Abstract
Introduction:
Clinical interventional studies in diabetes mellitus usually exclude patients undergoing peritoneal dialysis (PD). This study evaluates the impact of an educational program and a basal-bolus insulin regimen on the blood glucose level control and risk of hypoglycemia in this population.
Methods:
A before-and-after study was conducted in type 1 and type 2 DM patients undergoing PD at the Renal Therapy Services (RTS) clinic network, Bogota, Colombia. An intervention was instituted consisting of a three-month educational program and a basal-bolus detemir (Levemir, NovoNordisk) and aspart (Novorapid, NovoNordisk) insulin regimen. Prior to the intervention and at the end of treatment were conducted measures of HbA1c levels and continuous glucose monitoring (CGM).
Results:
Forty-seven patients were recruited. Mean HbA1c level decreased from 8.41% ± 0.83 to 7.68% ± 1.32 (mean difference −0.739, 95% CI −0.419, −1.059; P < .0001). Of subjects, 52% achieved HbA1c levels <7.5% at the end of study. Mean blood glucose level reduced from 194.0 ± 42.5 to 172.9 ± 31.8 mg/dl (P = .0015) measured by CGM. Significant differences were not observed in incidence of overall (P = .7739), diurnal (P = .3701), or nocturnal (P = .5724) hypoglycemia episodes nor in area under the curve (AUC) <54 mg/dl (P = .9528), but a reduction in AUC >180 (P < .01) and AUC >250 (P = .01) was evidenced for total, diurnal, and nocturnal episodes.
Conclusions:
An intervention consisting of an educational program and a basal-bolus insulin regimen in type 1 and type 2 diabetes mellitus patients undergoing PD caused a decrease in HbA1c levels, and mean blood glucose levels as measured from CGM with no significant increases in hypoglycemia episodes.
Keywords: diabetes mellitus type 1, diabetes mellitus type 2, peritoneal dialysis, hypoglycemia, insulin
Diabetes mellitus (DM) is the main underlying cause of chronic kidney disease (CKD) and kidney failure worldwide.1 Available modalities of dialysis for patients requiring renal replacement therapy include hemodialysis (HD) and peritoneal dialysis (PD). PD has several theoretical advantages as are improved hemodynamic tolerance, preserved residual renal function,2 lowered costs and more independence for patients, reasons why PD is frequently chosen as dialysis therapy.3
However, patients with diabetes undergoing PD are at increased risk for mortality when compared with patients undergoing PD for other indications.4,5 One key management strategy for these patients undergoing PD is to achieve good glycemic control,6 which is associated with lower mortality.7 Achieving this goal is a challenge, since PD with dextrose dialysates involves an 100-300 g increased glucose absorption, which is associated with poor metabolic control.8
Clinical interventional studies on diabetes usually exclude patients with end-stage renal disease, therefore, the data available on this population, and especially on patients undergoing PD, are limited. This real-life study is aimed at assessing if an intervention consisting of an educational program and a basal-bolus insulin regimen can improve the glycemic control without increase the risk of hypoglycemia in this population, as measured by continuous glucose monitoring (CGM).
Methods
A prospective study was conducted in type 1 and type 2 DM patients undergoing peritoneal dialysis at Renal Therapy Services (RTS) clinic network, Bogota, Colombia. These patients were recruited between August 2013 and January 2014. There were included patients older than 18 years of age, with Hba1c levels above 7.5% within three months prior to recruitment and with less than 48 months of PD therapy. Exclusion criteria were pregnancy, use of corticosteroids, kidney transplant during the study, peritonitis within 6 months prior to the study and exposure to icodextrin solutions during dialysis. All patients signed an informed consent form. The study was approved by the institution’s Research Ethics Committee.
Prior to study initiation, patients were receiving treatment with insulin or oral hypoglycemic agents, as recommended by their treating physician, but with HbA1c falling outside of target goal, that is, HbA1c >7.5%. At the Visit 1 was recollected information on demographic characteristics and received treatment regime; in addition, a sample was taken for HbA1c using immunoturbidimetry technique. Following the verification of inclusion criteria and the signing of an informed consent, a continuous glucose monitor (CGM) equipment, iPro2 (Medtronic, Minneapolis, MN, USA) with Enlite sensor (Medtronic) was installed to each patient. Calibration was performed with four daily measurements of capillary blood glucose using a standardized glucometer (Abbott precision, Alameda, CA). All patients were instructed to conduct stringent measurements of preprandial and two-hour postprandial capillary blood glucose, for six daily measurements in total. In addition, they were instructed to conduct other measurements whether they present signs or symptoms suggestive of hypoglycemia. Patients were asked to continue on both their prior daily diet and pharmacological management routine during the 6-day follow up and not to conduct extenuating physical activity during this phase.
