Prevalent anuric peritoneal dialysis (PD) patients usually have higher mortality than PD patients with residual urine volume. We aimed to evaluate the predictors of survival in anuric PD patients. Anuric PD patients (n = 505, <100 mL of daily urine) enrolled in Korean nationwide prospective cohort were analyzed. Survived and non-survived anuric PD patients were compared by propensity score matching analysis with a ratio of two to one. The propensity method was used to adjust for patient age, dialysis duration, and presence of diabetes. Among the total anuric PD patients, non-survived patients showed a significantly older age, higher incidence of diabetes, coronary artery disease, and arrhythmia, and lower serum creatinine and albumin. After propensity score matching, multivariate Cox regression analysis for patient survival showed a decreasing risk as serum albumin increased (HR = 0.347, p = 0.0094). Analysis using the receiver-operating-characteristic (ROC) curve showed that survival could be predicted with a sensitivity of 59.4% and a specificity of 63.2% using a cutoff value of 3.6 g/dL of serum albumin in unmatched total PD patients. The beneficial impact of high albumin level on death was significantly greater for patients with older age (≥50 years), no diabetes, low ultrafiltration (UF) volume (<1000 mL/day), and low levels of serum creatinine (<10 mg/dL), total cholesterol (<177.5 mg/dL), ferritin (<100 ng/mL), and high-sensitivity C-reactive protein (hs-CRP) (<0.1 mg/dL). Survival in anuric PD patients was associated with age, comorbidities, and nutritional factors such as creatinine and albumin. After adjustment by propensity score matching, serum albumin level was an independent predictor for survival in anuric PD patients.
Citation: Park J-Y, Cho J-H, Jang HM, Kim YS, Kang S-W, Yang CW, et al. (2018) Survival predictors in anuric patients on peritoneal dialysis: A prospective, multicenter, propensity score-matched cohort study. PLoS ONE 13(4): e0196294. https://doi.org/10.1371/journal.pone.0196294
Editor: Vivekanand Jha, Postgraduate Medical Institute, INDIA
Received: September 12, 2017; Accepted: April 10, 2018; Published: April 25, 2018
Copyright: © 2018 Park et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: The data underlying this study are from the CRC (clinical research center) for ESRD study, and are available upon request for legal reasons. Korea Health Industry Development Institute (KHIDI) is the institution which has imposed the restrictions on the data. Patients only approved of opening their data to the research center and data are available under the authority of the management committee of CRC (clinical research center) for ESRD. Researchers interested in the data may contact the management committee of the CRC for ESRD is as follows: Yong-Lim Kim, MD, PhD. Kyungpook National University School of Medicine. Tel: +82-53-200-5553, E-mail: firstname.lastname@example.org. Contact information of another researcher who can provide data on request is as follow: Yeong-Woo Park. E-mail: email@example.com. An institutional contact where data may be requested is as follows: Clinical Research Center for End Stage Renal Disease, Daegu, Korea, E-mail: firstname.lastname@example.org.
Funding: This research was supported by a grant of the Korean Healthcare Technology R&D Project through the Korea Health Industry Development Institute (KHIDI, URL: http://www.khidi.or.kr/kps, recipient: YLK), funded by the Ministry of Health and Welfare, Republic of Korea (URL: http://www.mohw.go.kr, recipient: YLK) (Korea National Institute of Health HI15C0001 and HC15C1129).
Competing interests: The authors have declared that no competing interests exist.
Patients with end-stage renal disease (ESRD) show much lower survival rate compared to general population of the same age . Peritoneal dialysis (PD) is an established treatment modality for patients with ESRD. In several retrospective and prospective cohort studies, predictors of outcome in patients treated with PD have been investigated. The survival of patients on PD is associated with various clinical factors such as demographic findings, comorbidities, nutritional markers, and peritoneal clearance [2–5].
