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NDT Advance Access originally published online on January 4, 2008
Nephrology Dialysis Transplantation 2008 23(7):2356-2364; doi:10.1093/ndt/gfm921
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© The Author [2008]. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.For Permissions, please e-mail: journals.permissions@oxfordjournals.org


Baseline peritoneal solute transport rate is not associated with markers of systemic inflammation or comorbidity in incident Korean peritoneal dialysis patients

Kook-Hwan Oh1, Ju-Young Moon1, Jieun Oh2, Seong Gyun Kim3, Young-Hwan Hwang1, Suhnggwon Kim1, Jung Sang Lee1 and Curie Ahn4,5,6

1 Department of Internal Medicine, Seoul National University Hospital 2 Department of Medicine, Hallym University 3 Department of Internal Medicine & Kidney Research Institute, Hallym University College of Medicine 4 Department of Internal Medicine, Seoul National University Hospital 5 Transplantation Research Institute 6 Cancer Research Institute, Seoul National University, Seoul, Korea

Correspondence and offprint requests to: Curie Ahn, Department of Internal Medicine, Seoul National University Hospital, Chongno Gu, 110-744, Seoul, Korea. Tel: +82-2-2072-2222; Fax: +82-2-741-4876; E-mail: curie{at}snu.ac.kr



   Abstract
Top
 Abstract
Introduction
 Subjects and methods
 Results
 Discussion
 References
 
Background. It is controversial whether comorbid status or systemic inflammation has an influence on the peritoneal solute transport rate (PSTR). Our aim is to elucidate whether baseline PSTR is associated with markers of systemic inflammation or degree of comorbidity in incident peritoneal dialysis (PD) patients.

Methods. One hundred and ninety-five incident PD patients were prospectively included. Results of their baseline peritoneal equilibration test (PET) using 3.86% glucose PD fluid were analysed. Clinical and laboratory parameters of inflammation, comorbidity, nutritional status, dialysis adequacy and residual renal function (RRF) were assessed at the time of PET.

Results. Mean dialysate-to-plasma ratio for creatinine at 4 h (D/Pcr4) of our patients was 0.72 ± 0.11. High-sensitivity C-reactive protein (hsCRP), serum interleukin-6 (IL-6) and serum albumin concentrations were closely interrelated to one another and these markers of systemic inflammation were also related to the Davies comorbidity score. No differences in age, sex ratio, body mass index, body surface area and presence of diabetes were found among four transport groups. RRF, total Kt/V, haemoglobin, nitrogen appearance and the Davies comorbidity score were not different either. High-sensitivity CRP, serum IL-6 and albumin concentrations were not associated with the baseline PSTR. By multiple linear regression analysis, only the serum albumin concentration measured at the time of PET (β = –0.081 ± 0.020, P < 0.001) remained significantly associated with D/Pcr4.

Conclusion. In our study with incident Korean PD patients, the baseline PSTR was not influenced by markers of systemic inflammation or comorbidity. For a subgroup of PD patients without serious comorbidity, other mechanisms of high baseline PSTR need to be elucidated.

Keywords: comorbidity; inflammation; interleukin-6; peritoneal solute transport



   Introduction
Top
 Abstract
 Introduction
Subjects and methods
 Results
 Discussion
 References
 
Peritoneal solute transport rate (PSTR) is a major determinant of patient survival in peritoneal dialysis (PD) patients [1,2], and increasing PSTR is associated with an increasing risk for mortality and a tendency to an increased technique failure [2]. Besides, PSTR determines dialysis prescription for the patients [3].

Development of high PSTR has been attributed to numerous factors such as hypoalbuminaemia, comorbid disease, duration of PD and exposure to high glucose, number and severity of peritonitis, residual renal function (RRF) and bioincompatible dialysis fluid [4–6]. It has been suggested that uraemia per se might increase peritoneal membrane (PM) permeability [7]. Age and racial origin were also predictive of higher peritoneal transport status [8]. Oriental (Chinese and Polynesian) PD patients were less likely to be high transporters than either Caucasian or African American patients [9]. Compared with Caucasians, Maori/Pacific Islander racial origin was associated with an increased risk for high transport status, whereas Indian racial origin predicted a lower risk for rapid peritoneal small-solute clearance [8].

