Individuals with kidney disease receiving maintenance hemodialysis exhibit improved survival with higher baseline body mass index and weight gain over time (1Kalantar-Zadeh K. Kopple J.D. Kilpatrick R.D. McAllister C.J. Shinaberger C.S. Gjertson D.W. et al.Association of Morbid Obesity and Weight Change Over Time With Cardiovascular Survival in Hemodialysis Population.Am J Kidney Dis. 2005 Sep; 46: 489-500Abstract Full Text Full Text PDF PubMed Scopus (253) Google Scholar). This reversal of risk factors compared to the general population (often misnamed "reverse epidemiology" (2Levin N.W. Handelman G.J. Coresh J. Port F.K. Kaysen G.A. Reverse Epidemiology: A Confusing, Confounding, and Inaccurate Term.Semin Dial. 2007 Nov; 20: 586-592Crossref PubMed Scopus (64) Google Scholar)) has been substantiated by metrics of body composition obtained through bioimpedance spectroscopy. Specifically, bioimpedance-spectroscopy-data have indicated survival was optimal with pre-dialysis lean tissue index (LTI) ranging from 15-20kg/m2 and fat tissue index (FTI) from 4-15kg/m2, respectively (3Marcelli D. Usvyat L.A. Kotanko P. Bayh I. Canaud B. Etter M. et al.Body composition and survival in dialysis patients: results from an international cohort study.Clin J Am Soc Nephrol CJASN. 2015 Jul 7; 10: 1192-1200Crossref PubMed Scopus (0) Google Scholar). Bioimpedance-derived estimates of pre-dialysis fluid status are also associated with increased mortality when exceeding 2.5L absolute volume overload (VO) and 15% relative VO as a percentage of extracellular water (4Wizemann V. Wabel P. Chamney P. Zaluska W. Moissl U. Rode C. et al.The mortality risk of overhydration in haemodialysis patients.Nephrol Dial Transplant Off Publ Eur Dial Transpl Assoc - Eur Ren Assoc. 2009 May; 24: 1574-1579Crossref PubMed Scopus (0) Google Scholar). Although reference individuals for LTI and FTI were age- and sex-matched (5Wieskotten S. Heinke S. Wabel P. Moissl U. Becker J. Pirlich M. et al.Bioimpedance-based identification of malnutrition using fuzzy logic.Physiol Meas. 2008 May 1; 29: 639-654Crossref PubMed Scopus (62) Google Scholar), those for VO were not (4Wizemann V. Wabel P. Chamney P. Zaluska W. Moissl U. Rode C. et al.The mortality risk of overhydration in haemodialysis patients.Nephrol Dial Transplant Off Publ Eur Dial Transpl Assoc - Eur Ren Assoc. 2009 May; 24: 1574-1579Crossref PubMed Scopus (0) Google Scholar). In light of current efforts to better understand sex discrepancies in kidney disease patients (6Chesnaye N.C. Carrero J.J. Hecking M. Jager K.J. Differences in the epidemiology, management and outcomes of kidney disease in men and women.Nat Rev Nephrol. 2024 Jan; 20: 7-20Crossref Scopus (7) Google Scholar), we aimed to explore whether there are differences in pre-dialysis body composition and fluid status between male and female patients on hemodialysis. We retrospectively analyzed pre-dialysis bioimpedance measurements conducted in patients on maintenance hemodialysis between November 2022 and January 2023 at the "Vienna Dialysis-Center" (a tertiary care facility in Vienna, Austria). Patients were measured with the Body Composition Monitor (Fresenius Medical Care) and the Cella (Cella Medical) bioimpedance spectroscopy devices in standard wrist-to-ankle setups using pre-gelled electrodes. Detailed methodology and further results are provided in the Item S1-S2. In November 2022, the Vienna Dialysis-Center cared for 304 patients (285 patients on regular twice- or thrice-weekly hemodialysis, 11 undergoing in-hospital treatment, 8 on vacation). Pre-dialysis bioimpedance data from 159 patients were available for initial evaluation. After excluding erroneous measurements (Fig S1), 137 patients remained for sex comparisons, 85 (62.0%) of whom were male and 52 (38.0%) were female. Study population data and bioimpedance data from the Body Composition Monitor are shown overall and stratified by sex in Table 1. Pre-dialysis VO (higher in males), LTI (higher in males) and FTI (higher in females) differed significantly between sexes while relative VO did not. The proportion of patients within LTI measurements of 15-20kg/m2 (the range with optimal survival) differed significantly between males and females (27.1% vs. 7.7%, p<0.01), but there was no difference for the above-mentioned thresholds of absolute and relative VO or FTI (Fig 1 and Fig S2). Body Composition Monitor and Cella devices differed significantly in all parameters (Table S1 and Fig S3-S7).Table 1General data, dialysis therapy data and bioimpedance data of the study population overall and stratified by sexCharacteristicMissing (n, %)Overall, n = 137Male, n = 85Female, n = 52PPopulation characteristicsAge, years0 (0%)63.0 (52.0, 74.0)60.0 (48.0, 72.0)65.5 (57.8, 75.3)0.08 †Height, cm0 (0%)170.0 (162.0, 176.0)174.0 (170.0, 180.0)160.0 (157.0, 164.3)<0.01 †Body mass index, kg/m20 (0%)26.6 (23.2, 31.1)26.5 (23.3, 30.6)27.1 (22.4, 33.3)0.6 †Body mass pre-HD, kg2 (1.5%)78.3 (67.1, 89.6)80.8 (69.6, 94.4)72.7 (63.3, 86.6)<0.01 †Intradialytic weight loss, kg5 (3.6%)2.4 (1.3, 3.0)2.5 (1.8, 3.3)2.0 (1.1, 2.5)<0.01 †Difference to dry weight post-HD, kg10 (7.3%)0.1 (-0.1, 0.8)0.1 (-0.1, 1.0)0.1 (0.0, 0.7)0.9 †Interdialytic weight gain from last session, kg4 (2.9%)2.3 (1.1, 3.2)2.5 (1.6, 3.3)1.8 (0.7, 2.5)<0.01 †Interdialytic weight gain to next session, kg6 (4.4%)2.3 (1.0, 3.1)2.5 (1.4, 3.3)1.8 (0.5, 2.8)0.01 †Dialysis vintage, months3 (2.2%)27.8 (12.6, 56.8)28.9 (12.1, 52.7)27.2 (14.8, 61.9)0.8 †Ultrafiltration volume, L4 (2.9%)2.5 (1.7, 3.1)2.8 (1.9, 3.5)2.3 (1.5, 2.7)<0.01 †Dialysis therapy duration, minutes43 (31%)228.5 (207.3, 234.0)229.0 (218.0, 234.0)212.0 (181.3, 234.0)0.03 †Systolic BP pre-HD, mmHg3 (2.2%)144.5 (131.3, 158.0)143.0 (131.0, 158.0)146.0 (135.3, 157.0)0.8 †Diastolic BP pre-HD, mmHg3 (2.2%)73.5 (65.0, 82.0)74.5 (67.0, 83.3)71.5 (62.3, 81.0)0.12 †Systolic BP post-HD, mmHg4 (2.9%)140.0 (123.0, 156.0)138.0 (120.0, 157.5)144.0 (126.5, 153.8)0.7 †Diastolic BP post-HD, mmHg4 (2.9%)72.0 (63.0, 82.0)74.0 (64.0, 86.5)70.0 (62.0, 77.0)0.02 †Intradialytic hypotension, (n, %)7 (5.1%)13.0 (10.0%)7.0 (8.8%)6.0 (12.0%)0.8 ‡Venous hemoglobin pre-HD, g/dL3 (2.2%)11.4 (10.7, 12.2)11.7 (10.8, 12.3)11.2 (10.6, 12.0)0.09 †Previous albumin, g/dL2 (1.5%)3.4 (3.2, 3.7)3.4 (3.2, 3.7)3.4 (3.2, 3.7)0.7 †Previous total protein, g/dL2 (1.5%)6.9 (6.5, 7.2)7.0 (6.6, 7.2)6.9 (6.4, 7.2)0.2 †Bioimpedance spectroscopy characteristicsExtracellular resistance, Ohm0 (0%)530.2 (457.9, 590.6)518.5 (446.4, 564.1)554.4 (494.6, 620.6)0.01 †Intracellular resistance, Ohm0 (0%)1,596.7 (1,337.0, 1,959.3)1,501.7 (1,247.7, 1,838.5)1,844.2 (1,406.1, 2,174.0)<0.01 †Resistance at infinite frequency, Ohm0 (0%)400.8 (342.3, 445.6)386.1 (327.4, 425.5)427.4 (371.0, 476.4)<0.01 †Capacitance, nF0 (0%)1.2 (0.9, 1.7)1.4 (1.0, 1.8)1.0 (0.8, 1.3)<0.01 †Time delay, ns0 (0%)0.2 (-1.3, 3.1)0.3 (-1.4, 3.1)0.2 (-1.3, 3.3)0.7 †α, radian0 (0%)0.6 (0.6, 0.7)0.7 (0.6, 0.7)0.6 (0.6, 0.7)0.04 †Extracellular water, L0 (0%)18.5 (16.3, 21.3)19.8 (17.9, 22.7)16.3 (14.1, 18.3)<0.01 †Intracellular water, L0 (0%)18.4 (15.6, 21.5)20.7 (17.7, 23.3)15.6 (13.6, 18.0)<0.01 †Total body water, L0 (0%)36.7 (31.8, 42.6)40.7 (36.2, 45.6)31.4 (28.1, 35.8)<0.01 †Volume overload pre-HD, L0 (0%)2.4 (1.4, 3.5)2.7 (1.5, 4.0)1.9 (1.0, 3.0)0.03 †Volume overload pre-HD <2.5 L0 (0%)69.0 (50.4%)37.0 (43.5%)32.0 (61.5%)0.06 ‡Relative volume overload pre-HD, %0 (0%)13.4 (7.9, 18.5)14.3 (8.2, 19.5)12.0 (6.0, 17.3)0.4 †Relative volume overload pre-HD <15%0 (0%)80.0 (58.4%)47.0 (55.3%)33.0 (63.5%)0.4 ‡Lean tissue index, kg/m20 (0%)12.4 (10.5, 14.6)13.4 (11.2, 15.6)11.0 (9.5, 13.0)<0.01 †Lean tissue index Δ reference, kg/m20 (0%)0.0 (-1.9, 1.7)-0.4 (-2.1, 1.7)0.4 (-0.8, 2.1)0.02 †Lean tissue index between 15-20 kg/m20 (0%)27.0 (19.7%)23.0 (27.1%)4.0 (7.7%)<0.01 ⋇Fat tissue index, kg/m21 (0.7%)12.2 (9.6, 17.7)11.1 (9.1, 16.4)14.2 (9.9, 22.0)0.04 †Fat tissue index Δ reference, kg/m21 (0.7%)6.5 (3.6, 11.3)6.4 (3.7, 9.3)7.1 (3.0, 14.6)0.5 †Fat tissue index between 4-15 kg/m21 (0.7%)83.0 (61.0%)57.0 (67.9%)26.0 (50.0%)0.06 ‡Characteristics are reported as number (%) or median (interquartile range). Albumin and total protein measurements were extracted form the most recent routine laboratory before the bioimpedance measurement. Abbreviations: BP, blood pressure; HD, hemodialysis.