Catabolism in critical illness: estimation from urea nitrogen appearance and creatinine production during continuous renal replacement therapy.

Thirty-eight intensive care unit (ICU) patients (26 men and 12 women with a mean age of 57.0 +/- 16.6 years) with acute renal failure (ARF) treated by venovenous continuous renal replacement therapy (CRRT) were evaluated while in relatively steady metabolic control. Twenty-seven were undergoing continuous venovenous hemodialysis, nine were undergoing continuous venovenous hemodiafiltration, and two were undergoing continuous venovenous hemofiltration. Periods of analysis varied between 24 and 408 hours (mean duration, 82.7 +/- 70.6 hours; median, 72 hours). Their mean Acute Physiology and Chronic Health Evaluation II (APACHE II) score within 24 hours of admission to the ICU was 21.3 +/- 6.3 and survival rate was 31.6%. Urea nitrogen and creatinine concentrations were determined every 6 to 12 hours in both serum (Cun and Cc, respectively) and effluent (spent dialysate and/or ultrafiltrate). The mean effluent rate was 1,472 +/- 580 mL/h and blood flow rate, 166 +/- 32 mL/min. Urine was collected daily for urea nitrogen and creatinine measurement. Urea nitrogen appearance rate (UnA) and creatinine production rate (Pc), calculated from urea nitrogen (UnMR) and creatinine mass removal (CMR) from both the effluent and the urine, using Garred mass balance equations and the Forbes-Bruining formula, allowed normalized protein catabolic rate (nPCR) and estimates of lean body mass (LBM) to be derived. Creatinine metabolic degradation rate (Dc), estimated by the Mitch formula, was included in the calculation. The lowest body weight recorded during the study period was considered as dry weight (BW). The creatinine index (CI) was also obtained. For each parameter, the results are presented as mean, median, and range values: UnMRe (from effluent), 13.6 +/- 7.2, 12.5, 1.6 to 32.6 mg/min; UnMRu (from urine), 0.13 +/- 0.40, 0, 0 to 2.30 mg/min; UnA, 13.6 +/- 7.0, 12.5, 3.8 to 32.1 mg/min; nPCR, 1.75 +/- 0.82, 1.60, 0.61 to 4.23 g/kg/d; CMRe (from effluent), 942.0 +/- 362.3, 918.0, 211.2 to 1,641.6 mg/d; CMRu (from urine), 44.4 +/- 138.8, 0, 0 to 698.5 mg/d; Dc, 94.6 +/- 49.9, 81.9, 31.0 to 294.1 mg/d; Pc total, 1,067.1 +/- 409.7, 1,053.7, 261.5 to 1,988.2 mg/d; LBM, 38.3 +/- 11.9, 37.9, 15.0 to 65.0 kg; LBM/BW ratio, 49.5% +/- 14.0%, 50.3%, 22.5% to 86.0%; and CI, 13.7 +/- 4.7, 14.2, 4.1 to 25.8 mg/kg/d. When Pc was estimated from the Cockcroft-Gault equations (as Pc'), the mean value for Pc and Pc' was similar (1,067.1 +/- 409.7 v 1,284.9 +/- 484.1 mg/d), but there were relatively large differences for the majority of cases. A positive correlation was observed between UnA and Pc (R = 0.42). Serum albumin and LBM/BW correlated poorly (R = 0.20). Outcome was weakly related to UnA and to nPCR (R = 0.29 and R = 0.31, respectively). Urea nitrogen appearance appears widely variable in critically ill ARF patients. This simple approach can provide useful information for an easy estimate of net protein catabolism in critically ill patients with ARF undergoing CRRT.

Evaluation of high-flux hemodiafiltration efficiency using an on-line urea monitor.

