INTRODUCTION
Peritoneal dialysis (PD) has become an established form of renal replacement therapy for patients with end-stage renal disease (ESRD) in the past thirty years 1. In 2008, there were approximately 196,000 PD patients worldwide, representing 11% of the dialysis population 2 and the number is increasing by at least 6% per annum 3.
Conventional peritoneal dialysis solutions (CS) are acidic and contain high levels of glucose degradation products (GDPs) as a result of the heat sterilization process 9. GDPs as a major factor in the bioincompatibility of peritoneal solutions10, exert potentially negative effects on both the structural and functional deterioration of peritoneum and systemic metabolic disturbance, leading to treatment failure and an increase in cardiovascular morbidity and mortality 11. Residual renal function (RRF) plays a vital role in the prognosis of patients on dialysis4, which evaluates the excretion of small solute and middle-molecular uremic toxins 5, salt and water homeostasis, acid-base balance, nutritional status and associated survival6-8. Accumulating evidence from epidemiological and experimental researches 10,12-14 reveals that low-GDP peritoneal dialysis solutions (LS) may play a role in retarding RRF loss in PD patients 14. However, not all clinical trials show encouraging results of the perceived advantages that LSs have on RRF 15,16. The impact of the low GDP in RRF protection and other beneficial effects remain insufficiently described, even though there has been interest in evaluating the systemic biocompatibility of these solutions 17. Therefore, we conducted a meta-analysis to examine the effect of LS on RRF and other related factors known to affect PD in PD patients compared with CS.
SUBJECTS AND METHODS
Study Inclusion and Exclusion Criteria
Studies that met all the following basic criteria were included in our meta-analysis: (1) a randomized controlled trial (RCT) for patients on continuous ambulatory peritoneal dialysis (CAPD) or automated peritoneal dialysis (APD) as the treatment of ESRD; (2) LS was compared with CS. The crossover randomized trials or RCTs that did not assess RRF were excluded.
Search Strategy
We identified eligible RCTs by searching the PubMed, Embase, Wiley, Scopus, Ovid databases and abstracts presented at the annual meetings of the American Society of Nephrology (ASN), the National Kidney Foundation (NKF), and the European Renal Association (ERA), from inception to July 2014, using appropriate Medical Subject Headings (MeSH) and text words: peritoneal dialysis, glucose degradation products, biocompatible solution, low-GDP, APD, CAPD in combination with “residual renal function”. Further, the reference lists of retrieved articles were then searched for additional relevant studies. No language restrictions were imposed.
Study Selection
We included RCTs examining the effect of LSs on RRF in PD patients >18 years old compared with CSs. PD modality was restricted as either CAPD or APD. The outcomes of RCTs should include the RRF value, which is measured as the arithmetic means of residual renal clearances of urea and creatinine by collecting 24-hour urine volume. Other endpoints for the evaluation may include small solute clearance, peritoneal solute transport rate (PSTR), nutritional status, and all-cause mortality of PD patients. The study had at least 12 months of duration of follow-up without restriction on sample size. Two investigators (NZ and JW), independently, screened titles and abstracts of all electronic citations to select studies that met the inclusion criteria for further analysis. All articles identified by the investigators were retained.
Study Validity Assessment
We used the Cochrane Collaboration’s bias tool and Jadad score for assessing the risk of bias for the included studies. The first approach incorporates assessment of randomization (sequence generation and allocation sequence concealment), blinding (participants, personnel, and outcome assessors), completeness of outcome data, selection of outcomes reported, and other sources of bias. The items were scored with “yes,” “no,” and “unclear” 18. The Jadad scale score ranged from 0 to 5 points about the randomization, double-blinding, and withdrawals and dropouts 19.
Data Extraction
Two investigators extracted the useful data independently and reached a consensus on all eligible data. Relevant information was obtained by contacting the corresponding authors of the respective studies.
Study characteristics were extracted from all included trials with respect to year of publication, the study sample, baseline characteristics of the trials, follow-up, and the following reported outcomes of different follow-up months (baseline, 6, 12, and 24 months): (1) RRF (mL/min) (2) total weekly urea clearance (total Kt/V) and peritoneal urea clearance (peritoneal Kt/V), (3) total creatinine clearance (total CrCl) (L/week/1.73m2), and peritoneal creatinine clearance (peritoneal CrCl) (L/week/1.73m2), (4) daily urine volume (UV) (mL), daily peritoneal ultrafiltration (UF) (mL) and daily glucose exposure (g), (5) dialysate-to-plasma ratio of creatinine at 4 hours of peritoneal equilibration test (PET) (D/Pcr) and D/D0 glucose at 4 hours (D/D0 glucose), (6) blood pressure (mmHg) including systolic blood pressure (SBP) and diastolic blood pressure (DBP), (7) nutritional data, including serum albumin (g/dL), subjective global assessment (SGA) and normalized protein nitrogen appearance (nPNA) (g/kg/day), (8) all-cause mortality.
