In this protocol, we explain how to obtain and interpret phase angle values and bioelectrical impedance vectorial analysis (BIVA) Z-score obtained by bioelectrical impedance in patients with acute heart failure admitted to the Emergency Department and their clinical applicability as a predictive marker for the prognosis of a 90-day event.
Acute heart failure is characterized by neurohormonal activation, which leads to sodium and water retention and causes alterations in body composition, such as increased body fluid congestion or systemic congestion. This condition is one of the most common reasons for hospital admission and has been associated with poor outcomes. The phase angle indirectly measures intracellular status, cellular integrity, vitality, and the distribution of spaces between intracellular and extracellular body water. This parameter has been found to be a predictor of health status and an indicator of survival and other clinical outcomes. In addition, phase angle values of <4.8° upon admission were associated with higher mortality in patients with acute heart failure. However, low phase angle values may be due to alterations-such as the shifting of fluids from an intracellular body water (ICW) compartment to an ECW (extracellular body water) compartment and a concurrent decrease in body-cell mass (which can reflect malnutrition)-that are present in heart failure. Thus, a low phase angle may be due to overhydration and/or malnutrition. BIVA provides additional information about the body-cell mass and congestion status with a graphical vector (R-Xc graph). In addition, a BIVA Z-score analysis (the number of standard deviations from the mean value of the reference group) that has the same pattern as that of the ellipses for the percentiles on the original R-Xc graph can be used to detect changes in soft-tissue mass or tissue hydration and can help researchers compare changes in different study populations. This protocol explains how to obtain and interpret phase angle values and BIVA Z-score analyses, their clinical applicability, and their usefulness as a predictive marker for the prognosis of a 90-day event in patients admitted to an emergency department with acute heart failure.
Acute heart failure (AHF) results from the rapid onset of signs, symptoms, and exacerbation of derivates of HF and a combination of clinical, hemodynamic, and neurohormonal abnormalities, including systemic inflammatory activation, which leads to sodium and water retention1. This long-term accumulation causes the interstitial glycosaminoglycan (GAG) networks to become dysfunctional, resulting in reduced buffering capacity and changing the form and function of the GAG networks1,2. This contributes to alterations in body composition due to the shifting of fluids from intracellular to extracellular space3, thus inducing an increase in body fluids and leading to congestion, which is the most common cause of hospitalization with HF. It is principally fluid overload, compartmental fluid redistribution, or a combination of both mechanisms that require immediate medical attention4,5. This condition is one of the main predictors of a poor prognosis6,7.
Considering that AHF is the most common cause of hospital admissions in patients older than 65 years of age8, around 90% of those who are admitted to an emergency department present fluid overload6, and approximately 50% of these patients are discharged with persistent symptoms of dyspnea and fatigue, and/or minimal or no weight loss9. In-hospital mortality rates range from 4% to 8% after discharge; there is an increase from 8% to 15% at three months, and for re-hospitalization, the rates range from 30% to 38% at 3 months10. Therefore, the quick and accurate evaluation of congestion in real-time and acute settings, such as an emergency department, is crucial for therapeutic management11 and determining disease prognosis, morbidity, and mortality6.
Bioelectrical impedance analysis (BIA) has been suggested for estimating body composition for being safe, noninvasive and portable techinque12. To estimate a whole-body impedance, BIA uses a phase-sensitive impedance analyzer that introduces a constant alternating current through tetrapolar surface electrodes placed on the hands and feet12. This method combines the resistance (R), reactance (Xc), and phase angle (PhA)13, where R is the opposition to the flow of the alternating current through the intracellular and extracellular ionic solution. Xc is the delay in the conduction (dielectric components) or compliance of the tissue interfaces, cell membranes, and organelles with the passage of the administered current12. The PhA reflects the relationship between R and Xc. It is derived from the electrical properties of the tissue; it is expressed as the lag between the voltage and current at the cell membrane and tissue interfaces and is measured with phase-sensitive devices14,15,16,17.
The PhA is calculated from raw data on R and Xc (PA [degrees] = arctangent (Xc/R) x (180°/π)), and it is considered one of the indicators of cellular health and cell membrane structure18, as well as an indicator of the distribution of ICW and ECW spaces, i.e., altered redistributions of the compartments (specifically, changes from intracellular to extracellular water, which low phase angles can show)19. Thus, a low PhA value may be due to overhydration and/or malnutrition, and the Z-score could be used to differentiate if this low PhA is due to the loss of soft tissue mass, an increase in tissue hydration, or both. In addition, the transformation of the Z-score could help researchers compare changes in different study populations3,14.
In addition, PhA is considered a predictor of health status, an indicator of survival, and a prognostic marker for different clinical outcomes3,20, even under other clinical conditions20,21,22,23, where high PhA values indicate greater cell membrane integrity and vitality10,13and therefore greater functionality. This is in contrast to low PhA values, which reflect membrane integrity and permeability loss, leading to impaired cell function or even cell death14,22,24. In patients with chronic heart failure (CHF), smaller PhA values were associated with a worse functional class classification25. In addition, one of the advantages of PhA measurement is that it does not require recalled parameters, body weight, or biomarkers.