On-line urea monitoring of the effluent dialysate offers a real-time assessment of dialysis efficiency and metabolic/nutritional characteristics of hemodialysis patients. Quantitative parameters were evaluated by dialysate urea kinetic modeling (DUKM) with an on-line urea sensor in 23 patients treated by high-flux hemodiafiltration (HDF) (215 sessions of 210 to 240 minutes with a mean blood flow rate of 367 +/- 44 mL/min). Overall, the mean effective Kt/V was 1.52 +/- 0.29, the urea mass removed (22.8 +/- 5.5 g/session or 814 +/- 198 mmol/session), the solute removal index (SRI) 73% +/- 6.1%, and the mean normalized protein catabolic rate (nPCR), 1.15 +/- 0.31 g/kg/day. Blood urea kinetic modeling (BUKM), based on pre- and postsession urea concentrations, using equations from Daugirdas and Garred to calculate equilibrated Kt/V and nPCR, respectively, were in good agreement with DUKM, the differences observed appearing not clinically relevant. The variability of evaluated parameters was verified over consecutive sessions for a mean period of 3 weeks in the entire group. Mean variation in Kt/V was 8%; in urea mass removal, 18%; and in nPCR, 18%. When assessed over 1 week in a subgroup of 13 patients, Kt/V and PCR remained relatively stable, and urea mass removal per- and postsession declined from 23.5 +/- 8.0 g (840 +/- 285 mmol) to 18.7 +/- 6.3 g (667 +/- 225 mmol) from the first to the third session of the week, most likely as a consequence of interdialytic intervals. Predialysis urea concentrations followed the same trend. In the current study, DUKM with on-line urea sensor has confirmed that HDF is a highly efficient renal replacement modality; the variability observed in quantitative parameters supports a need for frequent adequacy monitoring. On-line urea monitoring of effluent dialysate is a simple device that provides the opportunity to tailor treatment to patient needs.

Urea kinetic modeling with a prototype urea sensor in the spent dialysate stream.

The authors have previously demonstrated the feasibility and accuracy of urea kinetic modeling (UKM) based on monitoring urea concentration in the spent dialysate stream (SDS) throughout the hemodialysis (HD) session. They describe here a prototype urea sensor for this purpose and initial experience with HD patients. The sensor is based on ammonium ion and reference electrodes housed in a cell through which the entire SDS passes. The two electrode tips are bathed in urease solution on one side of a dialysis membrane; the SDS flows along the adjacent side. Urea diffusing across the membrane from the SDS is converted by the urease into ammonium ion, which is measured by the electrode pair. For evaluation, the prototype flowthrough urea sensor was installed in the SDS of a Cobe Centry 3 HD machine for 36 HD sessions. Independent measurement demonstrated a linear relationship between mv output of the sensor and logarithm of SDS urea concentration. The use of SDS urea concentration time profiles obtained with this sensor to obtain accurate values of patient protein catabolic rate (PCR) and KT/V is illustrated. Incorporation of urea sensors such as this prototype into HD machines, will permit complete automation of UKM in the near future.

Protein catabolic rate determination from a single measurement of dialyzed urea.

Protein catabolic rate (PCR, in g protein/kg/day) for anuric patients can be accurately determined without blood sampling by equating urea generation over 7 days to the urea dialyzed in the three dialyses of this period as measured by partial dialysate collection (PDC) or with a urea monitor. The feasibility of determining the week's dialyzed urea from measurement of urea dialyzed in a single session, obviating the need to monitor three consecutive dialyses, was examined in a steady-state simulation of 540 anuric patients spanning the full range of dialysis parameters. It was found that the first, midweek, and last dialyses account for nearly constant fractions (37.9, 32.1, and 30.0%, respectively) of the week's urea removal, leading to equations of the form: PCR = CU/BW + 0.17 where U is the grams of urea dialyzed in the first, midweek, or final dialysis of the week, C = 2.45, 2.89, or 3.10, respectively, and BW is the patient's dry weight in kilograms. These equations were tested on 1312 weeks of PDC data gathered in 42 dialysis patients. Using the midweek U resulted in a mean absolute error in PCR < 0.05 g/kg/day when compared to PCR determined using all three of the week's U values.

Simple equations for protein catabolic rate determination from pre dialysis and post dialysis blood urea nitrogen.