Data Synthesis and Analysis
Continuous outcomes results were presented as the mean difference (MD) and its 95% confidence intervals (CIs). Dichotomous outcomes were reported as the risk ratio (RR) and 95% CIs. Statistical pooling was performed with a random-effect model, via generic inverse variance weighting. All the statistical analyses in this meta-analysis were performed using Review Manager 5 software (RevMan 2012) for the meta-analysis.
Hypothesis testing was set at the twotailed and results were considered statistically significant at 0.05 level. The I2 statistic was calculated as a measure of statistical heterogeneity, and I2 values of 25%, 50%, and 75% corresponded to low, medium, and high levels of heterogeneity. When heterogeneity was found (I2>25%), sensitivity analysis was performed in an attempt to explain the findings. When doing a pool for some outcome assessment, we excluded the study which has the significant difference at baseline to keep two groups in all studies have the consistent outcome at the baseline. For each parameter estimate, an integrated analysis was given, finally.
The meta-analysis was performed in accordance with the recommendations by Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) workgroup 20.
RESULTS
Study Characteristics
A total of 223 potentially relevant citations were identified and screened, of which 197 were selectively excluded from the study because they were not clinical RCTs or did not expose the outcome of interest. Twenty-six articles were retrieved for detailed evaluation. Overall, seven RCTs were included with a combined total of 632 patients 3,15,17,21-24 (Fig. 1).

Fig 1 Flow chart showing the number of citations retrieved by individual searches and the number of trials included in the review.
The details of the characteristics and the demographic data of the RCTs included in our analysis were summarized in Table 1. These studies varied in sample size, and follow-up duration differed from 12 to 24 months, spanning nearly 10 years. The mean age of the populations ranged from 51~62 years and the mean of body mass index (BMI) ranged from 23~28.4 kg/m2. The prevalence of diabetes in the patients was from 11%~56%. More than half of the patients in both groups used angiotensin converting-enzyme inhibitors (ACEI) or angiotensin II receptor blockers (ARB) and half of the patients in both groups used diuretics in two studies 3,23. All trials evaluated the LS (Balance: Fresenius Medical Care) compared with a CS (Stay•Safe: Fresenius Medical Care). Almost all studies included incident CAPD patients except the Choi et al.21 study, and patients with CAPD modality except the balANZ Trial 3.
Table 1 Characteristics of the included RCTs in this analysis.
Note: data are presented as mean or median (range). NA, not available. L/C, neutral pH and low-GDP PDSs/conventional PDSs; DM, diabetes mellitus; BMI, body mass index; ACEi, angiotensin-converting enzyme inhibitor; ARB, angiotensin II receptor blocker.
Baseline of outcomes in these included studies were shown in Table 2. Kim et al.22 demonstrated that there were no significant differences of all outcomes between the two groups except CrCl (LS group, 95.5±5.0 vs. CS group, 78.6±11.8 L/week/1.73m2, p<0.05) and nPNA (LS group, 0.85±0.07 vs. CS group, 1.06±0.11 g/kg/day, p<0.05). The D/Pcr at the baseline was higher in the LS group than in the CS group in the two trials studied by Kim et al. 23 and Park et al.17. Moreover in the study by Park et al. 17 peritoneal CrCl and was higher in the LS group, peritoneal UF volume was lower in the LS group at baseline in keeping with higher peritoneal transport characteristics in this group. Szeto et al.15 showed that at baseline, the CS group had a better nutritional status than the LS group (serum albumin, p=0.004 and SGA, p=0.023), but the difference disappeared in 12 months.
Table 2 The baseline of outcomes in the included RCTs.
