Anthropometrically estimated total body water volumes are larger than modeled urea volume in chronic hemodialysis patients: effects of age, race, and gender

A Holistic Framework for the Evaluation of Kidney Function in a Gender-Diverse Landscape

The most commonly used equations to estimate glomerular filtration rate incorporate a binary male-female sex coefficient, which has important implications for the care of transgender, gender-diverse, and nonbinary (TGD) people. Whether "sex assigned at birth" or a binary "gender identity" is most appropriate for the computation of estimated glomerular filtration rate (eGFR) is unknown. Furthermore, the use of gender-affirming hormone therapy (GAHT) for the development of physical changes to align TGD people with their affirmed gender is increasingly common, and may result in changes in serum creatinine and cystatin C, the biomarkers commonly used to estimate glomerular filtration rate. The paucity of current literature evaluating chronic kidney disease (CKD) prevalence and outcomes in TGD individuals on GAHT makes it difficult to assess any effects of GAHT on kidney function. Whether alterations in serum creatinine reflect changes in glomerular filtration rate or simply changes in muscle mass is unknown. Therefore, we propose a holistic framework to evaluate kidney function in TGD people. The framework focuses on kidney disease prevalence, risk factors, sex hormones, eGFR, other kidney function assessment tools, and the mitigation of health inequities in TGD people.

Dialysis Adequacy: A Cross-Sectional Study to Assess the Reliability of the Online Clearance Monitor to Measure Dialysis Dose

Background Frequent assessment of the dialysis dose delivered to hemodialysis patients might help improve morbidity and mortality. Daugirdas' second-generation formula is the recommended method for calculating dialysis doses. However, urea reduction ratios (URRs) and online clearance monitors (OCMs) are frequently used to assess dialysis adequacy due to their more straightforward concept and ease of use. This study was conducted to determine the most reliable method for measuring dialysis adequacy by comparing the correlation of urea reduction ratio and online clearance monitor measurements with the dialysis dose measured using the recommended Daugirdas' second-generation formula. Methods This study was an observational, cross-sectional, single-center study. The dialysis dose was measured as a urea reduction ratio and by an online clearance monitor simultaneously for 50 patients. It was compared to the dialysis dose measurements obtained using Daugirdas' second-generation formula. Results There was a statistically significant strong positive correlation (r = 0.929; p ≤ 0.001) of the urea reduction ratio and a poor concordance (ρC = 0.401; p ≤ 0.001) of online clearance monitor measurements with the dialysis dose measured using Daugirdas' second generation formula. Conclusion Our findings illustrate that the urea reduction ratio may be a more straightforward and reliable means for assessing the adequacy of intermittent hemodialysis with minimal errors in patients compared to online clearance monitors. Online clearance monitors offer easy estimation and practicality with minimal effort but are prone to multiple errors and may not be accurate in some settings.

Prediction of end-dialysis serum sodium concentration in severely hyponatremic kidney failure patients undergoing conventional hemodialysis using sodium kinetic equation

Background and Objectives

Conventional hemodialysis (HD) for kidney failure patients with severe hyponatremia may be complicated by rapid correction of hyponatremia, which increases the risk of osmotic demyelination syndrome. A simple sodium kinetic equation was effective in prediction of end-dialysis serum Na+ in severely hyponatremic kidney failure patient treated with continuous venovenous hemofiltration, but was not tested in conventional HD. The aim of this study was to assess the validity of this equation when used in conventional HD.

Methods

Twenty conventional HD sessions were delivered to 12 kidney failure patients with severe hyponatremia (serum Na+  < 120 mEq/L). The target change in serum Na+ was 4 mEq/L. The DNa.t/V that obtained this change was predetermined according to the sodium kinetic equation and monitored in real time by online clearance monitoring software embedded in dialysis machine. The dialysis session was terminated once the target DNa.t/V was achieved.

Results

The mean observed and predicted serum Na+ were 119.80 ± 3.42 mEq/L and 119.45 ± 3.12 mEq/L, respectively. Bland–Altman plot analysis revealed a mean difference ± SD of 0.33 ± 1.26 mEq/L, and 95% limits of agreement of − 2.13 to 2.83. The imprecision in prediction of end-dialysis serum Na+ was 2.52 mEq/L. The small difference and clinically insignificant 95% limits of agreement indicate a good agreement between the observed and predicted serum Na+.

Conclusion

The sodium kinetic equation was effective in prediction of end-dialysis serum Na+ in kidney failure patients with severe hyponatremia.

Comparison of measured vs kinetic-model predicted phosphate removal during hemodialysis and hemodiafiltration

BACKGROUND

To what extent hemodiafiltration (HDF) improves management of hyperphosphatemia over hemodialysis (HD) is a subject of ongoing investigation.

METHODS

We modified a previously described phosphate kinetic model to include incorporation of EUDIAL recommended equations for hemodiafiltration (HDF) clearance. We used the model to predict the recovery of phosphate from spent dialysate/hemofiltrate and compared this with averaged data from five published studies. Mean study average predialysis serum phosphate was 1.81 ± 0.20 mmol/L. Session length was close to 240 min per treatment. All HDF was done postdilution, at an average rate of 65 ± 24 mL/min.

RESULTS

Measured mean phosphate removal was 1039 ± 136 mg (33.5 ± 4.41 mmol, slightly lower than the model-predicted mean value of 1092 ± 127 mg (35.3 ± 4.09 mmol). The measured ratio of phosphate removal with HDF compared with HD averaged 1.15 ± 0.22, ranging from 1.01 to 1.44. Using mean study input parameters for patient size and treatment characteristics, the predicted ratio of phosphate removal with HDF compared with HD averaged 1.095 ± 0.029, ranging from 1.05 to 1.13.

CONCLUSIONS

Addition of EUDIAL-recommended convective clearance equations to a phosphate kinetic model predicts a 10% or greater benefit in terms of phosphate removal for HDF compared with HD at typical dialysis and hemodiafiltration treatment settings. These predictions are similar to the HDF advantage reported in the literature in studies where phosphate removal has been measured in spent dialysate.

What Total Body Water Measurement Should Be Used for Prescribing the Dialysis Dose in Low-Flow Home Daily Dialysis?

INTRODUCTION

In low-flow home daily dialysis (HDD), the dialysis dose is evaluated from the total body water (TBW). TBW can be estimated by anthropometric methods or bioimpedance spectroscopy.

METHODS

A multicentric cross-sectional study of patients in HDD for >3 months was conducted to assess the correlation and the difference between the anthropometric estimate of TBW (Watson-TBW) and the bioimpedance estimate (BIS-TBW) and to analyse the impact on the dialysate volume prescribed.

RESULTS

Forty patients from 10 centres were included. The median BIS-TBW and Watson-TBW were 35.1 (29.1-41.4 L) and 36.9 (32-42.4 L), respectively. The 2 methods had a good correlation (r = 0.87, p < 0.05). However, Bland-Altman analysis showed an overestimation of TBW with Watson's formula, with a bias of 2.77 L. For 4, 5, or 6 sessions per week, the use of Watson-TBW increases the dialysate prescription per week by 100 L, 45 L, or 10 L, respectively, over our entire cohort. There is no increase in the volume of dialysate prescribed with the 7 sessions per week schedule.

CONCLUSION

BIS-TBW and Watson-TBW estimation have a good correlation; however, Watson's equation overestimates TBW. This overestimation is negligible for a prescription frequency of >5 sessions per week.

New Estimation Formulas for Daily Sodium Intake in Hemodialysis Patients by a Duplicate Portion Method

OBJECTIVE

Excess sodium intake is associated with volume overload and increased blood pressure. Therefore, to prevent future cardiovascular events, a sodium-restricted diet is strongly recommended for patients on maintenance hemodialysis (HD). However, only one formula for estimating dietary sodium intake in HD patients is available, and its validity has not been adequately evaluated. This study aimed to measure daily sodium intake using the duplicate portion method and provide a new formula for estimating dietary sodium intake.

