Validating the use of bioimpedance spectroscopy for assessment of fluid status in children.

BACKGROUND: 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. METHODS: TBW_BCM and excess fluid was determined from standard wrist-to-ankle BCM measurement. TBW_D2O was determined from deuterium concentration decline in serial urine samples over 5 days in healthy children. UKM was used to measure body water in children receiving haemodialysis. Agreement between methods was analysed using paired t test and Bland-Altman method comparison. RESULTS: In 61 healthy children (6-14 years, 32 male), mean TBW_BCM and TBW_D2O were 21.1 ± 5.6 and 20.5 ± 5.8 L respectively. There was good agreement between TBW_BCM and TBW_D2O (R2 = 0.97). In six haemodialysis children (4-13 years, 4 male), 45 concomitant measurements over 8 months showed good TBW_BCM and TBW_UKM agreement (mean difference - 0.4 L, 2SD = ± 3.0 L). In 634 healthy children (2-17 years, 300 male), BCM-measured overhydration was - 0.1 ± 0.7 L (10-90th percentile - 0.8 to + 0.6 L). There was no correlation between age and OH (p = 0.28). CONCLUSIONS: These results suggest BCM can be used in children as young as 2 years to measure normally hydrated weight and assess fluid status.

Use of the Body Composition Monitor for Fluid Status Measurements in Subjects with High Body Mass Index.

BACKGROUND: Fluid management is a central aspect of haemodialysis (HD). Body composition monitor (BCM)-measured overhydration (OH) can improve fluid management strategies, but there remains uncertainty about its use in subjects with high body mass index (BMI). This study explored whether the observed tendency for HD patients with high BMI to complete dialysis fluid depleted according to BCM is associated with an artefact in the BCM models, or with systematic differences in the prescription and delivery of treatment. METHODS: To isolate the effect of BMI from effects relating to treatment, BCM measurements were made on 20 healthy subjects with high BMI. Mean OH was compared with a previously reported cohort of healthy subjects with normal BMI. To further explore BCM-measured OH in HD patients, measurements were made pre- and post-dialysis on 10 patients with high BMI alongside relative blood volume monitoring. Body shape was classified to assess associations between shape and OH. RESULTS: The mean OH for healthy subjects with high BMI was -0.1 litres, which was not different from that of healthy subjects with normal BMI. Median BCM-measured OH for HD patients was 1.8 and -1.8 litres pre- and post-dialysis respectively, while blood volume and blood pressure were maintained. Body shape correlated with OH in control subjects but not HD patients. CONCLUSIONS: We found no evidence of systematic bias in BCM-measured OH with high BMI in healthy subjects. BCM-measured post-dialysis fluid depletion in asymptomatic patients with high BMI appears to result from greater tolerance of ultrafiltration and ability to maintain blood volume.

Identificar situaciones de riesgo para los pacientes en hemodiálisis mediante la adecuada valoración de su composición corporal / Risk identification in haemodialysis patients by appropriate body composition assessment

Introducción Circunstancias como el género, la edad, la presencia de diabetes mellitus (DM) y la insuficiencia renal tienen impacto sobre la composición corporal de los pacientes. Sin embargo, a la hora de evaluar parámetros nutricionales como el tejido magro y graso de los pacientes en hemodiálisis (HD) se emplean valores de referencia provenientes de población sana. Objetivos: Analizar la composición corporal mediante bioimpedancia espectroscópica (BIS) de 6.395 pacientes en HD para obtener valores de referencia de índice de tejido magro (ITM) y de índice de tejido graso (ITG) procedentes de pacientes en HD y confirmar su validez al demostrar que aquellos con un ITM por debajo del percentil 10 calculado para su grupo tienen mayor riesgo de muerte. Material y métodos Usamos la BIS para determinar el ITM e ITG de nuestra cohorte de pacientes en HD en España. Calculamos el percentil 10 y el percentil 90 del ITM e ITG en cada decil de edad de pacientes, agrupados según su género y presencia de DM. Recogemos parámetros clínicos, analíticos y demográficos. Resultados: Objetivamos que los valores del percentil 10 y del 90 de ITM/ITG varían en función del grupo (edad, género y presencia de DM) y que, tras ajustar por otros factores de riesgo como la sobrehidratación, los pacientes con ITM inferior al percentil 10 tienen mayor riesgo relativo de muerte (OR 1,57) que aquellos con valores superiores. Conclusiones: Monitorizar el ITM e ITG de los pacientes en HD CON adecuados valores de referencia puede ser útil para identificar situaciones de riesgo en los pacientes en HD (AU)