Note: data are presented as mean±SD or median (range). NA, not available. Bold indicates the parameters have significant differences between the two groups and asterisk (*) indicates p<0.05 versus CS group. RRF, mean of creatinine clearance (Ccr) and urea clearance (Curea); Kt/V, total weekly urea clearance; peritoneal Kt/V, weekly peritoneal urea clearance; CrCl, total creatinine clearance; peritoneal CCr, peritoneal creatinine clearance; peritoneal UF, peritoneal ultrafiltration; D/Pcr, dialyzate-to-plasma creatinine ratio at 4 hours of peritoneal equilibration test (PET); D/D0 glucose, D/D0 glucose at 4 hours of PET; SBP, systolic blood pressure; DBP, diastolic blood pressure; SGA, subjective global assessment; nPNA, normalized protein nitrogen appearance.
Quality Assessment
Two investigators assessed the quality of the included studies independently. All RCTs were considered fair to good quality (Fig. 2). Allocation methods and concealment were generally, incompletely reported and therefore difficult to assess. Allocation concealment was adequate in four studies (43%). Six studies (86%) were classified as low risk of performance bias and only one study was unclearly reported. However, no information about the blinding of outcome assessment (detection bias) of the studies was provided. Completeness of outcome reporting and intention-to-treat analysis methodology was applied in 29% of included studies. Selective reporting was observed in six studies (86%). No other significant biases were identified in these seven studies, except an unclear description of participant details in four studies. The Jadad score was 3 or higher (Table 1), even though the method of random sequence generation, blinding of participants and allocation concealment were not mentioned in most studies.
Outcome Measurement
PD patients in these different studies were followed up for different periods, which may have influenced the effectiveness of the outcomes of this analysis. Therefore, subgroup analysis was used to decrease clinical heterogeneity according to the follow-up periods.
Residual Renal Function
Two studies 17,23 of seven RCTs were undertaken to calculate the RRF of 226 patients after 6 months of follow-up, and indicated that LS group was beneficial for preserving RRF compared with the control group (MD 1.28 mL/min, 95% CI 0.52 to 2.03, p=0.0009; I²=0%). Similar results were obtained after 12 months of follow-up in all studies including 520 patients (MD 0.60 mL/min, 95% CI 0.18 to 1.02, p=0.005; I2=11%). The balANZ Trial 3 followed up 24 months and RRF was measured at baseline, 12 and 24 months, as well as the study by Bajo et al.24, and the pooled data indicated no difference between the two groups (p=0.76). As the studies duration continued from 6 to 24 months, the difference of RRF between the two groups was reduced gradually. This should be commented in the abstract and/or conclusions. Considering the heterogeneity, exclusion of the study 24 with a small sample size did not materially change the results of the meta-analysis or the subgroup analyses Overall, the use of LS induced a reduction in RRF decline compared with the control group (MD 0.66 mL/min, 95% CI 0.34 to 0.99; p<0.0001; I2=4%; Fig. 3).
Daily Urine Volume
Three studies 3,17,23 with a total of 377 patients and five studies 3,15,17 21,23 with a total of 462 patients showed the 24h urine volume separately at 6 and 12 months. The 24h urine volume in the LS group was higher than that in the CS group (MD 155.42 mL/d, 95% CI 37.84 to 273.00; p=0.01) at 6 months. A total of 238 patients were followed up in the LS groups and 224 patients were followed up in the CS groups after 1 year’s study. Patients with the LS had more daily urine volume than the CS group (MD 158.93 mL/d, 95% CI 83.22 to 234.64; p<0.0001). Only the balANZ Trial 3 reported the urine volume at 24 months follow-up, and there was no significant difference between the two groups. As the study duration continued from 12 to 24 months, the MD of the residual urine volume decreased from 158.93 mL/d to 115.00 mL/d. The pooled urine volume in patients using LS was greater than using CS (MD 153.15 mL/d, 95% CI 96.62 to 209.68; p<0.00001; I2=0%; Table 2). Overall, our meta-analysis indicated that the LS had a significant effect on RRF with an increase in daily urine output compared with the CS group.
Small solute clearance
At 6 months, Kim et al.23 and Park et al.17 published the data of total Kt/V and peritoneal Kt/V showing that there was no statistical difference between the two groups (p=0.99; p=0.18). After one year follow up, five studies involving 360 patients reported the effect of LS on total Kt/V in PD patients 15,17,21-23. Compared to the CS group, the LS group showed significantly increased Kt/V (MD 0.13, 95% CI 0.06 to 0.20; p=0.0002). Overall, we found that patients with LS had higher total Kt/V than with CS (MD 0.11, 95% CI 0.05 to 0.17; p=0.0007; I2=0%) (Fig. 4) and the CS group had a higher peritoneal Kt/V than the LS group (MD -0.10, 95% CI -0.20 to -0.01; p=0.03; I2=0%) (Table 2).
