Assessment of bioimpedance spectroscopy devices: a comparative study and error analysis of gold-plated copper electrodes.

Objective. Bioimpedance spectroscopy (BIS) is a non-invasive diagnostic tool to derive fluid volume compartments from frequency dependent voltage drops in alternating currents by extrapolating to the extracellular resistance (R0) and intracellular resistance (Ri). Here we tested whether a novel BIS device with reusable and adhesive single-use electrodes produces results which are (in various body positions) equivalent to an established system employing only single-use adhesive electrodes.Approach. Two BIS devices ('Cella' and the 'Body Composition Monitor' [BCM]) were compared using four dedicated resistance testboxes and by measuring 40 healthy volunteers.Invivocomparisons included supine wrist-to-ankle (WA) reference measurements and wrist-to-wrist (WW) measurements with pre-gelled silver/silver-chloride (Ag/AgCl) electrodes and WW measurements with reusable gold-plated copper electrodes.Main results. Coefficient of variation were <1% for all testbox measurements with both BIS devices. Accuracy was within ±1% of true resistance variability, a threshold which was only exceeded by the Cella device for all resistances in a testbox designed with a lowR0/Riratio.Invivo, WA-BIS differed significantly between BIS devices (p< 0.001). Reusable WW electrodes exhibited larger resistances than WW-BIS with Ag/AgCl electrodes (R0: 738.36 and 628.69 Ω;Ri: 1508.18 and 1390 Ω) and the relative error varied from 7.6% to 31.1% (R0) and -15.6% to 37.3% (Ri).Significance. Both BIS devices produced equivalent resistances measurements but different estimates of body composition bothinsilicoand in WA setupsinvivo, suggesting that the devices should not be used interchangeably. Employing WW reusable electrodes as opposed to WA and WW measurement setups with pre-gelled Ag/AgCl electrodes seems to be associated with measurement variations that are too large for safe clinical use. We recommend further investigations of measurement errors originating from electrode material and current path.

Day-to-day variability in euvolemic body mass.

Short-term variability in body mass is a common, everyday phenomenon; however, data on body mass variability are scarce. While the physiological variability of body mass is negligible in healthy individuals, it could have implications for therapy in patients with impaired volume homeostasis, for example, patients with kidney failure undergoing kidney replacement therapy. We analyzed a long-term dataset comprising 9521 days of standardized body mass measurements from one healthy male individual and assessed the variability in body mass as a positive or negative relative difference in body mass measured on subsequent days. The average and median relative differences were zero, with a standard deviation (SD) of 0.53% for the one-day interval, increasing to 0.69% for the 7-day interval, and this variability was constant throughout the observation period. A body mass variability of approximately 0.6% (±450 mL in a 75-kg patient) should be taken into consideration when weight-dependent treatment prescriptions, e.g. the ultrafiltration rates in patients on hemodialysis, are being set. Consequently, a "soft target weight", considering the longitudinal variation of volume markers, such as body mass, might improve treatment quality.

Differences in bioimpedance-derived fluid status between two versions of the Body Composition Monitor.

OBJECTIVES: The Body Composition Monitor (BCM) (Fresenius Medical Care) measures body impedances in alternating currents to subsequently calculate fat and lean tissue mass, fluid compartments, and overhydration (OH). The aim of this study was to investigate differences between two versions of the BCM (an older version, 3.2.5, and a newer version, 3.3.3). METHODS: Between September 2021 and December 2021, 28 hemodialysis patients were included to undergo BCM measurements before each of 14 consecutive dialysis sessions with versions 3.2.5 and 3.3.3 devices. Measurements were performed according to instructions provided by the manufacturer. Differences between BCM devices were tested for statistical significance using paired Wilcoxon tests, neglecting clustering. RESULTS: A total of 288 measurement pairs of 27 patients were left after exclusion of 43 flawed data points. The mean difference in OH between both BCM devices was 0.548 L (higher for version 3.2.5). Analysis of impedance data revealed differences in the high-frequency spectrum, quantifiable by the intracellular resistance, Ri (median Ri version 3.2.5 = 1750.3 Ω; Ri version 3.3.3 = 1612.45 Ω; P < 0.001), and the time delay, Td (median Td version 3.2.5 = 1.85 ns; Td version 3.3.3 = 8.88 nanoseconds; P < 0.001). CONCLUSIONS: This study finds that results between the two versions of the BCM differed in a clinically meaningful fashion and that the newer version 3.3.3 device had a bias toward less OH. Circulating BCM devices should be checked for versions and only devices of the same version should be used for each patient to ensure better within-patient consistency.

Ultrafiltration-induced decrease in relative blood volume is larger in hemodialysis patients with low specific blood volume: Results from a dialysate bolus administration study.