At the Visit 2, CGM was removed and data were downloaded with the standardized software iPro CareLink Personal version 3.0 (Medtronic). Subjects were interviewed to obtain information on hypoglycemia events, complications or acute diseases during the 6 days with a CGM. In that moment, the intervention consisting of an educational diabetes program and a basal-bolus detemir (Levemir, NovoNordisk) and aspart (Novorapid, NovoNordisk) insulin regimen was instituted, patients under oral agents were instructed to suspend it. Basal-bolus therapy was initiated at a 0.5 IU/kg dose, using 50% basal insulin with detemir once daily and 50% preprandial boluses at the three main meals. Basal insulin dose was titrated every third day in a treat-to-target regimen looking for obtaining a fasting blood glucose goal between 100 mg/dl and 130 mg/dl. Once achieved the fasting goal, the pre-prandial insulin dose was titrated with pre- and postprandial blood glucose recording indications to achieve a postprandial level lower than 180 mg/dl, indicating a 2-unit increase in insulin aspart dose prior to the corresponding meal that did not achieve this defined goal level. Once achieved the goal this boluses were fixed and adjusted again in the next visit. If blood glucose levels were higher than 180 mg/dl prior to dinner, once the fasting goal was achieved, initiation of a second insulin detemir dose (25% of the nocturnal dose) in the morning was indicated.
At Visit 3 and Visit 4 (30 and 60 days later, respective), the compliance was assessed, doses were adjusted and any new hypoglycemic event was recorded. At Visit 5, three months after the Visit 1, a second CGM was conducted for six days, following the same indications as above, and HbA1c was measured again. Patients were able to seek advice from certified diabetes educators via the phone for resolving questions, inquiries and assistance during all the study.
The definition recently given by the American Diabetes Association for hypoglycemia was used: a blood glucose value <70 mg/dl is an alert for hypoglycemia and an indicator for insulin dose reduction on therapy, and a value <54 mg/dl9 means confirmed hypoglycemia. Hyperglycemia was defined as a blood glucose value >180 mg/dl.
Monitoring data obtained from the CareLink® platform were imported into a calculation software developed in MATLAB® to preprocessing of records. To guarantee adequate accuracy, only the CGM with r > 0.8 were included in the analysis. Each patient’s data records were split up into three groups: calendar days (00:00 to 23:59 hours), diurnal (06:00 to 21:00 hours) and nocturnal (21:00 to 06:00 hours). Days of monitoring records with consecutive loss of data greater than 50 samples, 31 samples and 19 samples were discarded in each group, for calendar days,10 diurnal records and nocturnal records, respectively. Lower losses were linearly interpolated. The following metrics were calculated for each group, mean, standard deviation (SD), area under the curve (AUC) for hyperglycemia and hypoglycemia, and number of hyperglycemia and hypoglycemia events lasting minimum 20 minutes each.
For continuous variables, mean and standard deviations were reported for variables with normal distribution, and medians and interquartile ranges if this assumption is not met. The Shapiro-Wilk test was used to determine the normality of the distribution. For categorical variables, tables of frequency and percentages were reported. The Wilcoxon signed-rank test or a paired t-test was used, as appropriate, to assess continuous variables change over time. The incidence of hypoglycemia was compared using the Cochrane Q test. Statistics package STATA version 14.0 was used for the analysis.
Results
Forty-seven patients were included in the analysis. Table 1 shows demographics and clinical characteristics at enrollment. Mean age was 58.57 ± 11.49 years and mean BMI was 27.15 ± 3.64 kg/m2. Most patients had type 2 DM (91.49%), and more than 10 years from DM diagnosis (77%). The most frequent prior pharmacological management was with insulin analogues (93.62%) for both basal insulin (glargine or detemir) and prandial insulin (aspart, lispro); only one subject analyzed was in basal-bolus management with insulin NPH (neutral protamine hagedorn) and insulin crystalline. In addition, 15% of patients were under management with at least one oral hypoglycemic agent type DDP4i.
Table 1.