Our subgroup analyses showed no statistical differences of total CrCl and peritoneal CrCl between the LS and CS groups at 6 and 12 months (Table 2). We excluded the total CrCl data of the follow-up period from the study performed by Kim et al.22 who reported the significant difference between the two groups at baseline but no statistical difference observed at 12 months. The study by Park et al.17 was excluded because this study published that peritoneal CrCl was higher in the LS group at baseline and there was no significant difference after 6 months.
Peritoneal Ultrafiltration and Glucose Load
Five studies 3,15,17,21,23 published the daily peritoneal UF volume in the followup period. Park et al.17 indicated that the CS group had higher UF than the LS group at baseline and 6 months. After exclusion of this study, we pooled the data at 6 months, showing the higher UF in the CS group (MD -261.97 mL/d, 95% CI -427.73 to -96.21; p=0.002). In the subgroup analyses of 12 months, Choi et al.21 who included all prevalent PD patients with more than half number of anuric, revealed the outcome that UF was significantly higher in the LS group than in the CS group at all follow-up visits. The exclusion of this study did materially change the results of the meta-analysis or the subgroup analyses. Table 3 showed that patients with the LS had less daily peritoneal UF volume than the CS (MD -193.45 mL/d, 95% CI -315.36 to -71.54; p=0.002; I2=36%). The subgroup analyses of glucose load suggested that there was no statistically significant difference between patients using the LS and CS at 6 and 12 months.
Table 3 Comparison of low glucose degradation products (GDP) versus standard glucose dialysate.
| Outcome or subgroup title | No. of studies | No. of patients (LS/CS) | Statistical method | Effect size | p | Heterogeneity |
|---|---|---|---|---|---|---|
| Residual renal function | ||||||
| 6 months | 2 | 120/106 | Mean Difference (IV, Random, 95% CI) | 1.28 [0.52, 2.03] | 0.0009 | I2=0% |
| 12 months | 7 | 267/253 | Mean Difference (IV, Random, 95% CI) | 0.60 [0.18, 1.02] | 0.005 | I2=11% |
| 24 months | 2 | 55/68 | Mean Difference (IV, Random, 95% CI) | 0.16 [-0.87, 1.19] | 0.76 | I2=0% |
| Total | 442/427 | Mean Difference (IV, Random, 95% CI) | 0.66 [0.34, 0.99] | <0.0001 | I2=4% | |
| Daily Urine Volume | ||||||
| 6 months | 3 | 196/181 | Mean Difference (IV, Random, 95% CI) | 155.42 [37.84, 273.00] | 0.01 | I2=0% |
| 12 months | 5 | 238/224 | Mean Difference (IV, Random, 95% CI) | 158.93 [83.22, 234.64] | <0.0001 | I2=7% |
| 24 months | 1 | 42/48 | Mean Difference (IV, Random, 95% CI) | 115.00 [-146.33, 376.33] | 0.39 | |
| Total | 476/453 | Mean Difference (IV, Random, 95% CI) | 153.15 [96.62, 209.68] | <0.00001 | I2=0% | |
| Peritoneal Ultrafiltration | ||||||
| 6 months | 2 | 117/114 | Mean Difference (IV, Random, 95% CI) | -261.97 [-427.73, -96.21] | 0.002 | I2=0% |
| 12 months | 3 | 123/124 | Mean Difference (IV, Random, 95% CI) | -200.57 [-389.25, -11.88] | 0.04 | I2=48% |
| 24 months | 1 | 42/48 | Mean Difference (IV, Random, 95% CI) | 65.00 [-234.81, 364.81] | 0.67 | |
| Total | 282/286 | Mean Difference (IV, Random, 95% CI) | -193.45 [-315.36, -71.54] | 0.002 | I2=36% | |
| glucose load | ||||||
