Skip to main content

Peritoneal dialysis assists residual renal function to maintain glucose tolerance: a prospective observational study

Abstract

Background

Renal failure can cause the deterioration of glucose metabolism and increase blood glucose fluctuations, which have been reported to be a factor in the progression of vascular disorders. Little information is available on the daily variation in blood glucose levels in patients with end-stage renal disease (ESRD) and peritoneal dialysis (PD).

Methods

Daily plasma glucose excursion was evaluated by continuous glucose monitoring (CGM) for 24–72 h. Fourteen ESRD patients without type 2 diabetic nephropathy (non-diabetic patients) and six ESRD patients with type 2 diabetic nephropathy (diabetic patients) participated in this study. ESRD patients started PD which were undergone in only the daytime, and not in the night time. As the PD solution, Dianeal®1.5 % PD-2N (1.5 L) was infused intraperitoneally for 3 h three times daily. The patients received standard meals with a total calorie intake of 30 kcal/kg/day and a protein intake of 0.8 g/kg/day before and after initiation of PD. Daily glucose profiles were measured both 2 week before and 1 week after the commencement of PD with CGM system (CGMS).

Results

CGMS parameters were compared between before and after the initiation of PD. In non-diabetic patients with ESRD, the maximum glucose concentration (GC) and area under the curve (AUC) of GC >140 mg/dL significantly decreased after PD initiation. In diabetic patients with ESRD, the mean GC, SD, minimum value, AUC of GC >140 mg/dL, and maximum nocturnal GC significantly decreased, while the percentage of nocturnal GC <70 mg/dL markedly increased after PD commencement. In all patients, there was a significant negative correlation between the incidence of hypoglycemia and residual renal function before the initiation of PD and the correlation disappeared after PD initiation. In all patients, the GC range and coefficient of variation were negatively associated with the peritoneal Kt/V value.

Conclusions

Residual renal function promotes the maintenance of glucose tolerance in patients with ESRD. Glucose fluctuation improved shortly after initiation of PD, whereas nocturnal hypoglycemia was evident in diabetic patients.

Background

In patients with renal failure, glucose metabolism is abrogated, and fluctuation in plasma glucose levels is significantly enhanced because of increased insulin resistance [1–7]. Recent clinical studies have demonstrated that acute glucose excursions, postprandial hyperglycemia, and hypoglycemia, in addition to mean blood glucose levels, have a major influence on vascular endothelial function and are related to cardiovascular disease through the promotion of oxidative stress [8–11]. In in vitro research, apoptosis of human umbilical vein endothelial cells was shown to increase during glucose fluctuations as compared to during constant high glucose concentrations (GCs) [12]. However, blood glucose fluctuations of patients with end-stage renal disease (ESRD) have not been precisely evaluated [13, 14].

The recently developed continuous glucose monitoring system (CGMS) allows precise assessment of daily blood glucose fluctuations, hypoglycemia, and hyperglycemia [15–20]. The present study was performed to determine the blood glucose profiles of patients with ESRD before and after the initiation of peritoneal dialysis (PD) in order to evaluate the effects of this dialysis modality. Furthermore, residual renal function plays a key role in regulating the blood glucose level of patients with ESRD [5, 6, 21, 22]. Focusing on these points, the blood glucose level was measured before and at 1 week after introduction of PD in the prospective study. This is the first study to compare glucose metabolism in patients with ESRD before and after the initiation of PD, which causes dynamic changes in systemic glucose homeostasis.

Methods

Aims

The aims are to reveal the exacerbation of blood glucose fluctuation in ESRD patients and how peritoneal dialysis affects the glucose metabolism in the induction period.

Participants

Twenty patients without infectious diseases including an exit-site infection and peritonitis, with a mean age of 59.63 years, participated in this study. Six patients had type 2 diabetic nephropathy and 14 patients had no history of diabetes, in our medical record. They underwent CGM after we acquired their informed consent.