Several simple equations exist for Kt/V determination from pre dialysis (Cpre) and post dialysis (Cpost) blood urea. However, comparable equations have not been available for calculation of protein catabolic rate (PCR), an essential parameter for assessing patient status. Three simple formulas for PCR determination were developed from the urea mass balance equation for an anuric patient in protein steady state receiving thrice weekly dialysis. The simplest formula, PCR = 0.0076 [Kt/V] [Cpre + Cpost] + 0.17 relates PCR (in g protein/kg/day) to Kt/V and pre and post dialysis blood urea nitrogen measurements (in mg urea nitrogen/dl) for the midweek session. When tested for 540 simulated patients spanning a range of Kt/V (0.6-1.6); PCR (0.6-1.6 g/kg/day); dialysis duration t (2-4 hrs) and interdialytic weight gain expressed as a percentage of dry body weight gained daily (0-4%), this equation yielded a maximum error of less than +/- 5%, within the accuracy generally required for clinical needs. A more accurate formula, [formula: see text] where Clm is the logarithmic mean of Cpre and Cpost, gave maximum errors in PCR estimation for the same 540 simulated patients of less than +/- 0.6%. Both formulas require a precise value of Kt/V. The equation below incorporates a very accurate simple Kt/V equation recently published by the authors, allowing PCR to be expressed in terms of Cpre, the ratio of Cpost to Cpre (R), the ratio of session ultrafiltration volume (delta BW) to urea distribution volume (V), and dialysis time (t, in min). [formula: see text] This equation was accurate to within a maximum error of +/- 1% for the simulated patient group. These equations allow simple and accurate patient PCR determination, and should be used in conjunction with a simple formula for accurate Kt/V determination to guide end-stage renal failure patient therapy.

Simple Kt/V formulas based on urea mass balance theory.

The ratio Kt/V (K is patient clearance, t dialysis time, V urea space) has become the standard measure of dialysis adequacy. In this article simple Kt/V equations are developed theoretically from the urea mass balance equation. Two approximations lead to the most precise equation: [formula: see text] where R is the post to pre dialysis urea ratio, BW/V is the amount of fluid removed during dialysis (delta BW) expressed as a fraction of urea distribution space (V) at dry body weight (BW), and t is dialysis length in hours. A second equation arises with V approximated as 58% of BW. One further approximation leads to a simpler but slightly less precise Kt/V formula: [formula: see text] These and earlier published equations were tested with two sets of data: 1) 49 sessions involving 17 patients on maintenance dialysis and 2) 540 computer simulations spanning all likely values of Kt/V (0.6-1.6), protein catabolic rate (0.6-1.6), interdialytic weight gain (0-4% of BW per day) and dialysis session length (2-4 hr). The most precise formula (upper equation above) had a maximum error of 0.031 and 0.035 Kt/V units for the clinical and simulated data, respectively, whereas the lower equation was slightly less accurate with maximum Kt/V errors of 0.079 and 0.081, respectively. The proposed Kt/V equations are considerably more accurate than previously published formulas.

On-line dialysis quantification in acutely ill patients: preliminary clinical experience with a multipurpose urea sensor monitoring device.

Direct dialysis quantification offers several advantages compared with conventional blood urea kinetic modeling, and monitoring urea concentration in the effluent dialysate with an on-line urea sensor is a practical approach. Such a monitoring device seems desirable in the short-term dialysis setting to optimize and personalize both renal replacement therapy and nutritional support of acutely ill patients. We designed a urea monitoring device consisting of a urea sensor, a multichannel hydraulic circuit, and a PC microcomputer. The sensor determines urea from catalysis of its hydrolysis by urease in liquid solution during neutral conditions. Hydrolysis of urea produces NH4+, and creates an electrical potential difference between two electrodes. Each concentration determination of urea is the average value of 10 measurements; samples are diverted and measured every 7 min. Laboratory calibration of the urea sensor has demonstrated linearity over the range 2-35 mmol/L. Urea monitoring was performed throughout the treatment course, either on the effluent dialysate or ultrafiltrate in seven acutely ill patients treated by either hemofiltration (n=5) or hemodiafiltration (n=2). The slope of the concentration of urea in the effluent over time was used to calculate an index of the dialysis dose delivered (Kt/V), urea mass removal, and protein catabolic rate. In addition, samples of the effluent were drawn every 21 min, and sent to the central laboratory for measurement of urea concentrations using an autoanalyzer. Kt/V values also were calculated with Garred's equation using pre and post session concentrations of urea in blood. Concentrations of urea in the effluent determined by the urea sensor were found to be very close to those obtained from the central laboratory over a wide range of values (3 to 42 mmol/L). In addition, Kt/V values for both hemofiltration and hemodiafiltration, when calculated with concentrations of urea in the effluent obtained by the urea sensor, did not significantly differ from Kt/V values obtained from the laboratory concentrations of urea in the effluent. On-line urea sensor monitoring of the effluent suppresses the cumbersome task of total effluent collection, and the complexity of urea kinetic analysis. The multipurpose prototype described here represents a new, simple, and direct assessment of dialysis dose and protein nutritional status of acutely ill patients, and is suitable for various modalities.

