Association of Continuous-Equivalent Urea Clearances with Death Risk in Intermittent Hemodialysis

Background. Several reports describe favorable results from frequent hemodialysis, but due to the lack of unequivocal dosemeasures it is not clear whether the benefits are due to more efficient toxin removal or other factors. Methods. The associations with death risk of six continuous-equivalent urea clearance measures were compared in 57 conventional in-center hemodialysis treatment periods of 51 patients, together 114 patient years. The double pool dose measures were calculated with the Solute-Solver program and separately scaled to urea distribution volume or normalized with body surface area. Results. Mortality associated significantly with equivalent renal urea clearance (EKR) scaled to urea distribution volume (V) (p = 0.033) and with EKR normalized with body surface area (BSA) (p = 0.044) but not with V-scaled (p = 0.059) nor BSA-normalized (p = 0.183) standard clearance (stdK). Women had significantly higher normalized protein catabolic rate (nPCR), EKR/V, and stdK/V than men but slightly lower BSA-normalized dose measures and lower mortality. Protein catabolic rate and dialysis dose correlated positively with each other and with survival. Conclusions. The prognostically most valid continuous-equivalent clearance in the present material was EKR/V, calculated from double pool urea generation rate, distribution volume, and time-averaged concentration.


Introduction
Survival correlates with urea-based hemodialysis session dose in many large registry studies (Lowrie et al. [1]: 43,334 patients, Port et al. [2]: 84,936 patients, and Miller et al. [3]: 88,153 patients) in conventional thrice-weekly schedule, but in the randomized controlled HEMO trial mean equilibrated K / (eK / ) 1.53 did not result in a significantly better outcome than 1.16 [4].
Intermittent hemodialysis treatments can be compared to each other by the session dose measures URR, K , K / , and eK / only if the treatment frequency is equal. Several observational studies, referred to in [5,6], and the randomized controlled FHN trial [7] describe positive results from frequent ("daily") hemodialysis. However, the role of solute removal efficiency remains obscure.
Urea distribution volume ( ) is an essential variable in kinetic modeling and can be used as a representative of patient size, a scaling factor. However, it may have also an independent effect on outcome [1,8], which weakens the value of K / as a prognostic factor. BSA has recently been recommended for scaling of dialysis dose similarly as in expressing the glomerular filtration rate [9]. -scaled dosing may result in suboptimal outcome in women and children.
Equivalent renal urea clearance (EKR, Casino and Lopez) [10] and standard clearance (stdK, Gotch) [11,12] take treatment frequency and residual renal function (RRF) into account and they were intended for use in comparing dialysis doses in different schedules and for continuous dialysis and renal function [13,14].
RRF may contribute significantly to the total weekly solute removal [14] but only minimally (usually <1%) to the delivered K / or URR measured from blood samples. Renal clearance (K r ) can be added mathematically to session K / [15][16][17]. Continuous-equivalent clearance based on UKM 2 Advances in Nephrology  includes K r automatically. Renal function is "qualitatively" better than dialysis with equal urea clearance [18]. In theory, the continuous-equivalent average clearance based on double pool UKM and including RRF is fine, but the best measure is the one most closely associated with outcome. Only few earlier reports correlate mortality directly with ECC [7,[19][20][21][22]. The aim of the present preliminary study was to compare the prognostic value of different continuousequivalent urea clearances as dialysis dose measures.

Subjects and Methods
The study is a retrospective registry analysis from a hospital providing adult hemodialysis services in a district with a catchment area of some 50,000 inhabitants in Eastern Finland. The observation time was nine years, from January 1, 1998, to December 31, 2006. The material comprises 57 conventional in-center hemodialysis treatment periods of 51 patients, in total 114 patient years. Periods lasting under 90 days are not included. Patient characteristics are described in Table 1. Table 2 presents the characteristics of the dialysis treatment periods. "Decision" refers to a unanimous decision by patient and physician to discontinue renal replacement therapy.
Dosing of dialysis, including treatment frequency, was prescribed by the first author on multiple criteria (weight, hydration status, predialysis plasma urea concentration, and other laboratory values, eK / targets, and patient's preferences). Renal diagnosis, comorbidity, functional status, waiting for transplantation, age, anticipated survival time, and protein catabolic rate (PCR) were not used as dosing criteria. The patients were encouraged by a dietician to use a diet containing protein 1.2 g/kg/day, but the actual dietary protein intake was not controlled.
Urea kinetic modeling with interdialysis urine collection was performed monthly. K r was interpolated from previous and next measurements if urine collection occasionally failed. RRF was detected in 68% of UKM sessions. In 15% of them, K r was interpolated. The numbers describing the patient characteristics and dialysis dose measures are means of each treatment period.
Dialyzer mass area coefficient (K 0 ) reported by the dialyzer manufacturer is used in Solute-Solver in calculating dialyzer clearance (K d ) from b and d with Michaels' equation [24].
Six double pool continuous-equivalent urea clearance measures were compared:  Univariate and multivariable binary logistic regression analyses were performed to identify variables associated with death. Variables with a univariate value < 0.10 were entered into the multivariable models. Odds ratios (ORs) and 95% confidence intervals (CIs) are reported.
Linear regression analysis was used to evaluate the interaction of dialysis dose and nPCR ( Figure 1) and the material was split into two groups on the basis of EKR/ and nPCR (