For each 1-year increase in age, the risk of death increases by 4%, and patients with diabetes have a 30% increased risk of death compared with non-diabetic patients . Cardiovascular disease accounts for most deaths in dialysis patients (approximately 50%). In addition, malnutrition is a negative predictor of survival in patients with ESRD. Fluid status and volume homeostasis are important in patients on PD, and a number of studies have shown that fluid overload is prevalent in patients on PD. Inadequate fluid removal in this population contributes to hypertension and is associated with an increased risk of cardiovascular disease, hypoalbuminemia, and systemic inflammation [7–9]. However, this effect was found to depend mainly on the contribution of residual glomerular filtration rate (GFR) . Regardless of how long the residual renal function can be maintained in patients on PD, patients will ultimately lose their residual renal function completely.
Prevalent PD patients might have higher mortality rate when they become anuric during dialysis. The purpose of this study was to identify the factors that predict survival in anuric patients on PD.
Materials and methods
Patients and data collection
We conducted a prospective observational cohort study on Korean dialysis patients at the Clinical Research Center for End-Stage Renal Disease (CRC for ERSD, NCT00931970). Patients who were at least 20 years old and who began treatment with maintenance PD because of ESRD within 3 months were included for the study. Patients scheduled to receive kidney transplantation within 3 months were excluded. Between September 2008 and June 2011, 505 anuric patients on continuous ambulatory peritoneal dialysis (CAPD) were recruited into the study with the mean follow-up duration of 21.4±7.9 months. Anuria was defined as a 24-h urine output lower than 100 mL. Demographic variables at enrollment included age, gender, duration of dialysis, primary renal disease, comorbidities, laboratory data, and dialysis information. Comorbid conditions included chronic lung disease, coronary artery disease, peripheral vascular disease, cerebrovascular disease, diabetes mellitus, congestive heart failure, arrhythmia, connective tissue disease, peptic ulcer disease, mild liver disease, and moderate to severe chronic liver disease. Laboratory data were available for hemoglobin, serum blood urea nitrogen (BUN), creatinine, albumin, total cholesterol, triglyceride, ferritin, and high-sensitivity C-reactive protein (hs-CRP). PD information included membrane transport status, UF volume, weekly dialysate Kt/Vurea, body mass index (BMI), and blood pressure. The erythropoiesis-stimulating agents used in this study were epoetin-α and darbepoetin, using a conventional ratio of 200:1 to convert from epoetin-α to darbepoetin. Comorbidities, laboratory data, and dialysis information were followed at 3 and 6 months after the start of renal replacement therapy, and then at 6-month intervals thereafter. The present study used the data at the recruitment period of anuric PD patients. Patient’s death, a primary end point of the study, was reported within 1 month after the event and ascertained by data from Statistics Korea. The study had local ethical committee clearance at all sites. Written informed consent was obtained from all studied subjects before inclusion. The Institutional Review Board of Kyungpook National University Hospital approved the study protocol, and all clinical investigations were conducted in accordance with the guidelines of the 2008 Declaration of Helsinki.
Results of continuous variables were expressed as mean ± standard deviation (SD) for normal distribution. For categorical variables, the results were expressed as frequencies and percentages. Comparisons of continuous variables and categorical data between the two study groups were tested by the t-test and Chi-square test.
To increase the power of the statistical analysis, we constructed a propensity score-matching model. The model included age, comorbid diabetes at baseline, and dialysis vintage. Propensity score matching was conducted using a 2:1 matching procedure, whereby each non-survived anuric patient on PD was matched with two survived anuric patients on PD. The predictors for survival were analyzed using a multivariate Cox’s proportional-hazard model in which all the significant variables from the univariate analysis were included. Proportional hazard assumptions were tested using Schoenfeld residuals. Survival curves were generated by the Kaplan-Meier method. For the comparison of two scales as predictors for hypoalbuminemia, a receiver operating characteristic (ROC) curves analysis was performed.
We performed subgroup analyses in patients categorized by age (<50 years, ≥50 years), gender, diabetes, dialysis vintage (<5 years, ≥5 years), UF volume (<1000 mL/day, ≥1000 mL/day), hemoglobin (<10 g/dL, ≥10 g/dL), serum creatinine (<10 mg/dL, ≥10 mg/dL), total cholesterol (<177.5 mg/dL, ≥177.5 mg/dL), ferritin (<100 mg/dL, ≥100 mg/dL), hs-CRP (<0.1 mg/dL, ≥0.1 mg/dL). All statistical analyses were performed using SAS system for Windows, version 9.2 (SAS Institute Inc., Cary, NC). Differences were regarded as statistically significant when p < 0.05.
