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• W2048555639 abstract "Bioimpedance analysis (BIA) derives two main pieces of information—total tissue fluid content, which when referring to the whole patient is equivalent to the total body water (TBW), and cell mass, which in the limbs mainly reflects muscle. The relationship between these measures, expressed in different ways, is abnormal in dialysis patients due to muscle wasting combined with tissue overhydration. In both dialysis modalities this is associated with aging, comorbidity, and inflammation, and there is a conflict between achieving euvolemia to improve blood pressure control and prevent left ventricular hypertrophy on one hand, but risking episodes of hypovolemia and loss of residual renal function on the other. In peritoneal dialysis, the situation is exacerbated by hypoalbuminemia, whereas in hemodialysis BIA is unable to distinguish between the plasma volume and tissue edema components of interdialytic weight gain. In longitudinal studies BIA can identify changes in hydration following a defined intervention, and spontaneous loss in TBW consequent on muscle wasting not appreciated clinically, resulting in a failure to sufficiently reduce the dry weight. Cardiac biomarkers provide additional information but it is not clear whether this reflects fluid status or underlying structural organ damage. Intervention studies are now needed that show how this information is best used to improve patient outcomes, including meaningful end points such as hospitalization and survival. Bioimpedance analysis (BIA) derives two main pieces of information—total tissue fluid content, which when referring to the whole patient is equivalent to the total body water (TBW), and cell mass, which in the limbs mainly reflects muscle. The relationship between these measures, expressed in different ways, is abnormal in dialysis patients due to muscle wasting combined with tissue overhydration. In both dialysis modalities this is associated with aging, comorbidity, and inflammation, and there is a conflict between achieving euvolemia to improve blood pressure control and prevent left ventricular hypertrophy on one hand, but risking episodes of hypovolemia and loss of residual renal function on the other. In peritoneal dialysis, the situation is exacerbated by hypoalbuminemia, whereas in hemodialysis BIA is unable to distinguish between the plasma volume and tissue edema components of interdialytic weight gain. In longitudinal studies BIA can identify changes in hydration following a defined intervention, and spontaneous loss in TBW consequent on muscle wasting not appreciated clinically, resulting in a failure to sufficiently reduce the dry weight. Cardiac biomarkers provide additional information but it is not clear whether this reflects fluid status or underlying structural organ damage. Intervention studies are now needed that show how this information is best used to improve patient outcomes, including meaningful end points such as hospitalization and survival. Fluid management is one of the principle objectives of dialysis treatment, and this requires the clinician to make an accurate assessment of fluid status. Traditionally, this was achieved using clinical examination and in particular blood pressure measurement combined with (usually downward) titration of the target dry weight until normovolemia was obtained. It is now realized that clinical assessment is much more complex than this, confounded by vascular stiffness, cardiac dysfunction, hypoalbuminemia, and multimorbidity and the desire to preserve residual kidney function such that other, more objective tools are required. Bioimpedance, with or without the associated use of cardiac biomarkers, has the potential to fulfill this role. This review will briefly introduce the concepts underpinning bioimpedance and how the new information from electrical measurements is manipulated to quantify hydration status in dialysis patients. This is followed by a discussion of what this technique has taught us first about peritoneal dialysis and then hemodialysis treatment. The picture is complex, and despite limitations there is evidence emerging that bioimpedance is providing useful information that could help direct treatment. The challenge now is to demonstrate the best use of this technology in the clinic. BIA gives the clinician two measures over and above height and weight that provide new information related to body composition.1.Jaffrin M.Y. Morel H. Body fluid volumes measurements by impedance: a review of bioimpedance spectroscopy (BIS) and bioimpedance analysis (BIA) methods.Med Eng Phys. 2008; 30: 1257-1269Abstract Full Text Full Text PDF PubMed Scopus (316) Google Scholar In a simple direct current electrical circuit, flow at a given voltage is determined by resistance. When an alternating current is applied, however, as in BIA, there is a second quantifiable factor causing impedance to flow, termed phase but usually expressed as reactance (see Figure 1); this provides the additional metric that enables BIA to distinguish fluid compartments. Therefore, when an alternating current is applied to mammalian tissue, the measurement of resistance is inversely proportional to the total (intracellular and extracellular water (ECW)) content between two electrodes placed at a distance on the skin, whereas the reactance, a measure of electrical capacitance, is proportional to the cell mass in this tissue volume. The various methods of capturing and interpreting this information (total body, segmental, single or multiple frequency, vector displays, or compartment volume interpolation) are all variously sophisticated versions of obtaining indirect measures of tissue water content and the proportion that is in the intracellular and extracellular spaces. Because an electrical current will always find the path of least resistance, the limbs with their neurovascular bundles and high muscle (thus water) content proportional to their cross-sectional area provide disproportionately more information (>80%) when using BIA than the trunk. This has led some users to prefer segmental measurements (e.g., the lower leg,2.Zhu F. Kuhlmann M.K. Kaysen G.A. et al.Segment-specific resistivity improves body fluid volume estimates from bioimpedance spectroscopy in hemodialysis patients.J Appl Physiol (1985). 2006; 100: 717-724Crossref PubMed Scopus (68) Google Scholar chest wall3.Nescolarde L. García-González M.A. Rosell-Ferrer J. et al.Thoracic versus whole body bioimpedance measurements: the relation to hydration status and hypertension in peritoneal dialysis patients.Physiol Meas. 2006; 27: 961-971Crossref PubMed Scopus (14) Google Scholar) and the development of devices with up to eight electrodes (e.g. InBody, Seoul, Korea) placed so that each limb and the trunk can be analyzed separately. Although combining several segmental measurements may give a more precise description of body composition,2.Zhu F. Kuhlmann M.K. Kaysen G.A. et al.Segment-specific resistivity improves body fluid volume estimates from bioimpedance spectroscopy in hemodialysis patients.J Appl Physiol (1985). 2006; 100: 717-724Crossref PubMed Scopus (68) Google Scholar there is no clear evidence that this translates into better hard clinical outcomes or is better at identifying excess truncal obesity or third-space fluid, which BIA is least good at doing. A further advantage of a single segment approach is the possibility of making continuous measurements during a procedure (e.g., hemodialysis),4.Zhu F. Leonard E.F. Levin N.W. Extracellular fluid redistribution during hemodialysis: bioimpedance measurement and model.Physiol Meas. 2008; 29: S491-S501Crossref PubMed Scopus (37) Google Scholar enabling tracking of hydration to the point of normalization without interference from other equipment, as will be discussed later. The behavior of an alternating electrical current that is passed through tissues is dependent on its frequency—when low, typically 5MHz, the impedance is higher as the proportion stored by cell membranes is greater; the inverse is true at high frequencies, e.g., 1000MHz.1.Jaffrin M.Y. Morel H. Body fluid volumes measurements by impedance: a review of bioimpedance spectroscopy (BIS) and bioimpedance analysis (BIA) methods.Med Eng Phys. 2008; 30: 1257-1269Abstract Full Text Full Text PDF PubMed Scopus (316) Google Scholar The use of multiple frequencies, usually termed bioimpedance spectroscopy,5.Moissl U.M. Wabel P. Chamney P.W. et al.Body fluid volume determination via body composition spectroscopy in health and disease.Physiol Meas. 2006; 27: 921-933Crossref PubMed Scopus (459) Google Scholar enables the calculation of theoretical resistance values at zero and infinite frequencies by fitting a polynomial curve termed the Cole–Cole plot, and thus improving the accuracy of equations that are used to derive intracellular and extracellular compartments. Different devices use different fitting equations to achieve this, for example, attempting to correct for varying degrees of obesity, which can result in quite different and variably validated extrapolated volumes. However, the ratio between these two theoretical values of resistance, the phase angle at individual frequencies (e.g. 