fresenius bcm user manual

Volume status improvement as a result of awareness Group 1: Patients and their primary nurses were informed of their hydration status. Evaluate fluid intake first In the evaluation of the causes of fluid imbalance, screening for reversible causes first, is imperative. Any improvement in intake compliance facilitates the overall correction of fluid imbalance. Use the power of awareness for better patient compliance. P3 Volume Control recommends an approach that is easy for your staff and even easier for your patients. Improve fluid intake compliance A randomized controlled study with the BCM-Body Composition Monitor showed conclusive results. Within three months of follow-up, patients who had knowledge of their fluid status, provided by the BCM-Body Composition Monitor, attained better volume control. Adapted PD By combining sequences of short dwell times and small fill volumes with long dwell times and large fill volumes, adapted PD promotes both the process of UF and clearance, at no additional time and cost, while reducing glucose absorption over the dialysis session. 3 Maintain RRF and UF capacity to maximize output RRF is important for fluid removal. Studies confirm that RRF can be preserved longer in patients using ultra-low GDP PD fluids compared to conventional PD fluids. 4,5 Ultra-low GDP PD fluids can also help to reduce the deleterious effects of chronic exposure to the peritoneal membrane and to preserve the membrane function longer. 6,7,8 Maintaining RRF is important for urine output and regulation of fluid status, thus the use of ultra-low GDP fluids can be an important part of your patient’s fluid management.

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Achieving optimal fluid balance is therefore one of the central challenges in routine dialysis practice. 1 The BCM is an innovative analysis system that enables fast, accurate and non-invasive fluid status monitoring. In addition, the BCM distinguishes muscle mass from pathological fluid overload thereby allowing the detection of malnutrition in patients with kidney failure. Not all products are cleared or available for sale in all EU countries. Please check the relevant country web site for details. By clicking on the button “Accepted and Confirmed” you assure that you have taken note of this information and that you are a healthcare professional located within the European Union. Back to Homepage Accepted and Confirmed Volume control in peritoneal dialysis A practical way to assess and help correct fluid status Quickly assess fluid status and recognize the trend Make therapeutic changes earlier Effortlessly use a wider range of practical volume control tools DISCLAIMER Not all products and services are cleared or available for sale in all EU countries. Check your country web site for details. Key features Volume control - three steps for better volume control Assess status and trend BCM-Body Composition Monitor Routinely assess fluid status The easy-to-use BCM-Body Composition Monitor is a powerful addition to the routine evaluation of your patients and is becoming a standard in leading PD centers. By providing you with a more precise picture of actual fluid status through quantified overhydration, this state-of-the-art technology helps you manage the fluid status of your patients better. Analyze the fluid status trend The BCM-Body Composition Monitor can be used effectively to continually monitor changes and trend of the fluid status over time. Trend analysis can provide important feedback and guidance on therapy decision-making by you and your staff 1.

Biocompatibility and tolerability of a purely bicarbonate-buffered peritoneal dialysis solution. Peritoneal Dialysis International 2009;29(6):630-633. 8 Rippe B, Simonsen O, Heimburger O, Christensson A, Haraldsson B, et al. Long-term clinical effects of a peritoneal dialysis fluid with less glucose degradation products. Kidney International 2001;59(1):348-57. KGaA 2019 Host: fresmedi-corporate-prod-pub-i-0674c154c6df6cdca. Author manuscript; available in PMC 2018 May 25. Published in final edited form as: Biomed Phys Eng Express. 2017 May 25; 3(3): 035017.Associated Data Supplementary Materials Appendices. NIHMS73750-supplement-Appendices.pdf (502K) GUID: 47E2DAE6-3F47-4667-90C2-67DB591D8026 Abstract Bioimpedance measurements with the Body Composition Monitor (BCM) have been shown to improve fluid management in haemodialysis. However, there is a lack of a sufficiently robust evidence-base for use of the BCM outside of standard protocols. This study aims to characterise BCM measurement variation to allow users to make measurements and interpret the results with confidence in a range of clinical scenarios. BCM measurements were made in 48 healthy controls and in 48 stable haemodialysis patients before and immediately after dialysis. The effect of utilising alternative measurement paths was assessed using mixed effects models and the effect of measuring post-dialysis was assessed by comparing changes in BCM-measured overhydration (OH) with weight changes over dialysis. The data from healthy controls suggest that there is no difference in BCM-measured OH between all the whole-body paths other than the foot-to-foot measurement. Dialysis patients showed similar results other than having higher BCM-measured OH when measured across the site of a vascular access. There was good agreement between BCM-measured OH and change in weight, suggesting post-dialysis measurements can be utilised.