Baseline Characteristics of Recruited Patients.
| Variable | N = 47 |
|---|---|
| Sex male, n (%) | 26 (55.32) |
| Age in years, mean (SD) | 58.57 ± 11.49 |
| BMI (kg/m2), mean (SD) | 27.15 ± 3.64 |
| Diabetes type | |
| Type 1, n (%) | 4 (8.51) |
| Type 2, n (%) | 43 (91.49) |
| Diabetes duration in years, n (%) | |
| <5 | 7 (14.89) |
| 5-10 | 4 (8.51) |
| >10 | 36 (76.60) |
| Previous therapy, n (%) | |
| Oral antidiabetic agents | 7 (14.89) |
| Basal insulin alone | 1 (2.12) |
| Basal-bolus insulin | 44 (93.62) |
| TDI (UI/day), mean (SD) | 27.15 ± 3.65 |
| TDI (IU/kg/day), mean (SD) | 0.68 ± 0.38 |
| Microvascular complications, n (%) | |
| Retinopathy | 40 (85.11) |
| Neuropathy | 15 (31.91) |
| Diabetic foot | 5 (10.64) |
| HbA1c | 8.41 ± 0.83 |
| Severe hypoglycemic episodes in last 6 months, median (IQR) | 2 (0-7) |
| Basal hemoglobin (gr/dl), mean (SD) | 12.34 (1.69) |
The etiology of end-stage renal impairment was diabetic nephropathy in 40 patients, hypertension in 1 case, autoimmune glomerulonephritis (1 patient), and unknown in 5 patients. In Table 2 are listed the characteristics associated with peritoneal dialysis. In all, 85% were assigned to automated peritoneal dialysis (APD), while the remaining group (15%) initiated management with continuous ambulatory peritoneal dialysis (CAPD). The dextrose solution for peritoneal dialysis contained a mean glucose load of 215.74 ± 60.33 g in 24 hours. According to the peritoneal equilibration test for glucose, it was found that 70.21% were low-affinity transporters, followed by 28% middle-affinity transporters and 2.13% high-affinity transporters, whereas for the peritoneal equilibration test for creatinine most were average-affinity transporters (66%).
Table 2.
Peritoneal Dialysis Therapy Characteristics and Peritoneal Equilibration Test for Glucose and Creatinine.
| N = 47 | |
|---|---|
| Type of PD, n (%) | |
| CAPD | 7 (14.89) |
| APD | 40 (85.11) |
| Type of APD prescription, n (%) | |
| Dry during day | 18 (45) |
| Wet during day | 19 (47.5) |
| CCPD + CAPD | 3 (7.5) |
| Dextrose solution, mean ± SD | |
| Glucose load (g/24 h) | 215.74 ± 60.33 |
| Glucose load in higher dialysate fluid exchange (g) | 383.76 ± 103.76 |
| Peritoneal equilibration test for glucose, n (%) | |
| Low | 33 (70.21) |
| Average | 13 (27.66) |
| High | 1 (2.13) |
| Peritoneal equilibration test for creatinine, n (%) | |
| Low | 12 (25.53) |
| Average | 31 (65.96) |
| High | 4 (8.51) |
Preintervention mean HbA1c value was 8.41% ± 0.83. Three months after of initiated the educational program and basal-bolus insulin regimen, a clinically and statistically significant decrease up to 7.68% ± 1.32 was observed (mean difference: −0.739, 95% CI, −0.419, −1.059, P < .0001). At the end of study, 52.2% subjects achieved HbA1c levels below 7.5%.
The accuracy of sensor was evaluated, The MARD of CGM performed before the intervention was 14.64% (SD 6.16), and 18.96% (SD 7.5) for CGM performed after it. According to CGM, the pre-intervention mean blood glucose value was 194.03 ± 42.55 mg/dl, with a significant reduction of up to 172.97 ± 31.85 mg/dl (P = .0015) at the end of study. When diurnal and nocturnal CGM data were submitted to a disaggregated analysis, significant reductions were observed in mean blood glucose value from 185.72 ± 41.80 mg/dl to 168.39 ± 29.34 mg/dl (P < .01) and from 202.35 ± 47.63 mg/dl to 177.55 ± 165.52 mg/dl (P < .01), respectively. Figure 1a shows a comparison between pre- and 24-hour postintervention CGM mean blood glucose values of the pooled study population. Figures 1b and 1c shows the same information disaggregated for APD and CAPD patients.
