Pietro Scicchitano1, Marco Matteo Ciccone2, Andrea Passantino3, Roberto Valle4, Micaela De Palo5, Paolo Sasanelli6, Mariella Sanasi6, Assunta Piscopo6, Piero Guida7, Pasquale Caldarola8, Francesco Massari6. 1. Cardiology Section, F. Perinei Hospital, SS 96 Altamura-Gravina Km 73.800, 70022, Altamura, Bari, Italy; Section of Cardiovascular Diseases, Department of Emergency and Organ Transplantation, University of Bari, Bari, Italy. Electronic address: pietrosc.83@libero.it. 2. Section of Cardiovascular Diseases, Department of Emergency and Organ Transplantation, University of Bari, Bari, Italy. 3. Division of Cardiology and Cardiac Rehabilitation, IRCCS, Scientific Clinical Institutes Maugeri, Institute of Bari, Bari, Italy. 4. Cardiology Department, Hospital of Chioggia, Chioggia, Venezia, Italy. 5. Section of Cardiac Surgery, Department of Emergency and Organ Transplantation, University of Bari, Bari, Italy. 6. Cardiology Section, F. Perinei Hospital, SS 96 Altamura-Gravina Km 73.800, 70022, Altamura, Bari, Italy. 7. Ospedale Generale Regionale "F. Miulli", Acquaviva delle Fonti, Bari, Italy. 8. Cardiology Section, S. Paolo Hospital, Bari, Italy.
Abstract
BACKGROUND: The whole-body bioelectrical phase-angle (PhA) is emerging as a new tool in stratifying prognosis in patients with both acute (AHF) and chronic heart failure (CHF). OBJECTIVE: To evaluate the determinants of PhA in HF patients. METHODS: We analyzed data from 900 patients with AHF or CHF (mean age: 76±10 years, 54% AHF). Clinical, serum biochemical, echocardiographic and bioelectrical measurements were collected from all of patients. PhA was quantified in degrees. Congestion was assessed by a multiparametric approach, including the presence of peripheral edema, brain natriuretic peptides (BNP) plasma levels, blood urea nitrogen to creatinine ratio (BUN/Cr), and relative plasma volume status (PVS) calculated by Kaplan-Hakim's formula. Geriatric Nutritional Risk Index (GNRI) was adopted as indicator for nutritional status. RESULTS: At univariate analysis, PhA was significantly lower in females, in patients with peripheral edema, and AHF. PhA significantly correlates age, BNP, PVS, BUN/Cr, and GNRI. At multivariate analysis, congestion biomarkers emerged as the major determinant of PhA as they explained the 34% of data variability, while age, GNRI, and gender only explained 6%, 0.5%, and 0.5%, respectively (adjusted R2 = 0.41). In particular, PVS (regression of coefficient B=-0.17) explained the 20% of PhA variability, while peripheral congestion (B=-0.27) and BNP (B=-0.15) contributed to 10% and 2%, respectively. CONCLUSIONS: The main determinant of bioelectrical PhA in patients with HF is congestion and PVS in particular, while nutritional status has marginal impact.
BACKGROUND: The whole-body bioelectrical phase-angle (PhA) is emerging as a new tool in stratifying prognosis in patients with both acute (AHF) and chronic heart failure (CHF). OBJECTIVE: To evaluate the determinants of PhA in HF patients. METHODS: We analyzed data from 900 patients with AHF or CHF (mean age: 76±10 years, 54% AHF). Clinical, serum biochemical, echocardiographic and bioelectrical measurements were collected from all of patients. PhA was quantified in degrees. Congestion was assessed by a multiparametric approach, including the presence of peripheral edema, brain natriuretic peptides (BNP) plasma levels, blood ureanitrogen to creatinine ratio (BUN/Cr), and relative plasma volume status (PVS) calculated by Kaplan-Hakim's formula. Geriatric Nutritional Risk Index (GNRI) was adopted as indicator for nutritional status. RESULTS: At univariate analysis, PhA was significantly lower in females, in patients with peripheral edema, and AHF. PhA significantly correlates age, BNP, PVS, BUN/Cr, and GNRI. At multivariate analysis, congestion biomarkers emerged as the major determinant of PhA as they explained the 34% of data variability, while age, GNRI, and gender only explained 6%, 0.5%, and 0.5%, respectively (adjusted R2 = 0.41). In particular, PVS (regression of coefficient B=-0.17) explained the 20% of PhA variability, while peripheral congestion (B=-0.27) and BNP (B=-0.15) contributed to 10% and 2%, respectively. CONCLUSIONS: The main determinant of bioelectrical PhA in patients with HF is congestion and PVS in particular, while nutritional status has marginal impact.