50MHz), and even the extrapolated intracellular water/ECW (or ECW/total body water (TBW)) ratio are all highly correlated (typically R2>0.86). There are a number of ways in which the electrical data from BIA can be used in the clinic, as summarized in Table 1 along with their advantages and disadvantages. The simplest approach is a vector plot, as shown in Figure 1, which is strongly predictive of patient outcomes6.Pillon L. Piccoli A. Lowrie E.G. et al.Vector length as a proxy for the adequacy of ultrafiltration in hemodialysis.Kidney Int. 2004; 66: 1266-1271Abstract Full Text Full Text PDF PubMed Scopus (99) Google Scholar and has been exploited by Piccoli7.Piccoli A. Identification of operational clues to dry weight prescription in hemodialysis using bioimpedance vector analysis. The Italian Hemodialysis-Bioelectrical Impedance Analysis (HD-BIA) Study Group.Kidney Int. 1998; 53: 1036-1043Abstract Full Text Full Text PDF PubMed Scopus (167) Google Scholar to track body composition longitudinally. This enables visualization of the direction in which the body composition is changing (e.g., becoming more overhydrated), but when adjusting the dry weight of dialysis patients clinicians like to think in kilograms or liters of fluid. Ideally, therefore the raw electrical data from BIA would be interpolated into liters of body fluid according to their compartment. This is only possible because the human body can be considered to consist approximately of 5 cylinders, four limbs, and the trunk, and by combining resistance and reactance data with height and weight, which approximate to cylinder length and cross-sectional area, respectively. Equations used to make this transformation, such as those using Hanai mixture theory, also include empirically derived correction factors to account for gender, tissue resistivity, and body mass index that are usually device specific.5.Moissl U.M. Wabel P. Chamney P.W. et al.Body fluid volume determination via body composition spectroscopy in health and disease.Physiol Meas. 2006; 27: 921-933Crossref PubMed Scopus (459) Google Scholar,8.De Lorenzo A. Andreoli A. Matthie J. et al.Predicting body cell mass with bioimpedance by using theoretical methods: a technological review.J Appl Physiol (1985). 1997; 82: 1542-1558PubMed Google Scholar This can mean that in the same patients quite different values for absolute fluid volumes may be obtained using different devices (see Figure 2), whereas the ratios, e.g., ECW to TBW (ECW/TBW) correlate well. In other words, when interpreting BIA data, a distinction needs to be drawn between approaches that use the relationship that the two electrical measures resistance and reactance have with each other and those that focus on the accuracy with which they estimate absolute volumes (see Table 1). Both approaches can be used to manage patients and predict outcomes, but there are limitations; the Body Composition Monitor (BCM Fresenius, Bad Homburg, Germany)5.Moissl U.M. Wabel P. Chamney P.W. et al.Body fluid volume determination via body composition spectroscopy in health and disease.Physiol Meas. 2006; 27: 921-933Crossref PubMed Scopus (459) Google Scholar,9.Chamney P.W. Wabel P. Moissl U.M. et al.A whole-body model to distinguish excess fluid from the hydration of major body tissues.Am J Clin Nutr. 2007; 85: 80-89PubMed Google Scholar is perhaps the best validated device in this respect, with good overall agreement to the gold-standard isotope dilution techniques for the determination of ECW and TBW, but even here the 95% confidence interval in the agreement of ECW is ±2.8liters, typically 17%, and may be wider in dialysis patients, setting the current limit of precision for any BIA methodology in determining absolute fluid volumes.5.Moissl U.M. Wabel P. Chamney P.W. et al.Body fluid volume determination via body composition spectroscopy in health and disease.Physiol Meas. 2006; 27: 921-933Crossref PubMed Scopus (459) Google Scholar Comparisons of some of these methods in determining hydration status are shown in Figures 2 and 3.Table 1Comparison of the different approaches to using data derived from BIA to determine the hydration status in dialysis patientsType of approachMethod of normalizationExample of device(s)Advantages and normal valuesLimitationsVector plot of resistance (R) and reactance (Xc) (see Figure 1) to show vector length (Z) and phase angle (θ).Height, either as R/H and Xc/H or as H2/R and H2/Xc. This method inverts the relationship but is easier to use.RJL Systems or BIA 2000-SLarge database of normal values showing the effect of age, sex, and BMI (15,605 children and 213,294 adults).41.Bosy-Westphal