Study design and protocol

This study was conducted as a prospective observational study. The CGM device used in this study was an iPro® 2 CGM (Medtronic, Minneapolis, MN). The recorder of the iPro® 2 is small (3.5 × 2.8 × 0.9 cm), lightweight (5.7 g), and waterproof, allowing it to be comfortably worn on the body. All CGM data are strongly correlated with blood glucose levels because they are adjusted for data obtained every 8 h by self-monitoring of blood glucose levels [23–25]. The protocol of the study is shown in Fig. 1. Baseline CGM data were obtained 2 weeks before the initiation of PD by continuous monitoring for 24 to 72 h. CGM was repeated 1 week after the initiation of PD and was performed for 24 to 72 h. During CGM, PD was performed by infusing 1.5 L of 1.5 % glucose dialysate solution (Dianeal, Baxter, Chicago, IL) for 3 h, three times per day, starting at 10:00 AM. A PD catheter was inserted 1 week before the initiation of dialysis. None of the subjects developed any infections, including catheter exit-site infections, while CGM was performed, before and after the initiation of PD. None of the subjects were positive for C-reactive protein at the time of CGM. All subjects were hospital patients receiving a standard hospital diet, regardless of PD status, with a protein intake of 0.8 g/kg, salt intake of 6 g/day, and total calorie intake of 30 kcal/kg/day. No snacks were allowed between meals. This diet was provided throughout the present study. We also confirmed the participants ate almost all the diet, in our medical record. Because retention of dialysate for PD induces abdominal distension, food consumption might be reduced. In the present study, dialysate was only retained in the peritoneal cavity for 9 h a day, so distension-associated reduction of food consumption did not occur. Anti-diabetic therapy, including oral hypoglycemic reagents or insulin injection, was not changed after PD initiation. This study was approved by the Ethics Committee of Keio University School of Medicine (the IRB number; 20120065) and was registered with the University Hospital Medical Information Network (UMIN) clinical trial registry before the start of the study (ID: UMIN000013483). After each patient was provided with a detailed explanation of the study, informed consent to participate was obtained.

Fig. 1
figure 1

Protocol of the present study. Time schedules, diet, and peritoneal dialysis (PD) protocol for the present study. Continuous glucose monitoring (CGM) was performed 2 weeks before and 1 week after the initiation of PD

Statistics

Statistical analyses were performed using Microsoft Office Excel 2007 and IBM SPSS statistics 22.0 software (IBM Corp., Armonk, NY). The Kolmogorov-Smirnov test was used to examine the normality of data distribution, after which a paired t test, ANOVA, or a nonparametric procedure (Wilcoxon signed-rank test) was used to confirm statistically significant differences, with p < 0.05 indicating significance. Results are expressed as the mean ± standard deviation (SD). The mean blood glucose levels of each patient were calculated and compared before and after the introduction of PD. Therefore, the effects of differences in the duration of CGM measurement before and after introduction of PD were excluded.

Results

Baseline characteristics of the subjects and biochemical parameters before and after PD in all patients

Baseline characteristics of the patients without diabetic nephropathy with ESRD (non-diabetic ESRD, n = 14) and patients with type 2 diabetic nephropathy with ESRD (diabetic ESRD, n = 6) are shown in Table 1. Among the two groups, mean age, sex ratio, and body mass index were similar. With respect to oral antihypertensive medications, non-diabetic ESRD patients were primarily taking calcium channel blockers, and all diabetic ESRD patients were taking ARBs. Diabetic ESRD patients were treated primarily with insulin or α-glucosidase inhibitors as hypoglycemic drugs.

Table 1 Baseline characteristics and biochemical parameters before and after PD

In non-diabetic ESRD patients, TP increased significantly after the introduction of PD, while BUN and creatinine decreased significantly. In diabetic ESRD patients, TP and Hgb increased significantly after initiation of PD, while BUN declined significantly after its introduction (Table 1).