†Two-sample Wilcoxon test‡Chi-square test⋇Fisher's exact test Open table in a new tab Characteristics are reported as number (%) or median (interquartile range). Albumin and total protein measurements were extracted form the most recent routine laboratory before the bioimpedance measurement. Abbreviations: BP, blood pressure; HD, hemodialysis. †Two-sample Wilcoxon test ‡Chi-square test ⋇Fisher's exact test In summary, we found significant differences between males and females in pre-dialysis VO, LTI and FTI not only in absolute terms, but also in the proportion of patients considered to be "in-range" of LTI. Although higher LTI was previously associated with lower mortality in patients on maintenance hemodialysis (3Marcelli D. Usvyat L.A. Kotanko P. Bayh I. Canaud B. Etter M. et al.Body composition and survival in dialysis patients: results from an international cohort study.Clin J Am Soc Nephrol CJASN. 2015 Jul 7; 10: 1192-1200Crossref PubMed Scopus (0) Google Scholar), bioimpedance-derived sarcopenia was not (Item S3a). In another study, subjectively-assessed muscle atrophy was associated with mortality more often in females, who also exhibited poor nutritional status (Item S3b). In our study, differences in pre-dialysis VO were present only in absolute terms. Other studies, while not prominently stressing these findings, also indicate larger absolute (Item S3c-e) and even relative (Item S3f) pre-dialysis VO in males. While some authors suggested that the threshold for relative VO should be sex-specific (7Zoccali C. Moissl U. Chazot C. Mallamaci F. Tripepi G. Arkossy O. et al.Chronic Fluid Overload and Mortality in ESRD.J Am Soc Nephrol JASN. 2017 Aug; 28: 2491-2497Crossref PubMed Scopus (0) Google Scholar), evidence supporting this claim is so far lacking. Reasons for pre-dialysis differences may in part originate from physiological differences (less extracellular water, therefore less VO) and in part from varying patient preferences. Differences in body composition between sexes are expected, but whether differences in VO are true remains unclear. In bioimpedance spectroscopy, body composition is modeled using the input variables extra- and intracellular resistance, body mass and body height (8Moissl U.M. Wabel P. Chamney P.W. Bosaeus I. Levin N.W. Bosy-Westphal A. et al.Body fluid volume determination via body composition spectroscopy in health and disease.Physiol Meas. 2006 Sep; 27: 921-933Crossref PubMed Scopus (500) Google Scholar,9Chamney P.W. Wabel P. Moissl U.M. Müller M.J. Bosy-Westphal A. Korth O. et al.A whole-body model to distinguish excess fluid from the hydration of major body tissues.Am J Clin Nutr. 2007 Jan; 85: 80-89Abstract Full Text Full Text PDF PubMed Scopus (390) Google Scholar). In the equations used in the Body Composition Monitor, sex-dependent resistivities, body shape factor and body density were combined into one empirically-derived expression with linear dependence on body mass index (8Moissl U.M. Wabel P. Chamney P.W. Bosaeus I. Levin N.W. Bosy-Westphal A. et al.Body fluid volume determination via body composition spectroscopy in health and disease.Physiol Meas. 2006 Sep; 27: 921-933Crossref PubMed Scopus (500) Google Scholar). Reference populations to derive this body composition model did not exhibit under- or overrepresentation of sexes (8Moissl U.M. Wabel P. Chamney P.W. Bosaeus I. Levin N.W. Bosy-Westphal A. et al.Body fluid volume determination via body composition spectroscopy in health and disease.Physiol Meas. 2006 Sep; 27: 921-933Crossref PubMed Scopus (500) Google Scholar,9Chamney P.W. Wabel P. Moissl U.M. Müller M.J. Bosy-Westphal A. Korth O. et al.A whole-body model to distinguish excess fluid from the hydration of major body tissues.Am J Clin Nutr. 2007 Jan; 85: 80-89Abstract Full Text Full Text PDF PubMed Scopus (390) Google Scholar) but were based on narrower ranges of body mass index than typical hemodialysis populations (25.2 ± 3.7kg/m2 (9Chamney P.W. Wabel P. Moissl U.M. Müller M.J. Bosy-Westphal A. Korth O. et al.A whole-body model to distinguish excess fluid from the hydration of major body tissues.Am J Clin Nutr. 2007 Jan; 85: 80-89Abstract Full Text Full Text PDF PubMed Scopus (390) Google Scholar) vs. 26 ± 5.3kg/m2 (3Marcelli D. Usvyat L.A. Kotanko P. Bayh I. Canaud B. Etter M. et al.Body composition and survival in dialysis patients: results from an international cohort study.Clin J Am Soc Nephrol CJASN. 2015 Jul 7; 10: 1192-1200Crossref PubMed Scopus (0) Google Scholar)), which could lead to erroneous estimates in patients outside of the initial validation range. Body shape is largely different between sexes, independent of body mass index. The present study is limited by its relatively small sample size and retrospective, cross-sectional design. In conclusion, we identified notable sex differences in pre-dialysis fluid status and body composition among patients on maintenance hemodialysis at a single center. For VO, these differences have also been observed but have not been commented on or discussed in previous datasets. Considering that the survival of females undergoing hemodialysis is equal to (although in some strata slightly better than) males (10ERA Registry: ERA Registry Annual Report 2021. Amsterdam UMC, location AMC, Department of Medical Informatics, Amsterdam, the Netherlands, 2023.Google Scholar), thresholds of body composition parameters associated with increased mortality may not be equal between sexes if the values themselves are sex-dependent. We therefore recommend reanalyzing existing large-scale datasets for sex differences in mortality and bioimpedance-derived measures of body composition. Conceptualization: SM, PW, MH; Methodology: SM; Software: SM; Formal Analysis: SM; Investigation: SM, JN, CM, SW; Resources: MH; Data curation: SM; Visualization: SM; Supervision: MH; Project administration: SM, MH; Funding acquisition: MH. Each author contributed important intellectual content during manuscript drafting or revision and accepts accountability for the overall work by ensuring that questions pertaining to the accuracy or integrity of any portion of the work are appropriately investigated and resolved. This work was supported by the Vienna Science and Technology (WWTF) Precision Medicine Grant LS20-079. CC and PW were previously employees of Fresenius Medical Care, which produces the Body Composition Monitor. DS is a coinventor of patents in the field of blood volume and bioimpedance applications in hemodialysis and is a member of the American Renal Associates research board. MH served as a speaker and/or consultant for Astellas Pharma, AstraZeneca, Eli Lilly, Fresenius Medical Care, Janssen-Cilag, Siemens Healthcare, and Vifor and has previously received academic study support from Astellas Pharma, Boehringer Ingelheim, Eli Lilly, Nikkiso, and Siemens Healthcare (not related to the present work). The remaining authors have nothing to declare. Data will be made available upon reasonable request to the corresponding author. Received March 2, 2024. Evaluated by 1 external peer reviewer, with direct editorial input from the Statistical Editor and the Editor-in-Chief. Accepted in revised form April 30, 2024. The authors wish to thank all medical staff at the Vienna Dialysis-Center and Ole Schecker and Moritz Reuth for additional data acquisition. Download .pdf (1.49 MB) Help with pdf files