| 6 months | 3 | 203/185 | Mean Difference (IV, Random, 95% CI) | 1.35 [-1.76, 4.47] | 0.40 | I2=0% |
| 12 months | 5 | 250/234 | Mean Difference (IV, Random, 95% CI) | 0.25 [-3.25, 3.74] | 0.89 | I2=0% |
| 24 months | 1 | 42/48 | Mean Difference (IV, Random, 95% CI) | 4.30 [-17.76, 26.36] | 0.70 | |
| Total | 495/467 | Mean Difference (IV, Random, 95% CI) | 0.90 [-1.41, 3.21] | 0.45 | I2=0% | |
| Small solute clearance total Kt/V | ||||||
| 6 months | 2 | 120/104 | Mean Difference (IV, Random, 95% CI) | -0.00 [-0.25, 0.25] | 0.99 | I2=45% |
| 12 months | 5 | 192/168 | Mean Difference (IV, Random, 95% CI) | 0.13 [0.06, 0.20] | 0.0002 | I2=0% |
| 24 months | 0 | |||||
| Total | 312/274 | Mean Difference (IV, Random, 95% CI) | 0.11 [0.05, 0.17] | 0.0007 | I2=0% | |
| Peritoneal Kt/V | ||||||
| 6 months | 2 | 120/106 | Mean Difference (IV, Random, 95% CI) | -0.08 [-0.19, 0.04] | 0.18 | I2=0% |
| 12 months | 2 | 100/80 | Mean Difference (IV, Random, 95% CI) | -0.16 [-0.33, 0.01] | 0.06 | I2=0% |
| 24 months | 0 | |||||
| Total | 220/186 | Mean Difference (IV, Random, 95% CI) | -0.10 [-0.20, -0.01] | 0.03 | I2=0% | |
| total CrCl | ||||||
| 6 months | 2 | 120/106 | Mean Difference (IV, Random, 95% CI) | 4.82 [-6.96, 16.61] | 0.42 | I2=45% |
| 12 months | 3 | 151/133 | Mean Difference (IV, Random, 95% CI) | 3.60 [-2.48, 9.67] | 0.25 | I2=34% |
| 24 months | 0 | |||||
| Total | 271/239 | Mean Difference (IV, Random, 95% CI) | 3.39 [-0.75, 7.53] | 0.11 | I2=17% | |
| Peritoneal CrCl | ||||||
| 6 months | 1 | 48/43 | Mean Difference (IV, Random, 95% CI) | 1.50 [-2.91, 5.91] | 0.05 | |
| 12 months | 2 | 99/96 | Mean Difference (IV, Random, 95% CI) | -0.08 [-2.09, 1.93] | 0.94 | I2=0% |
| 24 months | 1 | 91/91 | Mean Difference (IV, Random, 95% CI) | 2.00 [-1.07, 5.07] | 0.20 | |
| Total | 238/230 | Mean Difference (IV, Random, 95% CI) | 0.67 [-0.90, 2.24] | 0.40 | I2=0% | |
| Peritoneal Solute Transport Rate D/Pcr | ||||||
| 6 months | 0 | |||||
| 12 months | 2 | 54/40 | Mean Difference (IV, Random, 95% CI) | 0.00 [-0.02, 0.02] | 1 | I2=0% |
| 24 months | 1 | 37/47 | Mean Difference (IV, Random, 95% CI) | 0.00 [-0.04, 0.04] | 1 | |
| Total | 91/87 | Mean Difference (IV, Random, 95% CI) | 0.00 [-0.02, 0.02] | 1 | I2=0% | |
| D/D0 glucose | ||||||
| 6 months | 1 | 41/39 | Mean Difference (IV, Random, 95% CI) | -0.05 [-0.11, 0.01] | 0.09 | |
| 12 months | 2 | 52/43 | Mean Difference (IV, Random, 95% CI) | -0.03 [-0.06, 0.00] | 0.08 | I2=40% |
| 24 months | 0 | |||||
| Total | 93/82 | Mean Difference (IV, Random, 95% CI) | -0.03 [-0.05, -0.01] | 0.01 | I2=17% | |
| Blood Pressure systolic blood pressure | ||||||
| 6 months | 2 | 155/142 | Mean Difference (IV, Random, 95% CI) | 0.96 [-3.67, 5.60] | 0.68 | I2=0% |
| 12 months | 2 | 126/113 | Mean Difference (IV, Random, 95% CI) | 2.89 [-2.41, 8.18] | 0.29 | I2=0% |
| 24 months | 1 | 42/48 | Mean Difference (IV, Random, 95% CI) | -10.80 [-19.24, -2.36] | 0.01 | |
| Total | 323/303 | Mean Difference (IV, Random, 95% CI) | -0.29 [-5.04, 4.46] | 0.91 | I2=53% | |
| diastolic blood pressure | ||||||
| 6 months | 2 | 155/142 | Mean Difference (IV, Random, 95% CI) | 1.01 [-1.84, 3.85] | 0.49 | I2=0% |
| 12 months | 2 | 126/113 | Mean Difference (IV, Random, 95% CI) | 1.10 [-1.88, 4.07] | 0.47 | I2=0% |