Direct determination of blood recirculation rate in hemodialysis by a conductivity method.

Blood recirculation is one of the key factors of decreasing dialysis efficiency. Determination of recirculation rate (R) is necessary to optimize effective dialysis delivery and to monitor vascular access function. R can be directly measured by a conductivity method in paired filtration dialysis (PFD), a double-compartment hemodiafiltration system that permits direct access to plasma water via the ultrafiltration stream. Measurement of R, in this system, involves the first of two conductivity sensors integrated in a urea monitor (UMS, BelIco-Sorin, Mirandola, Italy), and two saline injections. The rise in conductivity (deltaC1) induced by a 2.7 ml bolus of hypertonic saline 20% (mg/dl) in the arterial line serves for calibration, and is followed by an equivalent injection into the venous line, giving rise to deltaC2. The ratio deltaC2/deltaC1 equals R. A comparison between R values obtained with this method and with the low-flow technique in 31 chronic dialysis patients during 138 PFD sessions is reported. Mean R+/-SD by the conductivity method was 5.1+/-2.0 and 5.7+/-2.0% after 65 and 155 minutes of PFD (correlation coefficient, r = 0.75), whereas it was 6.4+/-4.9% and 5.5+/-4.6% after 30 sec of low blood pump flow for urea and creatinine markers, respectively (r = 0.35). After 120 sec of low flow, mean R increased to 9.0+/-5.1 and 8.8+/-4.6% for urea and creatinine, respectively (r = 0.45). Considerable discrepancies were found in R values measured simultaneously with the two blood markers. Statistically significant differences were found between the two measurement modalities (blood-side and conductivity); the correlation coefficients (r) varied between 0.28 and 0.41. The observed differences in mean R results do not seem considerable from a clinical perspective. The best agreement between blood-side and conductivity R measurements was obtained with Rcreat after 30 sec of low flow. Overall, a wider distribution was found in R values from blood-side determinations, most likely consequent to variability in the dosing method. The conductivity method appears more accurate and simple in assessing total R, and can be readily automated and integrated into the dialysis machine. The authors, therefore, recommend evaluation of R using methods not based on chemical blood concentration values.

Urea kinetic modelling by partial dialysate collection.

Conventional urea kinetic modelling (UKM) has several drawbacks, in particular the complexity of the required calculations and the need for accurate values of parameters which are difficult to measure, such as dialyzer clearance and blood flow. An alternative method of UKM is proposed based on collecting a small fraction of spent dialysate flow for 3 consecutive dialyses. Application of a urea mass balance to the 7 day period permits neglecting changes in body urea stores. Thus no blood sampling is required for most patients. The required calculations are simple and straightforward. The partial dialysate collection (PDC) method was compared to conventional UKM in a 3 patient, 15 week study. Protein catabolic rate (PCR) from PDC was a smooth curve and consistent with dietary estimation for each patient. Conventional UKM gave variable PCR results which were 17-27% higher on average. This discrepancy was attributed to overestimation of dialyzer clearance. PDC was concluded to be more convenient and accurate than conventional UKM and therefore ideal for routine clinical use.

Dialysate-based kinetic modeling.

The focus of this review article is urea kinetic modeling based on the exploitation of concentration measurements in the spent dialysate stream. After a review of blood-based urea kinetic modeling, dialysate-based techniques are considered, beginning with dialysate collection techniques and their associated urea kinetic modeling equations. Partial dialysate collection methods and equations for the determination of protein catabolic rate based on a 7-day mass balance period are explored next. This is followed by a description of urea sensors and their application for dialysate-based modeling including the determination of protein catabolic rate, predialysis blood urea nitrogen (BUN), and KT/V. How the output of a urea sensor may allow the detection of significant changes in patient clearance during the course of dialysis is illustrated, as well as how double-pool urea kinetics may be accounted for in KT/V determination. Routine determination of patient lean body mass using creatinine kinetic modeling based on partial dialysate collection or a dialysate-based creatinine concentration sensor is demonstrated. Finally, the potential for complete automation of urea kinetic modeling in dialysis machines of the future is explored.

Mathematical modeling of erythropoietin therapy.