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.

Objective: A feasible method has recently been proposed for estimating absolute blood volume (ABV) in hemo-dialysis (HD) patients based on intradialytic infusion of a dialysate bolus and visual assessment of the subsequent increase in relative blood volume (RBV) tracked by the dialysis machine. The aim of this study was to develop a method for more objective determination of such RBV increase to improve the accuracy of ABV estimation.Methods: We proposed a numerical algorithm consisting of interpolation and polynomial fitting of RBV signals, which we evaluated on data from 64 HD sessions in 48 patients with 240 mL of dialysate infused approximately 1 h into HD. The estimated ABV values were compared with those from a simple two-point method described previously as well as with the values calculated using the Nadler formula and the Lemmens-Bernstein-Brodsky formula.Results: Compared to the simple method, the improved method provided higher (more plausible) estimates of ABV (median 4.79 vs 4.53 L, p < 0.001) and specific ABV (median 68.5 vs 66.4 mL/kg, p < 0.001). The improved method also provided much lower intra-patient variability of ABV estimated in different sessions of the same week (median spread 180 vs 462 mL, p < 0.001) and showed narrower limits of agreement with both Nadler and Lemmens-Bernstein-Brodsky formulae.Conclusion: The proposed numerical method constitutes a substantial improvement over the simple method by averaging the noise and short-term variability in RBV signals.Significance: More accurate estimates of ABV in HD patients could aid in managing their fluid status.