DESIGN AND METHODS

Nineteen Japanese patients undergoing HD were enrolled in this cross-sectional multicenter study. The daily sodium intake of these patients was measured directly using the duplicate portion method. Two formulas for estimating sodium intake were developed by stepwise regression analysis. Their validities were compared with the validity of the previous formula. Furthermore, using these new formulas, we estimated the daily consumption of sodium in a large number of Japanese HD patients.

RESULTS

The previous formula underestimated true sodium intake using Bland-Altman diagrams. No significant correlation was noted between the measured sodium intake and the estimated intake (r = 0.30, P = .23, Fisher's Z-transformation). The new formulas 1 and 2, which included age, predialysis and postdialysis serum sodium levels, predialysis body weight, and interdialytic body weight gain, accurately estimated sodium consumption. The coefficients of correlation between the estimated values and the true sodium intake were r = 0.858 and r = 0.805, respectively. The simulation model using data from the Japanese Society for Dialysis Therapy showed that the distribution of the estimated sodium intake using the previous formula shifted left compared with that using the new formulas.

CONCLUSIONS

The new formulas accurately estimated the daily sodium consumption in HD patients. Further longitudinal studies are required to determine whether the estimated sodium intake level calculated using the new formulas would serve as a potential marker and/or therapeutic target to prevent cardiovascular events in HD patients.

Routine assessment of kidney urea clearance, dialysis dose and protein catabolic rate in the once-weekly haemodialysis regimen

BACKGROUND

The dialysis dose (Kt/V) and normalized protein catabolic rate (PCRn) are the most useful indices derived from the urea kinetic model (UKM) in haemodialysis (HD) patients. The kidney urea clearance (Kru) is another important UKM parameter which plays a key role in the prescription of incremental HD. Ideally, the three kinetic parameters should be assessed using the complex software Solute Solver based on the double pool UKM. In the clinical setting, however, the three indices are estimated with simplified formulae. The recently introduced software SPEEDY assembles the aforementioned equations in a plain spreadsheet, to produce quite accurate results of Kru, Kt/V and PCRn. Unfortunately, specific equations to compute Kt/V and PCRn for patients on a once-weekly HD regimen (1HD/wk) were not available at the time SPEEDY was built-up. We devised a new version of SPEEDY (SPEEDY-1) and an even simpler variant (SPEEDY-1S), using two recently published equations for the 1HD/wk schedule . Moreover, we also added a published equation to estimate the equivalent renal clearance (EKR) normalized to urea distribution volume (V) of 35 L (EKR₃₅) from Kru and Kt/V . Aim of the present study was to compare the results obtained using the new methods (SPEEDY-1 and SPEEDY-1S) with those provided by the reference method Solute Solver.

SUBJECTS AND METHODS

One hundred historical patients being treated with the once-weekly HD regimen were enrolled. A total of 500 HD sessions associated to the availability of monthly UKM studies were analysed in order to obtain Kru, single pool Kt/V (spKt/V), equilibrated Kt/V (eKt/V), V, PCRn and EKR₃₅ values by using Solute Solver, SPEEDY-1 and SPEEDY-1S.

RESULTS

When comparing the paired values of the above UKM parameters, as computed by SPEEDY-1 and Solute Solver, respectively, all differences but one were statistically significant at the one-sample t-test; however, the agreement limits at Bland-Altman analysis showed that all differences were negligible. When comparing the paired values of the above UKM parameters, as computed by SPEEDY-1S and Solute Solver, respectively, all differences were statistically significant; however, the agreement limits showed that the differences were negligible as far as Kru, spKt/V and eKt/V are concerned, though much larger regarding V, PCRn and EKR₃₅.

CONCLUSIONS

We implemented SPEEDY with a new version specific for the once-weekly HD regimen, SPEEDY-1. It provides accurate results and is presently the best alternative to Solute Solver. Using SPEEDY-1S led to a larger difference in PCRn and EKR₃₅, which could be acceptable for clinical practice if SPEEDY-1 is not available.

Quantitative assessment of sodium mass removal using ionic dialysance and sodium gradient as a proxy tool: Comparison of high-flux hemodialysis versus online hemodiafiltration

Restoration and maintenance of sodium are still a matter of concern and remains of critical importance to improve the outcomes in homeostasis of stage 5 chronic kidney disease patients on dialysis. Sodium mass balance and fluid volume control rely on the "dry weight" probing approach consisting mainly of adjusting the ultrafiltration volume and diet restrictions to patient needs. An additional component of sodium and fluid management relies on adjusting the dialysate-plasma sodium concentration gradient. Hypotonicity of ultrafiltrate in online hemodiafiltration (ol-HDF) might represent an additional risk factor in regard to sodium mass balance. A continuous blood-side approach for quantifying sodium mass balance in hemodialysis and ol-HDF using an online ionic dialysance sensor device ("Flux" method) embedded on hemodialysis machine was explored and compared to conventional cross-sectional "Inventory" methods using anthropometric measurement (Watson), multifrequency bioimpedance analysis (MF-BIA), or online clearance monitoring (OCM) to assess the total body water. An additional dialysate-side approach, consisting of the estimation of inlet/outlet sodium mass balance in the dialysate circuit was also performed. Ten stable hemodialysis patients were included in an "ABAB"-designed study comparing high-flux hemodialysis (hf-HD) and ol-HDF. Results are expressed using a patient-centered sign convention as follows: accumulation into the patient leads to a positive balance while recovery in the external environment (dialysate, machine) leads to a negative balance. In the blood-side approach, a slight difference in sodium mass transfer was observed between models with hf-HD (-222.6 [-585.1-61.3], -256.4 [-607.8-43.7], -258.9 [-609.8-41.3], and -258.5 [-607.8-43.5] mmol/session with Flux and Inventory models using V_Watson , V_MF-BIA , and V_OCM values for the volumes of total body water, respectively; global P value < .0001) and ol-HDF modalities (-235.3 [-707.4-128.3], -264.9 [-595.5-50.8], -267.4 [-598.1-44.1], and -266.0 [-595.6-55.6] mmol/session with Flux and Inventory models using V_Watson , V_MF-BIA , and V_OCM values for the volumes of total body water, respectively; global P value < .0001). Cumulative net ionic mass balance on a weekly basis remained virtually similar in hf-HD and ol-HDF using Flux method (P = n.s.). Finally, the comparative quantification of sodium mass balance using blood-side (Ionic Flux) and dialysate-side approaches reported clinically acceptable (a) agreement (with limits of agreement with 95% confidence intervals (CI): -166.2 to 207.2) and (b) correlation (Spearman's rho = 0.806; P < .0001). We validated a new method to quantify sodium mass balance based on ionic mass balance in dialysis patients using embedded ionic dialysance sensor combined with dialysate/plasma sodium concentrations. This method is accurate enough to support caregivers in managing sodium mass balance in dialysis patients. It offers a bridging solution to automated sodium proprietary balancing module of hemodialysis machine in the future.

Adequacy of hemodialysis in acute kidney injury: Real-time monitoring of dialysate ultraviolet absorbance vs. blood-based Kt/Vurea

BACKGROUND

Current guidelines recommend monitoring the adequacy of hemodialysis (HD) treatments in patients with acute kidney injury (AKI). Blood-based methods for calculating urea such as reduction ratio (URR) and single-pool Kt/Vurea (spKt/Vurea) require pre- and post-HD blood urea nitrogen (BUN) measurements. This study aims to compare real-time monitoring of urea clearance using dialysate ultraviolet absorbance (UV) with laboratory-measured spKt/Vurea.

METHODS

We conducted a single-center, retrospective study among hospitalized patients with AKI, who required intermittent hemodialysis (IHD). Those patients whose dialysis dose was simultaneously monitored by spKt/Vurea and UV-absorbance (UV-spKt/Vurea) were included in the study. The statistical correlation between both methods was assessed by means of the Pearson moment product correlation, Mann-Whitney U-test and Bland-Altman analysis of agreement.

RESULTS

Thirty patients with AKI were evaluated. There was no statistical difference between the mean spKt/Vurea calculated by traditional methods and the mean UV-spKt/Vurea. (1.37 ± 0.37 vs. 1.28 ± 0.36, P = 0.12, CI: 95%). A Pearson moment correlation analysis revealed a close agreement between both methods (r = 0.79, P < 0.001). Furthermore, Bland-Altman analysis showed that >95% of the data points were confined within the upper and lower levels of agreement.

