title: Clinical Implications of Cluster Analysis-Based Classification of Acute Decompensated Heart Failure and Correlation with Bedside Hemodynamic Profiles.
abstract: BACKGROUND
  Classification of acute decompensated heart failure (ADHF) is based on subjective criteria that crudely capture disease heterogeneity. Improved phenotyping of the syndrome may help improve therapeutic strategies.
  
  
  OBJECTIVE
  To derive cluster analysis-based groupings for patients hospitalized with ADHF, and compare their prognostic performance to hemodynamic classifications derived at the bedside.
  
  
  METHODS
  We performed a cluster analysis on baseline clinical variables and PAC measurements of 172 ADHF patients from the ESCAPE trial. Employing regression techniques, we examined associations between clusters and clinically determined hemodynamic profiles (warm/cold/wet/dry). We assessed association with clinical outcomes using Cox proportional hazards models. Likelihood ratio tests were used to compare the prognostic value of cluster data to that of hemodynamic data.
  
  
  RESULTS
  We identified four advanced HF clusters: 1) male Caucasians with ischemic cardiomyopathy, multiple comorbidities, lowest B-type natriuretic peptide (BNP) levels; 2) females with non-ischemic cardiomyopathy, few comorbidities, most favorable hemodynamics; 3) young African American males with non-ischemic cardiomyopathy, most adverse hemodynamics, advanced disease; and 4) older Caucasians with ischemic cardiomyopathy, concomitant renal insufficiency, highest BNP levels. There was no association between clusters and bedside-derived hemodynamic profiles (p = 0.70). For all adverse clinical outcomes, Cluster 4 had the highest risk, and Cluster 2, the lowest. Compared to Cluster 4, Clusters 1-3 had 45-70% lower risk of all-cause mortality. Clusters were significantly associated with clinical outcomes, whereas hemodynamic profiles were not.
  
  
  CONCLUSIONS
  By clustering patients with similar objective variables, we identified four clinically relevant phenotypes of ADHF patients, with no discernable relationship to hemodynamic profiles, but distinct associations with adverse outcomes. Our analysis suggests that ADHF classification using simultaneous considerations of etiology, comorbid conditions, and biomarker levels, may be superior to bedside classifications.
authors: Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut, United States of America.
authors: Tariq
authors: T
authors: Ahmad
authors: Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut, United States of America.
authors: Nihar
authors: N
authors: Desai
authors: Program for Translational Medicine, Yale University School of Medicine, New Haven, Connecticut, United States of America.
authors: Francis
authors: F
authors: Wilson
authors: Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota, United States of America.
authors: Phillip
authors: P
authors: Schulte
authors: Duke Clinical Research Institute, Durham, North Carolina, United States of America.
authors: Allison
authors: A
authors: Dunning
authors: Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut, United States of America.
authors: Daniel
authors: D
authors: Jacoby
authors: Division of Cardiology, Department of Medicine, University of Colorado, Denver, Colorado, United States of America.
authors: Larry
authors: L
authors: Allen
authors: Duke Clinical Research Institute, Durham, North Carolina, United States of America.
authors: Mona
authors: M
authors: Fiuzat
authors: Duke Clinical Research Institute, Durham, North Carolina, United States of America.|Division of Cardiology, Duke University Medical Center, Durham, North Carolina, United States of America.
authors: Joseph
authors: J
authors: Rogers
authors: Duke Clinical Research Institute, Durham, North Carolina, United States of America.|Division of Cardiology, Duke University Medical Center, Durham, North Carolina, United States of America.
authors: G Michael
authors: GM
authors: Felker
authors: Inova Heart and Vascular Institute, Falls Church, Virginia, United States of America.
authors: Christopher
authors: C
authors: O'Connor
authors: Duke Clinical Research Institute, Durham, North Carolina, United States of America.|Division of Cardiology, Duke University Medical Center, Durham, North Carolina, United States of America.
authors: Chetan B
authors: CB
authors: Patel
mesh_terms: D000208:Acute Disease; D000328:Adult; D001741:Black or African American; D000368:Aged; D002407:Catheterization, Swan-Ganz; D016000:Cluster Analysis; D005260:Female; D006333:Heart Failure / Q000145:classification* / Q000401:mortality / Q000503:physiopathology; D006439:Hemodynamics; D006801:Humans; D008297:Male; D008875:Middle Aged; D011379:Prognosis; D016016:Proportional Hazards Models; D044465:White People