CGM results before and after initiation of PD in non-diabetic ESRD patients

The daily GC profiles before and after initiation of PD in non-diabetic patients are shown in Fig. 2a, b, respectively. The data for each CGM parameter before and after the initiation of PD are listed in Table 2. The maximum GC level and the area under the curve (AUC) of GC >140 mg/dL significantly decreased after the initiation of PD. Other CGM parameters were not altered after initiation of PD. These data indicated that the increased glucose excursion in patients with ESRD was partially ameliorated by PD.

Fig. 2
figure 2

Daily glucose concentration (GC) profile based on continuous glucose monitoring (CGM) in non-diabetic end-stage renal disease (ESRD) patients. a Daily CG profile for each ESRD patient without diabetes before peritoneal dialysis (PD) initiation (n = 14). b Daily CG profile for each ESRD patient without diabetes after PD initiation (n = 14). The x-axis represents the time at which GC was measured. The y-axis represents GC level. Each line corresponds to the result of one subject. The GC range of 70–140 mg/dL is shadowed in blue in the graph. The daytime period, which ranges from 0800 h to 2000 h, is indicated by a box on the x-axis

Table 2 The CGMS parameters of non-diabetic patients with ESRD

CGM results before and after initiation of PD in diabetic ESRD patients

The profiles of GC changes in diabetic ESRD patients before and after PD initiation are shown in Fig. 3a, b, respectively. Data for each CGM parameter before and after PD initiation are listed in Table 3. The mean GC level, SD, AUC of GC >140 mg/dL, and maximal nocturnal GC levels significantly decreased after the initiation of PD. Of note, in diabetic ESRD patients, minimum GC levels significantly decreased, and the percentage of nocturnal GC <70 mg/dL significantly increased after PD initiation. In diabetic patients, PD resolved glucose fluctuations, similar to what was observed in non-diabetic ESRD patients. However, nocturnal GC levels tended to be lower after the initiation of PD, which was attributed to nocturnal hypoglycemia.

Fig. 3
figure 3

The daily glucose concentration (GC) profile based on continuous glucose monitoring (CGM) in diabetic end-stage renal disease (ESRD) patients. a Daily CG profile of each ESRD patient with diabetes before peritoneal dialysis (PD) initiation (n = 6). Before initiation of PD, CGM was performed for 17 days (total number of days for all patients) in six patients with diabetic ESRD. b Daily CG profile of each ESRD patient with diabetes after PD initiation (n = 6). After initiation of PD, CGM was performed for 10 days in the same six patients with diabetic ESRD. The x-axis represents the time at which GC was measured. The y-axis represents GC level. Each line corresponds to the result of one subject. The GC range between 70 and 140 mg/dL is shadowed in blue in the graph. The daytime period, which ranges from 8:00 to 20:00, is indicated by a box on the x-axis

Table 3 CGMS parameters of diabetic patients with ESRD

Correlations of biochemical and PD-related parameters with CGM parameters

The correlations between biochemical and CGM parameters were examined in non-diabetic ESRD patients and diabetic ESRD patients. The correlation between CGM parameters and the index of dialysis efficiency, including peritoneal Kt/V, renal Kt/V, and total Kt/V, were also analyzed. In all patients, the incidence of hypoglycemia (GC <70 mg/dL) was negatively correlated with residual renal function before the start of PD (Fig. 4a, left; R = −0.539, p = 0.014). However, there was no significant correlation between the incidence of hypoglycemia and residual renal function after commencing PD (Fig. 4a, right). In all patients, after the initiation of PD, peritoneal Kt/V showed a significant correlation with the GC coefficient of variation as well as with GC range (Fig. 4b), indicating that peritoneal function has some influence on GC fluctuation, regardless of diabetic status. After the introduction of PD, the blood glucose level and the SD were 130.89 ± 19.67 mg/dL and 17.81 ± 8.50, respectively, when PD solution was retained for 9 h (between 10:00 and 19:00). Before the introduction of PD, the blood glucose level and the SD was 137.45 ± 27.83 mg/dL and 22.54 ± 12.86, respectively (between 10:00 and 19:00). There were no significant differences of blood glucose and SD between before and after the introduction of PD (130.89 ± 19.67 vs 137.45 ± 27.83, p = 0.247 and 17.81 ± 8.50 vs 22.54 ± 12.86, p = 0.062, respectively).