Figure 1.
Preintervention and end-of-study 24-hour mean glucose profile as measured by continuous glucose monitoring. (A) Total population. (B) Population on continuous peritoneal ambulatory dialysis (CAPD). (C) Automated peritoneal dialysis. Dots represent preintervention mean glucose value and Xs represent mean level at the end of study. Mean and SD are calculated based on glucose measures at specific hours.
When comparing the number of episodes of hypoglycemia (<54 mg/dl) detected in pre-intervention CGM (10 episodes) with CGM at the end of study (14 episodes), no statistically significant increase was observed (P = .7739). Similarly, no significant differences in the incidence of episodes of hypoglycemia were evidenced when comparing diurnal episodes (P = .3701) and nocturnal episodes (P = .5724), or when comparing episodes occurring with APD (P = .6444) and CAPD (P = .8187) (Table 3).
Table 3.
Pre- and Postintervention Hypoglycemia Events.
| Mean ± SD |
P value | ||
|---|---|---|---|
| Pre | Post | ||
| Total events of hypoglycemia <54, n (%) | |||
| 0 | 40 (85.1) | 38 (80.9) | .7739 |
| 1 | 4 (8.5) | 5 (10.6) | |
| 2 | 3 (6.4) | 3 (6.4) | |
| 3 | 0 (0.0) | 1 (2.1) | |
| Diurnal events of hypoglycemia <54, n (%) | |||
| 0 | 41 (87.2) | 41 (87.2) | .3701 |
| 1 | 4 (8.5) | 5 (10.6) | |
| 2 | 2 (4.3) | 1 (2.1) | |
| 3 | 0 (0.0) | 0 (0.0) | |
| Nocturnal events of hypoglycemia <54, n (%) | |||
| 0 | 43 (91.5) | 41 (87.2) | .5724 |
| 1 | 4 (8.5) | 4 (8.5) | |
| 2 | 0 (0.0) | 1 (2.1) | |
| 3 | 0 (0.0) | 1 (2.1) | |
| Total events of hypoglycemia <54, APD, n (%) | |||
| 0 | 36 (90.0) | 33 (82.5) | .6444 |
| 1 | 2 (5.0) | 4 (10.0) | |
| 2 | 2 (5.0) | 2 (5.0) | |
| 3 | 0 (0.0) | 1 (2.5) | |
| Diurnal events of hypoglycemia <54, APD, n (%) | |||
| 0 | 36 (90.0) | 35 (87.5) | .2998 |
| 1 | 2 (5.0) | 4 (10.0) | |
| 2 | 2 (5.0) | 1 (2.5) | |
| Nocturnal events of hypoglycemia <54, APD, n (%) | |||
| 0 | 39 (97.5) | 33 (82.5) | .1870 |
| 1 | 1 (2.5) | 4 (10.0) | |
| 2 | 0 (0.0) | 2 (5.0) | |
| 3 | 0 (0.0) | 1 (2.5) | |
| Total events of hypoglycemia <54, CAPD, n (%) | |||
| 0 | 4 (57.1) | 5 (71.4) | .8187 |
| 1 | 2 (28.6) | 1 (14.3) | |
| 2 | 1 (14.3) | 1 (14.3) | |
| Diurnal events of hypoglycemia <54 CAPD, n (%) | |||
| 0 | 5 (71.4) | 6 (85.7) | .3173 |
| 1 | 2 (28.6) | 1 (14.3) | |
| Nocturnal events of hypoglycemia <54 CAPD, n (%) | |||
| 0 | 4 (57.1) | 6 (85.7) | .3173 |
| 1 | 3 (42.9) | 1 (14.3) | |
The rows represent the amount of patients in each category according with the number of hypoglycemia events during the continuous glucose monitoring.
No significant differences were found in area under the curve of total episodes of hypoglycemia <54 mg/dl (P = .9528) and <70 mg/dl (P = .9850). Similar results were evidenced for AUC <54 mg/dl of diurnal (P = .8089) and nocturnal (P = .6606) episodes of hypoglycemia. In contrast, a significant decrease was observed in AUC >180 (P < .01) and AUC >250 (P = .01) for both total episodes and diurnal and nocturnal episodes (Table 4).
Table 4.