Results
The overall mortality was 140 per 1,000 patient years. The main results are shown in Table 1. Mortality was significantly associated only with EKR/ and nEKR. In multivariable analysis, EKR/ was the only variable having an association with death risk (OR = 0.326, CI = 0.117-0.912, and = 0.033). Figure 1 illustrates the linear regression between nPCR and EKR/ . To eliminate the confounding effect of nPCR on the dose-mortality relationship, the material was split into two groups with approximately equal mean nPCR but different mean EKR/ . The line separating the groups is depicted in Figure 1. Table 3 shows that the difference in mortality between the low and high dose groups is still significant.
Men had lower nPCR, EKR/ , and stdK/ and higher mortality than women (Table 4). Diabetics had higher weight, BMI, and BSA but did not differ significantly from nondiabetics in mortality (Table 5).
Correlations between some patient characteristics and continuous-equivalent clearances are shown in Table 6. All clearances correlate with each other.

Discussion
The association of six continuous-equivalent urea clearance measures with death risk was evaluated by statistical analysis. The most significant predictor in univariate analysis and the only significant one in multivariable analysis was EKR/ , calculated from TAC ( = 0.033). The value of stdK/ (from PAC) was 0.059. In the old NCDS, TAC had a closer correlation with outcome than PAC [25]. The stdK concept is compliant with the peak concentration hypothesis [26], not supported by the present results.
Normalizing with BSA was tested by the variables nEKR and nstdK, with mL/min/1.73 m 2 (or L/week/1.73 m 2 ) as their unit. nEKR was significantly associated with death risk, but nstdK was not. In the present study, K d was derived from b , d , and K 0 reported by the dialyzer manufacturer.    Table 3.
Calculated with Michaels' equation [24], a 50% error in K 0 causes an error of some 10% in K d with usual b and d . Errors in K d cause in UKM proportional errors in and .
In EKR/ and stdK/ , the errors cancel each other out, but not in nEKR and nstdK. Two other BSA-normalized continuous-equivalent clearances nEKRant and nstdKant were calculated applying the method of Daugirdas et al. described in the Appendix [9,27]. The anthropometric total body water is usually larger compared to the kinetic . Thus, nEKRant and nstdKant are higher than the simple BSA-normalized values. They are UKM-based continuous-equivalent hemodialysis dose measures, where the possible errors in K d are eliminated, normalized with two anthropometric measures of body size and with mL/min/1.73 m 2 as unit. However, normalizing with BSA with either method did not improve the predictive value of EKR/ and stdK/ .
In the HEMO trial, the age-adjusted mortality did not differ significantly between genders, but women did benefit from higher dose [28]. In the present study, women had lower mortality and got higher EKR/ and stdK/ but slightly lower BSA-normalized doses (Table 4). Comorbidity other than diabetes was not analyzed.
The rather wide range of dialysis doses in the present study is probably due to the opportunistic aspect: more may be better, but with large patients it is not easy to achieve a high dose (Table 6). In Table 3, the distribution volume and the proportion of men were higher in the low dose group. Men had higher mortality and volume and lower -scaled dialysis dose ( Table 4).
The patient characteristics and dialysis dose measures have multiple correlations or dependencies (Table 6). Figure 1 shows the linear regression between nPCR and EKR/ . PCR is a function of EKR/ or stdK/ ((B.3) and (B.4) in Appendix). Thus, mathematical coupling is inevitable. It is also possible that nPCR depends on the dialysis dose  (causality) or that dosing of dialysis is guided by urea concentrations or adjusted for protein catabolic rate [29] as recommended by Gotch et al. [12,30,31] (reverse causality). All these factors may have a role in the present study, but their separate contribution could not be specified. In the HEMO trial, the effect of dose on nPCR and the role of mathematical coupling were estimated to be small [32]. PCR reflects dietary protein intake, which correlates with nutritional status and outcome [33]. In a recent large registry material mortality decreased with increasing nPCR until 1.3 g/kg/day [34]. Table 3 shows that in the present study EKR/ had a significant association with mortality, although nPCR was slightly higher in the low EKR/ group. nPCR is associated with mortality directly and with the dialysis dose through the "fear of high urea concentrations" effectan example of the mechanisms possibly underlying the dosetargeting bias [35]. nPCR and dialysis dose may have a synergistic effect on survival.
A limitation of the present study is the small number of patients, which prevents robust conclusions. On the other hand, different dosing definitions were compared in the same material-a response to the challenge presented by Debowska et al. [36].
In summary, EKR/ and nEKR were significantly associated with mortality but stdK/ and nstdK were not. Normalizing with BSA [9,37] did not improve the significance of the ECC measures. In EKR, is the time-average concentration (TAC) and, in stdK, it is the average predialysis concentration (peak average concentration, PAC): The unit is, for example, mL/min or L/week. Both may be scaled to body size by dividing by urea distribution volume and expressed as EKR/ and stdK/ : , , TAC, and PAC are determined by kinetic modeling, in the present study with Solute-Solver. TAC and PAC are whole-body water concentrations and is the postdialysis total volume . The  Postdialysis .

Ethical Approval
The study was based on an analysis of register data collected and utilized during the routine care of patients and conducted with the permission of the medical director of the hospital. There was no control group or randomization. The study was not presented to an ethics committee because there were no interventions and, according to Finnish law, registry reports are not subject to evaluation by ethics committees. The patient data were anonymized and deidentified prior to analysis.