Fig. 4
figure 4

The relationships between biochemical and peritoneal dialysis (PD)-related parameters and continuous glucose monitoring (CGM) parameters. a Correlation between the percentage of GC <70 mg/dL and renal Kt/V, before and after the initiation of PD. b Correlation between the PD-related parameters and CGM parameters in all ESRD patients

Discussion

The GC data obtained by CGM in the present study revealed that ESRD patients had abnormal glucose metabolism, even when diabetes was not present. In these patients, both mean GC and the GC SD increased. Progression of renal failure causes a deterioration of insulin sensitivity [3–7], and improvement can occur after hemodialysis (HD) or PD [6, 26, 27]. Dialysis also increases the insulin sensitivity of pancreatic β cells and peripheral tissues [6], which can contribute to restoration of β cell function [21, 28, 29]. Several underlying mechanisms have been suggested to explain uremia-associated defects in insulin sensitivity. Urea induces reactive oxygen species that exacerbate insulin resistance in mouse visceral adipose tissue [7]. Other uremic factors, including acidemia, have also been reported to influence glucose metabolism [22, 30, 31]. In the present study, due to these uremic factors, daily GC levels and daily GC fluctuations in the CGMS were increased in non-diabetic patients.

It is conceivable that PD itself is disadvantageous for the control of systemic blood glucose levels, since the PD solution contains 1.5 % glucose (1500 mg/dL). However, in this study, it was revealed that there was little deterioration in glucose metabolism while PD was performed. In the early phase after introduction of PD, there were no significant differences of the mean blood glucose levels and SD at the times with retention of PD solution (from 10:00 to 17:00) between before and after introduction of PD. It has been reported that, unlike with PD solutions containing 4.25 % glucose, PD solutions containing 1.5 % glucose did not cause excessive β cell stimulation and had few adverse effects on glucose metabolism [32]. Although the peritoneum is highly permeable and absorption of glucose occurs rapidly, free water and uremic substances that can induce insulin resistance can be rapidly and simultaneously removed, thereby preventing an increase in blood glucose. DeFronzo et al. have reported that HD improves insulin resistance [6], while it has also been reported that uremic toxins, p-cresyl sulfate and urea, induce insulin resistance [3, 7]. The balance between the addition of glucose dialysate and the removal of free water and uremic substances may prevent the elevation of GC, despite the glucose loading from the PD solution.

Our data also suggested that hypoglycemia occurs in diabetic patients because insulin resistance is increased due to reduced renal function, leading to hyperinsulinemia, while hypoglycemia may occur in non-diabetic patients due to reduction of renal gluconeogenesis related to renal dysfunction [33–35]. This suggests that residual renal function can have an important influence on the blood glucose profile. The incidence of hypoglycemia was lower among patients who had better residual renal function before initiation of PD. After the start of PD, such an influence was no longer observed. Because PD reduced uremic toxicity, the tendency for patients with impaired renal function to be prone to develop hypoglycemia completely disappeared (Fig. 4a, right). The effect of renal dysfunction may be attributable to retention of insulin or uremic toxins that impair glucose tolerance, and PD may compensate for the effect. During long-term PD, residual renal function might decline further and PD might not be able to remove sufficient uremic toxins, which might then induce insulin resistance and inflammation. Consequently, glucose in PD dialysates might increase the blood glucose level. But further research is needed to verify this assumption. The peritoneal Kt/V value was negatively correlated with the parameters for GC excursion, the coefficient of variation, and range of GC. Although glucose load increases with high peritoneal efficiency, uremic substances might have been more efficiently removed. This escape from the uremic condition is more important for GC fluctuations. These findings suggest that PD may reduce the risk of hypoglycemia over the medium to long term after initiation, not shortly after initiation, especially in patients with low residual renal function.