Every hemodialysis session starts with the question of how much fluid should be removed, which can currently not be answered precisely. Herein, we first revisit the "probing-dry-weight" concept, using the historical example of Tassin/France (practicing also "long, slow dialysis"): Mortality outcomes were, in the 1980s, better than registry data, but are nowadays similar to European average. In view of the negative primary end point in a recent trial on dry weight assessment, based on lung ultrasound-guided evaluation of fluid excess in the lungs, and a meta-analysis of prospective studies failing to show that bioimpedance-based interventions for correction of volume overload had a direct effect on all-cause mortality, we ask how to ever move forward. Clinical reasoning demands that as much information as possible should be gathered on the fluid status of patients undergoing dialysis. Besides body weight and blood pressure, measurements of bioimpedance and dialysate bolus-derived absolute blood volume can in principle be automatized, whereas lung ultrasound can be obtained routinely. In the era of machine learning, fluid management could consist of flexible target weight prescriptions, adjusted on a daily basis and accounting even for fluctuations in fluid-free body mass. In view of all the negative prospective results surrounding fluid management in hemodialysis, we propose this as a "never-give-up" approach.

10.1093/ndt/gfad206 Video Watch the video of this contribution at https://academic.oup.com/ndt/pages/author_videos gfad206Media1 6340506020112

Abstract Background and Aims Bioimpedance spectroscopy (BIS) is a non-invasive diagnostic tool to assess volume status and body composition through the measurement of voltage drops in alternating currents and subsequent extrapolation of extracellular (R0), intracellular (Ri), and total body (RInf) resistances. Currently available devices mostly rely on disposable electrodes and require supine body position. Here we tested whether a new, more versatile BIS device with reusable electrodes matches an established system in various setups, aiming to enable daily BIS-measurements in the near future. Method Two BIS devices (“Cella” and the “Body Composition Monitor” [BCM]) were compared both with four resistance testboxes (circuit boards with resistors and capacitors simulating different body conditions) and in 40 healthy volunteers. In-vivo comparisons included supine hand-to-foot (HF) reference measurements with adhesive disposable electrodes and hand-to-hand (HH) measurements with adhesive disposable and prototype reusable electrode sets (Figure 1). Results Analyses of testboxes were reproducible in both devices (intra-device coefficients of variation <1%). Mean differences from testbox components were similar and small for R0 (2-3 Ohm) but not for Ri, where Cella was off by 101 Ohm compared to the BCM's 29 Ohm in a testbox designed with a deliberately low R0/Ri ratio. In-vivo, HF measurements with disposable electrodes differed significantly between both devices (p < 0.001). Prototype reusable HH electrodes exhibited a bias towards larger resistances than HF measurements (R0: 738.36 Ohm vs. 643.09 Ohm; Ri: 1508.18 Ohm vs. 1257.17 Ohm; RInf 500.03 vs. 423.81 Ohm, respectively) and the HH/HF ratio varied between 1.0-1.4 (R0 and RInf) and 0.9-1.6 (Ri). Conclusion While the Cella BIS device was shown to produce results with comparable consistency to the BCM in-vivo, the latter measured more accurately under testbox conditions. Accuracy of in-vivo measurements could not be determined for lack of gold-standard measurements. Implementation of HH reusable electrodes will require per-patient calibration against HF measurements due to the large inter-patient fluctuations in the HH/HF ratio. We recommend further longitudinal analyses of intra-patient HH/HF ratios to investigate long-term variabilities.

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.

BACKGROUND:Absolute blood volume (ABV) is a critical component of fluid status, which may inform target weight prescriptions and hemodynamic vulnerability of dialysis patients. Here, we utilized the changes in relative blood volume (RBV), monitored by ultrasound (BVM) upon intradialytic 240 mL dialysate fluid bolus-infusion 1 h after hemodialysis start, to calculate the session-specific ABV. With the main goal of assessing clinical feasibility, our sub-aims were to (i) standardize the BVM-data read-out; (ii) determine optimal time-points for ABV-calculation, "before-" and "after-bolus"; (iii) assess ABV-variation.METHODS:We used high-level programming language and basic descriptive statistics in a retrospective study of routinely measured BVM-data from 274 hemodialysis sessions in 98 patients.RESULTS:Regarding (i) and (ii), we automatized the processing of RBV-data, and determined an algorithm to select the adequate RBV-data points for ABV-calculations. Regarding (iii), we found in 144 BVM-curves from 75 patients, that the average ABV ± standard deviation was 5.2 ± 1.5 L and that among those 51 patients who still had ≥2 valid estimates, the average intra-patient standard deviation in ABV was 0.8 L. Twenty-seven of these patients had an average intra-patient standard deviation in ABV <0.5 L.CONCLUSIONS:We demonstrate feasibility of ABV-calculation by an automated algorithm after dialysate bolus-administration, based on the BVM-curve. Based on our results from this simple "abridged" calculation approach with routine clinical measurements, we encourage the use of multi-compartment modeling and comparison with reference methods of ABV-determination. Hopes are high that clinicians will be able to use ABV to inform target weight prescription, improving hemodynamic stability.

Bioimpedance spectroscopy (BIS) is routinely used in peritoneal dialysis patients and might aid fluid status assessment in patients with liver cirrhosis, but the effect of ascites volume removal on BIS-readings is unknown. Here we determined changes in BIS-derived parameters and clinical signs of fluid overload from before to after abdominal paracentesis. Per our pre-specified sample size calculation, we studied 31 cirrhotic patients, analyzing demographics, labs and clinical parameters along with BIS results. Mean volume of the abdominal paracentesis was 7.8 ± 2.6 L. From pre-to post-paracentesis, extracellular volume (ECV) decreased (20.2 ± 5.2 L to 19.0 ± 4.8 L), total body volume decreased (39.8 ± 9.8 L to 37.8 ± 8.5 L) and adipose tissue mass decreased (38.4 ± 16.0 kg to 29.9 ± 12.9 kg; all p < 0.002). Correlation of BIS-derived parameters from pre to post-paracentesis ranged from R² = 0.26 for body cell mass to R² = 0.99 for ECV. Edema did not correlate with BIS-derived fluid overload (FO ≥ 15% ECV), which occurred in 16 patients (51.6%). In conclusion, BIS-derived information on fluid status did not coincide with clinical judgement. The changes in adipose tissue mass support the BIS-model assumption that fluid in the peritoneal cavity is not detectable, suggesting that ascites (or peritoneal dialysis fluid) mass should be subtracted from adipose tissue if BIS is used in patients with a full peritoneal cavity.