Many conflicting results have been reported on the demographic and clinical determinants that seem to be associated with the PSTR. Greater body mass index (BMI) (≥25 kg/ m2) was associated with a decreased risk for higher peritoneal transport status in one study [8], while no correlation between the dialysate-to-plasma ratio for creatinine at 4 h (D/Pcr4) and body surface area (BSA) was observed in another [5]. Diabetes mellitus (DM) may represent another conflicting factor. The CANUSA prospective study showed a greater proportion of diabetics among high transporter PD patients [1]. DM has been known to be significantly associated with high PSTR in some studies [10–17], while no significance was reported in others [18–23].

There has also been a controversy as to whether comorbidity or systemic inflammation has an influence on the PSTR in the PD patients. In one study, comorbidity was associated with increased PSTR at initiation of PD [6], while not in another [24]. Plasma and dialysate concentrations of interleukin-6 (IL-6) were shown to be associated with high PSTR [25], suggesting the role of chronic inflammation to influence the PSTR. However, others reported no significant association between serum concentration of C-reactive protein (CRP) or other inflammatory markers and solute transport rate [8,26,27], although some studies were limited by the small number of subjects.

It might be said that the relationship between PSTR and patient factors depends on the specific population of the study. Furthermore, baseline high transport status does not share the same underlying mechanisms as the acquired high transport status that develops after long-term PD [28,29]. Longitudinal studies of PD patients have shown that small solute transport increased over time with PD [30] and cumulative glucose exposure and peritonitis are major contributing factors to these changes [31]. Therefore, various results on the PSTR should be interpreted in the context of the specific patient population and the time point when the test was performed [8]. By analysing incident Korean patients with peritoneal equilibration test (PET) results within 6 months after commencing PD and without any previous history of peritonitis, we tried to exclude any acquired effects of PD-related factors such as peritonitis and prolonged exposure to the components of PD fluid.

We investigated the association between the various patient factors and baseline PSTR within 6 months after initiating PD in Korean patients. Especially, we aimed to elucidate whether baseline peritoneal solute transport characteristics in incident patients are associated with markers of systemic inflammation or degree of comorbidity.



   Subjects and methods
Top
 Abstract
 Introduction
 Subjects and methods
Results
 Discussion
 References
 
Patients
One hundred and ninety-five incident patients starting PD between July 2004 and April 2007 were enrolled in four centres in Seoul, Korea, after having given their informed consent. Patients were eligible if there was a PET within 6 months of starting dialysis. All patients were ethnic Korean and older than 18 years. In all these patients, PET using 3.86% glucose PD fluid (3.86%-PET) was performed. Patients who had peritonitis before or during the PET test were excluded. Clinical and laboratory parameters of inflammation, cardiovascular disease, nutritional status and dialysis adequacy were assessed at the time of PET. Analysis of comorbidity was performed on the basis of the Davies comorbidity score [6]. The Davies comorbidity score comprises seven comorbid conditions, leading to three risk groups, i.e. low (no comorbid disease), intermediate (one or two comorbid diseases) and high (three or more comorbid diseases) risk groups. Blood samples were taken for biochemical parameters both at the time of PD catheter insertion (within 30 days before starting PD) and at the time of PET.

PET
The 3.86%-PET was performed and the peritoneal transport type of each patient was classified as described elsewhere [32]. In short, after overnight dwell with 1.36% glucose PD fluid, patients were subjected to 4-h dwell with 3.86% glucose dialysis fluid. Dialysate samples were taken at 0, 1, 2 and 4 h during the test. Blood samples were taken at 2 h. The dialysate-to-plasma ratios for creatinine (D/Pcr) and sodium (D/PNa) were calculated as dialysate concentration at each time point divided by plasma concentration. Dip D/PNa is the difference between the initial D/P ratio and the D/P ratio for sodium at 1 h. The dialysate albumin concentration was measured from overnight dialysate effluent from exchanges with 2 L 1.36% glucose dialysis fluid.

Analytical method
Glucose concentration was measured by colorimetry using the glucose oxidase method and serum albumin by the bromcresol green method. Serum and dialysate creatinine were measured by the kinetic alkaline picrate (Jaffe) method with a sensitivity of 0.2 mg/dL. The dialysate creatinine concentration was corrected for high dialysate glucose concentration according to the correction factor of each local laboratory. High-sensitivity CRP (hsCRP), IL-6 and serum albumin concentrations were employed as markers of systemic inflammation. Serum albumin concentration was measured twice, i.e. within 30 days before starting PD (mostly at the time of PD catheter insertion) and at the time of PET. The hsCRP was measured by immunoturbidometry (latex) with a sensitivity of 0.1 mg/L (normal values < 5 mg/L). Samples for the determination of serum IL-6 concentration were obtained from the serum taken during the PET test and immediately frozen at –70°C until analysis. Serum IL-6 concentrations were analysed using the Bio-Plex Multiplex Cytokine Assay according to the manufacturer's instructions (Biorad Laboratories, Hercules, CA, USA). The limit of detection in the serum was defined as 0.17 pg/mL.