HD has also been shown to improve both β cell sensitivity to glucose and tissue sensitivity to insulin [6]. However, HD is an intermittent treatment that is performed for several hours at a time, three times per week. Therefore, HD causes large fluctuations in the levels of uremic toxins and body fluid homeostasis, and it is not well understood how such fluctuations affect blood glucose levels [26, 27] and nocturnal hypoglycemia [36]. On the other hand, PD is performed slowly and continuously, leading to more stable uremia correction as compared to that with HD. Unlike the PD protocol in the present study, if dialysate is retained in the peritoneal cavity overnight as when ordinary PD is performed, PD might also be able to reduce the occurrence of nocturnal hypoglycemia. Hypoglycemia in patients with chronic kidney disease or patients on dialysis could increase the risk of stroke [37]. The ACCORD study suggested that severe hypoglycemia was likely to result in cardiovascular events [38]. Moreover, a meta-analysis revealed that severe hypoglycemia was associated with a 2.05-fold higher risk of cardiovascular disease, while a bias analysis of the data showed that severe hypoglycemia was correlated with an increased risk of cardiovascular events, unless the underlying disease was related to both severe hypoglycemia and cardiovascular risk factors [39]. A large-scale study showed that ESRD patients on PD had a better prognosis than did those on HD for several years after the initiation of dialysis therapy [2, 40, 41]. This difference may be partly attributed to the advantageous effects of PD on glucose metabolism. On the other hand, our study highlights the risk of hypoglycemic adverse effects in diabetic ESRD patients at the initiation of PD. The incidence of nocturnal hypoglycemia was significantly higher after the initiation of PD in patients with ESRD due to diabetic nephropathy. In patients with diabetic ESRD, HOMA-IR was high before the initiation of PD and declined after PD was commenced, although the decrease was not significant (data not shown). In patients with non-diabetic ESRD, HOMA-IR was not particularly high before the initiation of PD and showed little change after PD was commenced. These findings appear to suggest that the incidence of nocturnal hypoglycemia might be higher in patients with diabetic ESRD, after the initiation of PD. Physicians should be aware of the risk of nocturnal hypoglycemia, especially in diabetic patients. In the present study, the mean HbA1c was 4.82 ± 0.37 in patients with hypoglycemia and 5.66 ± 0.81 in patients without hypoglycemia, and the difference was significant (p = 0.039). Therefore, we suggest that the target HbA1c was 5.6 %. However, further research will be needed to confirm this conclusion.

Limitations of this study are it is a single-center study and a small-sized study. However, this study was significant because this is the first study evaluating the blood glucose fluctuation before and after the PD initiation under the same condition in meals and PD menu.

Conclusions

We found that daily GC fluctuation was disturbed in ESRD patients irrespective of their diabetic condition and that PD had a beneficial effect on blood glucose levels. We also demonstrated that the risk of nocturnal hypoglycemia was increased, particularly in diabetic patients at the initiation of PD. To detect these changes in glucose metabolism, monitoring GC with CGMS is recommended in ESRD patients, especially when they begin peritoneal dialysis therapy.

Abbreviations

AUC:

Area under the curve

CGM:

Continuous glucose monitoring system

Non-diabetic patients:

ESRD patients without type 2 diabetic nephropathy

Diabetic patients:

ESRD patients with type 2 diabetic nephropathy

GC:

Glucose concentration

HD:

Hemodialysis

PD:

Peritoneal dialysis

SD:

Standard deviation

UMIN:

University Hospital Medical Information Network

References

  1. Schmitz O, Orskov L, Lund S, et al. Glucose metabolism in chronic renal failure with reference to GH treatment of uremic children. J Pediatr Endocrinol. 1993;6(1):53–9.