| 24 months | 1 | 42/48 | Mean Difference (IV, Random, 95% CI) | -3.10 [-8.51, 2.31] | 0.26 | |
| Total | 323/303 | Mean Difference (IV, Random, 95% CI) | 0.53 [-1.40, 2.45] | 0.59 | I2=0% | |
| Nutritional Status Serum albumin | ||||||
| 6 months | 3 | 203/185 | Mean Difference (IV, Random, 95% CI) | -0.09 [-0.28, 0.10] | 0.35 | I2=59% |
| 12 months | 5 | 225/209 | Mean Difference (IV, Random, 95% CI) | -0.16 [-0.28, -0.05] | 0.005 | I2=45% |
| 24 months | 1 | 42/48 | Mean Difference (IV, Random, 95% CI) | -0.20 [-0.41, 0.01] | 0.06 | |
| Total | 470/442 | Mean Difference (IV, Random, 95% CI) | -0.14 [-0.23, -0.05] | 0.002 | I2=45% | |
| nPNA | ||||||
| 6 months | 3 | 203/185 | Mean Difference (IV, Random, 95% CI) | -0.02 [-0.07, 0.02] | 0.29 | I2=0% |
| 12 months | 5 | 250/234 | Mean Difference (IV, Random, 95% CI) | -0.03 [-0.07, 0.01] | 0.18 | I2=0% |
| 24 months | 1 | 42/48 | Mean Difference (IV, Random, 95% CI) | 0.00 [-0.12, 0.12] | 1 | |
| Total | 495/467 | Mean Difference (IV, Random, 95% CI) | -0.02 [-0.05, 0.00] | 0.10 | I2=0% | |
| SGA score | ||||||
| 6 months | 1 | 79/67 | Mean Difference (IV, Random, 95% CI) | 0.20 [-0.19, 0.59] | 0.31 | |
| 12 months | 2 | 115/100 | Mean Difference (IV, Random, 95% CI) | 0.36 [-0.02, 0.73] | 0.06 | I2=45% |
| 24 months | 0 | 0 | Mean Difference (IV, Random, 95% CI) | |||
| Total | 194/167 | Mean Difference (IV, Random, 95% CI) | 0.33 [0.08, 0.57] | 0.009 | I2=21% | |
| all-cause mortality | Total events (LS/CS) | |||||
| 6 months | 0 | I2=0% | ||||
| 12 months | 5 | 9/10 | Odds Ratio (M-H, Fixed, 95% CI) | 0.80 [0.32, 2.03] | 0.64 | I2=0% |
| 24 months | 2 | 10/9 | Odds Ratio (M-H, Fixed, 95% CI) | 1.18 [0.46, 3.03] | 0.73 | |
| Total | 19/19 | Odds Ratio (M-H, Fixed, 95% CI) | 0.97 [0.50, 1.88] | 0.93 | I2=0% |
Blood Pressure
The balANZ Trial 3 and the study by Park et al.17 followed up the blood pressure of the two groups. There was no significant difference between the two -groups in controlling blood pressure during 1 year of follow-up (SBP, p=0.91; DBP, p=0.59) (Table 3).
Peritoneal Solute Transport Rate
Five studies 3,17,21-23 published the D/Pcr. In the study by Kim et al. 23, the D/Pcr was higher in the LS group than in the CS group, and this difference persisted throughout the treatment period. Similar results were obtained from Park et al.17, but after 6 months, the D/Pcr showed no difference between the two groups. The patients of two groups in these three included studies 3,21,22 had high average transport status. Overall, there was no statistically significant difference in the D/Pcr between the two groups (MD 0.00, 95% CI -0.02 to 0.02; p=1.00; I2=0%) (Table 3).
However, two studies 22,23 with a difference on D/D0 glucose were small sample trials. The pooled analysis suggested that the CS had a higher D/D0 than the LS (MD -0.03, 95% CI -0.05 to -0.01; p=0.01; I2=17%) (Table 3).
Overall, the D/Pcr and D/D0 glucose of all patients included in this subgroup analysis indicated that both the LS group and the CS group had high-average transport characteristics of peritoneal membrane 6.
Nutritional Status
Our meta-analysis indicated that patients using the LS had lower serum albumin than the CS (MD -0.14 g/dL, 95% CI -0.23 to -0.05; p=0.002; I2=45%) (Table 3).