Dialysis adequacy and nutritional parameters
Twenty-four hour urine and dialysate collection was performed for the measurement of weekly urea clearance, weekly creatinine clearance (Ccr), protein excretion through urine and dialysate and normalized protein equivalent of nitrogen appearance (nPNA).

Calculation
The D/Pcr was corrected for glucose interference using the correction factor derived by our laboratory. Peritoneal albumin clearance was assessed by the following formula: clearance = Cd x Vd/Cp x t, where Cd is the concentration in the dialysate (µg/dL), Vd is the drained volume in mL, Cp is the plasma concentration in mg/dL and t is the dwell time in minutes. Albumin clearance was expressed in µL/min.

RRF was estimated using the glomerular filtration rate (GFR) calculated as the average of residual urea and creatinine clearance from 24-h collection of urine. Patient's normalized BSA was calculated by the Du Bois and Du Bois equation [33]. Residual renal (Kt/V) urea was calculated using 24-h collection of urine. Urea distribution volume was calculated using the Watson equation [34].

Peritoneal Kt/V urea and Ccr were calculated using total urea and creatinine clearances by performance of 24-h collection of dialysate effluent. Total (Kt/V) urea was calculated by the sum of renal and peritoneal (Kt/V) urea.

Statistical analysis
Normality of data distribution was tested using the Kolmogorov–Smirnov test. Variables without a normal distribution were either transformed into the logarithmic scale and subjected to parametric tests or analysed by a nonparametric test. Values with normal distribution were expressed as mean ± standard deviation, while those without normal distribution were shown as median and interquartile range. For continuous variables, a comparison between two groups was made by using Student's t-test or the Mann–Whitney U-test. A comparison between three or more groups was performed using either analysis of variance (ANOVA) and the Tukey test or the Kruskal–Wallis test. The chi-square test was used for categorical variables. Correlation between two continuous variables was analysed by the Pearson correlation test. Multiple linear regression analysis was performed to examine the factors related to the baseline PSTR. D/Pcr4 was a dependent variable and all the possible parameters—either clinical or laboratory—that might predict the baseline PSTR were screened. Statistical significance threshold for inclusion and exclusion at each stepwise run were set at 0.05 and 0.1. In all the statistical analysis, P < 0.05 was considered statistically significant. SPSS version 12.0 for Windows (SPSS Inc., Chicago, IL, USA) was used for the statistical analysis.



   Results
Top
 Abstract
 Introduction
 Subjects and methods
 Results
Discussion
 References
 
Demographics and clinical profiles
One hundred and ninety-five patients were enrolled in our study and the details are shown in Table 1. Patients were 49.9 ± 14.4 years old. Among them, 110 patients (56%) were male. Patients had been receiving PD for a median time of 1.3 (interquartile range 1.07–1.87) months when they underwent the PET test. Their RRF was 42.9 ± 33.7 L/ week/1.73 m2 at the time of PET. Among the 195 patients, only 15 patients had three or more comorbid conditions and 84 patients had one or two.


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  		Table 1 Characteristics of the patients (n = 195)

 
Parameters of inflammation and comorbidity were interrelated
By the Pearson correlation test, the three markers of systemic inflammation, i.e. hsCRP, IL-6 and serum albumin concentrations, were closely interrelated to one another (Figure 1). Patients with an intermediate or high comorbidity score had higher CRP, higher serum IL-6 concentration and lower serum albumin concentration (Figure 2). Therefore, it can be said that those three markers of systemic inflammation are mutually linked and closely associated with comorbid conditions.


Figure 1
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  		Fig. 1 Close association between the markers of systemic inflammation employed in the present study: (A) between log CRP and log IL-6 (r = 0.576, P < 0.001), (B) between log CRP and serum albumin concentration (r = –0.379, P < 0.001) and (C) between log IL-6 and serum albumin concentration (r = –0.309, P < 0.001). Serum albumin concentration was measured at the time of PET. Correlations between two continuous variables were analysed by the Pearson correlation.