    Article  CAS  PubMed  Google Scholar 

  2. Ansari A, Thomas S, Goldsmith D, et al. Assessing glycemic control in patients with diabetes and end-stage renal failure. Am J Kidney Dis. 2003;41(3):523–31.

    Article  PubMed  Google Scholar 

  3. Koppe L, Pillon NJ, Vella RE, et al. p-Cresyl sulfate promotes insulin resistance associated with CKD. J Am Soc Nephrol. 2013;24(1):88–99.

    Article  CAS  PubMed  Google Scholar 

  4. Kurella M, Lo JC, Chertow GM. Metabolic syndrome and the risk for chronic kidney disease among nondiabetic adults. J Am Soc Nephrol. 2005;16(7):2134–40.

    Article  PubMed  Google Scholar 

  5. DeFronzo RA, Alvestrand A, Smith D, et al. Insulin resistance in uremia. J Clin Invest. 1981;67(2):563–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. DeFronzo RA, Tobin JD, Rowe JW, et al. Glucose intolerance in uremia. Quantification of pancreatic beta cell sensitivity to glucose and tissue sensitivity to insulin. J Clin Invest. 1978;62(2):425–35.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. D’Apolito M, Du X, Zong H, et al. Urea-induced ROS generation causes insulin resistance in mice with chronic renal failure. J Clin Invest. 2010;120(1):203–13.

    Article  PubMed  Google Scholar 

  8. Monnier L, et al. Activation of oxidative stress by acute glucose fluctuations compared with type 2 diabetes. JAMA. 2006;295(14):1681–7.

    Article  CAS  PubMed  Google Scholar 

  9. Ceriello A, et al. Oscillating glucose is more deleterious to endothelial function and oxidative stress than mean glucose in normal and type 2 diabetic patients. Diabetes. 2008;57(5):1349–54.

    Article  CAS  PubMed  Google Scholar 

  10. Oizumi T, et al. Impaired glucose tolerance is a risk factor for stroke in a Japanese sample—the Funagata study. Metabolism. 2008;57(3):333–8.

    Article  CAS  PubMed  Google Scholar 

  11. O’Keefe JH, et al. Strategies for optimizing glycemic control and cardiovascular prognosis in patients with type 2 diabetes mellitus. Am J Cardiol. 2007;100:899–904.

    Article  PubMed  Google Scholar 

  12. Risso A, et al. Intermittent high glucose enhances apoptosis in human umbilical vein endothelial cells in culture. Am J Physiol Endocrinol Metab. 2001;281(5):E924–30.

    CAS  PubMed  Google Scholar 

  13. Meyer L, Chantrel F, Imhoff O, et al. Glycated albumin and continuous glucose monitoring to replace glycated haemoglobin in patients with diabetes treated with haemodialysis. Diabet Med. 2013;30(11):1388–9.

    Article  CAS  PubMed  Google Scholar 

  14. Hoshino J, Mehrotra R, Rhee CM, et al. Using hemoglobin A1c to derive mean blood glucose in peritoneal dialysis patients. Am J Nephrol. 2013;37(5):413–20.

    Article  CAS  PubMed  Google Scholar 

  15. Zijlstra E, Heise T, Nosek L, et al. Continuous glucose monitoring: quality of hypoglycaemia detection. Diabetes Obes Metab. 2013;15(2):130–5.