Studies EuroBCM Study maintaining euvolemia in PD EuroBCM Study results 1 Out of 639 patients from 28 centers in 6 countries: 40% were normohydrated 7% were dehydrated 53% were overhydrated Important factors to consider in fluid status: UF alone can be misleading in evaluating patients’ fluid status Fluid status is mainly the result of the balance of intake and output over time. To improve a patient’s fluid status, both sides should be controlled in order to determine the fluid status trend Blood pressure can be a misleading parameter to evaluate fluid status and can prompt false therapy decisions Fluid status is mainly the result of the balance of intake and output over time Related Content Adapted APD Achieving more with the same input. 1 Van Biesen W, Williams JD, Covic AC, Fan S, Claes K, et al. (2011) Fluid Status in Peritoneal Dialysis Patients: The European Body Composition Monitoring (EuroBCM) Study Cohort. Peritoneal Dialysis International 2011; 31(4):450-8. 4 Kim S, Oh J, Kim S, Chung W, Ahn C, Kim SG, Oh KH. Benefits of biocompatible PD fluid for preservation of residual renal function in incident CAPD patients: a 1-year study. Nephrol Dial Transplant 2009;24(9):2899-90. 5 Haag-Weber M, Kramer R, Haake R, Islam MS, Prischl F, Haug U, Nabut JL, Deppisch R. Low-GDP fluid (Gambrosol trio) attenuates decline of residual renal function in PD patients: a prospective randomized study. On behalf of the DIUREST Study Group. Nephrology Dialysis Transplantation 2010;25(7):2288-96. 6 Williams JD, Topley N, Craig KJ, Mackenzie RK, Pischetsrieder M, Lage C,Passlick-Deetjen J; Euro Balance Trial Group. The Euro-Balance Trial: the effect of a new biocompatible peritoneal dialysis fluid (balance) on the peritoneal membrane. Kidney International 2004;66(1):408-18. 7 Weiss L, Stegmayr B, Malmsten G, Tejde M, Hadimeri H, Siegert CE, Ahlmen J, Larsson R, Ingman B, Simonsen O, van Hamersvelt HW, Johansson AC, Hylander B, Mayr M, Nilsson PH, Andersson PO, De los Rios T.

The only investigation to consider alternative paths with BIS measurements was in preliminary work for this study, where it was shown that BCM-measured overhydration (OH) from the hand-to-hand path is an acceptable alternative to the standard path ( Keane and Lindley, 2015 ). When considering post-dialysis measurements, it is accepted that haemodialysis induced changes in fluid distributions affect whole-body bioimpedance ( Zhu et al., 1999 ), but the clinical significance of this when using BCM needs clarification. In order to allow greater understanding of the effect of making measurements outside the manufacturer’s protocol, this study aimed to characterise the effect of changing measurement path and time of measurement on body composition parameters. Methods Subjects Ethical approval was granted by a local ethics committee and all participants provided informed consent. Routine target weights were defined on the basis of clinical examination and BCM on indication. Sample size Pilot work comparing BCM measurements from hand-to-hand and from hand-to-foot showed standard deviations of the mean difference in OH of around 1.0 litres ( Keane and Lindley, 2015 ). Recruiting 48 subjects into each cohort would allow differences of 0.3 litres to be measured between the primary two paths at the level of 5% type I error with 80% power using a two sided t-test. This is deemed an acceptable sample size; differences below 0.3 litres will fall below the limits of reproducibility of the device ( Wieskotten et al., 2013 ). Data collection Healthy controls had height measured using a stadiometer and weight measured using calibrated scales. For haemodialysis patients, height was taken from their clinical notes and pre- and post-dialysis weights were obtained as part of normal care. BCM measurements were made with a standard BCM and also with a modified BCM - the 8-lead BCM - which had four additional cables allowing leads to be connected to electrodes on both hands and both feet.