 

Figure 2
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  		Fig. 2 Distribution of systemic inflammatory markers for Davies comorbidity risk groups. Box plot representation: 75% percentile, 25% percentile, median and maximum and minimum values. (A) hsCRP levels were elevated higher in the intermediate than low comorbidity group (P < 0.01) and in the high than intermediate comorbidity group (borderline significance), (B) Serum IL-6 concentration was higher in the high than low comorbidity group (P < 0.05) and (C) serum albumin concentration at the time of PET was lower in the intermediate versus low and high versus low comorbidity groups (P < 0.001). Analysed by the Mann–Whitney U-test.

 
Baseline PSTR and clinical or laboratory parameters
D/Pcr4 of our patients was 0.72 ± 0.11 (mean ± standard deviation). Our PET data showed similar reference values compared to those obtained from Caucasian patients elsewhere [32]. No differences in age, male-to-female ratio, BMI or BSA were found among the four transport groups (Table 2). RRF, total Kt/V, haemoglobin, nPNA and the Davies comorbidity score were not different among four groups. Nine (31%) patients in the high transport group had no comorbid conditions at all and only two (7%) patients belonged to the high-risk group with three or more comorbid conditions (Table 2). These figures were not different from other transport categories. D/Pcr4 was associated with the urine volume (β = 938 ± 366, P = 0.011) even after adjustment for age, sex and diabetes. In a multiple regression model adjusted for age, sex and diabetes, D/Pcr4 was a significant determinant for 24-h urine protein excretion (β = 2.8 ± 1.1, P = 0.009). However, further adjustment for the urine volume attenuated the association between D/Pcr4 and 24-h urine protein excretion towards the null (β = 1.5 ± 1.0, P = 0.14).


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  		Table 2 Clinical characteristics of the patients according to peritoneal transport type

 
As shown in Table 2, none of the markers of systemic inflammation—hsCRP, serum IL-6 and serum albumin concentration before initiating PD—were associated with the baseline PSTR. Serum IL-6 concentration was only marginally elevated in high average transporters compared to others (P = 0.08). However, the Pearson correlation analysis revealed no significant correlation between D/Pcr4 and log serum IL-6 (P = 0.231, r = 0.12, Figure 3d). The proportions of diabetic patients among the four groups were not different (Table 2). Serum albumin concentration before starting PD was not different among the four categories. However, serum albumin concentration measured at the time of PET showed significant differences, i.e. lowest concentration from the high-transport group and highest from the low transport group (Table 2). Peritoneal albumin clearance was significantly correlated with D/Pcr4 (r = 0.379, P = 0.001) and inversely correlated with serum albumin concentration measured at the time of PET (r = –0.537, P = 0.001). Diabetes (β = –0.26 ± 0.08, P < 0.001), D/Pcr4 (β = –1.50 ± 0.33, P < 0.001), haemoglobin (β = 0.08 ± 0.02, P < 0.001), BMI (β = 0.03 ± 0.01, P = 0.003), hsCRP (β = –0.14 ± 0.05, P = 0.005) and age (β = –0.007 ± 0.003, P = 0.013) were significant independent predictors for serum albumin concentration in a multiple regression model that included age, sex, diabetes, hsCRP, haemoglobin, BMI, BSA, D/Pcr4 and 24-h urine protein excretion.


Figure 3
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  		Fig. 3 Pearson correlation of PSTR with various parameters. (A) Correlation between dipping of D/P sodium and D/Pcr4 (r = –0.344, P < 0.001), (B) correlation between serum albumin and D/Pcr4 (r = –0.312, P < 0.001), (C) correlation between log CRP and D/Pcr4 (P = 0.52) and (D) correlation between log IL-6 and D/Pcr4 (P = 0.231). D/Pcr4: dialysate-to-plasma ratio of creatinine concentration at 4 h, Dip D/PNa: dipping of dialysate-to-plasma sodium concentration ratio, S-alb: serum albumin concentration measured at the time of PET.