See Clinical Research on Page 1670 See Clinical Research on Page 1670 The clinical excellence of Japanese hemodialysis practice can hardly be overestimated, as substantially better outcomes have consistently been reported for Japan in comparison with other nations. In a narrative review,1Port F.K. Practice-based versus patient-level outcomes research in hemodialysis: the DOPPS (Dialysis Outcomes and Practice Patterns Study) experience.Am J Kidney Dis. 2014; 64: 969-977Abstract Full Text Full Text PDF PubMed Scopus (11) Google Scholar written on receiving the David M. Hume Memorial Award, Friedrich K. Port recapitulated that better survival among Japanese versus US hemodialysis patients became evident as early as 1990, through comparison of registry data.2Held P.J. Brunner F. Odaka M. et al.Five-year survival for end-stage renal disease patients in the United States, Europe, and Japan, 1982 to 1987.Am J Kidney Dis. 1990; 15: 451-457Abstract Full Text PDF PubMed Scopus (270) Google Scholar By initiating the international Dialysis Outcomes and Practice Patterns Study (DOPPS), Dr. Port and colleagues responded to the critical need of studying ways to improve care and outcomes for hemodialysis patients in the United States. In consequence, Japan was among the first countries whose hemodialysis data were recorded and analyzed in DOPPS. The current issue of Kidney International Reports now includes an analysis from the Japanese (J) DOPPS alone. Using J-DOPPS data, Takashi et al.3Hara T. Kimachi M. Akizawa T. et al.Interdialytic weight gain effects on hemoglobin concentration and cardiovascular events.Kidney Int Rep. 2020; 5: 1670-1678Abstract Full Text Full Text PDF Scopus (6) Google Scholar found that hemodialysis patients in the highest interdialytic weight gain (IDWG) category of ≥6% had a higher risk for major adverse cardiovascular events if their hemoglobin (Hb) concentration was ≥11.0 to <12.0 g/dl, when compared with patients with an Hb concentration ≥10.0 to <11.0 g/dl. The relative excess risk due to interaction between IDWG and Hb was 0.22, and the corresponding 95% confidence interval excluded zero, indicating a synergistic interaction between Hb and IDWG on major adverse cardiovascular events.3Hara T. Kimachi M. Akizawa T. et al.Interdialytic weight gain effects on hemoglobin concentration and cardiovascular events.Kidney Int Rep. 2020; 5: 1670-1678Abstract Full Text Full Text PDF Scopus (6) Google Scholar This study brings to light several questions worth discussing regarding its definitions, outcomes and analysis. In the article by Takashi et al.,3Hara T. Kimachi M. Akizawa T. et al.Interdialytic weight gain effects on hemoglobin concentration and cardiovascular events.Kidney Int Rep. 2020; 5: 1670-1678Abstract Full Text Full Text PDF Scopus (6) Google Scholar IDWG was expressed as a percentage (without specifying whether this percentage referred to pre- or postdialysis body weight). Intradialytic weight loss was used as a proxy for IDWG and was assessed in the first session of the week at the enrollment into J-DOPPS. This approach, however, is not optimal and is not consistent with the most recent international DOPPS analysis, which used actual weight data (predialysis body weight minus postdialysis body weight of the previous hemodialysis session) from 3 consecutive dialysis sessions rather than from the first session of the week, calculating IDWG in percentage of postdialysis weight.4Wong M.M. McCullough K.P. Bieber B.A. et al.Interdialytic weight gain: trends, predictors, and associated outcomes in the international Dialysis Outcomes and Practice Patterns Study (DOPPS).Am J Kidney Dis. 2017; 69: 367-379Abstract Full Text Full Text PDF PubMed Scopus (74) Google Scholar The approach used by Takashi et al.3Hara T. Kimachi M. Akizawa T. et al.Interdialytic weight gain effects on hemoglobin concentration and cardiovascular events.Kidney Int Rep. 2020; 5: 1670-1678Abstract Full Text Full Text PDF Scopus (6) Google Scholar permitted including patients from the earliest DOPPS phase (1996–2001), where only intradialytic weight loss was available, and this strategy might have increased the fraction of patients with relatively high weight gains (IDWGs), who were more prevalent in the earlier DOPPS phases.4Wong M.M. McCullough K.P. Bieber B.A. et al.Interdialytic weight gain: trends, predictors, and associated outcomes in the international Dialysis Outcomes and Practice Patterns Study (DOPPS).Am J Kidney Dis. 2017; 69: 367-379Abstract Full Text Full Text PDF PubMed Scopus (74) Google Scholar However, using the first hemodialysis session of the week after the long interdialytic interval inevitably increases the number of patients with high IDWGs. Of note, the number of patients who actually fulfilled both criteria, high Hb and high IDWG, was small in this study: 230 of the entire study data set of 8234 patients (= 2.8%, deduced from Table 2 from Takashi et al.3Hara T. Kimachi M. Akizawa T. et al.Interdialytic weight gain effects on hemoglobin concentration and cardiovascular events.Kidney Int Rep. 2020; 5: 1670-1678Abstract Full Text Full Text PDF Scopus (6) Google Scholar). In the article by Takashi et al.,3Hara T. Kimachi M. Akizawa T. et al.Interdialytic weight gain effects on hemoglobin concentration and cardiovascular events.Kidney Int Rep. 2020; 5: 1670-1678Abstract Full Text Full Text PDF Scopus (6) Google Scholar the association between IDWG and mortality was assessed with a Cox model that used only IDWG at baseline (which encompasses the shortcoming of the single IDWG assessment specified previously). The most recent international DOPPS analysis also used a Cox model, where time at risk started at the baseline IDWG data collection.4Wong M.M. McCullough K.P. Bieber B.A. et al.Interdialytic weight gain: trends, predictors, and associated outcomes in the international Dialysis Outcomes and Practice Patterns Study (DOPPS).Am J Kidney Dis. 2017; 69: 367-379Abstract Full Text Full Text PDF PubMed Scopus (74) Google Scholar Both analyses excluded patients with hemodialysis vintage <6 months3Hara T. Kimachi M. Akizawa T. et al.Interdialytic weight gain effects on hemoglobin concentration and cardiovascular events.Kidney Int Rep. 2020; 5: 1670-1678Abstract Full Text Full Text PDF Scopus (6) Google Scholar and <12 months,4Wong M.M. McCullough K.P. Bieber B.A. et al.Interdialytic weight gain: trends, predictors, and associated outcomes in the international Dialysis Outcomes and Practice Patterns Study (DOPPS).Am J Kidney Dis. 2017; 69: 367-379Abstract Full Text Full Text PDF PubMed Scopus (74) Google Scholar respectively. In contrast to these approaches,4Wong M.M. McCullough K.P. Bieber B.A. et al.Interdialytic weight gain: trends, predictors, and associated outcomes in the international Dialysis Outcomes and Practice Patterns Study (DOPPS).Am J Kidney Dis. 2017; 69: 367-379Abstract Full Text Full Text PDF PubMed Scopus (74) Google Scholar the perhaps most prominent analysis of IDWG and mortality, published by Kamyar Kalantar-Zadeh et al.5Kalantar-Zadeh K. Regidor D.L. Kovesdy C.P. et al.Fluid retention is associated with cardiovascular mortality in patients undergoing long-term hemodialysis.Circulation. 2009; 119: 671-679Crossref PubMed Scopus (401) Google Scholar in 2009, used time-dependent (quarterly varying) Cox models that included IDWG as a repeated measure, averaged over each 13-week calendar quarter. Calculating the 13-week averaged predialysis and postdialysis weights for each patient during each of the calendar quarters of the cohort meant that up to 39 dialysis treatments per calendar quarter were considered.5Kalantar-Zadeh K. Regidor D.L. Kovesdy C.P. et al.Fluid retention is associated with cardiovascular mortality in patients undergoing long-term hemodialysis.Circulation. 2009; 119: 671-679Crossref PubMed Scopus (401) Google Scholar The association between IDWG and mortality, however, differs according to the statistical model (time-dependent vs. baseline model) that is used.6Hecking M. Moissl U. Genser B. et al.Greater fluid overload and lower interdialytic weight gain are independently associated with mortality in a large international hemodialysis population.Nephrol Dial Transplant. 2018; 33: 1842-1852Crossref PubMed Scopus (52) Google Scholar Patients who have high IDWGs should not automatically be equalized with patients who have chronic volume overload.7Hecking M. Karaboyas A. Antlanger M. et al.Significance of interdialytic weight gain versus chronic volume overload: consensus opinion.Am J Nephrol. 2013; 38: 78-90Crossref PubMed Scopus (97) Google Scholar Of note, when Hecking et al.6Hecking M. Moissl U. Genser B. et al.Greater fluid overload and lower interdialytic weight gain are independently associated with mortality in a large international hemodialysis population.Nephrol Dial Transplant. 2018; 33: 1842-1852Crossref PubMed Scopus (52) Google Scholar recently analyzed data from NephroCare, the highest mortality risk association was observed in the group of patients with low IDWG and chronic fluid overload, as shown by bioimpedance spectroscopy. In contrast to previous analyses, we statistically considered IDWG (i) as a time-varying 1-month average, (ii) as a time-varying 12-month moving average, and (iii) as a long-term risk factor, which we believe was an adequate compromise between the approaches taken by Kalantar-Zadeh et al.5Kalantar-Zadeh K. Regidor D.L. Kovesdy C.P. et al.Fluid retention is associated with cardiovascular mortality in patients undergoing long-term hemodialysis.Circulation. 2009; 119: 671-679Crossref PubMed Scopus (401) Google Scholar versus by the DOPPS group.4Wong M.M. McCullough K.P. Bieber B.A. et al.Interdialytic weight gain: trends, predictors, and associated outcomes in the international Dialysis Outcomes and Practice Patterns Study (DOPPS).Am J Kidney Dis. 2017; 69: 367-379Abstract Full Text Full Text PDF PubMed Scopus (74) Google Scholar With regard to the present study, the highest risk association (mortality and major adverse cardiovascular events) was observed in patients who had low Hb concentrations and low IDWGs (Tables 4 and 5 from Takashi et al.3Hara T. Kimachi M. Akizawa T. et al.Interdialytic weight gain effects on hemoglobin concentration and cardiovascular events.Kidney Int Rep. 2020; 5: 1670-1678Abstract Full Text Full Text PDF Scopus (6) Google Scholar), but was downplayed as being due to inflammatory factors that “could not be adjusted for.” According to Table 2 from Takashi et al.3Hara T. Kimachi M. Akizawa T. et al.Interdialytic weight gain effects on hemoglobin concentration and cardiovascular events.Kidney Int Rep. 2020; 5: 1670-1678Abstract Full Text Full Text PDF Scopus (6) Google Scholar, the number of patients at risk was substantially higher than those 2.8% with an Hb concentration ≥10.0 to <11.0 g/dl and IDWG ≥6%, and this number would likely have been much higher still, if patients with vintage <6 months had not been excluded. Patients with low Hb and low IDWG, on top of being inflamed, could be suffering from chronic fluid overload, and their low Hb concentrations could indicate hemodilution combined with malnutrition, as indicated by the lower albumin levels in these patients. Asking patients the simple question: “Have you recently stopped eating?” during rounds could help identify those patients who are likely at the very highest risk. The first international DOPPS publication on nonadherence8Saran R. Bragg-Gresham J.L. Rayner H.C. et al.Nonadherence in hemodialysis: associations with mortality, hospitalization, and practice patterns in the DOPPS.Kidney Int. 2003; 64: 254-262Abstract Full Text Full Text PDF PubMed Scopus (370) Google Scholar found that IDWG >5.7% of dry weight was most prevalent in Japan, although (as was also indicated by other nonadherence measures) Japanese patients are likely among the most “adherent” individuals worldwide. The most recent international DOPPS publication on IDWG confirmed that IDWGs are higher in Japan than in the other DOPPS countries.4Wong M.M. McCullough K.P. Bieber B.A. et al.Interdialytic weight gain: trends, predictors, and associated outcomes in the international Dialysis Outcomes and Practice Patterns Study (DOPPS).Am J Kidney Dis. 2017; 69: 367-379Abstract Full Text Full Text PDF PubMed Scopus (74) Google Scholar One reason for this finding might be higher salt consumption, and an indicator for this hypothesis could be the fact that hemodialysis patients in Japan have higher serum sodium concentrations than patients in most other DOPPS countries.4Wong M.M. McCullough K.P. Bieber B.A. et al.Interdialytic weight gain: trends, predictors, and associated outcomes in the international Dialysis Outcomes and Practice Patterns Study (DOPPS).Am J Kidney Dis. 2017; 69: 367-379Abstract Full Text Full Text PDF PubMed Scopus (74) Google Scholar Another plausible reason could be an excellent (somewhat dehydrated) volume status postdialysis in Japanese patients. Although data from Japan and the United States are not recorded in NephroCare, the analysis of this data set has shown that IDWG can be positively predicted by bioimpedance spectroscopy-proven fluid overload predialysis, and negatively predicted by fluid overload postdialysis.6Hecking M. Moissl U. Genser B. et al.Greater fluid overload and lower interdialytic weight gain are independently associated with mortality in a large international hemodialysis population.Nephrol Dial Transplant. 2018; 33: 1842-1852Crossref PubMed Scopus (52) Google Scholar Conceptually, this finding means that thirst induced by postdialysis dehydration cannot be ignored by patients, and some of the highest IDWG patients might be relatively more dehydrated. Lower levels of fluid overload in Japan could thus be one of the reasons for substantially better outcomes in this country. However, the latter theory is currently speculative. When Takeshi et al.3Hara T. Kimachi M. Akizawa T. et al.Interdialytic weight gain effects on hemoglobin concentration and cardiovascular events.Kidney Int Rep. 2020; 5: 1670-1678Abstract Full Text Full Text PDF Scopus (6) Google Scholar stated that the interaction between Hb and IDWG is not well understood, they cited a study that thoroughly evaluated Hb concentrations in a small cohort: before and after hemodialysis, after the long and the short interdialytic interval.9Bellizzi V. Minutolo R. Terracciano V. et al.Influence of the cyclic variation of hydration status on hemoglobin levels in hemodialysis patients.Am J Kidney Dis. 2002; 40: 549-555Abstract Full Text Full Text PDF PubMed Scopus (36) Google Scholar This study suggested that the short interdialytic period is the most appropriate timing for anemia assessment, but otherwise focussed on the short-term changes in Hb in consequence of the ultrafiltration during hemodialysis. In the data set analyzed by Takeshi et al.,3Hara T. Kimachi M. Akizawa T. et al.Interdialytic weight gain effects on hemoglobin concentration and cardiovascular events.Kidney Int Rep. 2020; 5: 1670-1678Abstract Full Text Full Text PDF Scopus (6) Google Scholar Hb concentrations tended to be lower in the group of patients with IDWG ≥6% (Table 1 in Takeshi et al.3Hara T. Kimachi M. Akizawa T. et al.Interdialytic weight gain effects on hemoglobin concentration and cardiovascular events.Kidney Int Rep. 2020; 5: 1670-1678Abstract Full Text Full Text PDF Scopus (6) Google Scholar), which might indicate a relationship between higher IDWG and lower Hb. Unfortunately, the authors did not dissect the relationship between IDWG and Hb any further, and did not report the correlation coefficient between IDWG and Hb. Thus, the relationship between Hb and IDWG has not been disentangled, and the next analytical steps would require additional assessment of fluid overload with an objective method. We have summarized our understanding of the interplay among IDWG, intradialytic weight loss, fluid overload, and Hb in Figure 1.6Hecking M. Moissl U. Genser B. et al.Greater fluid overload and lower interdialytic weight gain are independently associated with mortality in a large international hemodialysis population.Nephrol Dial Transplant. 2018; 33: 1842-1852Crossref PubMed Scopus (52) Google Scholar,9Bellizzi V. Minutolo R. Terracciano V. et al.Influence of the cyclic variation of hydration status on hemoglobin levels in hemodialysis patients.Am J Kidney Dis. 2002; 40: 549-555Abstract Full Text Full Text PDF PubMed Scopus (36) Google Scholar We recommend future studies with additional data collection on volume status with the aim to answer the questions that have been posed by Takashi et al.3Hara T. Kimachi M. Akizawa T. et al.Interdialytic weight gain effects on hemoglobin concentration and cardiovascular events.Kidney Int Rep. 2020; 5: 1670-1678Abstract Full Text Full Text PDF Scopus (6) Google Scholar All the authors declared no competing interests. Interdialytic Weight Gain Effects on Hemoglobin Concentration and Cardiovascular EventsKidney International ReportsVol. 5Issue 10PreviewAlthough predialysis hemoglobin concentration is affected by interdialytic weight gain (IDWG), the interaction between these parameters is not well understood. Full-Text PDF Open Access