These results suggest BCM protocols can be flexible regarding measurement paths and timing of measurement to ensure as many patients as possible can benefit from the technology. Introduction Fluid management is an important part of care for haemodialysis patients ( Wizemann et al., 2009 ). There is growing evidence that the use of bioimpedance measurements with the body composition monitor (BCM; Fresenius Medical Care, Germany) can help guide fluid management and improve outcomes ( Moissl et al., 2013, Onofriescu et al., 2014 ). However, there are few pragmatic studies that can help to inform the use of BCM outside of the strict protocol recommended for measurements and used in interventional studies, which can exclude a significant number of patients when BCM is used as part of routine care. Manufacturer’s guidance state that measurements should be made before dialysis with the patient in a supine position. This is related to the effect that ultrafiltration ( Abbas et al., 2014 ) and posture ( Zhu et al., 1998 ) have on fluid distributions in the body and that, due to the different shapes and sizes of the limbs, shifts in fluid from one compartment to another can have significant effects on the whole body impedance. However, in practice these requirements would exclude a relatively large number of patients from having BCM measurements. Validated alternative pathways would allow measurements to be made on patients who would have otherwise have been managed without BCM or managed based on poor quality data. There are also a number of situations where it would be helpful to make post-dialysis BCM measurements. Practicalities and staffing levels can sometimes make it difficult to carry out all necessary BCM measurements at the same time as putting patients on dialysis, while post-dialysis measurements also allow immediate action to be taken when intradialytic symptoms prompt a review of target weights.

Furthermore, the consistency of LTM and ATM from the start to end of dialysis was assessed based on the effect of measurement time in each of the mixed-effects models. The estimate of R E from the curve-fitting routine was used as a marker of relative changes in fluid status during dialysis for comparisons between the five body segments, where the whole-body analysis models are not appropriate. Results Model results Patient characteristics can be seen in table 1. Details of model checking can be seen in Appendix 2. Table 1 Subject demographics. Data are mean (standard deviation) for normal data and number (%) of subjects for categorical data. Comorbidities present included acute coronary syndrome, heart failure, cerebrovascular disease, liver disease, peripheral vascular disease and smoking. For the models investigating OH and ATM, age and sex were not associated with OH, while both age and sex were associated with LTM in both healthy controls and haemodialysis patients. For the models of LTM and ATM, including measurement time as an interaction term did not make a difference to the model, suggesting that the effect of measurement time on LTM and ATM was not different between the paths. For these models, measurement time was included as a predictor variable to investigate the validity of post-dialysis measurements of LTM and ATM. Table 2 Model for OH in healthy controls. Considering LTM and ATM, there was a significant difference between the reference path and most other paths, apart from the cross measurements, including higher LTM and lower ATM in the dominant arm and in the hand-to-hand path as compared to the reference path. Haemodialysis patients showed different pre-dialysis patterns than subjects with normal renal function. In particular, there was a significant difference in pre-dialysis BCM-measured OH between the side of the body where vascular access was situated as compared to the contralateral side (0.4 litres; 95% CI: 0.08 to 0.