Introduction: Circumstances such as gender, age, diabetes mellitus (DM) and renal failure impact on the body composition of patients. However, we use nutritional parameters such as lean and fat tissue with reference values from healthy subjects to assess the nutritional status of haemodialysis (HD) patients. Aims: To analyse body composition by bioimpedance spectroscopy (BIS) of 6395 HD patients in order to obtain reference values of lean tissue index (LTI) and fat tissue index (FTI) from HD patients; and to confirm its validity by showing that those patients with LTI below the 10th percentile calculated for their group have greatest risk of death. Material and methods: We used the BIS to determine the LTI and FTI in our cohort of HD patients in Spain. We calculated the 10th percentile and 90th percentile of LTI and FTI in each age decile for patients grouped by gender and presence of DM. We collected clinical, laboratory and demographic parameters. Results: The LTI/FTI 10 and 90 percentile values varied by group (age, gender and presence of DM) and, after adjusting for other risk factors such as fluid overload, those patients with LTI lower than percentile 10 had a higher relative risk of death (OR 1.57) than those patients with higher values. Conclusions: Monitoring the LTI and FTI of patients on HD using suitable reference values may help to identify risk in this patient population (AU)

Risk identification in haemodialysis patients by appropriate body composition assessment. / Identificar situaciones de riesgo para los pacientes en hemodiálisis mediante la adecuada valoración de su composición corporal.

INTRODUCTION: Circumstances such as gender, age, diabetes mellitus (DM) and renal failure impact on the body composition of patients. However, we use nutritional parameters such as lean and fat tissue with reference values from healthy subjects to assess the nutritional status of haemodialysis (HD) patients. AIMS: To analyse body composition by bioimpedance spectroscopy (BIS) of 6395 HD patients in order to obtain reference values of lean tissue index (LTI) and fat tissue index (FTI) from HD patients; and to confirm its validity by showing that those patients with LTI below the 10th percentile calculated for their group have greatest risk of death. MATERIAL AND METHODS: We used the BIS to determine the LTI and FTI in our cohort of HD patients in Spain. We calculated the 10th percentile and 90th percentile of LTI and FTI in each age decile for patients grouped by gender and presence of DM. We collected clinical, laboratory and demographic parameters. RESULTS: The LTI/FTI 10 and 90 percentile values varied by group (age, gender and presence of DM) and, after adjusting for other risk factors such as fluid overload, those patients with LTI lower than percentile 10 had a higher relative risk of death (OR 1.57) than those patients with higher values. CONCLUSIONS: Monitoring the LTI and FTI of patients on HD using suitable reference values may help to identify risk in this patient population.

Optimal fluid control can normalize cardiovascular risk markers and limit left ventricular hypertrophy in thrice weekly dialysis patients.