 
Baseline PSTR: no difference between diabetic versus non-diabetic patients
Diabetic patients (n = 81) were significantly older (P = 0.001) and more likely to be male gender (P = 0.005) than non-diabetic patients (n = 114). They had significantly higher BMI (P = 0.001) and larger BSA (P = 0.01) with lower serum albumin concentration (P = 0.001). They had a higher hsCRP level (P = 0.01) and a tendency to a higher serum IL-6 concentration (P = 0.053). However, no difference was found in D/Pcr4 (P = 0.75) or peritoneal albumin clearance (P = 0.33) between the diabetic and non-diabetic patients (Table 3).


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  		Table 3 Comparison between the diabetic and non-diabetic group

 
Factors determining baseline PSTR
Multiple linear regression analysis was performed to identify factors that determine the baseline PSTR (Table 4). Patient factors such as age, sex, BMI, BSA, RRF, the presence of DM, Davies comorbidity score, serum albumin concentration, nPNA, hsCRP and haemoglobin were screened as independent variables for possible association with D/Pcr4. DM and Davies comorbidity score were entered into a separate model because the latter involves the presence of DM by definition. Serum IL-6 concentration was excluded from covariates due to collinearity with hsCRP. Peritoneal albumin clearance was also excluded due to collinearity with serum albumin at the time of PET. Among those variables, only the serum albumin (β = –0.081 ± 0.020, P < 0.001) measured at the time of PET remained significantly associated with D/Pcr4 (Table 4, Figure 3).


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  		Table 4 Multiple linear regression analysis of factors associated with D/PCr4

 


   Discussion
Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
References
 
The overall profiles of the peritoneal small solute transport from ethnic Korean patients were similar to that reported for Caucasian patients [32]. Our study showed that the markers of systemic inflammation employed in our study, i.e. hsCRP, serum albumin and serum IL-6 are closely interrelated. It also showed that the baseline PSTR in incident PD patients was not related to these markers of systemic inflammation.

It has been speculated that systemic inflammation has a role in the PSTR [4,5] and the high transport group is associated with increased mortality due to a high level of chronic inflammation and volume overload [1,2,35]. However, in several small-scale cross-sectional studies, authors reported no association between the inflammatory markers and D/Pcr4 [26,27]. The European APD Outcome Study (EAPOS) showed that baseline D/Pcr4 had no impact on the patient or technique survival, if adequate UF volume could be obtained by using automated PD and icodextrin [36]. This suggests that the factors responsible for poorer survival in high transporters might be more associated with volume overload rather than chronic inflammation.

The present study shows that the baseline PSTR was not correlated with age, sex, body habitus, presence of DM, grade of comorbidity and various markers of systemic inflammation. No difference was found in RRF, adequacy and nutritional parameters depending on the transport categories, either. Our data show that the high transport group was seemingly associated with higher urine protein excretion in a model adjusted only for age, sex and diabetes. However, additional adjustment for the urine volume demonstrated that such an association subsequently attenuated towards the null. This suggests that the urine volume acts as a confounder linking D/Pcr4 and proteinuria. That is, an increase in D/Pcr4 in our study was associated with an increase in the urine volume, and the urine volume was associated with proteinuria. Association between D/Pcr4 and the urine volume is suggested in a randomized prospective trial with a low glucose degradation product (GDP) PD solution [37]. In that trial, low-GDP fluid use was associated with a higher D/Pcr4, lower peritoneal UF volume and higher urine volume. In our study, an increase in D/Pcr4 was associated with a decrease in peritoneal UF and an increase in the urine volume as well. For the high transport group, compensation for the lower peritoneal UF volume, in terms of overall fluid balance, could have resulted in a higher urine volume. One could suspect that D/Pcr4 might influence the urine volume and, in consequence, might be indirectly associated with the 24-h urine protein excretion. In order to elucidate the association between D/Pcr4 and urine volume in incident PD patients, further research is warranted, based on the control for diuretics, anti-hypertensive agents and dialysis solution, along with an accurate assessment of the fluid status.

Our study shows that diabetic patients have higher hsCRP and IL-6 concentrations and lower serum albumin concentration than non-diabetic subjects, suggesting a higher degree of comorbid conditions. However, in terms of PSTR, diabetic patients presented similar D/Pcr4 and peritoneal albumin clearance compared to non-diabetic patients. In our multiple regression model that included age, sex, diabetes, hsCRP, haemoglobin, BMI, BSA, D/Pcr4 and 24-h urine protein excretion, diabetes (β = –0.26 ± 0.08, P < 0.001) was an independent predictor of serum albumin concentration, irrespective of D/Pcr4, age, hsCRP, haemoglobin and BMI.