Area Under the Curve of Pre- and Postintervention Hypo and Hyperglycemia Episodes.
| Mean ± SD |
P value | ||
|---|---|---|---|
| Pre | Post | ||
| AUC <54 (overall) | 0.027 ± 0.12 | 0.026 ± 0.06 | .9526 |
| Diurnal monitoring | 0.021 ± 0.107 | 0.026 ± 0.08 | .8089 |
| Nocturnal monitoring | 0.030 ± 0.124 | 0.042 ± 0.12 | .6606 |
| AUC <70 (overall) | 0.173 ± 0.40 | 0.171 ± 0.34 | .9850 |
| Diurnal monitoring | 0.170 ± 0.408 | 0.138 ± 0.348 | .6972 |
| Nocturnal monitoring | 0.139 ± 0.411 | 0.268 ± 0.577 | .2229 |
| AUC >180 (overall) | 34.33 ± 29.07 | 19.96 ± 18.80 | <.01* |
| Diurnal monitoring | 30.67 ± 27.70 | 17.92 ± 17.98 | <.01* |
| Nocturnal monitoring | 40.91 ± 35.21 | 24.31 ± 26.17 | <.01* |
| AUC >250 (overall) | 10.16 ± 14.35 | 5.04 ± 8.11 | <.01* |
| Diurnal monitoring | 8.85 ± 12.43 | 4.29 ± 7.66 | <.01* |
| Nocturnal monitoring | 12.87 ± 19.49 | 6.60 ± 13.14 | .0270 |
Statistically significant difference.
No statistically significant difference was found in pre- and postintervention mean total daily insulin dose, adjusted for weight (0.68 ± 0.38 vs 0.73 ± 0.71 IU/kg/day, P = .63). A total of 15 patients (32%) required an additional detemir doses in the morning to achieve glucose goals before the dinner. The basal bolus ratio at first visit was 47% vs 53% respectively, and 57% vs 43% at the final visit.
Discussion
Patients with diabetes undergoing peritoneal dialysis with good glycemic control have lower mortality rates than those with poor control;7 however, this treatment goal often is not achieved due to the fear of hypoglycemia and therapeutic inertia. Our study shows that a therapeutic strategy based on education and a basal-bolus insulin regimen resulted in good metabolic control without a significant increase in episodes of hypoglycemia.
Nowadays, there is a controversy on which are the optimal values for glycemic control in diabetes patients with renal chronic disease. KDOQI Guidelines1 suggest HbA1c < 7% management goals for preventing or delaying the progression of microvascular complication of diabetes but are mainly focused in early stages of CKD and their applicability for patients with CKD undergoing dialysis is discussed. British guidelines have suggested less stringent glycemic control targets specific to patients undergoing dialysis and transplant patients (HbA1c 6.5%-7.5%).11 Data for defining optimal goals in patients undergoing PD are more limited. The impact of metabolic control, as measured by HbA1c in patients undergoing PD was specifically assessed in Duong’s study,12 and there was evidenced that a higher HbA1c level is associated with increased mortality, especially with levels above 8%.
This real-life study is the first to assess the impact of an intervention consisting of an educational program and a basal-bolus insulin regimen on the glycemic control for achieving such management goals. Results were significant, especially considering that all patients included had inappropriate metabolic control (in fact, one inclusion criterion was HbA1c levels > 7.5%). In all, 52.2% were able to reduce their levels to below the threshold after three months of treatment, with no significant increase in episodes of hypoglycemia.
Previous research intended to improve glycemic control in patients with DM undergoing PD has focused on evaluate the insulin administration route. A meta-analysis of nonrandomized clinical trials suggested that intraperitoneal insulin can improve glycemic control, as assessed with HbA1c compared con subcutaneous route.13 However, this treatment has not become popular for possible drawbacks like higher insulin requirements, lower HDL cholesterol levels and higher triglycerides levels. In addition, the impact on hypoglycemia rates is not clear. Few studies have evaluated the use of insulin analogues on patients with diabetes and chronic renal failure, and specially on those under dialysis.14 One study suggested that in patients with type 2 diabetes undergoing hemodialysis, insulin detemir had lower glycemic variability than with insulin glargine.15 Ours is the first study evaluating the use of insulin analogues as part of the treatment in patients under PD. Future research is needed to define the best analogues insulin regimen for these patients.