In the meta-analysis of five studies 3,15,17,21,23, we found there was no significant difference in nPNA between the two groups (MD -0.02 g/kg/d, 95% CI -0.05 to 0.00; p=0.10;I2=0%) (Table 3).
Only two studies 17,21, publishing the data of SGA were small sample trials. We found that the LS group had a better SGA score than the CS group (MD 0.33, 95% CI 0.08 to 0.57; p=0.009; I2=21%) (Table 3).
All-cause Mortality
All seven studies 3,15,17,21-24 published the effect of LS on patients’ survival. No patient died in the two groups at 6-month follow-up. At 12 months five studies 15,17,21-23 involving 417 patients and at 24 months two studies involving 215 patients were included in the subgroup analysis, suggesting that there was no significant difference between the two groups, respectively (Table 3).
DISCUSSION
Our study suggests that low GDP solution preserves RRF in PD patients over time, particularly in one year of treatment, and improves the dialysis adequacy especially the urea clearance without increasing the peritoneal solute transport rate. In addition, low-GDP solution was found to have no benefits on blood pressure, nutritional status and all-cause mortality.
The low GDP solution preserves more RRF as they may cause less intraperitoneal inflammation, thereby reducing peritoneal ultrafiltration and fluid losses. It is supported by a crossover designed RCT by EURO-BALANCE 14, which showed more urine volume and better clearance of both urinary urea and creatinine with the neutral pH low GDP glucose containing dialysates alongside lower serum concentrations of AGE markers. In addition, these findings were also confirmed by several clinical trials, suggesting better preservation of RRF compared with the conventional PD solutions 3,23. The improved preservation of RRF with low GDP solution was observed at all study time points 40. Kim et al. 23 firstly declared the beneficial effect of low GDP solution on RRF with more urine volume in a prospective RCT. The balANZ trial 3, as the largest RCT, observed that the rate of decline of renal function did not reach statistical significance in the first and the second year, but there was a significant delay in time to anuria. However, these beneficial effects on RRF were not substantiated by other studies 15,17,21,22,24. Szeto et al.15 failed to show any difference in RRF and urine output between the two groups because the small sample size was not adequately powered to elucidate the effect on RRF. Similarly, Fan et al. 16 reported negative results from a larger number of patients, which was due to the lack of homogeneity for the patients in each study group. Therefore, meta-analysis, differing from included single study, can exert statistical power and result in a highly reliability outcome. The benefits of low-GDP solution are biologically plausible, as GDPs have been demonstrated to exert nephrotoxic effects directly on renal tubular cells 11. One potential and underpinning mechanism is that low-GDP solution better preserves RRF in PD patients via reduction of GDP and the AGE in the systemic circulation 27. The other possible reason for the beneficial effect of low GDP solution on RRF could be that decreased peritoneal UF results in more urine output and higher residual renal clearance 28,29.
Weekly Kt/V is an important parameter for evaluating PD treatment adequacy. Our data indicate that although the use of the low GDP dialysates was not associated with increasing creatinine clearance (either total CrCl or peritoneal CrCl) or decreasing blood pressure (either SBP or DBP), it exhibited significant benefit in weekly Kt/V in 12 months of treatment. While patients using conventional PD solutions had a small advantage in the peritoneal Kt/V (p=0.03) which was consistent with the analysis of peritoneal UF (p=0.002) despite similar glucose load (p=0.73) (Supplementary Figure S3 and S6). Our study analyzed the nutritional status including serum albumin, nPNA and SGA score, which is important to evaluate the adequacy of peritoneal dialysis and CAPD patients survival 36. However, serum albumin suffered from a moderate level of statistical heterogeneity, which could not be satisfactorily explained 37. Improved nutritional status with low GDP PD solution was confirmed by the increase of SGA in the LS group. Inconsistency of these parameters for evaluating nutritional status may be due to heterogeneity among studies 27.
Most of the clinical studies find that low GDP solution reduces peritoneal UF accompanied by high average PSTR, whereas our review revealed that low GDP solution improved the dialysis adequacy with no expense of PSTR represented by D/Pcr and D/D0 glucose at 4 hours. Two studies by Choi et al.21 and Tranaeus et al.30 showed similar findings but with a high level of clinical heterogeneity. McDonald et al.31 thought that the reduction of peritoneal UF was an important cause of technique failure. However, excessive peritoneal UF may also play a causal role in the decline of RRF by provoking intravascular volume depletion 32,33. Thus, it is difficult to delimit UF volume as a clinical outcome, which is affected by many other variables such as fluid status, UV, PSTR and glucose load 34.