    Article  CAS  PubMed  Google Scholar 

  16. Valgimigli F, Lucarelli F, Scuffi C, et al. Evaluating the clinical accuracy of GlucoMenRDay: a novel microdialysis-based continuous glucose monitor. J Diabetes Sci Technol. 2010;4(5):1182–92.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Pretty CG, Chase JG, Compte AL, et al. Hypoglycemia detection in critical care using continuous glucose monitors: an in silico proof of concept analysis. J Diabetes Sci Technol. 2010;4(1):15–24.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Mazze RS, Strock E, Borgman S, et al. Evaluating the accuracy, reliability, and clinical applicability of continuous glucose monitoring (CGM): is CGM ready for real time? Diabetes Technol Ther. 2009;11(1):11–8.

    Article  CAS  PubMed  Google Scholar 

  19. Kovatchev BP, Shields D, Breton M, et al. Graphical and numerical evaluation of continuous glucose sensing time lag. Diabetes Technol Ther. 2009;11(3):139–43.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Poolsup N, Suksomboon N, Kyaw AM. Systematic review and meta-analysis of the effectiveness of continuous glucose monitoring (CGM) on glucose control in diabetes. Diabetol Metab Syndr. 2013;5(1):39.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Alvestrand A, Mujagic M, Wajngot A, Efendic S. Glucose intolerance in uremic patients: the relative contributions of impaired beta-cell function and insulin resistance. Clin Nephrol. 1989;131(4):175–83.

    Google Scholar 

  22. Siew ED, Ikizler TA. Insulin resistance and protein energy metabolism in patients with advanced chronic kidney disease. Semin Dial. 2010;23(4):378–82.

    Article  PubMed  Google Scholar 

  23. Marshall J, Jennings P, Scott A, et al. Glycemic control in diabetic CAPD patients assessed by continuous glucose monitoring system (CGMS). Kidney Int. 2003;64(4):1480–6.

    Article  PubMed  Google Scholar 

  24. Juvenile Diabetes Research Foundation Continuous Glucose Monitoring Study Group. Continuous glucose monitoring and intensive treatment of type 1 diabetes. N Engl J Med. 2008;359(14):1464–76.

    Article  Google Scholar 

  25. Tannenberg R, Bode B, Lane W, et al. Use of the continuous glucose monitoring system to guide therapy in patients with insulin-treated diabetes: a randomized control trial. Mayo Clin Proc. 2004;79(12):1521–6.

    Article  Google Scholar 

  26. Riveline JP, Teynie J, Belmouaz S, et al. Glycaemic control in type 2 diabetic patients on chronic haemodialysis: use of a continuous glucose monitoring system. Nephrol Dial Transplant. 2009;24(9):2866–71.

    Article  CAS  PubMed  Google Scholar 

  27. Sobngwi E, Ashuntantang G, Ndounia E, et al. Continuous interstitial glucose monitoring in non-diabetic subjects with end-stage renal disease undergoing maintenance haemodialysis. Diabetes Res Clin Pract. 2010;90(1):22–5.

    Article  CAS  PubMed  Google Scholar 

  28. Allegra V, Mengozzi G, Martimbianco L, Vasile A. Glucose-induced insulin secretion in uremia: effects of aminophylline infusion and glucose loads. Kidney Int. 1990;38(6):1146–50.

    Article  CAS  PubMed  Google Scholar 

  29. DeFronzo RA. Pathogenesis of glucose intolerance in uremia. Metabolism. 1978;12 Suppl 2:1866–80.

    Article  Google Scholar 

  30. Hung AM, Ikizler TA. Factors determining insulin resistance in chronic hemodialysis patients. Contrib Nephrol. 2011;171:127–34.

    Article  CAS  PubMed  Google Scholar 

  31. Mak RH. Effect of metabolic acidosis on insulin action and secretion in uremia. Kidney Int. 1998;54(2):603–7.

    Article  CAS  PubMed  Google Scholar 

  32. Armstrong VW, Creutzfeldt W, Ebert R, et al. Effect of dialysate glucose load on plasma glucose and glucoreguratory hormones in CAPD patients. Nephron. 1985;39(2):141–5.