Increased hemodialysis frequency can make fluid overload easier to treat, although most patients are still treated thrice weekly. Chronic fluid overload is associated with left ventricular hypertrophy and elevated serum cardiac biomarkers, recognized as mortality risk factors. Serum cardiac troponin T (cTnT), N-terminal prohormone brain natriuretic peptide (NT-proBNP), left ventricular mass index by cardiac magnetic imaging, and ambulatory blood pressure was measured in 30 thrice weekly hemodiafiltration patients. Time-averaged fluid overload (TAFO) was quantified by bioimpedance spectroscopy. In the study group, left ventricular hypertrophy was found to be 26% by cardiac magnetic resonance. Ambulatory blood pressure was 130 mmHg (112-151) requiring a low equivalent dose of medication of 0.25 units (0-1). Significantly, lower levels of left ventricular mass index (P < 0.05) were associated in those patients with TAFO <1 L or NT-proBNP <1200 pg/mL or cTnT <0.1 ug/L. In the subgroups, 16 patients had normal cTnT (<0.03 ug/L), 16 patients had NT-proBNP <400 pg/mL, and 20 patients had TAFO <1 L. Nine patients had both cTnT <0.03 ug/L and NT-proBNP <400 pg/mL. Normally hydrated thrice-weekly hemodiafiltration patients can have cardiac biomarker and TAFO levels indistinguishable from the normal healthy population. Obtaining TAFO by bioimpedance monitoring can offer a practical alternative to serum cardiac biomarkers.

Importance of normohydration for the long-term survival of haemodialysis patients.

BACKGROUND: Fluid overload and hypertension are among the most important risk factors for haemodialysis (HD) patients. The aim of this study was to analyse the impact of fluid overload for the survival of HD patients by using a selected reference population from Tassin. METHODS: A positively selected HD population (n = 50) from Tassin (Lyon-France) was used as a reference for fluid status and all-cause mortality. This population was compared to one dialysis centre from Giessen (Germany) which was separated into a non-hyperhydrated (n = 123) and a hyperhydrated (n = 35) patient group. The hydration status (ΔHS) of all patients was objectively measured with whole-body bioimpedance spectroscopy in 2003. All-cause mortality was analysed after a 6.5-year follow-up. RESULTS: Most of the reference patients from Tassin were normohydrated (ΔHS = 0.25 ± 1.15 L) at the start of the HD session. The hydration status of the Tassin patients was not different to the non-hyperhydrated Giessen patients (ΔHS = 0.8 ± 1.1 L) but significantly lower than in the hyperhydrated Giessen group (ΔHS = 3.5 ± 1.2 L). Multivariate adjusted all-cause mortality was significantly increased in the hyperhydrated patient group (hazard ratio = 3.41)- no difference in mortality could be observed between the Tassin and the non-hyperhydrated group from Giessen-even considering the fact that Tassin patients presented a significantly lower blood pressure. CONCLUSIONS: Fluid overload has a very high predictive value for all-cause mortality and seems to be one of the major killers in the HD population. Patients might strongly benefit from active management of fluid overload.

Guided optimization of fluid status in haemodialysis patients.

BACKGROUND: Achieving normohydration remains a non-trivial issue in haemodialysis therapy. Guiding the haemodialysis patient on the path between fluid overload and dehydration should be the clinical target, although it can be difficult to achieve this target in practice. Objective and clinically applicable methods for the determination of the normohydration status on an individual basis are needed to help in the identification of an appropriate target weight. METHODS: The aim of this prospective trial was to guide the patient population of a complete dialysis centre towards normohydration over the course of approximately 1 year. Fluid status was assessed frequently (at least monthly) in haemodialysis patients (n = 52) with the body composition monitor (BCM), which is based on whole body bioimpedance spectroscopy. The BCM provides the clinician with an objective target for normohydration. The patient population was divided into three groups: the hyperhydrated group (relative fluid overload >15% of extracellular water (ECW); n = 13; Group A), the adverse event group (patients with more than two adverse events in the last 4 weeks; n = 12; Group B) and the remaining patients (n = 27; Group C). RESULTS: In the hyperhydrated group (Group A), fluid overload was reduced by 2.0 L (P < 0.001) without increasing the occurrence of intradialytic adverse events. This resulted in a reduction in systolic blood pressure of 25 mmHg (P = 0.012). Additionally, a 35% reduction in antihypertensive medication (P = 0.031) was achieved. In the adverse event group (Group B), the fluid status was increased by 1.3 L (P = 0.004) resulting in a 73% reduction in intradialytic adverse events (P < 0.001) without significantly increasing the blood pressure. CONCLUSION: The BCM provides an objective assessment of normohydration that is clinically applicable. Guiding the patients towards this target of normohydration leads to better control of hypertension in hyperhydrated patients, less intradialytic adverse events and improved cardiac function.