CONCLUSION

In this pilot study of patients with AKI, UV-spKt/Vurea correlated with standard blood-based spKt/Vurea and may be a useful tool to monitor dialysis adequacy. Larger studies evaluating multiple UV and blood-based measurements per patient and a more diverse AKI population are needed to confirm this initial observation.

Routine Kt/V and Normalized Protein Nitrogen Appearance Rate Determined From Conductivity Access Clearance With Infrequent Postdialysis Serum Urea Nitrogen Measurements

RATIONALE & OBJECTIVES

Conventional monitoring of hemodialysis dose is implemented using urea kinetic modeling based on single-pool Kt/V, which requires both pre- and postdialysis serum urea nitrogen (SUN) measurements. We compared this conventional approach to one in which Kt/V is calculated using conductivity clearance, thereby reducing the need for regular postdialysis SUN measurements.

STUDY DESIGN

Comparative study of 2 diagnostic tests.

SETTING & PARTICIPANTS

Prevalent patients receiving maintenance hemodialysis for at least 2 years for whom both urea reduction ratio (URR) and average conductivity clearance (Kecn) were measured.

TESTS COMPARED

During the initial 8 months (baseline interval), average Kecn and URR were used to calculate a median patient-specific, modeled, calibration solute distribution volume (Vcal). During months 9 to 16 (period 1) and 17 to 24 (period 2), Kt/V was conventionally computed using URR and also by a new method using Vcal and Kecn without postdialysis SUN values. We examined the percentage error between these 2 methods of calculating Kt/V.

OUTCOMES

Concordance between the 2 methods of calculating Kt/V.

RESULTS

Among 1,093 patients, mean individual-level median single-pool Kt/V values derived using the conventional method during the baseline interval, period 1, and period 2 were 1.62±0.24 (SD), 1.66±0.24, and 1.67±0.24, respectively. During periods 1 and 2, patient-level median Kt/V values derived using Kecn were 1.64±0.24 and 1.65±0.24, respectively. Percent differences between patient-level median values of Kt/V (conductivity minus conventional URR methods) were-0.63%±7.7% and-0.75%±8.4% for periods 1 and 2. Normalized protein nitrogen appearance were comparable between the 2 methods.

LIMITATIONS

Data were collected over 2 years. Study was limited to in-center hemodialysis patients dialyzed 3 times per week. Dialysis session length was not adjusted for treatment interruptions.

CONCLUSIONS

A new method of calculating Kt/V based on Kecn that requires fewer postdialysis SUN measurements provided diagnostic data comparable to those from conventional use of URR and has the potential to avoid errors related to postdialysis blood sampling and measurement.

What volume to choose to assess online Kt/V?

INTRODUCTION

Urea distribution volume (V) can be assessed in different ways, among them the anthropometric Watson Volume (V_W). However, many studies have shown that V_W does not coincide with V and that the latter can be more accurately estimated with other methods. The present multicentre study was designed to answer the question: what V to choose to assess online Kt/V?

MATERIALS AND METHODS

Pre- and postdialysis blood urea nitrogen concentrations and the usual input data set for urea kinetic modelling were obtained for a single dialysis session in 201 Caucasian patients treated in 9 Italian dialysis units. Only dialysis machines measuring ionic dialysance (ID) were utilized. ID reflects very accurately the mean effective dialyser urea clearance (Kd). Six different V values were obtained: the first one was V_W; the second one was computed from the equation established by the HEMO Study to predict the single pool-adjusted modelled V from V_W (V_H) (Daugirdas JT et al. KI 64: 1108, 2003); the others were estimated kinetically as: 1. V_ID, in which ID is direct input in the in the double pool variable volume (dpVV) calculation by means of the Solute-solver software; 2. V_Kd, in which the estimated Kd is direct input in the dpVV calculation by means of the Solute-solver software; 3. V_KTV, in which V is calculated by means of the second generation Daugirdas equation; 4. V_SPEEDY, in which ID is direct input in the dpVV calculation by means of the SPEEDY software able to provide results quite similar to those provided by Solute-solver.

RESULTS

Mean± SD of the main data are reported: measured ID was 190.6 ± 29.6 mL/min, estimated Kd was 211.6 ± 29.0 mL/min. The relationship between paired data was poor (R² = 0.34) and their difference at the Bland-Altman plot was large (21 ± 27 mL/min). V_W was 35.3 ± 6.3 L, V_H 29.5 ± 5.5, V_{_}ID 28.99 ± 7.6 L, V_{_}SPEEDY 29.4 ± 7.6 L, V_KTV 29.7 ± 7.0 L. The mean ratio V_W/V_ID was 1.22, (i.e. V_W overestimated V_ID by about 22%). The mean ratio V_H/V_ID was 1.02 (i.e. V_H overestimated V_ID by only 2%). The relationship between paired data of V_ID and V_W was poor (R² = 0.48) and their mean difference at the Bland-Altman plot was very large (-  6.39 ± 5.59 L). The relationship between paired data of V_ID and V_H was poor (R² = 47) and their mean difference was small but with a large SD (- 0.59 ± 5.53 L). The relationship between paired data of V_ID and V_SPEEDY was excellent (R² = 0.993) and their mean difference at the Bland-Altman plot was very small (- 0.54 ± 0.64 L). The relationship between paired data of V_ID and V_KTV was excellent (R² = 0.985) and their mean difference at the Bland-Altman plot was small (- 0.85 ± 1.06 L).

CONCLUSIONS

V_ID can be considered the reference method to estimate the modelled V and then the first choice to assess Kt/V. V_SPEEDY is a valuable alternative to V_ID. V_KTV can be utilized in the daily practice, taking also into account its simple way of calculation. V_W is not advisable because it leads to underestimation of Kt/V by about 20%.

Eliminating the need for routine monthly postdialysis serum urea nitrogen measurement: A method for monitoring Kt/V and normalized protein catabolic rate using conductivity determined dialyzer clearance

Many dialysis machines can compute dialyzer sodium clearances at multiple time points during a dialysis treatment using conductivity. For a given treatment, the average dialyzer sodium clearance (K), when combined with treatment time (t), and the estimated urea distribution volume (V, usually based on either anthropometry or bioimpedance), can be used to estimate Kt/V, an important measure of hemodialysis adequacy. While this conductivity-derived value for Kt/V correlates moderately with Kt/V calculated from predialysis and postdialysis serum urea nitrogen (SUN) values (urea reduction ratio, URR), the ultrafiltration volume, and session length it is, unfortunately, not sufficiently accurate to replace URR-based Kt/V. Here we underline the potential utility of an alternative method to estimate Kt/V (a variant of a technique originally proposed by Gotch and Levin and their colleagues) using conductivity-derived sodium clearance (K) that does not require routine measurement of the postdialysis SUN but which should closely track Kt/V computed in the usual fashion. The increased accuracy with the new method is explained by the use of a patient-specific value of V, which is an average value calculated from several dialysis sessions where both conductivity dialyzer clearance and predialysis and postdialysis SUN have been measured. Once this patient-specific conductivity/URR-based value for V has been determined, it can be used to calculate Kt/V for subsequent treatments in which conductivity-based dialyzer clearances are measured, but around which predialysis and postdialysis SUN values have not been obtained. (If the predialysis SUN values for such a subsequent treatment are also measured, then a normalized protein catabolic rate that closely tracks the value from conventional urea modeling, can also be determined.) By reducing the number of postdialysis SUN measurements needed to monitor hemodialysis adequacy this new method of estimating Kt/V by conductivity should save staff time and laboratory costs, increase patient and staff safety, and decrease error rates associated with improper postdialysis blood sampling technique.

Correlation between Dt/V derived from ionic dialysance and blood-driven Kt/V of urea in African-American hemodialysis patients, based on body weight and ultrafiltration volume

Background

The Dt/V obtained by using ionic dialysance (D) as a surrogate for urea clearance (K) is a well-validated adjunct measure of hemodialysis adequacy, with a variable level of correlation with urea-based Kt/V. However, this correlation has not been examined based on patients’ body size and ultrafiltration (UF) volume during the dialysis session.