76; table 3 ), although this effect was not present post-dialysis. Unlike controls, there was no difference in LTM or ATM between the sides ( Appendix 3 ), despite the fact that vascular access is usually on the non-dominant side. Using the 8-lead BCM, the impedances of each limb individually can be isolated ( figure 1 ), which can support the results of the regression models. Estimation of RI has much greater uncertainty and for segmental measurements, especially, in the trunk, the data were largely uninformative. Table 4 Relative segmental resistances as a proportion of standard whole body path resistances. The only statistically significant interaction was for the foot-to-foot path, which suggests that there is a greater change in BCM-measured OH across this path compared to the other paths. This is supported by looking at the segmental impedance data. If relative changes in R E over dialysis are used to indicate changes in fluid status, it can be seen that the greatest relative change is in the leg segments ( table 5 ). Yet there is a lack of data to support use of BCM outside this standardised approach and there remains a great deal of uncertainty in utilisation of the technology in certain individuals. By making 8-lead BCM measurements on healthy controls and dialysis patients, the effect of a number of simple alterations to BCM measurements are characterised which will allow these measurements to be made with greater confidence. Use of alternate paths Measurements on healthy controls suggest there is no significant difference in OH from any whole-body path other than across the legs. In principle the models that were generated and validated for the standard path can be employed with alternate paths. Changing from a whole-body measurement to a hand-to-hand or cross measurement will involve substitution of one limb for another and a change in the pathway through the trunk.

This gave the possibility of making BCM measurements across a number of paths and also allowed the isolation of individual segments for measurement (see figure 1 ). Standard and 8-lead BCM measurements were made on healthy subjects on one occasion while dialysis patients had measurements made pre- and post-dialysis. All BCM measurements were checked visually for artefacts, and repeated until the difference in measured OH was no greater than 0.2 litres between readings (in almost all cases the discrepancy between the first and second readings was no more than 0.1 litre). The 8-lead device does not display Cole-plots or body composition data to allow real-time assessment of artefacts or consistency, so repeat measurements were not made. Measurements of resistance, reactance and phase angle were made at the same 50 frequencies as in the standard BCM, for seventeen combinations of voltage and current (see fig. 1 ) and data was extracted for analysis. Open in a separate window Figure 1 Specifications of an 8-lead BCM measurement. RH, RF, LH, LF refer to right hand, right foot, left hand and left foot respectively. 8-lead BCM data processing Programmes were written in Matlab (v. 2014a; Mathworks In, MA, USA) to process 8-lead BCM data. This provided equivalent data to the standard BCM device, which was validated by processing standard BCM impedance data with the custom analysis programme and comparing the results with those from the standard BCM (see appendix 1 ). Mixed-effects regression model The use of mixed-effects regression allowed a model to be built that could account for the repeated measures on an individual from the 8-lead BCM. This characterises the individual differences in fluid status and body composition and accounts for this when describing the differences between the paths at the cohort level. A different mixed effects model was used to analyse each of the principal BCM parameters - OH, lean tissue mass (LTM) and adipose tissue mass (ATM).

For healthy controls, subject was taken as the random effect and path, sex and age were taken as fixed effects. The paths included in the model were limited to the 6 whole-body paths: right side; left side; right hand-to-left foot (cross 1); left hand-to-right foot (cross 2); hand-to-hand; and foot-to-foot. For haemodialysis patients, the same model set up was used, only with the addition of measurement time (pre- or post-dialysis), which was added as a simple predictor variable for the models of LTM and ATM and as an interaction term for the model of OH, to allow assessment of ultrafiltration associated changes in fluid distributions between the paths. To present the data, results for a 60 year old female measured on the standard path acted as a reference (standard path was taken as hand-to-foot on the dominant side of the body for controls and on and the contralateral side of the body to the most recently used vascular access (VA) for dialysis patients). The mean value for the dependent variable measured on the standard path is presented separately for controls and pre- and post-dialysis for patients, with a 95% confidence interval and a p-value assessing against a null value of zero. For each of the other measurement paths, the difference compared to the reference path is detailed with 95% confidence interval and a p-value. Adjustments for age and sex in each model are given and also for measurement time in the models assessing LTM and ATM. Significance levels were set at 0.05. To examine each model, plots of standardised residuals against fitted values were used to check the assumption of homoscedasticity and a Q-Q plot of the residuals was used to assess normality. Statistical analysis To investigate the validity of post-dialysis measurements, the agreement between change in BCM-measured OH from the reference path and change in weight was assessed using Bland-Altman analysis.