Importance of whole-body bioimpedance spectroscopy for the management of fluid balance.

INTRODUCTION: Achieving normohydration remains a non-trivial issue in haemodialysis therapy. Preventing the deleterious effects of fluid overload and dehydration is difficult to achieve. Objective and clinically applicable methods for the determination of a target representing normohydration are needed. METHODS: Whole-body bioimpedance spectroscopy (50 frequencies, 5-1,000 kHz) in combination with a physiologic tissue model can provide an objective target for normohydration based on the concept of excess extracellular volume. We review the efficacy of this approach in a number of recent clinical applications. The accuracy to determine fluid volumes (e.g. extracellular water), body composition (e.g. fat mass) and fluid overload was evaluated in more than 1,000 healthy individuals and patients against available gold standard reference methods (e.g. bromide, deuterium, dual-energy X-ray absorptiometry, air displacement plethysmography, clinical assessment). RESULTS: The comparison with gold standard methods showed excellent accordance [e.g. R(2) (total body water) = 0.88; median +/- SD (total body water) = -0.17 +/- 2.7 litres]. Agreement with high-quality clinical assessment of fluid status was demonstrated in several hundred patients (median +/- SD = -0.23 +/- 1.5 litres). The association between ultrafiltration volume and change in fluid overload was reflected well by the method (median +/- SD = 0.015 +/- 0.8 litres). The predictive value of fluid overload on mortality underlines forcefully the clinical relevance of the normohydration target, being secondary only to the presence of diabetes. The objective normohydration target could be achieved in prevalent haemodialysis patients leading to an improvement in hypertension and reduction of adverse events. CONCLUSION: Whole-body bioimpedance spectroscopy in combination with a physiologic tissue model provides for the first time an objective and relevant target for clinical dry weight assessment.

The mortality risk of overhydration in haemodialysis patients.

BACKGROUND: While cardiovascular events remain the primary form of mortality in haemodialysis (HD) patients, few centres are aware of the impact of the hydration status (HS). The aim of this study was to investigate how the magnitude of the prevailing overhydration influences long-term survival. METHODS: We measured the hydration status in 269 prevalent HD patients (28% diabetics, dialysis vintage = 41.2 +/- 70 months) in three European centres with a body composition monitor (BCM) that enables quantitative assessment of hydration status and body composition. The survival of these patients was ascertained after a follow-up period of 3.5 years. The cut off threshold for the definition of hyperhydration was set to 15% relative to the extracellular water (ECW), which represents an excess of ECW of approximately 2.5 l. Cox-proportional hazard models were used to compare survival according to the baseline hydration status for a set of demographic data, comorbid conditions and other predictors. RESULTS: The median hydration state (HS) before the HD treatment (DeltaHSpre) for all patients was 8.6 +/- 8.9%. The unadjusted gross annual mortality of all patients was 8.5%. The hyperhydrated subgroup (n = 58) presented DeltaHSpre = 19.9 +/- 5.3% and a gross mortality of 14.7%. The Cox adjusted hazard ratios (HRs) revealed that age (HRage = 1.05, 1/year; P < 0.001), systolic blood pressure (BPsys) (HRBPsys = 0.986 1/mmHg; P = 0.014), diabetes (HRDia = 2.766; P < 0.001), peripheral vascular disease (PVD) (HRPVD = 1.68; P = 0.045) and relative hydration status (DeltaHSpre) (HRDeltaHSpre = 2.102 P = 0.003) were the only significant predictors of mortality in our patient population. CONCLUSION: The results of our study indicate that the hydration state is an important and independent predictor of mortality in chronic HD patients secondary only to the presence of diabetes. We believe that it is essential to measure the hydration status objectively and quantitatively in order to obtain a more clearly defined assessment of the prognosis of haemodialysis patients.