Methods

Simultaneous evaluations of online Dt/V and single-pool variable-volume urea Kt/V were made. Patients were categorized into three subgroups based on their weight (<60, 60–80 and ≥80 kg), body mass index (<25, 25–30 and >30 kg/m²) and UF volume (<1.5, 1.5–3 and >3 L). The correlation between Dt/V and Kt/V was evaluated for the entire cohort per dialysis session in each subgroup.

Results

Mean Kt/V was greater than the mean Dt/V (1.72 versus 1.50, P < 0.001), with an overall correlation r value of 0.602. This correlation was stronger in the medium weight group versus lower and higher weights. The correlation between Dt/V and Kt/V was inversely related to the UF volume (r = 0.698, 0.621 and 0.558 for those with UF volume of <1.5, 1.5–3.0 and >3 L, respectively). A total of 99.3% of patients with Dt/V of >1.2 also had Kt/V >1.2 and 9.5% of those with Dt/V <1.2 had their Kt/V <1.2.

Conclusions

There is a moderate degree of correlation between Dt/V and Kt/V in African-American hemodialysis patients, which is impacted by body size and UF volume. A Dt/V of >1.2 strongly predicts adequate dialysis as defined by Kt/V of >1.2.

Volume of urea cleared as a therapy dosing guide for more frequent hemodialysis

INTRODUCTION

With dialysis delivery systems that operate at low dialysate flow rates, prescriptions for more frequent hemodialysis (HD) employ dialysate volume as the primary parameter for small solute removal rather than blood-side urea dialyzer clearance (K). Such delivery systems, however, yield dialysate concentrations that almost completely saturate with blood (water), suggesting that the volume of urea cleared (the product of K and treatment time or Kt) can be readily estimated from the prescribed dialysate volume to target small solute removal. Methods For more frequent HD, we examined the volume of urea cleared per treatment required to achieve a minimal dose of small solute removal, comparing results based on body surface area (BSA) with those based on KDOQI clinical practice guidelines, that is, a weekly stdKt/V of 2.1. Estimates of the target volume of urea cleared were calculated for 4, 5, and 6 treatments per week, and compared for patients with different anthropometric estimates of total body water volume (V_ant ). BSA was assumed proportional to V_ant ^0.8 , and residual kidney function was neglected. Findings Whether based on BSA or weekly stdKt/V of 2.1, the target volume of urea cleared per treatment required to achieve a minimal dose of small solute removal was lower at higher treatment frequency. As with conventional thrice-weekly HD, target volumes of urea cleared for more frequent HD based on BSA were larger for patients with small V_ant and smaller for patients with large V_ant than those based on a weekly stdKt/V of 2.1. Discussion Prescription of more frequent HD using the volume of urea cleared per treatment, calculated from the prescribed dialysate volume, is simple in principle and can be readily implemented in clinical practice when using dialysis delivery systems that operate at low dialysate flow rates. Other aspects of dialysis adequacy require additional consideration.

Changes in Total Protein Concentration Due to Fluid Removal During and Shortly after Hemodialysis

BACKGROUND

Changes in plasma volume during hemodialysis are complex and have been shown to depend on the rate of fluid removal and the degree of fluid overload. We examined changes in total protein concentration during and shortly after a dialysis treatment in archived data from the HEMO study.

METHODS

During follow-up months 4 and 36 of the HEMO study, additional blood samples were obtained during a typical dialysis session at 30 and 60 min after dialysis. In 315 studies from 282 patients where complete data were available, we calculated the concentration change in total protein and compared it to the modeled change in both total body water and extracellular fluid space as derived from 2-pool urea kinetic modeling.

RESULTS

The mean postdialysis modeled urea volume (V) was 31.1 ± 6.18 L. Mean fluid removal was 2.76 ± 1.27 kg, over a session length of 207 ± 28 min. The ratio of predialysis V to postdialysis V averaged 1.090 ± 0.040. The mean TP ratios (post/pre) at 0, 30, and 60 min postdialysis averaged 1.121 ± 0.070 (SD), 1.091 ± 0.090, and 1.091 ± 0.086. The dialysate to serum sodium gradient, studied in a different group of treatments where this information was available, had no impact on these findings, nor did the length of the interdialytic interval.

CONCLUSIONS

On average, after equilibration, the change in plasma volume due to fluid removal is similar to the modeled change in total body water (urea space), irrespective of dialysate to serum sodium gradient. This supports previous observations that during dialysis with ultrafiltration, plasma volume contracts to a lesser degree than the interstitial volume and that some fluid may be removed from spaces other than the extracellular fluid.

Volume Estimates in Chronic Hemodialysis Patients by the Watson Equation and Bioimpedance Spectroscopy and the Impact on the Kt/Vurea calculation

Background

Accurate assessment of total body water (TBW) is essential for the evaluation of dialysis adequacy (Kt/V_urea). The Watson formula, which is recommended for the calculation of TBW, was derived in healthy volunteers thereby leading to potentially inaccurate TBW estimates in maintenance hemodialysis recipients. Bioimpedance spectroscopy (BIS) may be a robust alternative for the measurement of TBW in hemodialysis recipients.

Objectives

The primary objective of this study was to evaluate the accuracy of Watson formula-derived TBW estimates as compared with TBW measured with BIS. Second, we aimed to identify the anthropometric characteristics that are most likely to generate inaccuracy when using the Watson formula to calculate TBW. Finally, we derived novel anthropometric equations for the more accurate estimation of TBW.

Design and Setting

This was a cross-sectional study of prevalent in-center HD patients at St Michael's Hospital.

Patients

One hundred eighty-four hemodialysis patients (109 men and 75 women) were evaluated in this study.

Measurements

Anthropometric measurements including weight, height, waist circumference, midarm circumference, and 4-site skinfold (biceps, triceps, subscapular, and suprailiac) thickness were measured; fat mass was measured using the formula by Durnin and Womersley. We measured TBW by BIS using the Body Composition Monitor (Fresenius Medical Care, Bad Homburg, Germany).

Methods

We used the Bland-Altman method to calculate the difference between the TBW derived from the Watson method and the BIS. To derive new equations for TBW estimation, Pearson's correlation coefficients between BIS-TBW (the reference test) and other variables were examined. We used the least squares regression analysis to develop parsimonious equations to predict TBW.

Results

TBW values based on the Watson method had a high correlation with BIS-TBW (correlation coefficients = 0.87 and P < .001). Despite the high correlation, the Watson formula overestimated TBW by 5.1 (4.5-5.8) liters and 3.8 (3.0-4.5) liters, in men and women, respectively. Higher fat mass and waist circumference (general and abdominal obesity) were correlated with the greater TBW overestimation by the Watson formula. We created separate equations for men and women based on weight and waist circumference.

Limitations

The main limitation of our study was the lack of an external validation for our novel estimating equation. Furthermore, though BIS has been validated against traditional reference standards, our assumption that it represents the "gold standard" for body compartment assessment may be flawed.

Conclusions

The Watson formula generally overestimates TBW in chronic dialysis recipients, particularly in patients with the highest waist circumference. Widespread reliance on the Watson formula for derivation of TBW may lead to the underestimation of Kt/V_urea..

Online measurement of hemodialysis adequacy using effective ionic dialysance of sodium-a review of its principles, applications, benefits, and risks

Dialysis dose is an important determinant of clinical outcomes in patients with end stage renal disease on maintenance dialysis. In clinical practice dialysis dose is monitored at least monthly by urea clearance based on Urea Kinetic Modeling. Online clearance monitoring using effective ionic dialysance (EID) of sodium (Na⁺ ) is available on some hemodialysis machines. This paper reviews the background, methodology, additional applications, and potential risks associated with EID. Effective ionic dialysance provides a reliable, real-time, noninvasive, and inexpensive measurement of dialysis dose during an ongoing hemodialysis (HD) session to allow interventions and assess the impact of these changes on clearance. Surveillance of vascular access flow rates can be used to screen for access dysfunction and refer for interventions. There is a concern that EID measurements may cause Na⁺ loading because of high dialysate Na⁺ used during these measurements, however, mathematical models, in vitro experiments, and clinical studies in patients on maintenance HD do not show any evidence of Na⁺ loading during EID measurements. We cannot rule out the possibility of nonosmotic Na⁺ accumulation in the skin because no published literature exists on this topic as it pertains to clearance measurements based on EID of Na⁺ .