Several studies have recommended the use of raw BIA measurements in patients who had alterations in fluid shifts and fluid redistributions or non-constant hydration status, such as those in AHF26. This was because BIA is based on regression equations that estimate total body water (TBW), extracellular body water (ECW), and intracellular body water (ICW). Therefore, the lean and fat mass estimations in such patients are biased because of the physiological relationship with soft tissue hydration27.
The bioelectrical impedance vectorial analysis (BIVA) method overcomes some limitations of the conventional BIA method28. It provides additional information through a semiquantitative evaluation of body composition in terms of body-cell mass (BCM), cell mass integrity, and hydration status29. Thus, it allows an estimation of the body fluid volume through vector distribution and distance patterns on an R-Xc graph28,30. BIVA is used to create a vector plot of impedance (Z) using the whole-body R and Xc values derived from BIA at a frequency of 50 kHz.
To adjust the raw values of R and Xc, the parameters R and Xc are standardized by height (H), expressed as R/H and Xc/H in Ohm/m, and plotted as a vector; this vector has a length (proportional to the TBW) and a direction on the R-Xc graph16,28.
A sex-specific R-Xc graph contains three ellipses, which correspond to the 50%, 75%, and 95% tolerance ellipses of a healthy reference population28,31,32; the ellipsoidal form of the ellipses is determined by the relationship between R/H and Xc/H. However, to evaluate the impedance parameters in a gender-specific reference health population, the original raw BIA parameters were transformed into bivariate Z-scores (in a BIVA Z-score analysis) and plotted on an R-Xc Z-score graph33,34. This graph, compared with an R-Xc graph, represented the standardized R/H and Xc/H as a bivariate Z-score, i.e., Z(R) and Z(Xc) showed the number of standard deviations away from the mean value of the reference group33. The tolerance ellipses of the Z-score conserved the same pattern as that of the ellipses for the percentiles on the original R-Xc graph31,33. The Z-score graphs for R-Xc and R-Xc showed changes in soft tissue mass and tissue hydration independent of regression equations or body weight.
Vector displacements along the major axis of the ellipses indicated changes in hydration status; a shortened vector that fell below the 75% pole of an ellipse indicated pitting edema (sensibility = 75% and specificity = 86%); however, the optimal threshold for the detection of pitting edema was different in AHF and CHF patients, where the lower pole of 75% corresponded to AHF patients, and 50% corresponded to CHF patients edema (sensibility = 85% and specificity = 87%)35. On the other hand, vector displacements along the minor axis corresponded to cell mass. The left side of the ellipses indicated a high cell mass (i.e., more soft tissue), where shorter vectors corresponded to obese individuals and were characterized by phases similar to those of athletic ones, who had longer vectors. On the contrary, the right side indicated less body cell mass21,34; according to Picolli et al.31,33, the scores of the vectors of the anorexia, HIV, and cancer groups were located on the right side of the minor axis, which corresponds to the category of cachexia.
This study aimed to explain how to obtain and interpret PhA values by using BIA in patients with AHF who were admitted to an emergency department and to show their clinical applicability/usefulness as a predictive marker for the prognosis of 90-day events.
This protocol describes the utility of using R-Xc Z-score analysis in clinical practice for patients admitted to an emergency department with AHF. Considering that in patients with AHF, the main reason for hospital admission is congestion, its quick and accurate detection, and evaluation are crucial for patients' outcomes6.
This article illustrates the variety of clinical manifestations of AHF and how BIVA Z-score analysis (congestion status and BCM) can be used to …
The authors have nothing to disclose.
The authors would like to thank Prof(s). Piccoli and Pastori of the Department of Medical and Surgical Sciences, University of Padova, Italy, for providing the BIVA software. This research did not receive any specific grant from funding, agencies in the public, commercial, or not-for-profit sectors. This protocol/research is part of the Ph.D. dissertation of María Fernanda Bernal-Ceballos supported by the National Council of Science and Technology (CONACYT) scholarship (CVU 856465).
Alcohol 70% swabs | NA | NA | Any brand can be used |
BIVA software 2002 | NA | NA | Is a sofware created for academic use, can be download in http:// www.renalgate.it/formule_calcolatori/ bioimpedenza.htm in "LE FORMULE DEL Prof. Piccoli" section |
Chlorhexidine Wipes | NA | NA | Any brand can be used |
Examination table | NA | NA | Any brand can be used |
Leadwires square socket | BodyStat | SQ-WIRES | |
Long Bodystat 0525 electrodes | BodyStat | BS-EL4000 | |
Quadscan 4000 equipment | BodyStat | BS-4000 | Impedance measuring range: 20 – 1300 Ω ohms Test Current: 620 μA Frequency: 5, 50, 100, 200 kHz Accuracy: Impedance 5 kHz: +/- 2 Ω Impedance 50 kHz: +/- 2 Ω Impedance 100 kHz: +/- 3 Ω Impedance 200 kHz: +/- 3 Ω Resistance 50 kHz: +/- 2 Ω Reactance 50 kHz: +/- 1 Ω Phase Angle 50 kHz: +/- 0.2° Calibration: A resistor is supplied for independent verification from time to time. The impedance value should read between 496 and 503 Ω. |