuretic peptide and the Seattle Heart Failure Model for risk stratification in heart failure.

ABSTRACT:

Background

Heart failure (HF) guidelines recommend brain natriuretic peptide (BNP) and multivariable risk scores, such as the Seattle Heart Failure Model (SHFM), to predict risk in HF with reduced ejection fraction (HFrEF). A practical way to integrate information from these 2 prognostic tools is lacking. We sought to establish a SHFM+BNP risk-stratification algorithm.

Methods

The retrospective derivation cohort included consecutive patients with HFrEF at the Mayo Clinic. One-year outcome (death, transplantation or ventricular assist device) was assessed. The SHFM+BNP algorithm was derived by stratifying patients within SHFM-predicted risk categories (≤2.5%, 2.6% to ≤10%, >10%) according to BNP above or below 700 pg/ml and comparing SHFM-predicted and observed event rates wi

SUBMITTER: AbouEzzeddine OF 

PROVIDER: S-EPMC4917454 | biostudies-literature | 2016 Jun

REPOSITORIES: biostudies-literature