Body composition monitoring-derived urea distribution volume in children on chronic hemodialysis

BACKGROUND

Modern hemodialysis (HD) machines are able to measure ionic dialysance online and thereby continuously monitor Kt/V. The accuracy of measurement depends on the input of the correct urea distribution volume (V), available from anthropometric equations and body composition monitoring (BCM). The latter method, however, has not been validated in children.

METHODS

We compared V determined by BCM to that calculated using four different anthropometric formulas (Morgenstern, Mellits and Cheek, Hume-Weyers and Watson equations) in 23 pediatric HD patients. We also compared online Kt/V using BCM-derived V with the Kt/V calculated from pre- and post-dialytic urea concentrations using the single-pool second-generation Daugirdas equation.

RESULTS

The V calculated by the Morgenstern equation was similar to that derived by BCM, with a mean difference of -0.7% (95% limits of agreement -11.7 to 10.3%). In contrast, the V calculated by the other equations was 5.4, 6.2 and 18%, respectively higher than the BCM-derived V. The mean difference between Kt/V calculated using the Daugirdas equation and online Kt/V determination based on BCM-derived V data was 0.10 (95% limits of agreement -0.50 to 0.70%).

CONCLUSIONS

In our pediatric HD patients the V measured by BCM was in agreement with that calculated using the Morgenstern equation, which is the only equation which has been validated to date in children on dialysis. Online determination of Kt/V using a BCM-derived V largely agreed with that calculated by the Daugirdas equation. We therefore conclude that the former approach is suitable for frequent online assessment of dialytic small solute clearance.

Body Composition Affects Urea Distribution Volume Estimated by Watson's Formula

OBJECTIVE

Dialysis machines use the Watson formula (Vwatson) to estimate the urea distribution volume (UDV) to calculate the online Kt/V for each dialysis session. However, the equation could give rise to inaccuracies. The present study analyzes whether body composition affects UDV estimated by Vwatson in comparison to bioimpedance spectroscopy (Vbis) as the reference method.

DESIGN

This is a transversal study performed in the setting of a hemodialysis unit.

SUBJECTS

Prevalent hemodialysis patients.

INTERVENTION

The same day, UDV was measured using Vwatson and Vbis. We compared their results.

MAIN OUTCOME MEASURE

Differences between UDV using Watson equation and Vbis.

RESULTS

We included 144 prevalent patients. Vwatson overestimated the volume with regard to Vbis (Vwatson - Vbis) by 2.5 L (1.8 L; P = .001). We found an excellent correlation between the 2 methods. A higher mean Vwatson - Vbis value was correlated to older age (P = .03), body mass index (P = .01), fat tissue index (P = .001), lower lean tissue index (P = .001), lower extracellular water (P = .01), and intracellular water (P = .001).

CONCLUSION

Body composition affects UDV estimated by Vwatson, thus modifying the result of Kt/V. In young patients who present more lean tissue and less fat tissue, Kt/V is underestimated with Vwatson.

Ionic Dialysance and Determination of Kt/V in on-line Hemodiafiltration with Simultaneous Pre- and Post-dilution

Purpose

A direct determination of Kt/V using ionic dialysance for estimating K and bio-impedancemetry for estimating V is compared with the usual indirect estimation based on the second generation Daugirdas equation during a new technique of hemodiafiltration with simultaneous pre- and postdilution (mixed-HDF).

Methods

In 31 informed consented patients, the urea distribution volume (V) is estimated by total body water (VBCM) measured by the Body Composition Monitor (BCM; Fresenius Medical Care, Bad Homburg, Germany) based on bio-impedance spectroscopy. The value (KOCM t)/VBCM is calculated during 114 mixed-HDF sessions (duration 4 hours) from the measurement of ionic dialysance KOCM by the OCM module, standard on the 5008 dialysis monitor (Fresenius Medical Care, Germany). The single pool (Kt/V)sp is determined from blood urea concentration measurements using the Daugirdas equation.

Results

Mixed-HDF is a very high-efficiency hemodialysis with a delivered dialysis dose Kt/V near from 2 per 4-hour session. (KOCM t)/VBCM (1.97 ± 0.28) is consistent with (Kt/V)sp (2.01 ± 0.34) with a correlation coefficient at 0.72.

Conclusions

Direct calculation of Kt/V from estimating K by OCM and V by BCM is consistent with the usual indirect estimation by the second generation Daugirdas equation. Therefore, the regular determination of V by BCM allows the estimation of single-pool Kt/V at each session without the need of blood sampling.

Quantification of Hemodialysis Dose: What Kt/V to Choose?

Background

Quantification of hemodialysis became more accurate and easier after the advent of ionic dialysance and the use of methods for estimating urea distribution volume (V). The aim of this study was to compare different methods of hemodialysis dose assessment: Kt/VDau (Daugirdas 2nd generation), Kt/VOCM (Kt by OCM (Online Clearance Monitor) and V by Watson), and Kt/VBCM (Kt by OCM and V by bio-impedance); and to assess the dialysis adequacy, defined by a Kt/V≥1.4.

Design

Prospective, observational study.

Methods

35 hemodialysis sessions were evaluated in 35 chronic hemodialysis patients. During each session, we measured simultaneously, Kt/VOCM, Kt/VBCM and calculated Kt/VDau by performing blood samples before and after each session.

Results

35 patients, gender (M/F: 19/16), mean age of 50.49 years, were evaluated. We noted a difference between the three methods of evaluating Kt/V index: Kt/VDau, Kt/VOCM and Kt/VBCM (1.82 ± 0.29; 1.45 ± 0.23; 1.8 ± 0.33, p<0.001). Comparison of Kt/VOCM with Kt/VDau and Kt/VBCM leads to a significant systematic underestimate of Kt/V by 22% and 20.5% respectively. Better agreement between Kt/VDau and Kt/VBCM was observed. The adequate hemodialysis was achieved, according to three methods: Kt/VDau, Kt/VOCM and Kt/VBCM respectively in 100%, 57,1% and 88.6% of the cases.

Conclusions

The Kt/V index is different depending on the method used for its evaluation. The three methods can be used for quantification of hemodialysis with a better agreement between Kt/VDau and Kt/VBCM. In this study, Kt/VOCM results underestimate hemodialysis efficiency. This difference has to be considered when applying quantification of hemodialysis to clinical practice.

Urea concentration and haemodialysis dose

Background. Dialysis dose is commonly defined as a clearance scaled to some measure of body size, but the toxicity of uraemic solutes is probably associated more to their concentrations than to their clearance. Methods. 619 dialysis sessions of 35 patients were modified by computer simulations targeting a constant urea clearance or a constant urea concentration. Results. Urea generation rate G varied widely in dialysis patients, rather independently of body size. Dialysing to eKt/V 1.2 in an unselected patient population resulted in great variations in time-averaged concentration (TAC) and average predialysis concentration (PAC) of urea (5.9–40.2 and 8.6–55.8 mmol/L, resp.). Dialysing to equal clearance targets scaled to urea distribution volume resulted in higher concentrations in women. Dialysing to the mean HEMO-equivalent TAC or PAC (17.7 and 25.4 mmol/L) required extremely short or long treatment times in about half of the sessions. Conclusions. The relation between G and V varies greatly and seems to be different in women and men. Dialysing to a constant urea concentration may result in unexpected concentrations of other uraemic toxins and is not recommended, but high concentrations may justify increasing the dose despite adequate eKt/V, std EKR, or std K/V.