Demographic data of the study population are shown in Table 1. Among the 505 patients on CAPD in the study, the mean age was 50.29±12.94 years, and the duration of PD was 71.50±50.34 months. Diabetes was the most common cause of ESRD (39.56%), followed by hypertension (28.40%), glomerulonephritis (25.24%), and others (6.80%). By the end of follow-up, 61 (12.07%) patients had died, and 444 (87.93%) patients were alive. Compared to non-survived patients, survived patients had a lower number of risk factors including older age (49.04±12.66 vs. 59.44±11.23, p<0.0001), diabetes as the cause of renal failure (35.65% vs. 66.04%, p<0.0001), and cardiovascular diseases such as atrial fibrillation and coronary artery disease (p<0.05, Table 1). In addition, survived patients had significantly higher serum creatinine (11.40±7.23 vs. 9.90±3.17, p = 0.0053) and serum albumin (3.75±1.62 vs. 3.44±0.45, p = 0.0016) levels than non-survived patients (Table 2).
Univariate Cox regression analysis showed an increasing hazard ratio (HR) for patient survival with increasing patient age, decreasing duration of dialysis, and the presence of accompanying coronary artery disease or diabetes. Additionally, as UF volume, serum creatinine, and serum albumin increased, the HR decreased. Multivariate analysis conducted for these data showed increased HR with significant differences according to patient age (HR = 1.049, p = 0.0034) and diabetes (HR = 2.144, p = 0.0421), and with a decreased HR according to dialysis vintage (HR = 0.976, p = 0.0393) and serum albumin (HR = 0.471, p = 0.0480) (Table 3).
Propensity score analysis was conducted with ratio of 2:1 of survived patients to non-survived patients. Dialysis vintage, age at entry, and diabetes were used as variables for adjustment in the propensity score matching. The analysis was performed in 61 non-survived patients and 122 propensity score-matched survived patients (Table 4). After propensity score matching, survived patients showed higher serum albumin (3.63±0.46 vs. 3.44±0.45, p = 0.0111) and total cholesterol (184.79±45.83 vs. 169.90±41.81, p = 0.0390) levels with significant differences. However, other variables did not show any significant differences between the two groups (Table 5).
In addition, the univariate Cox regression analysis for patient survival showed a decreasing risk with increasing dialysis vintage (HR = 0.982, p = 0.0477), serum albumin (HR = 0.444, p = 0.0083) and total cholesterol (HR = 0.993, p = 0.0371), while no significant differences were observed for the other variables. Multivariate analysis showed a decreasing risk with increasing dialysis vintage (HR = 0.906, p<0.0001) and serum albumin (HR = 0.347, p = 0.0094), though total cholesterol level showed no significant difference between the two groups (HR = 0.992, p = 0.0600) (Table 6).
Analysis using the ROC curve for predicting death according to serum albumin level showed that death could be predicted with a sensitivity of 59.4% and a specificity of 63.2% using a cutoff serum albumin value of 3.6 g/dL. The areas under the curves of serum albumin for predicting survival was 0.658, demonstrating that serum albumin level could be considered as a fair predictor of survival. (Fig 1). When the serum albumin level of 3.6 g/dL was set as the standard, significant differences in the survival rate were observed in unmatched and matched groups (p = 0.0005 and p = 00297) (Fig 2).
Serum albumin levels below 3.6 g/dL predicted adverse renal outcome with a 59.4% sensitivity and a 63.2% specificity.
The positive association between high albumin level and survival was significantly greater for patients with older age (≥50 years), no diabetes, low UF volume (<1000 mL/day), and low levels of serum creatinine (<10 mg/dL), total cholesterol (<177.5 mg/dL), ferritin (<100 ng/mL), and hs-CRP (<0.1 mg/dL). In the context of albumin levels greater than 3.6 g/dL, a significantly increased survival rate was observed regardless of the sex, duration of dialysis, or hemoglobin level of the patients (Fig 3).
