Bioelectrical impedance vector analysis and clinical outcomes in patients with acute heart failure

J Cardiovasc Med (Hagerstown). 2016 Apr;17(4):283-90. doi: 10.2459/JCM.0000000000000208.

Abstract

Aims: 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%].

Conclusion: In patients admitted with AHF, BHS assessed before discharge was independently associated with the risk of death and AHF-readmission.

Publication types

  • Evaluation Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Acute Disease
  • Aged
  • Aged, 80 and over
  • Body Water
  • Electric Impedance
  • Female
  • Follow-Up Studies
  • Heart Failure / diagnosis*
  • Hospitalization
  • Humans
  • Kaplan-Meier Estimate
  • Male
  • Middle Aged
  • Patient Readmission
  • Prognosis
  • Prospective Studies
  • Risk Assessment / methods
  • Signal Processing, Computer-Assisted