A. Danielzik S. Dörhöfer R.P. et al.Phase angle from bioelectrical impedance analysis: population reference values by age, sex, and body mass index.JPEN J Parenter Enteral Nutr. 2006; 30: 309-316Crossref PubMed Scopus (343) Google Scholar Simple single-frequency device required, making no assumptions about absolute volumes. Both Z and θ are strong independent predictors of survival in dialysis.6.Pillon L. Piccoli A. Lowrie E.G. et al.Vector length as a proxy for the adequacy of ultrafiltration in hemodialysis.Kidney Int. 2004; 66: 1266-1271Abstract Full Text Full Text PDF PubMed Scopus (99) Google Scholar This method has been validated by Piccoli in hemodialysis patients.7.Piccoli A. Identification of operational clues to dry weight prescription in hemodialysis using bioimpedance vector analysis. The Italian Hemodialysis-Bioelectrical Impedance Analysis (HD-BIA) Study Group.Kidney Int. 1998; 53: 1036-1043Abstract Full Text Full Text PDF PubMed Scopus (167) Google ScholarNot intuitive to use clinically. Interpretation of a change in vector requires an understanding of how this reflects a change in weight, which may be fat, fluid, or muscle. Normal confidence ellipses can be shown on the vector plot as a guide7.Piccoli A. Identification of operational clues to dry weight prescription in hemodialysis using bioimpedance vector analysis. The Italian Hemodialysis-Bioelectrical Impedance Analysis (HD-BIA) Study Group.Kidney Int. 1998; 53: 1036-1043Abstract Full Text Full Text PDF PubMed Scopus (167) Google Scholar but may not help in renal failure.ECW/TBW ratio (sometimes expressed as ECW/ICW)Usually not normalized, but expressed as ratio; strictly should be normalized to sex and age.All devices (single or multifrequency)Easy to use, intuitive, and well validated as a predictor of survival. Using the Lindley–Lopot formula derived from healthy subjects that gives an age/sex-adjusted prediction:40.Lindley E. Devine Y. Hall L. et al.A ward-based procedure for assessment of fluid status in peritoneal dialysis patients using bioimpedance spectroscopy.Perit Dial Int. 2005; 25: S46-S48PubMed Google Scholar ±5% of predicted value (=±2 s.d.) is considered abnormal.Because it is a ratio either component could be abnormal. Small validation group and Lindley–Lopot formula only applies to Xitron Hydra device.ECW volumeHeight or weight by genderAll devices (single or multifrequency)Easy to use. In a clinically normovolemic group of dialysis patients, the 80th percentile values for ECW/weight were 0.245 and 0.232l/kg and for ECW/height were 10.96 and 9.13l/m in men and women, respectively.No independent survival data. ECW/H is reduced in renal failure compared with healthy subjects. Small validation group applicable to Xitron Hydra device only.OH indexECW volumeBCMProvides an easy-to-understand metric by using the BIA-derived ECW and ICW volumes and applying the normal hydration constants for lean and fat tissue to determine excess or reduced hydration.5.Moissl U.M. Wabel P. Chamney P.W. et al.Body fluid volume determination via body composition spectroscopy in health and disease.Physiol Meas. 2006; 27: 921-933Crossref PubMed Scopus (459) Google Scholar,9.Chamney P.W. Wabel P. Moissl U.M. et al.A whole-body model to distinguish excess fluid from the hydration of major body tissues.Am J Clin Nutr. 2007; 85: 80-89PubMed Google Scholar An OH/ECW index above or below 15% is abnormal. Recent RCT in HD patients demonstrating improved LVH using this approach.32.Hur E. Usta M. Toz H. et al.Effect of fluid management guided by bioimpedance spectroscopy on cardiovascular parameters in haemodialysis patients: a randomized controlled trial.Am J Kidney Dis. 2013; 61: 957-965Abstract Full Text Full Text PDF PubMed Scopus (252) Google ScholarEarly studies suggest that using this measure to guide fluid management in HD patients improved blood pressure and cardiac parameters. Data linking to clinical end points in PD patients are awaited.Abbreviations: BCM, body composition monitor; BIA, bioimpedance analysis; BMI, body mass index; ECW, extracellular water; HD, hemodialysis; ICW, intracellular water; LVH, left ventricular hypertrophy; OH, overhydration; RCT, recent randomized control trials; TBW, total body water. Open table in a new tab Figure 3The different approaches for determining fluid volumes in general show broad agreement when identifying patients with overhydration and underhydration, as shown here for 60 peritoneal dialysis (PD) patients. (a) Compares the use of a single-frequency vector plot (as shown in Figure 1) with the body composition monitor (BCM)-derived overhydration index (overhydration (OH)/extracellular water (ECW)): normal hydration , underhydration , and overhydration . (b) Compares the BCM OH index (same symbols as for a) with the ECW/total body water (TBW) ratio (observed—expected as determined by the Lindley–Lopot equation (see Appendix), in which two standard deviations of normal subjects should fall between ±5%.View Large Image Figure ViewerDownload (PPT) Abbreviations: BCM, body composition monitor; BIA, bioimpedance analysis; BMI, body mass index; ECW, extracellular water; HD, hemodialysis; ICW, intracellular water; LVH, left ventricular hypertrophy; OH, overhydration; RCT, recent randomized control trials; TBW, total body water. A consistent pattern of hydration status as determined by BIA and clinical phenotype is seen regardless of the device used. As with hemodialysis (HD) patients—and in common with many chronic diseases—the main abnormality in the body composition is reduced muscle mass (i.e., TBW), with extracellular tissue hydration being variably but often disproportionately increased.10.Woodrow G. Oldroyd B. Wright A. et al.Abnormalities of body composition in peritoneal dialysis patients.Perit Dial Int. 2004; 24: 169-175PubMed Google Scholar, 11.Plum J. Schoenicke G. Kleophas W. et al.Comparison of body fluid distribution between chronic haemodialysis and peritoneal dialysis patients as assessed by biophysical and biochemical methods.Nephrol Dial Transplant. 2001; 16: 2378-2385Crossref PubMed Scopus (113) Google Scholar, 12.van Biesen W. Claes K. Covic A. et al.A multicentric, international matched pair analysis of body composition in peritoneal dialysis versus haemodialysis patients.Nephrol Dial Transplant. 2013; 28: 2620-2628Crossref PubMed Scopus (56) Google Scholar This problem is exacerbated over time owing to progressive muscle loss, and one of the main challenges for clinicians is tracking this change. Overhydrated patients are older and more likely to be diabetic, have multimorbidity, and be hypoalbuminemic. The relationship with hypoalbuminemia is much more marked than that seen in HD patients, partly because plasma albumin is generally lower in the PD population owing to the significant peritoneal protein losses.11.Plum J. Schoenicke G. Kleophas W. et al.Comparison of body fluid distribution between chronic haemodialysis and peritoneal dialysis patients as assessed by biophysical and biochemical methods.Nephrol Dial Transplant. 2001; 16: 2378-2385Crossref PubMed Scopus (113) Google Scholar This likely explains the reported differences in tissue hydration according to modality, with PD patients having fluid status similar to predialysis HD patients. Radio labeled albumin used to determine plasma volume demonstrates that this increase in tissue fluid associated with hypoalbuminemia is due to extravascular rather than intravascular volume expansion.13.John B. Tan B.K. Dainty S. et al.Plasma volume, albumin, and fluid status in peritoneal dialysis patients.Clin J Am Soc Nephrol. 2010; 5: 1463-1470Crossref PubMed Scopus (97) Google Scholar On average, plasma volume is normal but shows higher variance than in the healthy population. Hydration status can also be affected by membrane function: rapid peritoneal solute transport is associated with increased protein losses, contributing to the hypoalbuminemia already discussed, but it also can predispose to excess dialysate reabsorption14.Asghar R.B. Davies S.J. Pathways of fluid transport and reabsorption across the peritoneal membrane.Kidney Int. 2008; 73: 1048-1053Abstract Full Text Full Text PDF PubMed Scopus (32) Google Scholar unless appropriate dialysis prescription with automated PD or icodextrin is used. The associations with blood pressure and biomarkers of cardiac injury are more complex. One large study found a modest but significant relationship between the overhydration index and blood pressure,15.Van Biesen W. Williams J.D. Covic A.C. EuroBCM Study Group et al.Fluid status in peritoneal dialysis patients: the European Body Composition Monitoring (EuroBCM) study cohort.PLoS One. 2011; 6: e17148Crossref PubMed Scopus (195) Google Scholar but this is not universal, and there is likely to be considerable confounding due to center practice patterns, case mix, and concomitant medication. Generally, the relationship of blood pressure with overhydration is more marked in case series with younger less comorbid patients. Similarly, there is much heterogeneity in the published literature linking cardiac biomarkers to hydration status. All studies find a strong relationship between raised brain natriuretic peptide (BNP) and cardiac abnormalities such as left ventricular hypertrophy, atrial enlargement, or estimated right ventricular systolic pressure;16.Wang A.Y. Lam C.W. Wang M. et al.Diagnostic potential of serum biomarkers for left ventricular abnormalities in chronic peritoneal dialysis patients.Nephrol Dial Transplant. 