    Article  CAS  PubMed  Google Scholar 

  33. Gerich JE, Meyer C, Woerle HJ, Stumvoll M. Renal gluconeogenesis: its importance in human glucose homeostasis. Diabetes Care. 2001;24(2):382–91.

    Article  CAS  PubMed  Google Scholar 

  34. Meyer C, Stumvoll M, Dostou J, Welle S, Haymond M, Gerich J. Renal substrate exchange and gluconeogenesis in normal postabsorptive humans. Am J Physiol Endocrinol Metab. 2002;282(2):E428–34.

    Article  CAS  PubMed  Google Scholar 

  35. Mather A, Pollock C. Glucose handling by the kidney. Kidney Int Suppl. 2011;120:S1–6.

    Article  CAS  Google Scholar 

  36. Pitkanen E, Koivula T. Continuous blood glucose monitoring and characteristics of diabetes in patients on maintenance haemodialysis treatment. Scand J Urol Nephrol. 1979;13(3):309–12.

    Article  CAS  PubMed  Google Scholar 

  37. Yu TM, Lin CL, Chang SN, Sung FC, Kao CH. Increased risk of stroke in patients with chronic kidney disease after recurrent hypoglycemia. Neurology. 2014;83(8):686–94.

    Article  CAS  PubMed  Google Scholar 

  38. Bonds DE, Miller ME, Bergenstal RM, et al. The association between symptomatic, severe hypoglycaemia and mortality in type 2 diabetes: retrospective epidemiological analysis of the ACCORD study. BMJ. 2010;340:b4909.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Goto A, Arah OA, Goto M, Terauchi Y, Noda M. Severe hypoglycaemia and cardiovascular disease: a systematic review and meta-analysis with bias analysis. BMJ. 2013;347:f4533.

    Article  PubMed  Google Scholar 

  40. Termorshuizen F, Korevaar JC, Dekker FW, Van Manen JG, Boeschoten EW, Krediet RT, Netherlands Cooperative Study on the Adequacy of Dialysis Study Group. Hemodialysis and peritoneal dialysis: comparison of adjusted mortality rates according to the duration of dialysis: analysis of The Netherlands Cooperative Study on the Adequacy of Dialysis. J Am Soc Nephrol. 2003;14(11):2851–60.

    Article  PubMed  Google Scholar 

  41. Vonesh EF, Snyder JJ, Foley RN, Collins AJ. Mortality studies comparing peritoneal dialysis and hemodialysis: what do they tell us? Kidney Int Suppl. 2006;103:S3–11.

    Article  Google Scholar 

Download references

Acknowledgements

The authors greatly appreciate the nursing staff of 5N and 8S wards in Keio University Hospital.

Funding

This study was supported by the fund from Baxter Co., Ltd. The fund was used for the purchases of CGM devices.

Availability of data and materials

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ contributions

NW and TK equally contributed to this study. NW, TK, and SW designed this study protocol. NW, TK, SW, and HI analyzed all the data and derived the conclusions. NW and SW drafted the manuscript. KH and HT participated in the data acquisition and helped lead to the conclusions by their advices. All authors read and approved the final manuscript.

Competing interests

NW belongs to the donated fund laboratory, Department of Integrated Renal Replacement Therapy in School of Medicine, Keio University, which was established by a fund from Baxter Co., Ltd. The other authors declare that they have no competing interests.

Consent for publication

Informed consent to publish was obtained from all individual participants included in this study.

Ethics approval and consent to participate

All procedures performed in this study were in accordance with the ethical standards of the Ethics Committee of Keio University School of Medicine at which this study was conducted (IRB approval number 20120065) and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Written informed consent to participate was obtained from all individual participants included in this study.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Naoki Washida.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Washida, N., Kasai, T., Hosoya, K. et al. Peritoneal dialysis assists residual renal function to maintain glucose tolerance: a prospective observational study. Ren Replace Ther 2, 57 (2016). https://doi.org/10.1186/s41100-016-0072-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s41100-016-0072-9

Keywords