Bioimpedance spectroscopy (BIS) is an easily applicable tool to assess body composition. The three compartment model BIS (3C BIS) conventionally expresses body composition as lean tissue index (LTI) (lean tissue mass [LTM]/height in meters squared) and fat tissue index (FTI) (adipose tissue mass/height in meters squared), and a virtual compartment reflecting fluid overload (FO). It has been studied extensively in relation to diagnosis and treatment guidance of fluid status disorders in patients with advanced-stage or end-stage renal disease. It is the aim of this article to provide a narrative review on the relevance of 3C BIS in the nutritional assessment in this population. At a population level, LTI decreases after the start of hemodialysis, whereas FTI increases. LTI below the 10th percentile is a consistent predictor of outcome whereas a low FTI is predominantly associated with outcome when combined with a low LTI. Recent research also showed the connection between low LTI, inflammation, and FO, which are cumulatively associated with an increased mortality risk. However, studies toward nutritional interventions based on BIS data are still lacking in this population. In conclusion, 3C BIS, by disentangling the components of body mass index, has contributed to our understanding of the relevance of abnormalities in different body compartments in chronic kidney disease patients, and appears to be a valuable prognostic tool, at least at a population level. Studies assessing the effect of BIS guided nutritional intervention could further support its use in the daily clinical care for renal patients.