A comparison of methods for determining urea distribution volume for routine use in on-line monitoring of haemodialysis adequacy.

BACKGROUND: The availability of haemodialysis machines equipped with on-line clearance monitoring (OCM) allows frequent assessment of dialysis efficiency and adequacy without the need for blood samples. Accurate estimation of the urea distribution volume 'V' is required for Kt/V calculated from OCM to be consistent with conventional blood sample-based methods. METHODS: Ten stable HD patients were monitored monthly for 6 months. Time-averaged OCM clearance (K(OCM)) and pre- and post-dialysis blood samples were collected at each monitored session. The second generation Daugirdas formula was used to calculate the single-pool variable volume Kt/V, (Kt/V)(D). Values of V to allow comparison between OCM and blood-based Kt/V were determined from Watson's formula (V(Watson)), bioimpedance spectroscopy (V(BIS)), classical urea kinetic modelling (V(UKM_C)) and a simple computation of V (V(UKM_S)) from the blood-based Kt/V and K(OCM)t. RESULTS: Comparison of K(OCM)t/V with (Kt/V)(D) shows that using V(Watson) leads to significant systematic underestimation of dialysis dose. K(OCM)t/V(BIS) agrees with (Kt/V)(D) to within +/- 10%. K(OCM)t/V(UKM_S) is, by definition, identical to (Kt/V)(D) when initially calculated. However, if a historical value of V is used, agreement between K(OCM)t/V and (Kt/V)(D) over 6 months varies by 5% for V(BIS) and 10% for V(UKM_S). CONCLUSIONS: When investigating the effect of different treatment strategies on dialysis efficiency, any estimate of V can be used provided it is constant, as K is the relevant parameter. When frequent supervision of actual dialysis dose is required, the greatest consistency between K(OCM)t/V and the reference, Kt/V(D), over time is achieved with V(BIS).

Towards improved cardiovascular management: the necessity of combining blood pressure and fluid overload.

BACKGROUND: Hypertension and fluid overload (FO) are well-recognized problems in the chronic kidney disease (CKD) population. While the prevalence of hypertension is well documented, little is known about the severity of FO in this population. METHODS: A new bioimpedance spectroscopy device (BCM-Body Composition Monitor) was selected that allows quantitative determination of the deviation in hydration status from normal ranges (DeltaHS). Pre-dialysis systolic blood pressure (BPsys) and DeltaHS was analysed in 500 haemodialysis patients from eight dialysis centres. A graphical tool (HRP-hydration reference plot) was devised allowing DeltaHS to be combined with measurements of BPsys enabling comparison with a matched healthy population (n = 1244). RESULTS: Nineteen percent of patients (n = 95) were found to have normal BPsys and DeltaHS in the normal range. Approximately one-third of patients (n = 133) exhibited reasonable control of BPsys and fluids (BPsys <150 mmHg and DeltaHS <2.5 L). In only 15% of patients (n = 74) was hypertension observed (BPsys >150 mmHg) with a concomitant DeltaHS >2.5 L (possible volume-dependent hypertension). In contrast, 13% of patients (n = 69) were hypertensive with DeltaHS <1.1 L (possible essential hypertension). In 10% of patients (n = 52), BPsys <140 mmHg was recorded despite DeltaHS exceeding 2.5 L. CONCLUSION: Our study illustrated the wide variability in BPsys regardless of the degree of DeltaHS. The HRP provides an invaluable tool for classifying patients in terms of BPsys and DeltaHS and the proximity of these parameters to reference ranges. This represents an important step towards more objective choice of strategies for the optimal treatment of hypertension and FO. Further studies are required to assess the prognostic and therapeutic role of the HRP.

A whole-body model to distinguish excess fluid from the hydration of major body tissues.