In this study, based on the results of multicenter prospective observation studies on dialysis patients in Korea, we implemented analyses of the factors that might influence prognosis in anuric patients on PD. Using propensity score matching, analyses with a ratio of 2:1 of survived patients to non-survived patients were conducted according to the differences in patient age, duration of dialysis, and the presence of diabetes. Serum albumin level was found to be an independent predictor for survival in anuric patients on PD. This is the largest prospective study ever published which investigated survival predictors in anuric PD patients.
The increasing dialysis vintage is associated with declining body weight and deterioration of nutritional status, which may affect survival of patients on PD . Because the present study included only the anuric PD patients at the recruitment, the exact duration of dialysis until anuria could not be evaluated. It is difficult to draw a definite conclusion from the univariate and multivariate analysis with duration of dialysis. Nevertheless, the duration of dialysis could be correlated with duration on dialysis of patients when they became anuric, especially when the duration is short. Therefore, relationship between dialysis duration and survival shown in our study might suggest that faster the patient becomes anuric, more likely the patient would not survive long. This has been reported in many studies suggesting preserving residual renal function is an important factor for longer survival in PD patients [11–13].
Nutritional markers are known to be as an important factor for survival in patients on PD [14–16], and among them, serum albumin concentration is often used as a surrogate measure of malnutrition. However, the utility of albumin as a marker of malnutrition in PD has remained controversial. The association between other measures of nutrition and albumin concentration is inconsistent, which may be due to multiple factors. Albumin is a negative acute-phase reactant and its production is suppressed in inflammatory states . In addition to inflammation, peritoneal albumin loss and volume overloading can lead to hypoalbuminemia in patients on PD . Although serum albumin concentration is not an effective isolated marker of nutritional status because of its multiple confounding factors, our study showed that serum albumin level may be considered an important and meaningful factor to facilitate the prediction of prognosis in anuric patients on PD. Jansen et al. also reported that several risk factors such as low serum albumin as well as old age, comorbidity, and dialysis vintage, were significantly associated with worse patient survival . However, they studied with relatively small number of anuric patients, to which comparison with propensity matching could not be applied. Moreover, we found that serum albumin concentration may differently affect patient survival according to age, status of diabetes, UF volume, serum creatinine level, total cholesterol level, ferritin level, and hs-CRP level. To ascertain the cause of the varying effects of hypoalbuminemia, further studies that elucidate the relationship between albumin and these factors are warranted.
Increased serum creatinine level has been associated with good survival, whereas lower serum creatinine level has been associated with increased mortality in hemodialysis patients [20, 21]. These findings suggest that serum creatinine level reflects muscle mass and that low muscle mass resulting from malnutrition is associated with poor outcomes. In a previous study, the association between serum creatinine level and survival was observed in a retrospective PD cohort . However, that previous study has a limitation in that residual renal function, which can directly affect serum creatinine level, was unable to be examined. Residual renal function may be better preserved and may contribute more significantly to total creatinine clearance, particularly in patients with a shorter PD duration [23, 24]. Given that residual GFR is an important predictor of survival, the association between serum creatinine and survival may be modified by residual GFR. Since our present study targeted anuric patients with PD, it was possible to exclude the influence of residual renal function on serum creatinine. In the unmatched cohort analysis, survived patients showed increased serum creatinine and a statistically significant difference in the survival rate, which increased with increasing serum creatinine levels and was confirmed in the Kaplan-Meier survival curves. These findings are in accordance with the results of previous studies. However, no significant difference in serum creatinine level was observed between the two groups in the propensity score analysis. This implies that serum creatinine may be used as a marker of nutritional status in patients with ESRD, but that it is not appropriate for predicting survival, especially anuric PD patients. Further studies are needed to verify the association between survival rate and serum creatinine level in anuric patients on PD.
The optimal UF volume of anuric patients on PD remains unknown . The European Best Practice Guideline Working Group on PD recommends the minimum net UF of 1 L/day in anuric patients on PD . However, the International Society for Peritoneal Dialysis states that no definite target for UF can be suggested from the previous studies . In the same context, our study revealed no significant difference in survival rate according to the UF volume was observed in the propensity score analysis. While current guidelines do not adequately address the optimal UF target for anuric patients on PD, optimizing therapy to meet UF goals remains an important clinical target.