High-sensitivity CRP, serum albumin and IL-6 concentration were employed as markers of systemic inflammation in our study. As shown in Figure 1, these markers were shown to be closely interrelated. In addition, grade of comorbidity estimated by the Davies comorbidity score was also closely related to all of these inflammatory markers. Nevertheless, none of the three inflammatory markers nor the Davies comorbidity score was associated with D/Pcr4 in our study (Table 2, Figure 3). Although serum IL-6 concentration was marginally higher in high average transporters than the others, Pearson's correlation analysis showed no correlation between D/Pcr4 and serum IL-6 concentration (Figure 3d). These evidences, as a whole, suggest that the baseline PSTR is not necessarily associated with the presence of systemic inflammation during the early stage of PD in our population.

Our results are in line with several recent studies with incident PD patients. Van Esch reported that three transport groups based on the mass transfer area coefficient (MTAC) did not present any difference in the degree of comorbidity, RRF, serum concentrations of acute-phase proteins, inflammatory markers and vascular endothelial growth factor (VEGF). Besides, no difference in MTAC creatinine was found between the three albumin tertile groups [24]. Another study with the incident PD patients comparing fast versus non-fast transporters showed that both the groups had similar age, BMI, RRF and comorbidity scores [28]. It showed no difference in CRP, serum IL-6 and markers of systemic atherosclerosis. After follow-up, the baseline PSTR was not a determinant of patient survival while the comorbidity score remained significant [28]. Recently, those authors reported no correlation between D/Pcr4 and systemic IL-6 [29].

Some authors reported that high transporters presented low serum albumin concentration even before initiation of PD, suggesting a possible link between chronic inflammation and PST [4,38,39]. Our study analysed a relatively large number of patients with a different ethnicity compared to those reports. We demonstrated no difference among four transport groups in the serum albumin concentration that was measured before initiation of PD. On the other hand, when measured at the time of PET (mostly 30–60 days after initiation of PD), serum albumin concentration correlated negatively with the baseline D/Pcr4 (r = –0.312, P = 0.001). D/Pcr4 was positively correlated with peritoneal albumin clearance (r = 0.379, P = 0.001). These results imply that the lower serum albumin concentration from the high transport group in the early period after starting PD reflects peritoneal albumin loss, rather than systemic inflammation or comorbidity. This is also in keeping with our view that the baseline PSTR early after starting PD might not constantly reflect systemic inflammation or comorbidity.

In conclusion, our study showed that patients with a higher degree of comorbidity or DM presented a higher level of systemic inflammatory markers. However, the baseline PSTR was not influenced by the markers of systemic inflammation or comorbidity. It can be said that heterogeneous mechanisms underlie high baseline PSTR. Therefore, the high baseline PSTR cannot be used to predict poorer patient survival, at least in such a subpopulation. For them, other mechanisms of the high baseline PSTR need to be elucidated. More benign factors that might determine the effective peritoneal surface area could be a candidate. Local production of the inflammatory cytokines or vasoactive growth factors from the peritoneum in response to the components of PD fluid or mechanical stress during PD fluid exchange might be responsible. In addition, the inter-personal diversity of such local response by the peritoneal tissue may be, in part, explained by genetic polymorphism, which could be one of the potential subjects to be investigated in the future.



   Acknowledgments
 
This study could not have been done without the help of our colleagues in the PD unit and participation of our patients. We thank Hyunjin Kang and Sang Hee Lim for their effort in collecting numerous serum and dialysate samples, Hyun Yee Yoon for her excellent work in ELISA and finally Myeong Ok Yoon for data collection and other laboratory support. We appreciate the expertise in statistical advice from the Medical Research Collaborating Center (MRCC), Seoul National University Medical College. Some part of this study was submitted to the Annual Meeting of Korean Society of Nephrology, 2005.

Conflict of interest statement. None declared.