BACKGROUND: Excess fluid (ExF) accumulates in the body in many conditions. Currently, there is no consensus regarding methods that adequately distinguish ExF from fat-free mass. OBJECTIVE: The aim was to develop a model to determine fixed hydration constants of primary body tissues enabling ExF to be calculated from whole-body measurements of weight, intracellular water (ICWWB), and extracellular water (ECWWB). DESIGN: Total body water (TBW) and ECWWB were determined in 104 healthy subjects by using deuterium and NaBr dilution techniques, respectively. Body fat was estimated by using a reference 4-component model, dual-energy X-ray absorptiometry, and air-displacement plethysmography. The model considered 3 compartments: normally hydrated lean tissue (NH_LT), normally hydrated adipose tissue (NH_AT), and ExF. Hydration fractions (HF) of NH_LT and NH_AT were obtained assuming zero ExF within the diverse healthy population studied. RESULTS: The HF of NH_LT mass was 0.703 +/- 0.009 with an ECW component of 0.266 +/- 0.007. The HF of NH_AT mass was 0.197 +/- 0.042 with an ECW component of 0.127 +/- 0.015. The ratio of ECW to ICW in NH_LT was 0.63 compared with 1.88 in NH_AT. ExF can be estimated with a precision of 0.5 kg. CONCLUSIONS: To calculate ExF over a wide range of body compositions, it is important that the model takes into account the different ratios of ECW to ICW in NH_LT and NH_AT. This eliminates the need for adult age and sex inputs into the model presented. Quantification of ExF will be beneficial in the guidance of treatment strategies to control ExF in the clinical setting.

Body fluid volume determination via body composition spectroscopy in health and disease.

The assessment of extra-, intracellular and total body water (ECW, ICW, TBW) is important in many clinical situations. Bioimpedance spectroscopy (BIS) has advantages over dilution methods in terms of usability and reproducibility, but a careful analysis reveals systematic deviations in extremes of body composition and morbid states. Recent publications stress the need to set up and validate BIS equations in a wide variety of healthy subjects and patients with fluid imbalance. This paper presents two new equations for determination of ECW and ICW (referred to as body composition spectroscopy, BCS) based on Hanai mixture theory but corrected for body mass index (BMI). The equations were set up by means of cross validation using data of 152 subjects (120 healthy subjects, 32 dialysis patients) from three different centers. Validation was performed against bromide/deuterium dilution (NaBr, D2O) for ECW/TBW and total body potassium (TBK) for ICW. Agreement between BCS and the references (all subjects) was -0.4 +/- 1.4 L (mean +/- SD) for ECW, 0.2 +/- 2.0 L for ICW and -0.2 +/- 2.3 L for TBW. The ECW agreement between three independent reference methods (NaBr versus D2O-TBK) was -0.1 +/- 1.8 L for 74 subjects from two centers. Comparing the new BCS equations with the standard Hanai approach revealed an improvement in SEE for ICW and TBW by 0.6 L (24%) for all subjects, and by 1.2 L (48%) for 24 subjects with extreme BMIs (<20 and >30). BCS may be an appropriate method for body fluid volume determination over a wide range of body compositions in different states of health and disease.

The relationship between systemic and whole-body hematocrit is not constant during ultrafiltration on hemodialysis.