Bhaskaran et al. performed a retrospective analysis of anuric peritoneal dialysis patients in Canada and were unable to find a significant effect of Kt/Vurea on the relative risk of death . However, multivariate analysis of a prospective cohort study of anuric patients in Hong Kong showed a significant effect of Kt/Vurea on survival advantage . Maarten et al. showed that peritoneal UF rate, Kt/Vurea <1.5/week, and creatinine clearance <40 L/week/1.73 m2 were associated with an increase in the relative risk of death. Furthermore, they suggested that a Kt/Vurea of 1.7/week and a creatinine clearance of at least 45 L/week were reasonable targets, which is in line with the results of the ADEMEX study in which a further increase in these solute transport levels was not found to lead to better patient survival. The Kidney Disease Outcomes Quality Initiative (KDOQI) provides specific guidelines for PD adequacy since higher small solute clearance is associated with improved survival on PD. According to our results, variations in peritoneal small solute clearances did not correspond to improved survival. Further studies that assess factors other than small-solute clearances are necessary to determine their effects on survival.
Numerous investigations have recently monitored certain biomarkers such as cardiac troponins and hs-CRP in addition to clinical data such as diabetes and hypertension in order to more clearly identify patients with coronary artery disease and enable the risk stratification of patients with ESRD [30, 31]. Several studies have shown that the elevated hs-CRP is related with cardiovascular disease and patient’s death [32–34], whereas other studies have reported no association between hs-CRP and survival [35, 36]. In the present study, significant differences in the prognosis of patients between the two groups according to blood pressure, presence of cardiomegaly in LV hypertrophy on EKG, and CXR were not observed, and similar results were shown in the propensity score analysis. In addition, in terms of hs-CRP level, there was no significant difference between the two groups, and a similar pattern was shown in the propensity score analysis. Previous study demonstrated the relationship between diminished residual renal function and increased level of CRP. However, there are several studies which failed to prove the correlation . Therefore, the question of whether hs-CRP is predictive of clinical outcomes in patients on PD irrespective of peritoneal clearance and residual renal function remains controversial. Further research is necessary to confirm the relevance of hs-CRP level in the prognosis of anuric patients on PD. However, this study showed that low hs-CRP levels decreased the hazard ratio for survival in anuric patients on PD, with higher serum albumin levels.
In conclusion, our study showed that in the absence of residual renal function, serum albumin level is an independent factor that influences the survival of patients on PD. Additionally, patients with relatively older age, no diabetes, peritoneal UF of less than 1000 mL/day, and low serum creatinine, total cholesterol, serum ferritin, and hs-CRP levels, survival rate was found to increase along with increasing serum albumin level. The statistical significance of the results was fortified through propensity score matching that was conducted using prognosis factors gleaned from previous studies of patients on PD. However, further large-scale research is necessary to confirm the relevance of cardiovascular factors, nutritional prognostic factors, and peritoneal clearance in predicting the prognosis of anuric patients on PD.
- 1. Valderrabano F, Jones EH, Mallick NP. Report on management of renal failure in Europe, XXIV, 1993. Nephrol Dial Transplant. 1995; 10 Suppl 5: 1–25.