A simple mathematical model to describe hemoglobin (Hb) concentration response to recombinant human erythropoietin (EPO) therapy is proposed. The model is based on the assumption that Hb production increases linearly with EPO dose level. The resulting equation contains two patient parameters: 1) S, the proportionality constant between g Hb generated/L blood/wk and IU EPO administered/kg body weight/wk; and 2) tau, the patient erythrocyte lifetime in weeks. The model was applied retrospectively to 67 patients from the Canadian Erythropoietin Study, yielding an average error of 5.5 g/L between 27 measured and predicted Hb value pairs over the 27 week study. The model parameters, S (mean +/- SD = 0.015 +/- 0.005) and tau (14.0 +/- 4.1), varied over an order of magnitude. The model was also used to predict the EPO dose required to reach a target Hb of 110 g/L; the EPO requirements varied from 55 to 742 IU EPO/kg/wk (mean +/- SD = 225 +/- 124). It is recommended, based upon the model results, that EPO therapy be initiated at 3 IU EPO/kg/wk for each g/L difference between target and baseline Hb, with subsequent EPO dose adjustment guided by patient modeling.

[Urea kinetic model analysis in dialysis: from theory to practice]. / Analyse cinétique modélisée de l'urée en dialyse: de la théorie à la pratique.

Urea kinetic modeling (UKM) has been originally proposed by F. Gotch and J. Sargent as a guide to optimize and individualize the dialysis prescription in uremic patients. In a recent report, the US National Cooperative Dialysis Study group, showed the power of this approach compared to conventional methods. It was also concluded that dialysis adequacy could be predicted with a high success rate by determining three parameters; uremia represented by the Urea Time Averaged Concentration, dialysis dose defined as KT/V ratio, and dietary protein intake calculated from the urea generation rate. In spite of its potential usefulness, UKM has not gained clinical acceptance among nephrologists since it appeared always complicated due to its mathematical formulation or cumbersome to be used routinely in dialyzed patients. In this paper the authors will bring the reader from basic concepts to practical use of UKM to guide dialysis strategy. Limits of validity and difficulty in using this approach are also discussed. It is concluded that UKM by using very simple and basic parameters is a practical, and very powerful tool for assessing the dialysis adequacy and nutritional status of dialyzed patients. Direct quantification from dialysate (or ultrafiltrate) collection appeared a simple and precise method which should avoided multiple blood sampling.

Germicidal effectiveness of Dialox, a new stable peroxyacetic acid solution, in the re-use of high-flux dialysers.

In this study we evaluate the effectiveness of a newly available peroxyacetic acid solution (Dialox) as a disinfecting agent in the re-use of highly permeable dialysers. The germicidal properties of Dialox were tested in an in vitro trial on previously used haemodiafilters (HF80, Fresenius) highly contaminated with Pseudomonas aeruginosa, Mycobacterium smegmatis or sporulated Bacillus cereus. Complete freedom from bacterial contamination was observed 5 min after the reprocessing treatment on a Renatron reprocessing machine, using the currently marketed Dialox concentrate.

Protein catabolic rate over lean body mass ratio: a more rational approach to normalize the protein catabolic rate in dialysis patients.

Protein catabolic rate (PCR), equivalent to dietary protein intake in "stable" dialysis patients, is widely accepted as a marker of their protein nutritional status. PCR is usually established from urea generation rate using urea kinetic modeling (UKM), but the normalizing factor is still a matter of controversy. By convention, PCR is expressed in grams of protein degraded daily divided by the dry body weight (BW) (nPCRBW). To be valid, this implies that dry BW is close to ideal BW and that body composition is preserved with a lean body mass (LBM) over BW ratio near 0.73. Such conditions being infrequently found in dialysis patients, it has been proposed to normalize PCR to ideal BW or to total body water, but these correction factors are not really appropriate. A more rational approach would be to express PCR as the ratio of protein degraded to the kilograms of LBM (nPCRLBM), thus offering the main advantage of directly coupling PCR to changes in protein or nitrogen reserve. In this study, we developed a combined kinetic model of urea and creatinine applied to the midweek dialysis cycle in 66 end-stage renal disease (ESRD) patients. UKM provided Kt/V and PCR, whereas creatinine kinetic modeling (CKM) was used to calculate LBM. Thirty-four patients with a preserved LBM (LBM/dry BW ratio equal to or greater than 0.70; mean ratio, 0.81 +/- 0.11) and with a dry/ideal BW ratio of 1.01 +/- 0.16 had a mean PCR of 1.14 +/- 0.30 g/kg/24 h when normalized to BW (nPCRBW) and of 1.40 +/- 0.30 g/kg/24 h when normalized to LBM (nPCRLBM). In the 32 patients with a reduced LBM (LBM/dry BW ratio, below 0.70; mean ratio, 0.60 +/- 0.09) and dry/ideal BW ratio of 1.11 +/- 0.23, the mean nPCRBW was 0.99 +/- 0.31 g/kg/24 h, whereas nPCRLBM was 1.62 +/- 0.32 g/kg/24 h. For both subgroups, Kt/V was similar, with mean values of 1.76 +/- 0.34 and 1.69 +/- 0.27. Normalizing PCR to LBM offers a double benefit: it compensates for the error induced by abnormal body composition (eg, obese patients) and permits PCR to be adjusted for the decrease in LBM that occurs with age. We propose nPCRLBM as a more rational index to express PCR in dialysis patients.