PSTR has been recognized as an important factor for the assessment of clinical outcomes, including technical failure and patient survival 35. Although the study by Kim et al. 23 was excluded for analyzing the effect of low GDP PD solution on PSTR because of a difference at baseline, the significant difference still existed at 6 and 12 months. It also supported our outcome that low GDP solution contributed to the lower UF without the difference of PSTR. Taken together, our results highlighted that the assessment for PSTR should be focused on process carefully rather than just an absolute value at the end of the study 34.
Concerning the survival advantage with low GDP PD solution, retrospective studies from Korea 38,39 suggested that the biocompatible solution improved the survival in patients with PD and reduced mortality risk by 39%. However, our data showed that low GDPs in PD solution have no statistical impact on the survival of PD patients at 1 year or even longer follow-up period.
Several limitations of this study should be considered. First, most of the studies included patients who were receiving RAS (renin-angiotensin system) blockers that might be effective in slowing the decrease in RRF in PD patients. In addition, the primary endpoints of the studies and the dose of peritoneal dialysis in patients were different. Furthermore, RCTs investigating the effects of neutral pH, low GDP PD solution on RRF and adequacy were limited in number and publication bias. The Balance® (Fresenius Medical Care, Bad Homburg, Germany), the only one particular solution analyzed in our meta-analysis, may not enough to represent the neutral pH, low GDP PD solutions. At last, PD treatment adequacy should be interpreted clinically rather than be evaluated by solute and fluid removal 28.
CONCLUSIONS
This meta-analysis suggests that low GDP PD solution significantly preserved residual renal function and improved dialysis adequacy without increasing the peritoneal solute transport rate (Table 4). Future randomized trials with adequate statistical power are needed to determine whether low GDP PD solution affects long-term clinical outcomes.
Table 4 Summary of findings for the main comparison
| Outcomes | Relative effect (95% CI) | No of Participants (studies) | Quality of the evidence (Grade) | Comments |
|---|---|---|---|---|
| Residual renal function | MD 0.66 (0.34, 0.99) | 442 (11) | high | Benefits reached significance as the study duration continued from 6 to 12 months |
| Daily Urine Volume | MD 153.15 (96.62, 209.68) | 476 (9) | high | Benefits reached significance as the study duration continued from 6 to 12 months |
| Small solute clearance total Kt/V | MD 0.11 (0.05, 0.17) | 312 (7) | high | Benefit reached significance after one year followed up |
| Peritoneal Kt/V | MD -0.10 (-0.20, -0.01) | 220 (4) | moderate | Benefit reached significance after one year followed up |
| total CrCl | MD 3.39 (-0.75, 7.53) | 271 (5) | Very low | |
| Peritoneal CrCl | MD 0.67 (-0.90, 2.24) | 238 (4) | Very low | Benefit reached significance at 6 months followed up |
| Peritoneal Ultrafiltration | MD -193.45 (-315.36, -71.54) | 282 (6) | high | Benefits reached significance as the study duration continued from 6 to 12 months |
| glucose load | MD 0.90 (-1.41, 3.21) | 495 (9) | Very low | |
| Blood Pressure systolic blood pressure | MD -0.29 (-5.04, 4.46) | 323 (5) | Very low | |
| diastolic blood p ressure | MD 0.53 (-1.40, 2.45) | 323 (5) | Very low | |
| Peritoneal Solute Transport Rate D/Pcr | MD 0.00 (-0.02, 0.02) | 91 (3) | Very low | |
| D/D0 glucose | MD -0.03 (-0.05, -0.01) | 91 (3) | high | |
| Nutritional Status Serum albumin | MD -0.14 (-0.23, -0.05) | 470 (9) | high | Benefit reached significance after one year followed up |
| nPNA | MD -0.02 (-0.05, 0.00) | 495 (9) | Very low | |
| SGA score | MD 0.33 (0.08, 0.57) | 194 (3) | high | |
| All-cause mortality | OR 0.97 (0.50, 1.88) | 19 (7) | Very low |
Low-glucose degradation product versus standard glucose dialysate
Patient or population: PD patients
Setting: community
Intervention: low GDP dialysate
Comparison: standard glucose dialysate











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