- 2. Avram MM, Goldwasser P, Erroa M, Fein PA. Predictors of survival in continuous ambulatory peritoneal dialysis patients: the importance of prealbumin and other nutritional and metabolic markers. Am J Kidney Dis. 1994; 23: 91–98. pmid:8285203
- 3. Blake PG, Flowerdew G, Blake RM, Oreopoulos DG. Serum albumin in patients on continuous ambulatory peritoneal dialysis—predictors and correlations with outcomes. J Am Soc Nephrol. 1993; 3: 1501–1507. pmid:8490120
- 4. Genestier S, Hedelin G, Schaffer P, Faller B. Prognostic factors in CAPD patients: a retrospective study of a 10-year period. Nephrol Dial Transplant. 1995; 10: 1905–1911. pmid:8592602
- 5. Davies SJ, Phillips L, Russell GI. Peritoneal solute transport predicts survival on CAPD independently of residual renal function. Nephrol Dial Transplant. 1998; 13: 962–968. pmid:9568858
- 6. Kendrick J, Teitelbaum I. Strategies for improving long-term survival in peritoneal dialysis patients. Clin J Am Soc Nephrol. 2010; 5: 1123–1131. pmid:20430945
- 7. Silberberg JS, Barre PE, Prichard SS, Sniderman AD. Impact of left ventricular hypertrophy on survival in end-stage renal disease. Kidney Int. 1989; 36: 286–290. pmid:2528654
- 8. Jones CH, Smye SW, Newstead CG, Will EJ, Davison AM. Extracellular fluid volume determined by bioelectric impedance and serum albumin in CAPD patients. Nephrol Dial Transplant. 1998; 13: 393–397. pmid:9509452
- 9. Chung SH, Heimburger O, Stenvinkel P, Bergstrom J, Lindholm B. 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. pmid:11682675
- 10. Avram MM, Mittman N, Fein PA, Agahiu S, Hartman W, Chattopadhyay N, et al. Dialysis vintage, body composition, and survival in peritoneal dialysis patients. Adv Perit Dial. 2012; 28: 144–147. pmid:23311232
- 11. Diaz-Buxo JA, Lowrie EG, Lew NL, Zhang SM, Zhu X, Lazarus JM. Associates of mortality among peritoneal dialysis patients with special reference to peritoneal transport rates and solute clearance. Am J Kidney Dis. 1999; 33: 523–534. pmid:10070917
- 12. Wang AY, Woo J, Wang M, Sea MM, Sanderson JE, Lui SF, et al. Important differentiation of factors that predict outcome in peritoneal dialysis patients with different degrees of residual renal function. Nephrol Dial Transplant. 2005; 20: 396–403. pmid:15187196
- 13. Kim HW, Kim SH, Kim YO, Jin DC, Song HC, Choi EJ, et al. The Impact of Timing of Dialysis Initiation on Mortality in Patients with Peritoneal Dialysis. Perit Dial Int. 2015; 35: 703–711. pmid:25292405
- 14. Ramkumar N, Pappas LM, Beddhu S. Effect of body size and body composition on survival in peritoneal dialysis patients. Perit Dial Int. 2005; 25: 461–469. pmid:16178479
- 15. Johansen KL, Young B, Kaysen GA, Chertow GM. Association of body size with outcomes among patients beginning dialysis. Am J Clin Nutr. 2004; 80: 324–332. pmid:15277152
- 16. Dong J, Li YJ, Lu XH, Gan HP, Zuo L, Wang HY. Correlations of lean body mass with nutritional indicators and mortality in patients on peritoneal dialysis. Kidney Int. 2008; 73: 334–340. pmid:18033246
- 17. Sezer S, Ozdemir FN, Akman B, Arat Z, Anaforoglu I, Haberal M. Predictors of serum albumin level in patients receiving continuous ambulatory peritoneal dialysis. Adv Perit Dial. 2001; 17: 210–214. pmid:11510278
- 18. Jones CH, Smye SW, Newstead CG, Will EJ, Davison AM. Extracellular fluid volume determined by bioelectric impedance and serum albumin in CAPD patients. Nephrol Dial Transplant. 1998; 13: 393–397. pmid:9509452
- 19. Jansen MA, Termorshuizen F, Korevaar JC, Dekker FW, Boeschoten E, Krediet RT. Predictors of survival in anuric peritoneal dialysis patients. Kidney Int. 2005; 68: 1199–1205. pmid:16105051
- 20. Walther CP, Carter CW, Low CL, Williams P, Rifkin DE, Steiner RW, et al. Interdialytic creatinine change versus predialysis creatinine as indicators of nutritional status in maintenance hemodialysis. Nephrol Dial Transplant. 2012; 27: 771–776. pmid:21775764