   References
Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 References
 

  1. Churchill DN, Thorpe KE, Nolph KD, et al. (the Canada–USA (CANUSA) Peritoneal Dialysis Study Group). Increased peritoneal membrane transport is associated with decreased patient and technique survival for continuous peritoneal dialysis patients. J Am Soc Nephrol (1998) 9:1285–1292.[Abstract]
  2. Brimble KS, Walker M, Margetts PJ, et al. Meta-analysis: peritoneal membrane transport, mortality, and technique failure in peritoneal dialysis. J Am Soc Nephrol (2006) 17:2591–2598.[Abstract/Free Full Text]
  3. Twardowski ZJ, Nolph KD, Khanna R. Peritoneal equilibration test. Perit Dial Bull (1987) 7:138–147.
  4. Margetts PJ, McMullin JP, Rabbat CG, et al. Peritoneal membrane transport and hypoalbuminemia: cause or effect? Perit Dial Int (2000) 20:14–18.[Abstract/Free Full Text]
  5. Chung SH, Heimburger O, Stenvinkel P, et al. Association between inflammation and changes in residual renal function and peritoneal transport rate during the first year of dialysis. Nephrol Dial Transplant (2001) 16:2240–2245.[Abstract/Free Full Text]
  6. Davies SJ, Phillips L, Naish PF, et al. Quantifying comorbidity in peritoneal dialysis patients and its relationship to other predictors of survival. Nephrol Dial Transplant (2002) 17:1085–1092.[Abstract/Free Full Text]
  7. Rubin J, Rust P, Brown P, et al. A comparison of peritoneal transport in patients with psoriasis and uremia. Nephron (1981) 29:185–189.[Web of Science][Medline]
  8. Rumpsfeld M, McDonald SP, Purdie DM, et al. Predictors of baseline peritoneal transport status in Australian and New Zealand peritoneal dialysis patients. Am J Kidney Dis (2004) 43:492–501.[CrossRef][Web of Science][Medline]
  9. Raj DS, Langos V, Gangam N, et al. Ethnic variability in peritoneal equilibration test and urea kinetics. Am J Kidney Dis (1997) 30:374–381.[Web of Science][Medline]
  10. Lamb EJ, Worrall J, Buhler R, et al. Effect of diabetes and peritonitis on the peritoneal equilibration test. Kidney Int (1995) 47:1760–1767.[Web of Science][Medline]
  11. Selgas R, Bajo MA, Castro MJ, et al. Risk factors responsible for ultrafiltration failure in early stages of peritoneal dialysis. Perit Dial Int (2000) 20:631–636.[Abstract/Free Full Text]
  12. Correa-Rotter R, Cueto-Manzano A. The problem of the high transporter: is survival decreased? Perit Dial Int (2001) 21(Suppl_3):S75–S79.[Abstract/Free Full Text]
  13. Cueto Manzano AM, Correa Rotter R. Is high peritoneal transport rate an independent risk factor for CAPD mortality? Kidney Int (2000) 57:314–320.[CrossRef][Web of Science][Medline]
  14. Tzamaloukas AH, Murata GH, Malhotra D, et al. Small-solute clearances in diabetic subjects on continuous ambulatory peritoneal dialysis: comparison to non-diabetic subjects. Adv Perit Dial (1999) 15:179–182.[Medline]
  15. Lin JJ, Wadhwa NK, Suh H, et al. Increased peritoneal solute transport in diabetic peritoneal dialysis patients. Adv Perit Dial (1995) 11:63–66.[Medline]
  16. Nakamoto H, Imai H, Kawanishi H, et al. Effect of diabetes on peritoneal function assessed by personal dialysis capacity test in patients undergoing CAPD. Am J Kidney Dis (2002) 40:1045–1054.[CrossRef][Web of Science][Medline]
  17. Park MS, Lee HA, Chu WS, et al. Peritoneal accumulation of AGE and peritoneal membrane permeability. Perit Dial Int (2000) 20:452–460.[Abstract/Free Full Text]
  18. Cueto Manzano AM, Diaz Alvarenga A, Correa Rotter R. Analysis of the peritoneal equilibration test in Mexico and factors influencing the peritoneal transport rate. Perit Dial Int (1999) 19:45–50.[Abstract/Free Full Text]
  19. Agarwal DK, Sharma AP, Gupta A, et al. Peritoneal equilibration test in Indian patients on continuous ambulatory peritoneal dialysis: does it affect patient outcome? Adv Perit Dial (2000) 16:148–151.[Medline]
  20. Wu CH, Huang CC, Huang JY, et al. High flux peritoneal membrane is a risk factor in survival of CAPD treatment. Adv Perit Dial (1996) 12:105–109.[Medline]