Using the segmental resistances in table 4, the different path resistances can be built from the segments and referenced to the standard path ( figure 3 ). For measurements of R E, substituting limbs and trunk paths does not significantly alter the overall path R E, for any of the whole body paths except the leg to leg path which is noticeably lower, consistent with results from the regression model. For the arm to arm path, the higher resistance of the arms seems to be compensated by a lower measured resistance for a current crossing the trunk from arm to arm than from arm to leg. Open in a separate window Figure 3 Re-calculating whole-body assessments of R E expressed as a % of the standard measurement path (hand-to-foot on the dominant side) in healthy controls based on the data in table 5 For haemodialysis patients, it has been suggested that the presence of vascular access in a patients’ arm can bias measurements of OH and so guidance suggests avoiding these paths. The evidence supporting this recommendation comes from studies using different bioimpedance with different analysis techniques to the BIS used in the BCM. The results here confirm that the presence of a vascular access does tend to increase OH. However, the effect (mean: 0.4; 95% CI: 0.1 to 0.8 litres) is arguably negligible from a clinical perspective, when considering the overall uncertainty in target weight prescription. Considering the model results for LTM and ATM in controls, it is important to note that the equivalence of OH across different paths does not translate to these compartments. Where accurate monitoring of body composition is important, the standard pathway is preferred and consistency is important. The dominant side has significantly increased LTM and reduced ATM as compared to the non-dominant side and the legs have increased LTM and reduced ATM compared to the arms (see Appendix 3 ).

This is consistent with previous work using BIA on controls that demonstrated decreased resistance in the dominant arm compared to the non-dominant arm ( Bedogni et al., 2002 ) and a decreased resistance of the legs compared to the arms ( Lorenzo and Andreoli, 2003 ) as decreased resistance is linked with greater muscle mass through the higher proportion of water in muscle than fat. Use of post-dialysis measurements Considering the use of post-dialysis BCM measurements, change in body weight was compared to change in BCM-measured OH as there is no accepted gold standard measure of OH to validate post-dialysis measurements. In theory, the change in OH over dialysis should equal the change in body weight, while there should be no change in LTM or ATM. El-Kateb et al. reported a similar dataset to that presented here ( El-Kateb and Davenport, 2015 ) with contrasting results, including a significant bias and limits of agreement three times larger than those observed in this study. This discrepancy seems likely to be due to artefactual BCM measurements and highlights the need for some expertise when making measurements ( Lindley et al., 2015 ). The BCM validation literature also suggests that a bias is introduced into measurements of LTM and ATM when measurements are made immediately after dialysis but within 30 minutes this becomes non-significant. Considering this, and the findings here, users should have a degree of caution using BCM-measured LTM and ATM from post-dialysis measurements. Despite the good agreement between change in BCM-measured OH and change in weight, the model for OH did suggest there was a degree of ultrafiltration induced changes in fluid distribution, with a larger change in the lower limbs than the upper. This would suggest that relatively more fluid is recruited from the legs than the upper body which is largely in agreement with previous work. Measurements over the first 75 minutes of dialysis using BIS ( Shulman et al.