- 21. Noori N, Kovesdy CP, Dukkipati R, Feroze U, Molnar MZ, Bross R, et al. Racial and ethnic differences in mortality of hemodialysis patients: role of dietary and nutritional status and inflammation. Am J Nephrol. 2011; 33: 157–167. pmid:21293117
- 22. Park J, Mehrotra R, Rhee CM, Molnar MZ, Lukowsky LR, Patel SS, et al. Serum creatinine level, a surrogate of muscle mass, predicts mortality in peritoneal dialysis patients. Nephrol Dial Transplant. 2013; 28: 2146–2155. pmid:23743018
- 23. Moist LM, Port FK, Orzol SM, Young EW, Ostbye T, Wolfe RA, et al. Predictors of loss of residual renal function among new dialysis patients. J Am Soc Nephrol. 2000; 11: 556–564. pmid:10703680
- 24. Jansen MA, Hart AA, Korevaar JC, Dekker FW, Boeschoten EW, Krediet RT. Predictors of the rate of decline of residual renal function in incident dialysis patients. Kidney Int. 2002; 62: 1046–1053. pmid:12164889
- 25. Lin X, Lin A, Ni Z, Yao Q, Zhang W, Yan Y, et al. Daily peritoneal ultrafiltration predicts patient and technique survival in anuric peritoneal dialysis patients. Nephrol Dial Transplant. 2010; 25: 2322–2327. pmid:20118483
- 26. The European Best Practice Guideline Working Group on Peritoneal Dialysis. Nephrol Dial Transplant. 2005; 20:
- 27. Lo WK, Bargman JM, Burkart J, Krediet RT, Pollock C, Kawanishi H, et al. Guideline on targets for solute and fluid removal in adult patients on chronic peritoneal dialysis. Perit Dial Int. 2006; 26: 520–522. pmid:16973505
- 28. Bhaskaran S, Schaubel DE, Jassal SV, Thodis E, Singhal MK, Bargman JM, et al. The effect of small solute clearances on survival of anuric peritoneal dialysis patients. Perit Dial Int. 2000; 20: 181–187. pmid:10809241
- 29. Szeto CC, Wong TY, Chow KM, Leung CB, Law MC, Wang AY, et al. Impact of dialysis adequacy on the mortality and morbidity of anuric Chinese patients receiving continuous ambulatory peritoneal dialysis. J Am Soc Nephrol. 2001; 12: 355–360. pmid:11158226
- 30. Apple FS, Murakami MM, Pearce LA, Herzog CA. Predictive value of cardiac troponin I and T for subsequent death in end-stage renal disease. Circulation. 2002; 106: 2941–2945. pmid:12460876
- 31. Ridker PM. Clinical application of C-reactive protein for cardiovascular disease detection and prevention. Circulation. 2003; 107: 363–369. pmid:12551853
- 32. Wang AY, Woo J, Lam CW, Wang M, Sea MM, Lui SF, et al. Is a single time point C-reactive protein predictive of outcome in peritoneal dialysis patients? J Am Soc Nephrol. 2003; 14: 1871–1879. pmid:12819248
- 33. Ducloux D, Bresson-Vautrin C, Kribs M, Abdelfatah A, Chalopin JM. C-reactive protein and cardiovascular disease in peritoneal dialysis patients. Kidney Int. 2002; 62: 1417–1422. pmid:12234314
- 34. Avram MM, Fein PA, Paluch MM, Schloth T, Chattopadhyay J. Association between C-reactive protein and clinical outcomes in peritoneal dialysis patients. Advances in peritoneal dialysis Conference on Peritoneal Dialysis. 2005; 21: 154–158. pmid:16686309
- 35. Herzig KA, Purdie DM, Chang W, Brown AM, Hawley CM, Campbell SB, et al. Is C-reactive protein a useful predictor of outcome in peritoneal dialysis patients? J Am Soc Nephrol. 2001; 12: 814–821. pmid:11274243
- 36. Oh KH, Moon JY, Oh J, Kim SG, Hwang YH, Kim S, et al. Baseline peritoneal solute transport rate is not associated with markers of systemic inflammation or comorbidity in incident Korean peritoneal dialysis patients. Nephrol Dial Transplant. 2008; 23: 2356–2364. pmid:18178604
- 37. Herzig KA, Purdie DM, Chang W, Brown AM, Hawley CM, Campbell SB, et al. Is C-reactive protein a useful predictor of outcome in peritoneal dialysis patients? J Am Soc Nephrol. 2001; 12: 814–821. pmid:11274243