Dialysis dose scaled to body surface area and size-adjusted, sex-specific patient mortality

BACKGROUND AND OBJECTIVES

When hemodialysis dose is scaled to body water (V), women typically receive a greater dose than men, but their survival is not better given a similar dose. This study sought to determine whether rescaling dose to body surface area (SA) might reveal different associations among dose, sex, and mortality.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

Single-pool Kt/V (spKt/V), equilibrated Kt/V, and standard Kt/V (stdKt/V) were computed using urea kinetic modeling on a prevalent cohort of 7229 patients undergoing thrice-weekly hemodialysis. Data were obtained from the Centers for Medicare & Medicaid Services 2008 ESRD Clinical Performance Measures Project. SA-normalized stdKt/V (SAN-stdKt/V) was calculated as stdKt/V × ratio of anthropometric volume to SA/17.5. Patients were grouped into sex-specific dose quintiles (reference: quintile 1 for men). Adjusted hazard ratios (HRs) for 1-year mortality were calculated using Cox regression.

RESULTS

spKt/V was higher in women (1.7 ± 0.3) than in men (1.5 ± 0.2; P<0.001), but SAN-stdKt/V was lower (women: 2.3 ± 0.2; men: 2.5 ± 0.3; P<0.001). For both sexes, mortality decreased as spKt/V increased, until spKt/V was 1.6-1.7 (quintile 4 for men: HR, 0.62; quintile 3 for women: HR, 0.64); no benefit was observed with higher spKt/V. HR for mortality decreased further at higher SAN-stdKt/V in both sexes (quintile 5 for men: HR, 0.69; quintile 5 for women: HR, 0.60).

CONCLUSIONS

SA-based dialysis dose results in dose-mortality relationships substantially different from those with volume-based dosing. SAN-stdKt/V analyses suggest women may be relatively underdosed when treated by V-based dosing. SAN-stdKt/V as a measure for dialysis dose may warrant further study.

Dialysate saving by automated control of flow rates: comparison between individualized online hemodiafiltration and standard hemodialysis

Cost reduction and quality improvement seem to be conflicting issues. However, online hemodiafiltration (oHDF) with new automatic functions offers a cost-efficient therapy compared to hemodialysis (HD). Seven dialysis centers conducted a randomized clinical trial with cross-over design: high-flux HD vs. postdilutional oHDF with functions coupling both dialysate and substitution flow rates to blood flow rates. During the 6 weeks of the study, all treatment parameters remained unchanged for HD and oHDF, apart from dialysate and substitution flow rate. Treatment data were recorded during each treatment, and predialytic and postdialytic concentrations of urea were recorded at the end of each study phase. The analysis involved 956 treatments of 54 patients. The mean dialysate consumption was 123.2 ± 6.4 l for HD and 113.4 ± 14.9 l for oHDF (p < 0.0001), the mean dialysis dose was 1.42 ± 0.23 for HD and 1.47 ± 0.26 for oHDF (p < 0.0001); oHDF resulted in a lower dialysate consumption (8.0% less) and a slightly increased dialysis dose (Kt/V 3.5% higher) compared to HD. oHDF with the investigated automatic functions offers substantial savings in dialysate consumption without decreasing dialysis dose.

Equivalent continuous clearances EKR and stdK in incremental haemodialysis

BACKGROUND

Many haemodialysis patients have residual renal function (RRF), which as such is insufficient to maintain satisfactory quality of life but reduces the demands of treatment and improves outcomes. In incremental dialysis, the dose is adjusted according to RRF, but how should it be done?

METHODS

Urea generation rate (G) and distribution volume (V) were determined by the double-pool urea kinetic model in 225 haemodialysis sessions of 30 patients. The effect of different degrees of RRF on equivalent renal urea clearance (EKR), standard urea clearance (stdK) and urea concentrations and required treatment times to achieve the HEMO study standard dose equivalent EKR and stdK targets were studied by computer simulations.

RESULTS

Ignoring RRF leads to underestimation of EKR, stdK, urea generation rate and protein equivalent of nitrogen appearance. Both EKR and stdK increase linearly with renal urea clearance (Kr). The HEMO standard dose equivalent EKRc is 13.8 mL/min/40 L and stdK/V 2.29 /wk (9.1 mL/min/40 L). The required treatment time to achieve the HEMO-equivalent targets has an almost linear inverse relationship to Kr. If the HEMO standard dose equivalent EKR or stdK is used as the target, RRF may replace several hours of weekly dialysis treatment time. stdK appreciates RRF more than EKR.

CONCLUSIONS

RRF is included in the original EKR and stdK concepts. EKR and stdK--determined by kinetic modelling--are promising measures of adequacy in incremental dialysis.

Modeled urea distribution volume and mortality in the HEMO Study

BACKGROUND AND OBJECTIVES

In the Hemodialysis (HEMO) Study, observed small decreases in achieved equilibrated Kt/V(urea) were noncausally associated with markedly increased mortality. Here we examine the association of mortality with modeled volume (V(m)), the denominator of equilibrated Kt/V(urea).

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

Parameters derived from modeled urea kinetics (including V(m)) and blood pressure (BP) were obtained monthly in 1846 patients. Case mix-adjusted time-dependent Cox regressions were used to relate the relative mortality hazard at each time point to V(m) and to the change in V(m) over the preceding 6 months. Mixed effects models were used to relate V(m) to changes in intradialytic systolic BP and to other factors at each follow-up visit.

RESULTS

Mortality was associated with V(m) and change in V(m) over the preceding 6 months. The association between change in V(m) and mortality was independent of vascular access complications. In contrast, mortality was inversely associated with V calculated from anthropometric measurements (V(ant)). In case mix-adjusted analysis using V(m) as a time-dependent covariate, the association of mortality with V(m) strengthened after statistical adjustment for V(ant). After adjustment for V(ant), higher V(m) was associated with slightly smaller reductions in intradialytic systolic BP and with risk factors for mortality including recent hospitalization and reductions in serum albumin concentration and body weight.

CONCLUSIONS

An increase in V(m) is a marker for illness and mortality risk in hemodialysis patients.

Can rescaling dose of dialysis to body surface area in the HEMO study explain the different responses to dose in women versus men?

BACKGROUND AND OBJECTIVES

In the Hemodialysis (HEMO) Study, the lower death rate in women but not in men assigned to the higher dose (Kt/V) could have resulted from use of "V" as the normalizing factor, since women have a lower anthropometric V per unit of surface area (V/SA) than men.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

The effect of Kt/V on mortality was re-examined after normalizing for surface area and expressing dose as surface area normalized standard Kt/V (SAn-stdKt/V).

RESULTS

Both men and women in the high-dose group received approximately 16% more dialysis (when expressed as SAn-stdKt/V) than the controls. SAn-stdKt/V clustered into three levels: 2.14/wk for conventional dose women, 2.44/wk for conventional dose men or 2.46/wk for high-dose women, and 2.80/wk for high-dose men. V/SA was associated with the effect of dose assignment on the risk of death; above 20 L/m(2), the mortality hazard ratio = 1.23 (0.99 to 1.53); below 20 L/m(2), hazard ratio = 0.78 (0.65 to 0.95), P = 0.002. Within gender, V/SA did not modify the effect of dose on mortality.

CONCLUSIONS

When normalized to body surface area rather than V, the dose of dialysis in women in the HEMO Study was substantially lower than in men. The lowest surface-area-normalized dose was received by women randomized to the conventional dose arm, possibly explaining the sex-specific response to dialysis dose. Results are consistent with the hypothesis that when dialysis dose is expressed as Kt/V, women, due to their lower V/SA ratio, require a higher amount than men.

Dose of dialysis based on body surface area is markedly less in younger children than in older adolescents

BACKGROUND AND OBSERVATIONS: The current denominator for dosing dialysis is the urea distribution volume (V). Normalizing Kt/V to body surface area (S) has been proposed, but the implications of doing this in children have not been examined.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

Dialysis dose given to children and adolescents was calculated in terms of conventional V-based scaling and surface-area-normalized standard Kt/V (SAN-stdKt/V) calculated as stdKt/V x (Vant/S)/17.5, where Vant was an anthropometric estimate of V calculated using the Morgenstern equation. Formal 2-pool modeling was used to compute all dialysis adequacy outputs.