Urea rebound and delivered Kt/V determination with a continuous urea sensor.

BACKGROUND: The recent introduction of urea sensors for dialysis monitoring has made possible new approaches to urea kinetic modelling. In this study we show how the equilibrated postdialysis urea concentration (Ceq) and Kt/V corrected for double-pool urea kinetics (Kt/Vdp) can be accurately determined using an on-line sensor providing a continuous measure of blood water urea. A modification of the Smye constant volume double-pool theory led to the following equations for Ceq and Kt/Vdp [formula: see text] where Cpre is the blood concentration measured at the start of dialysis, t is the length of the dialysis session (in min) and S(ex) is the constant slope of the blood urea logarithm concentration decline following development of the intercompartmental urea concentration gradient in the first 30-60 min of dialysis. METHODS: These equations were tested in 11 patients undergoing 165-240 min of paired filtration dialysis with continuous monitoring of blood urea concentration. Cpre was determined as the plateau concentration during a preliminary period of 15-20 min of slow isolated ultrafiltration. S(ex) was accurately determined from linear regression applied to the urea sensor data from the 80-min point to the end of dialysis. RESULTS: Ceq and Kt/Vdp determined from the above equations compared closely to values determined from 25-40 min of urea rebound monitoring with the urea sensor: 10.6 +/- 3.0 versus 10.8 +/- 2.7 mmol/l (mean +/- SD) for Ceq and 1.21 +/- 0.24 versus 1.18 +/- 0.20 for Kt/Vdp, compared to single-pool values of Kt/V = 1.34 +/- 0.23. CONCLUSION: This technique may be readily programmed into on-line urea monitors to provide current and extrapolated values of Ceq and Kt/Vdp from about the first hour of dialysis.

KT/V and protein catabolic rate determination from serial urea measurement in the dialysate effluent stream.

A bloodless technique of evaluating protein catabolic rate (PCR) and KT/V (K, clearance; T, dialysis time; V, urea distribution volume) in hemodialysis patients is presented based on serial measurement of urea in the dialysate effluent stream. PCR follows from equating urea generation and urea removal over a 7 day cycle, changes in body stores being comparatively negligible: PCR = 0.026 [U1 + U2 + U3]/BWdry + 0.17, where U1 is the amount of urea in mmol appearing in the dialysate for each session in the 7 day period. KT/V is obtained from the slope of the natural logarithm of spent dialysate urea concentration-time plot: KT/V = [- slope.T + 3.delta BW/BWdry]/[1 - 0.01786.T(hr], where delta BW = amount ultrafiltered in liters. The dialysate-based approach was validated and compared with conventional urea kinetic modeling (UKM) for 17 patients studied for three consecutive dialyses. The dialysate-based and UKM values of PCR agreed well when in vivo clearance values based on total dialysate collection were used for UKM. KT/V values agreed poorly on a session-by-session basis but were nearly equivalent when averaged for the three dialyses of the week. These findings lay the foundation for UKM automation with a urea sensor in the effluent dialysate stream.

Reuse of "highly permeable" dialyzers with peroxyacetic acid as sole cleansing and disinfecting agent.

