title: Bioelectrical impedance vector analysis and clinical outcomes in patients with acute heart failure.
abstract: OBJECTIVE
  Fluid overload is a hallmark in acute heart failure (AHF). Bioelectrical impedance vector analysis (BIVA) has emerged as a noninvasive method for quantifying patients' hydration. We aimed to evaluate the effect of BIVA hydration status (BHS) measured before discharge on mortality and rehospitalization for AHF.
  
  
  METHODS
  We included 369 consecutive patients discharged from the cardiology department from a third-level hospital with a diagnosis of AHF. On the basis of BHS, patients were grouped into three categories: hyper-hydration (>74.3%), normo-hydration (72.7-74.3%) and dehydration (<72.7%). Appropriate survival techniques were used to evaluate the association between BHS and the risk of death and readmission for AHF.
  
  
  RESULTS
  At a median follow-up of 12 months (interquartile range, IQR: 5-19), 80 (21.7%) deaths and 93 (25.2%) readmissions for AHF were registered. The mortality and readmission rates for the BHS categories were hyper-hydration (3.28 and 3.83 per 10 persons-years); normo-hydration (1.43 and 2.68 per 10 persons-years); and dehydration (2.24 and 2.53 per 10 persons-years) (P < 0.05 for all comparisons). In an adjusted analysis, BHS displayed a significant association with mortality (P = 0.004), with a higher mortality risk in those with hyperhydration. Likewise, BHS showed to linearly predict AHF-readmission risk [hazard ratio 1.06 (1.03-1.10); P = 0.001 per increase in 1%].
  
  
  CONCLUSIONS
  In patients admitted with AHF, BHS assessed before discharge was independently associated with the risk of death and AHF-readmission.
authors.affiliation: aServicio de Cardiología, Hospital Clínico Universitario bServicio de Cardiología, Hospital de Manises cServicio de Cardiología, Hospital General Universitario de Valencia dServicio de Cardiología, Hospital Universitari Germans Trias i Pujol, Badalona, Spain.
authors.forename: Julio
authors.initials: J
authors.lastname: Núñez
authors.forename: Beatriz
authors.initials: B
authors.lastname: Mascarell
authors.forename: Hans
authors.initials: H
authors.lastname: Stubbe
authors.forename: Silvia
authors.initials: S
authors.lastname: Ventura
authors.forename: Clara
authors.initials: C
authors.lastname: Bonanad
authors.forename: Vicent
authors.initials: V
authors.lastname: Bodí
authors.forename: Eduardo
authors.initials: E
authors.lastname: Núñez
authors.forename: Gema
authors.initials: G
authors.lastname: Miñana
authors.forename: Lorenzo
authors.initials: L
authors.lastname: Fácila
authors.forename: Antonio
authors.initials: A
authors.lastname: Bayés-Genis
authors.forename: Francisco J
authors.initials: FJ
authors.lastname: Chorro
authors.forename: Juan
authors.initials: J
authors.lastname: Sanchis
mesh_terms: D000208:Acute Disease; D000368:Aged; D000369:Aged, 80 and over; D001834:Body Water; D017097:Electric Impedance; D005260:Female; D005500:Follow-Up Studies; D006333:Heart Failure / Q000175:diagnosis*; D006760:Hospitalization; D006801:Humans; D053208:Kaplan-Meier Estimate; D008297:Male; D008875:Middle Aged; D010359:Patient Readmission; D011379:Prognosis; D011446:Prospective Studies; D018570:Risk Assessment / Q000379:methods; D012815:Signal Processing, Computer-Assisted