HbA1c has been questioned as an appropriate method to assessing glycemic control in CKD patients,16 since the erythrocyte’s half-life may be reduced by 30%-70% in these patients; and therefore, affecting the reduction of hemoglobin’s exposure to glucose and the HbAc1 levels.17 However, HbA1c continue to be the most used method and this is considered a key element in the evaluation of long-term glycemic control.18 The hemoglobin levels did not seem to be a significant issue in our population, considering adequate basal levels of hemoglobin (12.3 g/dl) associated with long term treatment provided to optimize it. A reasonable alternative for following up with these patients is CGM,19 since it allows detecting the glycemic variability associated with glucose absorption from PD glucose solutions and episodes of inadvertent hypoglycemia. This study results show that changes detected in glycemic control are consistent with both methods and support the use of HbA1c due to its greater availability and ease of use. However, they give room for CGM as a method for following up with patients with high glycemic variability and frequent episodes of hypoglycemia.
It is noteworthy that no significant change in total daily weight-adjusted insulin dose was performed in this study, which makes evident the importance of an educational strategy within the intervention program offered to patients. In addition, it is important to underline that the educational program should not only involve patients but also the medical and nursing staff in charge of training patients and adjusting the insulin regimen. An additional explanation is the split of basal and prandial insulin, the higher proportion of basal insulin at the end of the study could be key in achieve the goals of glycemic control.
The data allow us to conclude that our intervention has an impact. The lack of a control group, which would give us the opportunity to assess the behavior in both glycemic control and episodes of hypoglycemia in treatment-naïve population, is considered a limitation of the study. Our treatment program included different important components including education, goal driven therapy with basal bolus regime using insulin analogues, frequent and active titration and availability of advice from certified diabetes educators via the phone, however our design do not let us to identify the importance of each component separately. Further controlled studies are needed to assess the impact of each component. The low number of episodes of hypoglycemia is considered to be a second limitation; however, AUC <54 mg/dl and AUC <70 mg/dl, are consistent with the conclusion that there is no significant impact on the risk of hypoglycemia in these patients. Future research in this area should consider CGM data including at least 12 days, as has been suggested to evaluate adequately glycemic variability.20
Conclusion
In type 1 and type 2 diabetes mellitus patients undergoing peritoneal dialysis with HbA1c >7.5%; an intervention consisting of an educational diabetes program and an insulin detemir and aspart basal-bolus regimen for 3 months, showed a clinically and statistically significant reduction of HbA1c levels and mean blood glucose levels as measured by CGM, with no significant increase in hypoglycemia episode frequency from baseline. In addition, more than 50% patients achieved the goal of HbA1c <7.5%. Considering the importance of glycemic control for the prognosis of these patients, an effective and safe strategy allowing short-term control is a therapeutic addition of great interest for the population of patients with diabetes undergoing PD.
Acknowledgments
The authors acknowledge Andrés Mantilla, Carolina Larrarte, Eduardo Zuñiga, David Camargo, Juan Carlo Castillo (nephrologists who participated in data gathering), Marisol Vergara (study nurse and educator). Medical writing and editorial assistance was provided by Dr Oscar Muñoz and funded by a grant from NovoNordisk. The authors take full responsibility for the content and conclusions stated in this manuscript. NovoNordisk neither influenced the content of this publication nor was involved in the study design, data collection, analysis, or interpretation.
Footnotes
Abbreviations: APD, automated peritoneal dialysis; AUC, area under the curve; BMI, body mass index; CAPD, continuous ambulatory peritoneal dialysis; CCPD, continuous cycling peritoneal dialysis; CGM, continuous glucose monitoring; DM1, type 1 diabetes mellitus; DM2, type 2 diabetes mellitus; HbA1c, glycated hemoglobin; IQR, interquartile range; PD, peritoneal dialysis; RTS, Renal Therapy Services clinic network; SD, standard deviation; TDI, total daily insulin dose.
Declaration of Conflicting Interests: The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: AMG reports speaker fees from NovoNordisk, Elli Lilly, MSD, Novartis, and Medtronic and research grants from Medtronic, Novartis, and Abbott. AJR reports speaker fees from Sanofi, Amgen, Valentech, AstraZeneca, Pfizer, and Tecnoquímicas, and research grants from Sanofi and Abbott. OMM reports research grants from NovoNordisk. No other potential conflicts of interest are reported.
Funding: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Research grant was provided by Baxter International Inc., renal division. The authors take full responsibility for the content and conclusions stated in this manuscript. Baxter neither influenced the content of this publication nor was involved in the study design, data collection, analysis, or interpretation.
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