The Body Composition Monitor (BCM) is a bioimpedance spectroscopy device to monitor the hydration status of dialysis and CKD patients. NICE (UK) reported only limited evidence on the clinical effectiveness in its Diagnostic Guidance 29. The aim of this work was to provide a structured review of the available evidence up to September 2018 grouped by the most important clinical outcomes (fluid overload, blood pressure, mortality and cardiovascular events). MEDLINE, Embase and Cochrane databases were interrogated from 2006 to September 2018. Search and review of identified studies was conducted in compliance with the guidelines for Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Of 4497 articles identified, 843 were included for full-text review; 424 were full publications and were selected for further analysis. Eight randomized controlled trial (RCT) studies and 150 observational studies met the predefined inclusion criteria; of these, observational studies that recruited at least 100 patients and additionally reported important clinical outcomes such as mortality, cardiovascular (CV) events or hospitalization were selected. Two further RCTs were identified by supplementary searches, giving a total of 10 RCTs (total 2.156 patients) and 41 observational studies (total 168.453 patients) included in this review. The data was grouped by reported outcomes and for each outcome it was analyzed if an effect of BCM-monitored fluid management, or an association between BCM assessment and the respective outcome could be shown. A meta-analysis of the results was not conducted. RCTs have shown that BCM-monitored fluid management and subsequent alteration of dialysis parameters can lead to effective reduction of fluid overload. RCTs have indicated that BCM-monitored fluid management can effectively lower blood pressure. Multiple observational studies have shown a strong association between BCM measurements and mortality. One RCT demonstrated that mortality outcomes can be significantly improved in HD patients with BCM-guided fluid management, while two RCTs reported no significant difference in mortality outcomes. Multiple observational studies have indicated that BCM measurements can predict CV events. One RCT indicated that CV events can be reduced by BCM-monitored fluid management, and two further RCTs indicated that using BCM guidance was at least as good as conventional fluid management. There is a strong body of evidence for various important outcomes covering a large patient basis - additional evidence is needed in well designed randomized controlled trials e.g. to demonstrate the effect of reducing BCM determined dehydration.

Bioimpedance analysis has become a widely used technology to assess body composition in health and disease. While most devices on the market use a single frequency, multifrequency devices have advantages in extremes of body composition. The BCM-Body Composition Monitor combines spectroscopy with the Chamney 3-compartment model (Chamney et al, AJCN 2007) to determine body composition independent of fluid status, and is thereby the only device suitable in patients with altered hydration status. While reference ranges for lean and fat tissue index (LTI, FTI) have been long available for Caucasians, no such data has yet been collected in a large and diverse Asian population.

Chronic fluid overload has been related to severely increased mortality in ESRD patients. In addition, the increasing prevalence of diabetes along with concomitant diseases make fluid management more difficult and calls for individualized fluid targets, taking co-morbidities into account. Aim of this work was to assess the mortality risk of diabetes in different degrees of chronic fluid overload, and to identify potential target ranges for optimal outcome.