In the past few years, dialyzer reuse has gained increased clinical acceptance. This has been due both to the availability of automated reconditioning machines and powerful chemical cleaning and disinfecting agents. In this study the authors evaluated the effectiveness of a newly available peroxyacetic acid solution (PAS) (Dialox) as the dual cleaning and disinfecting agent in the reuse of highly permeable dialyzers. An in vivo study was conducted with ten patients already involved in our center's reuse program using the Renatron reprocessing machine and PAS at various dilutions. One hundred forty dialyzers of three different brands and membrane types (HF80 used for hemodiafiltration [HDF], Filtral 16 used for hemodialysis [HD], and FH88 used for hemofiltration [HF]) were employed for a total of 1182 treatments, giving an average 8.4 uses per module. Significantly more uses were obtained with the HF80 and Filtral 16 dialyzers (9.7 and 9.4, respectively) than for the FH88 modules used by the HF patients (6.7 uses per module). Compromised cleaning by backfiltration due to the lack of a second dialysate port on the FH88 may be a possible explanation. Greater membrane plugging due to higher ultrafiltration rates in HF may be another factor. Patient variability was found to be another factor in dialyzer reuse. The cleaning effectiveness of various dilutions of PAS was also tested in this study. The number of uses achieved was not found to vary significantly with PAS strength; however, a greater frequency of second or third reprocessing was required with more dilute cleaning solution. The authors found the dilution achieved on the Renatron reprocessing machine using the currently marketed PAS concentrate to be the most cost effective.

Equations for the calculation of the protein catabolic rate from predialysis and postdialysis urea concentrations and residual renal clearance in stable hemodialysis patients.

Several simple equations exist for the calculation of K1/V from predialysis (Cpre) and postdialysis (Cpost) measurements of urea concentration. Analogous equations are needed for precise determination of patients protein catabolic rate (nPCR) from Cpre and Cpost. In this study we develop three simple nPCR equations from urea mass balance theory. The equations, which include a term for residual function, may be applied to any session of the week for patient dialyzed three times weekly who are in steady state with respect to dialysis dose and protein catabolism. The precision of each equation was tested with Cpre Cpost data obtained from steady state simulations of 540 patients without residual renal clearance (KR) and 972 simulated patients with significant residual KR. The simplest equation has the form: [formula: see text] where V is urea distribution volume and a and d are constants varying with session of the week. When compared to nPCR values calculated from formal urea kinetic modeling, the error determined with this formula never exceeded 5% for the midweek or final session. A more complicated equation of the form: [formula: see text] provided nPCR estimates with a maximum error < 1.3% for any dialysis session of the week and for KR up to 4 ml/min for a 70-kg patient. The only data required for the latter equation are Cpre, Cpost, length of dialysis session, volume ultrafiltered (delta BW), and an approximate value of the patient's urea distribution volume. The proposed equations permit nPCR to be calculated simply and accurately for stable patients dialyzed three times a week.

Creatinine kinetic modelling: a simple and reliable tool for the assessment of protein nutritional status in haemodialysis patients.

While the mathematical modelling of urea kinetics is in wide use for evaluating treatment adequacy and protein nutrition in dialysis patients, the kinetics of creatinine generation in dialysis patients has been relatively unexplored. In this study creatinine kinetic modelling as a clinical tool was investigated in a group of 90 patients treated by haemodialysis (n = 20), haemodiafiltration (60), haemofiltration (7), or biofiltration (3) over a 6-36-month period. A single pool model of creatinine kinetics was employed to obtain monthly values of creatinine distribution space and creatinine appearance rate. Extrarenal creatinine degradation rate, estimated using a clearance of 0.038 l/kg/24 h as suggested by Mitch and co-workers, was added to creatinine appearance rate in urine and dialysate to calculate a corrected creatinine index (CI). Extrarenal degradation accounted for 12 +/- 2% of CI. CI was higher in males (22.4 +/- 4.5 mg/kg/24 h) than females (19.8 +/- 4.8) and decreased with age, falling off more sharply for the female group (CI = 29.9-0.185.age, R = 0.72) than the males (CI = 24.1-0.030.age, R = 0.31). CI was found to correlate strongly with protein catabolic rate determined by urea kinetic modelling (CI = 8.84 +/- 10.91.PCR). Low or reduced CI was associated in this study group with severe malnutrition status and high mortality rate. CI is suggested as a strong predictor of patient morbidity and mortality.