The measurement of relative blood volume (RBV) changes during ultrafiltration assume a constant mass and distribution of circulating blood components such as hematocrit. The authors examine the validity of this assumption in 10 subjects undergoing repeated direct measurements of systemic hematocrit and plasma volume (PV(icg)) using indocyanine green dilution at four stages of dialysis with intermittent ultrafiltration. Ultrasonic RBV changes were monitored. Absolute blood volumes (ABV) were initially derived for each PV(icg) estimate, and corresponding measured systemic hematocrit was adjusted by a factor of 0.86 to correct for the difference between the systemic and whole-body hematocrit (constant Fcell ratio). PV(icg) and ABV changes correlated closely (R = 0.98; P <0.001). ABV changes overestimated reduction in PV(icg) during ultrafiltration (mean difference, -140 +/- 202 ml). The calculated red cell mass however was variable (P <0.01). Fcell ratio was then adjusted at each blood volume measurement (Fcell(1), 0.87 +/- 0.02; Fcell(2), 0.89 +/- 0.03; Fcell(3), 0.94 +/- 0.06; Fcell(4), 0.94 +/- 0.04; P <0.01) to maintain a constant red cell mass (2146 +/- 460 ml). When ABV was recalculated using PV(icg), systemic hematocrit and variable Fcell (ABV(Fvariable)), the mean difference between PV(icg) changes and ABV(Fvariable) changes, was negligible (-0.2 +/- 35 ml). During intermittent ultrafiltration, RBV changes systematically underestimated the percentage reduction in ABV (mean difference, 7.7 +/- 10.6%). When corrected for variations in Fcell, ABV(Fvariable) and RBV differences were negligible (mean difference 1.2 +/- 2.6%). Varying Fcell ratio probably reflects microvascular volume change with net fluid shift from the microcirculation to macrocirculation (intravascular refill). This may result in underestimation of changes in systemic hematocrit and RBV during dialysis such that they were less than those predicted by directly measured changes in plasma volume.

Serial determinations of absolute plasma volume with indocyanine green during hemodialysis.

Hemodynamic stability during hemodialysis depends largely on plasma volume (PV) preservation during ultrafiltration (UF). Current estimates of blood volume (BV) are indirect or involve the use of radioactive tracers, which does not allow repeated measurements during hemodialysis. Indocyanine green was used to measure PV during hemodialysis. After an initial pilot phase (phase I), PV values were determined before dialysis, repeatedly during isovolemic hemodialysis (phase II), and during stepwise UF (phase III). Absolute BV values were calculated from PV and hematocrit values. Patients were monitored for extracellular fluid volume (bioimpedance monitoring) and relative BV changes (ultrasonic monitoring). Phase I demonstrated dye stability in plasma, peak absorbance at 805 nm, and a short half-life (4.53 +/- 1.5 min). Ten milligrams of dye (2.5 mg/ml) were injected for each PV measurement. Eight plasma samples were obtained beginning 3 min after injection, at 1-min intervals, for assessment of decay characteristics. The isovolemic hemodialysis PV measurements demonstrated excellent reproducibility (r(2) = 0.98; method SD, 356 ml; mean coefficient of variation, 4.07%) and a difference of only 149 +/- 341 ml (mean +/- SD), compared with predialysis PV values (Bland-Altman method). PV values at the beginning of dialysis were significantly correlated with body surface area (r(2) = 0.82, P < 0.001) and extracellular fluid estimates (r(2) = 0.73, P < 0.001). BV prediction formulae significantly underestimated absolute BV at the start of dialysis (P < 0.0001). The findings demonstrate that this method can be used for repeated PV determinations during hemodialysis, with excellent reproducibility. It is a potential tool for further research on hemodynamic stability during UF.

Linear decay of relative blood volume during ultrafiltration predicts hemodynamic instability.

BACKGROUND: Relative blood volume (RBV) changes during hemodialysis (HD) are poorly understood. We wish to define characteristics of RBV profiles at different hydration states predictive of hemodynamic instability. METHODS: Thirty patients underwent online RBV monitoring during an HD session with intermittent ultrafiltration (UF) pulses administered until the onset of hypotension. The RBV decay constant (tau) was derived from curve fitting. Linear divergence, the net deviation of the RBV curve during UF from predicted linear decay, was computed from initial 1-minute slopes. RESULTS: The best correlation with proximity to dry weight (PDW) was provided by linear divergence (r = 0.817; P < 0.001), its major determinant in multiple regression analysis. Other predictors were RBV at initiation of UF pulse, UF pulse volume, and UF decay constant (tau(UF)). These parameters were significantly different in UF pulses within 1 kg and 1 kg or greater of dry weight. There were no correlations with refill parameters. The occurrence of hypotension was not different at RBVs less than 90% (7.4%) or 90% or greater (5.3%). tau(UF), linear divergence, RBV at initiation of UF pulse (all P < 0.001), and UF decay amplitude (P < 0.01) were different between hypotensive and normotensive UF pulses. Hypotension was the only independent predictor of tau(UF) (R2 = 0.40; P < 0.001). The only independent predictor of linear divergence was PDW (R2 = 0.667; P < 0.001). CONCLUSION: Approaching dry weight, the RBV decline during UF switched from exponential to linear decay, probably indicating failing vascular refill. Monitoring deviation from linearity may allow improved hemodynamic stability and attainment of optimal post-HD weight.