BACKGROUND:Both baseline fluid overload (FO) and fluid depletion are associated with increased mortality risk and cardiovascular complications in haemodialysis patients. Fluid status may vary substantially over time, and this variability could also be associated with poor outcomes. METHODS:In our retrospective cohort study, including 4114 haemodialysis patients from 34 Romanian dialysis units, we investigated both all-cause and cardiovascular mortality risk according to baseline pre- and post-dialysis volume status, changes in pre- and post-dialysis fluid status during follow-up (time-varying survival analysis), pre-post changes in volume status during dialysis and pre-dialysis fluid status variability during the first 6 months of evaluation. RESULTS:According to their pre-dialysis fluid status, patients were stratified in the following groups: normovolaemic with an absolute FO (AFO) compartment between -1.1 and 1.1 L, fluid depletion with an AFO below -1.1 L, moderate FO with an AFO compartment >1.1 but <2.5 L and severe FO with the AFO compartment >2.5 L. Baseline pre-dialysis FO and fluid depletion patients had a significantly elevated risk of all-cause mortality risk {hazard ratio [HR] 1.53 [95% confidence interval (CI) 1.22-1.93], HR 2.04 (95% CI 1.59-2.60) and HR 1.88 (95% CI 1.07-3.39) for moderate FO, severe FO and fluid depletion, respectively}. In contrast, post-dialysis fluid depletion was associated with better survival [HR 0.71 (95% CI 0.57-0.89)]. Similar results were found when using changes in pre- or post-dialysis fluid status during follow-up (time-varying values): FO patients had an increased risk of all-cause [moderate FO: HR 1.39 (95% CI 1.11-1.75); severe FO: HR 2.29 (95% CI 2.01-3.31] and cardiovascular (CV) mortality [moderate FO: HR 1.34 (95% CI 1.05-1.70); severe FO: HR 2.34 (95% CI 1.67-3.28)] as compared with normohydrated patients. Using pre-post changes in volume status during dialysis, we categorized the patients into six groups: Group 1, AFO <-1.1 L pre- and post-dialysis; Group 2, AFO between -1.1 and 1.1 L pre-dialysis and <-1.1 L post-dialysis (the reference group); Group 3, AFO between -1.1 and 1.1 L pre- and post-dialysis; Group 4, AFO >1.1 L pre-dialysis and <-1.1 L post-dialysis; Group 5, AFO >1.1 L pre-dialysis and between -1.1 and 1.1 L post-dialysis; Group 6, AFO >1.1 L pre- and post-dialysis. Using the baseline values, only patients in Groups 1, 5 and 6 maintained an increased risk for all-cause mortality as compared with the reference group. Additionally, CV mortality risk was significantly higher for patients in Groups 5 and 6. When we applied the time-varying analysis, patients in Groups 1, 5 and 6 had a significantly higher risk for both all-cause and CV mortality risk. In the last approach, the highest risk for the all-cause mortality outcome was observed for patients with high-amplitude fluctuation during the first 6 months of evaluation [HR 2.75 (95% CI 1.29-5.84)]. CONCLUSION:We reconfirm the association between baseline pre- and post-dialysis volume status and mortality in dialysis patients; additionally, we showed that greater fluid status variability is independently associated with higher mortality.

Bioimpedance spectroscopy (BIS) with a whole-body model to distinguish excess fluid from major body tissue hydration can provide objective assessment of fluid status. BIS is integrated into the Body Composition Monitor (BCM) and is validated in adults, but not children. This study aimed to (1) assess agreement between BCM-measured total body water (TBW) and a gold standard technique in healthy children, (2) compare TBW_BCM with TBW from Urea Kinetic Modelling (UKM) in haemodialysis children and (3) investigate systematic deviation from zero in measured excess fluid in healthy children across paediatric age range.

Long-term elevated blood sugar levels result in tissue matrix compositional changes in patients with diabetes mellitus type 2 (T2DM). We hypothesized that hemodialysis patients with T2DM might accumulate more tissue sodium than control hemodialysis patients. To test this, 23Na magnetic resonance imaging (23Na MRI) was used to estimate sodium in skin and muscle tissue in hemodialysis patients with or without T2DM. Muscle fat content was estimated by 1H MRI and tissue sodium content by 23Na MRI pre- and post-hemodialysis in ten hemodialysis patients with T2DM and in 30 matched control hemodialysis patients. We also assessed body fluid distribution with the Body Composition Monitor. 1H MRI indicated a tendency to higher muscle fat content in hemodialysis patients with T2DM compared to non-diabetic hemodialysis patients. 23Na MRI indicated increased sodium content in muscle and skin tissue of hemodialysis patients with T2DM compared to control hemodialysis patients. Multi-frequency bioimpedance was used to estimate extracellular water (ECW), and excess ECW in T2DM hemodialysis patients correlated with HbA1c levels. Sodium mobilization during hemodialysis lowered muscle sodium content post-dialysis to a greater degree in T2DM hemodialysis patients than in control hemodialysis patients. Thus, our findings provide evidence that increased sodium accumulation occurs in hemodialysis patients with T2DM and that impaired serum glucose metabolism is associated with disturbances in tissue sodium and water content.

Background. Fluid overload and interdialytic weight gain (IDWG) are discrete components of the dynamic fluid balance in haemodialysis patients. We aimed to disentangle their relationship, and the prognostic importance of two clinically distinct, bioimpedance spectroscopy (BIS)-derived measures, pre-dialysis and post-dialysis fluid overload (FOpre and FOpost) versus IDWG. Methods. We conducted a retrospective cohort study on 38 614 incident patients with one or more BIS measurement within 90 days of haemodialysis initiation (1 October 2010 through 28 February 2015). We used fractional polynomial regression to determine the association pattern between FOpre, FOpost and IDWG, and multivariate adjusted Cox models with FO and/or IDWG as longitudinal and time-varying predictors to determine all-cause mortality risk. Results. In analyses using 1-month averages, patients in quartiles 3 and 4 (Q3 and Q4) of FO had an incrementally higher adjusted mortality risk compared with reference Q2, and patients in Q1 of IDWG had higher adjusted mortality compared with Q2. The highest adjusted mortality risk was observed for patients in Q4 of FOpre combined with Q1 of IDWG [hazard ratio (HR) = 2.66 (95% confidence interval 2.21-3.20), compared with FOpre-Q2/IDWG-Q2 (reference)]. Using longitudinal means of FO and IDWG only slightly altered all HRs. IDWG associated positively with FOpre, but negatively with FOpost, suggesting a link with post-dialysis extracellular volume depletion. Conclusions. FOpre and FOpost were consistently positive risk factors for mortality. Low IDWG was associated with short-term mortality, suggesting perhaps an effect of protein-energy wasting. FOpost reflected the volume status without IDWG, which implies that this fluid marker is clinically most intuitive and may be best suited to guide volume management in haemodialysis patients.