, 2001 ) and over the whole haemodialysis session using SBIA ( Zhu et al., 2008 ) and segmental BIS ( Chanchairujira and Mehta, 2001 ) have demonstrated a greatest fractional change in fluid in the legs as compared to arms and trunk. Abbas et al ( Abbas et al., 2014 ) showed that there is a greater percentage removal of ECF from the legs than other compartments but that as ultrafiltration rate is increased, there is a preferential recruitment of fluid from the trunk. One of the implications of preferential removal of fluid from the legs than arms could be that the legs are the last segment that fluid is recruited from. If that is true, techniques for fluid management based on normalising calf ECF ( Seibert et al., 2013, Basile et al., 2015 ) could potentially leave other segments volume depleted and leave organs in danger of perfusion defects. Study limitations The study was not powered to address the multiple comparisons made by the models - the sample size was based on comparisons between the two primary whole-body paths only. A larger sample would allow better estimates of these different estimates. It would also have been interesting to extend the analysis to a group of haemodialysis patients who are defined as being prone to intradialytic hypotension (IDH), to investigate the relationship between fluid distributions, fluid dynamics and IDH. Conclusions In summary, these data helps BCM users make measurements and interpret results with greater confidence. Measurement protocols can be more flexible and individualised than the manufacturer’s guidance suggests, which will help as many patients as possible benefit from the technology. This is based on a number of key observations: Any of the whole body paths other than foot-to-foot can be used as an alternative to the standard path for measurement of OH, with an acknowledgement of the additional uncertainty when interpreting the results.

BCM-measured OH is greater when measuring across a site of vascular access, but the increase arguably is not clinically significant when the uncertainty in other methods of target weight assessment is considered. Making BCM measurements post-dialysis introduces a negligible bias to OH measurements but does increase measurement uncertainty, which should be accounted for when interpreting such data. This uncertainty will be reduced with time after dialysis, such as asking patients to move off the dialysis station to be weighed, before a measurement is made. This work was supported by the NIHR Healthcare Technology Cooperative Devices for Dignity. This report is independent research arising from a Healthcare Science Research Fellowship supported by the National Institute for Health Research. The views expressed in this publication are those of the authors and not necessarily those of the NHS, the National Institute for Health Research or the Department of Health. References Abbas S, Zhu F, Kaysen G, Kotanko P, Levin N. Effect of change in fluid distribution in segments in hemodialysis patients at different ultrafiltration rates on accuracy of whole body bioimpedance measurement. Assessing fluid change in hemodialysis: whole body versus sum of segmental bioimpedance spectroscopy. Bioelectrical impedance analysis--part I: review of principles and methods. Assessment of fat-free mass using bioelectrical impedance measurements of the human body. Body fluid volume determination via body composition spectroscopy in health and disease. Hemodialysis international. Preserving central blood volume: changes in body fluid compartments during hemodialysis. The effect of arteriovenous fistulae in haemodialysis patients on whole body and segmental bioelectrical impedance. Read our cookie policy. Because every patient deserves treatment as strong as they are. Supported browsers include Chrome, Edge, Firefox, and Safari.

Learn About the steps that we are taking to protect our patients, employees, physicians, and partners. If you are a patient with questions or concerns, please find additional information at FreseniusKidneyCare.com and AzuraVascularCare.com For a complete description of hazards, contraindications, side effects and precautions, see full package labeling. All Rights Reserved. All other trademarks are the property of their respective owners. By continuing to browse the website, you consent to our use of cookies. For details see our privacy policy. Not all products are cleared or available for sale in all Asia Pacific countries. Back to homepage Accepted and Confirmed Fluid management for hemodialysis Fresenius Medical Care, together with healthcare professionals worldwide, is dedicated to reducing the high cardiovascular morbidity and mortality of ESRD patients. Achieving optimal fluid balance is therefore one of the central challenges in routine clinical practice. Specifically designed for ESRD patients, the BCM, Body Composition Monitor, provides an objective measurement of overhydration. This opens the door for both reproducible and reliable assessment of fluid as well as nutrition status. The BCM can be an invaluable tool towards improved fluid management that enable ESRD patients to enjoy every important moment in their lives. It is ultimately one of the key factors contributing to the high CVD related morbidity and mortality amongst these patients. Vice versa, it was demonstrated that achieving normohydration through effective Fluid Management therapy is associated with better outcome of HD patients 1. The BCM - Body Composition Monitor is the core component of the Advanced Fluid Management therapy programme of Fresenius Medical Care. It measures and quantifies the patient’s fluid status and provides a reliable decision basis for effective fluid and nutritional management.