2009; 24: 1962-1969Crossref PubMed Scopus (41) Google Scholar some find no link with hydration status,17.Lee J.A. Kim D.H. Yoo S.J. et al.Association between serum n-terminal pro-brain natriuretic peptide concentration and left ventricular dysfunction and extracellular water in continuous ambulatory peritoneal dialysis patients.Perit Dial Int. 2006; 26: 360-365PubMed Google Scholar whereas others observe a longitudinal correlation between changes in ECW and BNP.18.Davenport A. Changes in N-terminal pro-brain natriuretic peptide correlate with fluid volume changes assessed by bioimpedance in peritoneal dialysis patients.Am J Nephrol. 2012; 36: 371-376Crossref PubMed Scopus (33) Google Scholar Given the increasing prevalence of heart failure in dialysis patients, it would be surprising if there was no association with overhydration and cardiac biomarkers, especially in those with systolic dysfunction, but the direction of causality will require a defined intervention study to clarify this. BIA is a highly reproducible measurement with interobserver and intraobserver errors usually quoted as <2%, making it an ideal tool for measuring the impact of an intervention designed to alter fluid status. Examples of this include evaluation of icodextrin and low sodium dialysate solution in which the changes in BIA-measured ECW correlated well with isotope-determined changes in TBW.19.Davies S.J. Garcia Lopez E. Woodrow G. et al.Longitudinal relationships between fluid status, inflammation, urine volume and plasma metabolites of icodextrin in patients randomized to glucose or icodextrin for the long exchange.Nephrol Dial Transplant. 2008; 23: 2982-2988Crossref PubMed Scopus (43) Google Scholar The lack of change in atrial natriuretic peptide observed with the significant fall in ECW observed with icodextrin suggests that these two estimates of fluid status are not tightly coupled or that most of the reduction in fluid was from the extravascular space. In diabetic patients who were relatively hypertensive, a reduction in ECW associated with icodextrin use was associated with improved blood pressure.20.Paniagua R. Orihuela O. Ventura M.D. et al.Echocardiographic, electrocardiographic and blood pressure changes induced by icodextrin solution in diabetic patients on peritoneal dialysis.Kidney Int Suppl. 2008; 108: S125-S130Abstract Full Text Full Text PDF PubMed Scopus (27) Google Scholar Several cohort studies have shown that overhydration as measured by the ECW/TBW ratio or vectors is strongly associated with less good survival in PD, even when corrected for known confounders such as comorbidity, inflammation, and hypoalbuminemia.21.Koh K.H. Wong H.S. Go K.W. et al.Normalized bioimpedance indices are better predictors of outcome in peritoneal dialysis patients.Perit Dial Int. 2011; 31: 574-582Crossref PubMed Scopus (26) Google Scholar,22.Paniagua R. Ventura M.D. Avila-Diaz M. et al.NT-proBNP, fluid volume overload and dialysis modality are independent predictors of mortality in ESRD patients.Nephrol Dial Transplant. 2009; 25: 551-557Crossref PubMed Scopus (189) Google Scholar Given the variable correlations seen between BNP and BIA, it is of interest that these two measures independently predict survival.22.Paniagua R. Ventura M.D. Avila-Diaz M. et al.NT-proBNP, fluid volume overload and dialysis modality are independent predictors of mortality in ESRD patients.Nephrol Dial Transplant. 2009; 25: 551-557Crossref PubMed Scopus (189) Google Scholar This suggests that combining them may add extra value in the longitudinal monitoring of dialysis patients, with BIA being a measure of overall tissue hydration and BNP a marker of cardiac injury and intravascular volume.23.Papakrivopoulou E. Lillywhite S. Davenport A. Is N-terminal probrain-type natriuretic peptide a clinically useful biomarker of volume overload inperitoneal dialysis patients?.Nephrol Dial Transplant. 2012; 27: 396-401Crossref PubMed Scopus (47) Google Scholar BIA has been used for some years to assess body water in HD patients. As with PD, changes in body composition, particularly loss of lean muscle mass and gains in adipose tissue, result in increased ECW/intracellular water or ECW/TBW ratios.12.van Biesen W. Claes K. Covic A. et al.A multicentric, international matched pair analysis of body composition in peritoneal dialysis versus haemodialysis patients.Nephrol Dial Transplant. 