INTRODUCTION: Prescribing the ultrafiltration in hemodialysis patients remains challenging and might benefit from the information on absolute blood volume, estimated by intradialytic dialysate bolus administration. Here, we aimed at determining the relationship between absolute blood volume, normalized for body mass (specific blood volume, Vs), and ultrafiltration-induced decrease in relative blood volume (∆RBV) as well as clinical parameters including body mass index (BMI). METHODS: This retrospective analysis comprised 77 patients who had their dialysate bolus-based absolute blood volume extracted routinely with an automated method. Patient-specific characteristics and ∆RBV were analyzed as a function of Vs, dichotomizing the data above or below a previously proposed threshold of 65 ml/kg for Vs. Statistical methodology comprised descriptive analyses, two-group comparisons, and correlation analyses. FINDINGS: Median Vs was 68.6 ml/kg (54.9 ml/kg [Quartile 1], 83.4 ml/kg [Quartile 3]). Relative blood volume decreased by 6.3% (2.6%, 12.2%) over the entire hemodialysis session. Vs correlated inversely with BMI (rs  = -0.688, p < 0.001). ∆RBV was 9.8% in the group of patients with Vs <65 ml/kg versus 6.0% in the group of patients with Vs ≥65 ml/kg (p = 0.024). The two groups did not differ significantly regarding their specific ultrafiltration volume, normalized for body mass, which amounted to 34.1 ml/kg and 36.0 ml/kg in both groups, respectively (p = 0.630). ∆RBV correlated inversely with Vs (rs  = -0.299, p = 0.008). DISCUSSION: The present study suggests that patients with higher BMI and lower Vs experience larger blood volume changes, despite similar ultrafiltration requirements. These results underline the clinical plausibility and importance of dialysate bolus-based absolute blood volume determination in the assessment of target weight, especially in view of a previous study where intradialytic morbid events could be decreased when the target weight was adjusted, based on Vs.

Revisiting the concept of constant tissue conductivities for volume estimation in dialysis patients using bioimpedance spectroscopy.

RATIONALE: Current estimation of body fluid volumes in hemodialysis patients using bioimpedance analysis assumes constant specific electrical characteristics of biological tissues despite a large variation in plasma Na+ concentrations [Na+], ranging from 130 to 150 mmol/L. Here, we examined the potential effect of variable [Na+] on bioimpedance-derived volume overload. METHOD: Volumes were calculated from published whole-body extra- and intracellular resistance data and relationships using either "standard" or "revised" specific electrical characteristics modeled as functions of [Na+]. RESULT: With "standard" assumptions, volumes increased with increasing [Na+]. The increase in volume overload was about 0.5 dm3 and 3% of extracellular volume per 10 mmol/dm3 of [Na+] in a 75 kg patient. This increase was abolished when the same bioimpedance data were analyzed under "revised" conditions. DISCUSSION: The overestimation in extracellular volume overload in the range of 0.5 dm3 per 10 mmol/dm3 [Na+] perfectly matches the positive relationship determined in a large cohort of hemodialysis patients. The bias may be considered moderate when interpreting data of individual patients, but may become important when comparing data of larger patient groups. The bias disappears when analysis of bioimpedance data accounts for differences in tissue electrical properties, using individual [Na+].

The systemic renin-angiotensin system in COVID-19.

SARS-CoV-2 gains cell entry via angiotensin-converting enzyme (ACE) 2, a membrane-bound enzyme of the "alternative" (alt) renin-angiotensin system (RAS). ACE2 counteracts angiotensin II by converting it to potentially protective angiotensin 1-7. Using mass spectrometry, we assessed key metabolites of the classical RAS (angiotensins I-II) and alt-RAS (angiotensins 1-7 and 1-5) pathways as well as ACE and ACE2 concentrations in 159 patients hospitalized with COVID-19, stratified by disease severity (severe, n = 76; non-severe: n = 83). Plasma renin activity (PRA-S) was calculated as the sum of RAS metabolites. We estimated ACE activity using the angiotensin II:I ratio (ACE-S) and estimated systemic alt-RAS activation using the ratio of alt-RAS axis metabolites to PRA-S (ALT-S). We applied mixed linear models to assess how PRA-S and ACE/ACE2 concentrations affected ALT-S, ACE-S, and angiotensins II and 1-7. Median angiotensin I and II levels were higher with severe versus non-severe COVID-19 (angiotensin I: 86 versus 30 pmol/L, p < 0.01; angiotensin II: 114 versus 58 pmol/L, p < 0.05), demonstrating activation of classical RAS. The difference disappeared with analysis limited to patients not taking a RAS inhibitor (angiotensin I: 40 versus 31 pmol/L, p = 0.251; angiotensin II: 76 versus 99 pmol/L, p = 0.833). ALT-S in severe COVID-19 increased with time (days 1-6: 0.12; days 11-16: 0.22) and correlated with ACE2 concentration (r = 0.831). ACE-S was lower in severe versus non-severe COVID-19 (1.6 versus 2.6; p < 0.001), but ACE concentrations were similar between groups and correlated weakly with ACE-S (r = 0.232). ACE2 and ACE-S trajectories in severe COVID-19, however, did not differ between survivors and non-survivors. Overall RAS alteration in severe COVID-19 resembled severity of disease-matched patients with influenza. In mixed linear models, renin activity most strongly predicted angiotensin II and 1-7 levels. ACE2 also predicted angiotensin 1-7 levels and ALT-S. No single factor or the combined model, however, could fully explain ACE-S. ACE2 and ACE-S trajectories in severe COVID-19 did not differ between survivors and non-survivors. In conclusion, angiotensin II was elevated in severe COVID-19 but was markedly influenced by RAS inhibitors and driven by overall RAS activation. ACE-S was significantly lower with severe COVID-19 and did not correlate with ACE concentrations. A shift to the alt-RAS axis because of increased ACE2 could partially explain the relative reduction in angiotensin II levels.