RESULTS

In 34 children (11 girls, 23 boys) dialyzed 3 times a week, age range 1.4 to 18 years, the mean delivered equilibrated Kt/V (eKt/V) was 1.40, and the mean stdKt/V was 2.49, both of which tended to be higher in younger children. The ratio of Vant to S was 15.6 +/- 2.69 and was strongly associated with age between ages 2 and 16. SAN-stdKt/V averaged 2.21 and was strongly correlated with age between ages 2 and 16. If one considers a desired target for SAN-stdKt/V to be 2.45, all children less than 10 years of age were below target, despite having relatively high values of eKt/V and stdKt/V.

CONCLUSIONS

If a surface-area-based denominator were to be adopted for dialysis dosing, most children under 10 years of age would receive markedly less dialysis than adolescent patients and would require 6- to 8-hour hemodialysis sessions or, for the youngest children, treatments given more frequently than 3 times/wk.

Surface-area-normalized Kt/V: a method of rescaling dialysis dose to body surface area-implications for different-size patients by gender

Dialysis is measured as Kt/V, which scales the dose (Kt) to body water content (V). Scaling dialysis dose to body surface area (S(dub)) has been advocated, but the implications of such rescaling have not been examined. We developed a method of rescaling measured Kt/V to S(dub) and studied the effect of such alternative scaling on the minimum adequacy values that might then be applied in male and female patients of varying body size. We examined anthropometric estimates of V and S (Watson vs. Dubois estimates) in 1765 patients enrolled in the HEMO study after excluding patients with amputations. An S-normalized target stdKt/V was defined, and an adequacy ratio (R) was computed for each patient as R = D/N where D = delivered stdKt/V (calculated using the Gotch-Leypoldt equation for stdKt/V) and N = the S-normalized minimum target value. In the HEMO data set, we determined the extent to which baseline (prerandomization) stdKt/V values would have exceeded such an S-based minimum target stdKt/V. The median V(wat):S(dub) ratios were significantly higher in men (21.34) than in women (18.50). The average of these (20) was used to normalize the current suggested minimally adequate value (stdKt/V > or = 2.0/week) to the S-normalized target value (stdKt/S > or = 40 L/M(2)), assuming that average modeled V = average anthropometric V. To achieve this S-normalized target, the required single-pool (sp) Kt/V was always higher in women than in men at any level of body size. For small patients (V(wat) = 25L), required stdKt/V values were 2.05 and 2.21/week for men and women, respectively, corresponding to spKt/V values of 1.31 and 1.52/session. On the other hand, large (V(wat) = 50L) male patients would need spKt/V values of only 1.0/session. Prerandomization baseline dialysis sessions in the HEMO study were found to meet such a new S-based standard in almost all (766/773) men and in 885/992 women. An analysis of scaling dose to anthropometrically estimated liver size (L) showed similar gender ratios for V(wat):L and V(wat):S(dub), providing a potential physiologic explanation underpinning S-based scaling. S-based scaling of the dialysis dose would require considerably higher doses in small patients and in women, and would allow somewhat lower doses in larger male patients. Current dialysis practice would largely meet such an S-based adequacy standard if the dose were normalized to a V(wat):S(dub) ratio of 20.

Development and Validation of Bioimpedance Analysis Prediction Equations for Dry Weight in Hemodialysis Patients

BACKGROUND

Accurate assessment of hydration status and specification of dry weight (DW) are major problems in the clinical treatment of hemodialysis (HD) patients. Bioelectrical impedance analysis (BIA) has been recognized as a noninvasive and simple technique for the determination of DW in HD patients.

DESIGN, SETTING, PARTICIPANTS, AND MEASUREMENTS

This study was designed to develop and validate BIA prediction equations for DW in HD patients. It included white adults (1540 disease-free adults with normal body mass index [BMI] and 456 prevalent and 27 incident HD patients). All participants underwent at least one single-frequency BIA measurement (800 muA and 50 kHz alternating sinusoidal current with a standard tetrapolar technique). The BIA variable measured was resistance (R). Data of 1463 (95% of the cohort) disease-free individuals with normal BMI (prediction sample) were used to establish best-fitting BIA prediction equations of body weight. The latter were cross-validated in the residual 5% subset (77 individuals) of the same cohort (validation sample).

RESULTS

Multiple regression analysis showed a significant relationship among body weight, R, age, and height in 739 men (R(2) = 0.82, P < 0.0001) and among body weight, R, and height in 724 women (R(2) = 0.68, P < 0.0001) in the prediction sample. The Bland Altman analysis showed a mean difference between predicted and measured body weight of 0.3 +/- 1.0 kg (95% confidence interval +/- 2.0 kg) in the validation sample. The BIA prediction equations that were obtained in disease-free individuals with normal BMI were applied to a cohort of 456 prevalent HD patients: The mean difference between achieved and estimated DW was 0.1 +/- 1.0 kg (P = 0.53) in men and -0.3 +/- 1.0 (P = 0.76) in women. Finally, BIA prediction equations were tested in a cohort of 27 incident HD patients. The mean difference between predicted and achieved DW was -0.6 +/- 1.0 kg (P = 0.76) in men and 0.6 +/- 1.0 (P = 0.50) in women.

CONCLUSIONS

This study was able to develop and validate BIA prediction equations for DW in HD patients. They seem to be a promising tool; however, they still need external validation.

Evaluating a new method to judge dialysis treatment using online measurements of ionic clearance

New technology now supports direct online measurements of total dialysis dose per treatment, Kt. An outcome-based, nonlinear method for estimating target Kt in terms of ionic clearance measurements and body surface area (BSA) has been described recently. This is a validation study of the new method that evaluates the relationship between the (actual Kt-target Kt) difference and death risk. Patients with Kt measurements during March 2004 were identified (N=59,644). Target Kt was determined for each patient using the new method. Patients were then grouped by (actual Kt-target Kt) decile. They were also grouped by (actual URR-target URR) decile. Cox analysis-based risk profiles were constructed using those groupings. The (actual Kt-target Kt) difference profiles suggested improving death risk as Kt increased from below target to equal target. Risk ratios then flattened and remained so until (actual Kt-target Kt) reached the highest decile at which it appeared to improve, suggesting a possible biphasic profile. The (URR-target URR) risk profile was U-shaped. Death risk was related to the difference between the actual Kt and a target Kt value selected using the new nonlinear method. The method is therefore valid for prescribing and monitoring hemodialysis treatment.

Downloadable computer models for renal replacement therapy

Mathematical models can predict solute clearances and solute concentrations during renal replacement therapy. At present, however, most nephrologists cannot use these models because they require mathematical software. In this report, we describe models of solute transport by convection and diffusion adapted to run on the commonly available software program Excel for Macintosh computers and PCs running Windows. Two programs have been created that can be downloaded from http://www.stanford.edu/~twmeyer/ or http://dev.satellitehealth.com/research/journal.asp. The first, called 'Dr Addis Clearance Calculator', calculates clearance values from inputs including the blood flow Q(b), the hematocrit, the ultrafiltration rate Q(f), the dialysate flow rate Q(d), the reflection coefficient sigma and the mass transfer area coefficient K(o)A for the solute of interest, and the free fraction f if the solute is protein bound. Solute concentration profiles along the length of the artificial kidney are displayed graphically. The second program, called 'Dr Coplon Dialysis Simulator', calculates plasma solute concentrations from the clearance values obtained by the first program and from additional input values including the number of treatments per week, the duration of the treatments, and the solute's production rate and volumes of distribution. The program calculates the time-averaged solute concentration and provides a graphic display of the solute concentration profile through a week-long interval.

Estimate of body water compartments and of body composition in maintenance hemodialysis patients: comparison of single and multifrequency bioimpedance analysis

OBJECTIVE

The goal of this study was to compare the adequacy of single and multifrequency bioimpedance analysis (BIA) to evaluate body water compartments, body composition, and nutritional status in maintenance hemodialysis patients.

DESIGN

Cross-sectional study.

SETTING

University-based hemodialysis unit.

PATIENTS

Nineteen patients (12 male, 7 female), ages 28 to 82 years (mean, 58.9), treated with maintenance hemodialysis (MHD) for 0.5 to 15 years (mean, 7.3).