2013; 28: 2620-2628Crossref PubMed Scopus (56) Google Scholar Isotopic validation studies were predominantly conducted in healthy Northern European Caucasoids, and as such ECW/TBW ratios are reported to be increased in type 2 diabetic patients and some ethnic groups, including Hispanics and South Asians.24.Davenport A. Hussain Sayed R. Fan S. The effect of racial origin on total body water volume in peritoneal dialysis patients.Clin J Am Soc Nephrol. 2011; 6: 2492-2498Crossref PubMed Scopus (31) Google Scholar Most HD patients gain weight in the interdialytic interval, and BIA studies have shown that the major increase in ECW occurs in the trunk and legs.25.Jain A.K. Lindsay R.M. Intra and extra cellular fluid shifts during the interdialytic period in conventional and daily hemodialysis patients.ASAIO J. 2008; 54: 100-324Crossref PubMed Scopus (8) Google Scholar,26.Kumar S. Khosravi M. Massart A. et al.Are serum to dialysate sodium gradient and segmental bioimpedance volumes associated with the fall in blood pressure with hemodialysis?.Int J Artif Organs. 2014; 1: 21-28Crossref Scopus (19) Google Scholar Vascular access, particularly upper arm fistulae, and central venous occlusion can also affect ECW changes in the arms; as these differences tend to be asymmetric, they can be detected by segmental bioimpedance devices but not by whole-body BIA. However, these are generally small when compared with the ECW gains in the legs and trunk.27.Kumar S. Khosravi M. Massart A. et al.Changes in upper limb extracellular water content ?during hemodialysis measured by multi-frequency bioimpedance.Int J Artif Organs. 2013; 36: 203-207Crossref PubMed Google Scholar Studies estimating compartmental fluid gains between dialysis sessions have reported that whereas initially there is greater expansion of extravascular volumes during the first 24h post dialysis, thereafter the extravascular compartment refills in conjunction with an exponential expansion of the blood volume" @default.
• W2048555639 created "2016-06-24" @default.
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• W2048555639 date "2014-09-01" @default.
• W2048555639 modified "2023-10-16" @default.
• W2048555639 title "The role of bioimpedance and biomarkers in helping to aid clinical decision-making of volume assessments in dialysis patients" @default.
• W2048555639 cites W1855505384 @default.
• W2048555639 cites W1881618187 @default.
• W2048555639 cites W1915684005 @default.
• W2048555639 cites W1966195317 @default.
• W2048555639 cites W1970605266 @default.
• W2048555639 cites W1972298257 @default.
• W2048555639 cites W1979149339 @default.
• W2048555639 cites W1992358166 @default.
• W2048555639 cites W1996011595 @default.
• W2048555639 cites W2008292341 @default.
• W2048555639 cites W2010238588 @default.
• W2048555639 cites W2012296884 @default.
• W2048555639 cites W2021338429 @default.
• W2048555639 cites W2044940037 @default.
• W2048555639 cites W2048313162 @default.
• W2048555639 cites W2055483573 @default.
• W2048555639 cites W2064433327 @default.
• W2048555639 cites W2069451427 @default.
• W2048555639 cites W2071851399 @default.
• W2048555639 cites W2073843574 @default.
• W2048555639 cites W2075350255 @default.
• W2048555639 cites W2077020945 @default.
• W2048555639 cites W2083436715 @default.
• W2048555639 cites W2087103143 @default.
• W2048555639 cites W2091776861 @default.
• W2048555639 cites W2096505591 @default.
• W2048555639 cites W2104476165 @default.
• W2048555639 cites W2109164500 @default.
• W2048555639 cites W2109558067 @default.
• W2048555639 cites W2115361253 @default.
• W2048555639 cites W2115611820 @default.
• W2048555639 cites W2123076939 @default.
• W2048555639 cites W2124619474 @default.
• W2048555639 cites W2125707967 @default.
• W2048555639 cites W2128202318 @default.
• W2048555639 cites W2128630371 @default.
• W2048555639 cites W2131145645 @default.
• W2048555639 cites W2132966651 @default.
• W2048555639 cites W2138734221 @default.
• W2048555639 cites W2139337436 @default.
• W2048555639 cites W2142564897 @default.
• W2048555639 cites W2146715480 @default.
• W2048555639 cites W2153293443 @default.
• W2048555639 cites W2155930657 @default.
• W2048555639 cites W2163887605 @default.
• W2048555639 cites W2164020604 @default.
• W2048555639 cites W2164635264 @default.
• W2048555639 cites W2168322079 @default.
• W2048555639 cites W2169293749 @default.
• W2048555639 cites W2169521769 @default.
• W2048555639 cites W2171680191 @default.
• W2048555639 cites W2331636073 @default.
• W2048555639 doi "https://doi.org/10.1038/ki.2014.207" @default.
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