  21. Lo WK, Brendolan A, Prowant BF, et al. Changes in the peritoneal equilibration test in selected chronic peritoneal dialysis patients. J Am Soc Nephrol (1994) 4:1466–1474.[Abstract]
  22. Graff J, Fugleberg S, Nielsen SL, et al. Transperitoneal transport in diabetic and non-diabetic patients on peritoneal dialysis. Clin Physiol (1999) 19:510–518.[CrossRef][Web of Science][Medline]
  23. Hung KY, Lin TJ, Tsai TJ, et al. Impact of peritoneal membrane transport on technique failure and patient survival in a population on automated peritoneal dialysis. ASAIO J (1999) 45:568–573.[Web of Science][Medline]
  24. van Esch S, Zweers MM, Jansen MA, et al. Determinants of peritoneal solute transport rates in newly started non-diabetic peritoneal dialysis patients. Perit Dial Int (2004) 24:554–561.[Abstract/Free Full Text]
  25. Pecoits-Filho R, Araujo MR, Lindholm B, et al. Plasma and dialysate IL-6 and VEGF concentrations are associated with high peritoneal solute transport rate. Nephrol Dial Transplant (2002) 17:1480–1486.[Abstract/Free Full Text]
  26. Wang T, Heimburger O, Cheng HH, et al. Does a high peritoneal transport rate reflect a state of chronic inflammation? Perit Dial Int (1999) 19:17–22.[Abstract/Free Full Text]
  27. Herzig KA, Purdie DM, Brown AM, et al. Is Creactive protein a useful prognostic marker in peritoneal dialysis patients? J Am Soc Nephrol (2001) 12:814–821.[Abstract/Free Full Text]
  28. Rodrigues AS, Almeida M, Fonseca I, et al. Peritoneal fast transport in incident peritoneal dialysis patients is not consistently associated with systemic inflammation. Nephrol Dial Transplant (2006) 21:763–769.[Abstract/Free Full Text]
  29. Rodrigues AS, Martins M, Korevaar JC, et al. Evaluation of peritoneal transport and membrane status in peritoneal dialysis: focus on incident fast transporters. Am J Nephrol (2007) 27:84–91.[CrossRef][Web of Science][Medline]
  30. Davies SJ, Phillips L, Griffiths AM, et al. What really happens to people on long-term peritoneal dialysis? Kidney Int (1998) 54:2207–2217.[CrossRef][Web of Science][Medline]
  31. Davies SJ, Phillips L, Naish PF, et al. Peritoneal glucose exposure and changes in membrane solute transport with time on peritoneal dialysis. J Am Soc Nephrol (2001) 12:1046–1051.[Abstract/Free Full Text]
  32. Smit W, van Dijk P, Langedijk MJ, et al. Peritoneal function and assessment of reference values using a 3.86% glucose solution. Perit Dial Int (2003) 23:440–449.[Abstract/Free Full Text]
  33. Du Bois D, Du Bois EF. A formula to estimate the approximate surface area if height and weight be known. Arch Intern Med (1916) 17:863–871.[Web of Science]
  34. Watson P, Watson I, Batt R. Total body water volumes for adult males and females estimated from simple anthropometric measurements. Am J Clin Nutr (1980) 33:27–39.[Abstract/Free Full Text]
  35. Wang T, Heimburger O, Waniewski J, et al. Increased peritoneal permeability is associated with decreased fluid and small-solute removal and higher mortality in CAPD patients. Nephrol Dial Transplant (1998) 13:1242–1249.[Abstract/Free Full Text]
  36. Brown EA, Davies SJ, Rutherford P, et al. Survival of functionally anuric patients on automated peritoneal dialysis: the European APD Outcome Study. J Am Soc Nephrol (2003) 14:2948–2957.[Abstract/Free Full Text]
  37. Williams JD, Topley N, Craig KJ, et al. (Euro Balance Trial Group). The Euro-Balance trial: the effect of a new biocompatible peritoneal dialysis fluid (balance) on the peritoneal membrane. In: Kidney Int (2004) 66:408–418.[CrossRef][Web of Science][Medline]
  38. Blake PG, Howerdew G, Blake RM, et al. Serum albumin in patients on continuous ambulatory dialysis—predictors and correlations with outcomes. J Am Soc Nephrol (1993) 3:1501–1507.[Abstract]
  39. Struijk DG, Krediet RT, Koomen GCM, et al. The effect of serum albumin at the start of continuous ambulatory peritoneal dialysis treatment on patient survival. Perit Dial Int (1994) 14:121–126.[Abstract/Free Full Text]
Received for publication: 3. 8.07
Accepted in revised form: 7.12.07


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