INTERVENTION

This was a noninterventional study. Patients gave their informed consent to the diagnostic procedures performed.

MAIN OUTCOME MEASURES

Total body water (TBW), extracellular water (ECW), fat-free mass (FFM), and body cell mass (BCM) volumes were estimated with single-frequency (sf BIA) and multifrequency (mf BIA) plethysmographs before and after a midweek dialytic session. Predialysis TBW also was estimated from anthropometric data (e TBW). Serum albumin, prealbumin and myoglobin, and creatinine index were determined as indicators of nutritional status and muscle mass.

RESULTS

Sf BIA and mf BIA gave very similar results for TBW volumes. A high linear correlation was also found between e TBW values and both sf TBW and mf TBW; however, a statistically significant difference was found between e TBW and sf and mf TBW. Sf BIA and mf BIA gave quite different results for ECW, particularly when measured predialysis. The results obtained for FFM indicate a poor agreement between sf and mf BIA. The agreement was better when FFM was measured postdialysis. The values of BCM, either measured predialysis or postdialysis, indicate a significant difference between sf and mf BIA. FFM and BCM estimated with mf BIA had a closer correlation with creatinine index than sf BIA. mf BCM had also a higher correlation with serum myoglobin, which is produced by muscle cells.

CONCLUSIONS

TBW can be estimated with enough confidence from either sf or mf BIA at any time. On the contrary, the results of ECW are significantly different with sf and mf BIA when measured predialysis. Thus, it seems more convenient to perform BIA after dialysis, in particular when assessing the "ideal" body weight. The measurements of FFM and BCM, obtained with either sf or mf BIA, are correlated with different indicators of nutritional status. In particular, mf BCM seems more appropriate than sf BCM for estimating muscle mass.

Resistance to intercompartmental mass transfer limits β2-microglobulin removal by post-dilution hemodiafiltration

Although clearance of beta(2)-microglobulin is greater with hemodiafiltration than with high-flux hemodialysis, beta(2)-microglobulin concentrations after long-term hemodiafiltration are only slightly less than those obtained with high-flux hemodialysis. Resistance to beta(2)-microglobulin transfer between body compartments could explain this observation. beta(2)-Microglobulin kinetics were determined in patients receiving on-line post-dilution hemodiafiltration for 4 h with 18 l of filtration. Plasma beta(2)-microglobulin concentrations were measured during and for 2 h following hemodiafiltration and immediately before the next treatment. The filter clearance of beta(2)-microglobulin was determined from arterial and venous concentrations. The beta(2)-microglobulin generation rate was calculated from the change in the plasma concentration between treatments. The intercompartmental clearance was obtained by fitting the observed concentrations to a two-compartment, variable volume model. The plasma clearance of beta(2)-microglobulin by the filter was 73 +/- 2 ml/min. Plasma beta(2)-microglobulin concentrations decreased by 68 +/- 2% from pre- to post-treatment (27.1 +/- 2.2-8.5 +/- 0.7 mg/l), but rebounded by 32+/-3% over the next 90 min. The generation rate of beta(2)-microglobulin was 0.136 +/- 0.008 mg/min. The model fit yielded an intercompartmental clearance of 82 +/- 7 ml/min and a volume of distribution of 10.2 +/- 0.6 l, corresponding to 14.3 +/- 0.7% of body weight. Hemodiafiltration provides a beta(2)-microglobulin clearance of similar magnitude to the intercompartmental clearance within the body. As a result, intercompartmental mass transfer limits beta(2)-microglobulin removal by hemodiafiltration. This finding suggests that alternative strategies, such as increased treatment times or frequency of treatment, are needed to further reduce plasma beta(2)-microglobulin concentrations.

Double target comparison of blood-side methods for measuring the hemodialysis dose

BACKGROUND

Despite the fact that urea kinetic modelling has been successfully applied to quantify the hemodialysis since the beginning of the 1980s, there is not a consensus yet concerning which is the most proper dialysis dose index and the method for calculating it. In this work, we propose that a combined measurement of the dialysis dose from two complementary perspectives of the removal process should provide a more complete description of dialysis than a measurement alone. This hypothesis is reviewed and the measuring methods are compared.

METHODS

A cross-sectional randomized clinical study over 98 stable ESRD patients submitted to thrice-weekly hemodialysis was carried out with the aim of comparing 16 blood-side methods for measuring the hemodialysis dose from patient and dialyzer perspectives. The availability of urea rebound measurements and computational resources have been taken into account.

RESULTS

The outcomes point to four novel blood-side methods as the most accurate for measuring the effective dialysis system Kt/V (mKt/V) in clinical conditions. Their limits of agreement (mean +/- 2.SD) range from 1.93 +/- 2.09% for a non-iterative method without the urea rebound measurement (BUN3) to -0.08 +/- 0.58% for an iterative method with BUN3. The best non-iterative blood-side method for measuring the equilibrated Kt/V (eKt/V) is the second generation formula of Daugirdas (-2.42 +/- 1.05%) when BUN3 is available and the rate equation of Daugirdas and Schneditz (-1.74 +/- 7.91%) when BUN3 is not available. The difference mKt/V-eKt/V is significant and positive, and increases with the dialysis dose in a personalized manner.

CONCLUSION

We have confirmed the arguments that support the hypothesis of the study. The best blood-side methods for the combined measurement of dialysis dose as a function of the available resources have been determined.

Are nutritional status indicators associated with mortality in the Hemodialysis (HEMO) Study?

BACKGROUND

The purpose of this study was to determine if indicators of nutritional status were associated with subsequent mortality in hemodialysis patients.

METHODS

Twelve selected nutrition indicators were measured prior to randomization in the Mortality and Morbidity in Hemodialysis (HEMO) Study. Relative risks (RR) of mortality were assessed at <6 months and >6 months of follow-up using Cox regression after controlling for case mix, comorbidity, and treatment assignment (high vs. standard Kt/V and high vs. low membrane flux).

RESULTS

Low values of most nutritional status indicators were associated with increased RR of mortality. RRs were greatest over the short term (<6 months) and diminished with increasing follow-up (>6 months). Increases in body mass index (BMI) at lower levels (e.g., < or =25 kg/m(2)) and increases in serum albumin at any level were associated with reduced short-term RR, even after adjusting for case mix, treatment assignment, and for the joint effects of equilibrated normalized protein catabolic rate, total cholesterol, and serum creatinine. For >6 months' follow-up, increases in values among those with lower levels of BMI and serum albumin (< or =3.635 g/dL) and increases in all serum creatinine levels were associated with lower RR.

CONCLUSION

Nutrition indicators are associated with subsequent mortality in a time-dependent manner, with greatest effects at <6 months of follow-up. The RR for these indicators may also vary within different ranges of values.

Dialysis dose as a determinant of adequacy

The intent-to-treat analyses of all patients in the HEMO trial suggested that increases in dose of dialysis as measured by urea Kt/V were of marginal or no benefit when dialysis was provided in a 3 times/wk schedule. The as-treated analysis in the HEMO trial pointed to markedly increased mortality when the delivered dose decreased even slightly below the targeted dose, evidence of a dose-targeting bias. The intent-to-treat HEMO study results suggested a potential interaction between sex and the dose-mortality relationship, and this also has been found in some cross-sectional studies, the cause of which remains unexplained. Whether dialysis dose should continue to be targeted based on urea distribution volume (V), or targeted to a body size measure that is a lower power of body weight (such as body surface area), remains an open question. The lack of benefit of increasing the dialysis dose in a 3 times/wk setting is more understandable if one looks at measures of equivalent continuous solute removal, such as the standard Kt/V. Differences in standard Kt/V in the 2 dose arms of the HEMO trial, for example, were only about 15%. Without going into removal of very large solutes (eg, beta-2-microglobulin), which is discussed elsewhere in this issue, or protein-bound uremic solutes, the only way to provide significantly more dialysis dose may be to move to more frequent dialysis schedules and/or to very long session lengths. Here, benefit may be related as much to better control of salt and water balance as to better removal of uremic toxins.