A new technique for establishing dry weight in hemodialysis patients via whole body bioimpedance.

BACKGROUND: Quantitative techniques are necessary to achieve dry weight (DW) in patients with kidney failure. Bioimpedance spectroscopy (BIS) is a non-invasive method that determines the volume of body fluid compartments. The current work evaluates the use of BIS data in hemodialysis patients for the prediction of DW. METHODS: A new technique has been devised for the estimation of DW that involves the intersection of two slopes, slope normovolemia (SNV) and slope hypervolemia (SHV). These slopes characterize the variation in extracellular water (ECW) with body weight (BW) in the states of normovolemia and hypervolemia, respectively. SNV was established via measurements of ECW and BW in 30 healthy subjects. In a longitudinal study in new hemodialysis patients, successive reduction of post-dialysis weight (PDW) was attempted until clinical signs of normovolemia were presented. Measurements of ECW and BW that were acquired at the beginning of each treatment were used to determine SHV. RESULTS: SNV was found to be 0.239 L/kg and 0.214 L/kg for male and female healthy subjects, respectively. A significant DeltaPDW predicted by the new method (-4.98 kg) was highly correlated to the DeltaPDW achieved in the study (-5.85 kg, R = 0.839). Blood pressure was reduced (P < 0.001) and an 86% decrease in antihypertensive agents was achieved. CONCLUSION: The method of intersecting slopes (SHV with SNV) via BIS is a new method for the prediction DW. This approach will offer considerable improvement for the routine management of DW in the dialysis setting.

Phosphate kinetics during hemodialysis: Evidence for biphasic regulation.

BACKGROUND: Hyperphosphatemia in the hemodialysis population is ubiquitous, but phosphate kinetics during hemodialysis is poorly understood. METHODS: Twenty-nine hemodialysis patients each received one long and one short dialysis, equivalent in terms of urea clearance. Phosphate concentrations were measured during each treatment and for one hour thereafter. A new model of phosphate kinetics was developed and implemented in VisSim. This model characterized additional processes involved in phosphate kinetics explaining the departure of the measured data from a standard two-pool model. RESULTS: Pre-dialysis phosphate concentrations were similar in long and short dialysis groups. Post-dialysis phosphate concentrations in long dialysis were higher than in short dialysis (P < 0.02) despite removal of a greater mass of phosphate (P < 0.001). In both long and short dialysis serum phosphate concentrations initially fell in accordance with two-pool kinetics, but thereafter plateaued or increased despite continuing phosphate removal. Implementation of an additional regulatory mechanism such that a third pool liberates phosphate to maintain an intrinsic target concentration (1.18 +/- 0.06 mmol/L; 95% confidence intervals, CI) explained the data in 24% of treatments. The further addition of a fourth pool hysteresis element triggered by critically low phosphate levels (0.80 +/- 0.07 mmol/L, CI) yielded an excellent correlation with the observed data in the remaining 76% of treatments (cumulative standard deviation 0.027 +/- 0.004 mmol/L, CI). The critically low concentration correlated with pre-dialysis phosphate levels (r=0.67, P < 0.0001). CONCLUSION: Modeling of phosphate kinetics during hemodialysis implies regulation involving up to four phosphate pools. The accuracy of this model suggests that the proposed mechanisms have physiological validity.