title: Derivation of baseline lung impedance in chronic heart failure patients: use for monitoring pulmonary congestion and predicting admissions for decompensation.
abstract: The instantaneous lung impedance (ILI) is one of the methods to assess pulmonary congestion or edema (PCE) in chronic heart failure (CHF) patients. Due to usually existing PCE in CHF patients when evaluated, baseline lung impedance (BLI) is unknown. Therefore, the relation of ILI to BLI is unknown. Our aim was to evaluate methods to calculate and appraise BLI or its derivative as reflecting the clinical status of CHF patients. ILI and New York Heart Association (NYHA) class were assessed in 222 patients (67 ± 11 years, LVEF <35 %) during 32 months of frequent outpatient clinic visits. ILI, measured in 120 asymptomatic patients at NYHA class I, with no congestion on the chest X-ray and a low-normal 6-min walk, was defined as BLI. Using measured BLI and ILI values in these patients, formulas for BLI calculation were derived based on logistic regression analysis or on the disparity between BLI and ILI values at different NYHA stages. Both models were equally reliable with <3 % difference between measured and calculated BLI (p = NS). ΔLIR = (ILI/BLI - 1) × 100 % reflected the degree of PCE, or deviation from baseline, correlated with NYHA class (r = -0.9, p < 0.001) and could serve for monitoring. Of study patients, 123 were re-hospitalized for PCE during follow up. Their ΔLIR decreased gradually from -21.7 ± 8.2 % 4 weeks pre-admission to -37.8 ± 9.3 % on admission (p < 0.001). Patients improved during hospital stay (NYHA 3.7 ± 0.5 to 2.9 ± 0.8, p < 0.0001) with ΔLIR increasing to -29.1 ± 12.0 % (p < 0.001). ΔLIR based on calculated BLI correlated with the clinical status of CHF patients and allowed the prediction of hospitalizations for PCE.
authors.affiliation: Heart Institute, Hillel Yaffe Medical Center, P.O. Box 169, 38100, Hadera, Israel, shochat1@yahoo.com.
authors.forename: Michael
authors.initials: M
authors.lastname: Shochat
authors.forename: Avraham
authors.initials: A
authors.lastname: Shotan
authors.forename: David S
authors.initials: DS
authors.lastname: Blondheim
authors.forename: Mark
authors.initials: M
authors.lastname: Kazatsker
authors.forename: Iris
authors.initials: I
authors.lastname: Dahan
authors.forename: Aya
authors.initials: A
authors.lastname: Asif
authors.forename: Ilia
authors.initials: I
authors.lastname: Shochat
authors.forename: Aaron
authors.initials: A
authors.lastname: Frimerman
authors.forename: Yoseph
authors.initials: Y
authors.lastname: Rozenman
authors.forename: Simcha R
authors.initials: SR
authors.lastname: Meisel
mesh_terms: D000368:Aged; D000465:Algorithms; D002908:Chronic Disease; D003198:Computer Simulation; D017097:Electric Impedance; D005260:Female; D006333:Heart Failure / Q000503:physiopathology* / Q000628:therapy*; D006760:Hospitalization; D006801:Humans; D008168:Lung / Q000503:physiopathology*; D008297:Male; D008875:Middle Aged; D008955:Models, Cardiovascular; D008991:Monitoring, Physiologic / Q000379:methods*; D010343:Patient Admission; D011446:Prospective Studies; D011652:Pulmonary Circulation; D012042:Registries; D012815:Signal Processing, Computer-Assisted; D016896:Treatment Outcome; D016277:Ventricular Function, Left / Q000502:physiology