Blood glucose fluctuations in hemodialysis patients with end stage diabetic nephropathy

What is the optimal dialysis method for diabetic patients with end stage kidney disease?

Diabetes is one of the most catastrophic diseases ruling every corner of the world, and this has led to elevated incidents of end-stage kidney disease (ESKD). The standard treatment for ESKD is kidney transplantation/replacement, which is limited due to a deficiency of donors. Hence, dialysis has become the second-best option for treating patients with ESKD. Patients with ESKD with underlying diabetes have an additional risk of complications and infections over non-diabetic ESKD patients. Furthermore, these patients also experience variations in blood glucose levels and are more liable to develop malnutrition. This article elaborates on the different dialysis methods for ESKD patients. This editorial highlights the evidence-based studies that include randomized clinical trials, cohort studies, retrospective studies and case-control studies and suggests the most suitable type of dialysis under the following components.

Efficacy of continuous glucose monitoring in people living with diabetes and end stage kidney disease on dialysis: a systematic review

BACKGROUND

Patients with diabetes on dialysis experience wide variations in glucose levels and an increased risk of hypoglycaemia. Due to the inaccuracies of HbA1c in dialysis patients, JBDS-IP and KDIGO recommend the use of continuous glucose monitoring (CGM). We conducted a systematic review to examine the current evidence for CGM use and its impact on clinical outcomes in patients with diabetes on dialysis.

METHODS

A search of MEDLINE(R) ALL, Ovid Emcare, Journals@Ovid Full Text and Embase databases were conducted. Clinical or observational trials in adults with Type 1(T1D) or Type 2 (T2D) diabetes on dialysis and CGM intervention reporting on glycaemic outcomes were included.

RESULTS

Of the 936 citations identified, 49 duplicates were removed. 887 citations were screened by title and abstract. 9 full texts were reviewed and a further 7 excluded due to duplications or failure to meet to selection criteria. Data was extracted for 2 studies, both prospective before-and-after interventional studies with no control group. Joubert et al. (2015) showed results for 15 participants with T1D. Mean CGM glucose level decreased from 8.37mmol/L at baseline to 7.7mmol/L at the end of the CGM period (p < 0.05) while HbA1c decreased from 6.9 to 6.5% (p < 0.05) during the same period. Mean CGM was lower on dialysis days (7.68mmol/L vs. 7.8mmol/L, p < 0.05). Képénékian et al. (2014) reported on data from 29 T2D patients. Following a 3 month CGM-adapted insulin regimen, HbA1c decreased from 8.4% at baseline to 7.6% (p < 0.01) by the end of study. Mean CGM values decreased from 9.9mmol/L to 8.9mmol/L (p = 0.05) and the frequency of glucose values > 10mmol/L decreased from 41 to 30% (p < 0.05), without a significant increase in hypoglycaemia frequency. Both studies were deemed to be of 'good' quality.

CONCLUSION

Evidence demonstrating the benefits of CGM in patients with diabetes receiving dialysis is lacking. There is a need for well-designed randomised controlled trials to ascertain the benefits of this technology in this patient group.

TRAIL REGISTRATION

PROSPERO registration number: CRD42023371635, https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=371635 .

Selection of dialysis methods for end-stage kidney disease patients with diabetes

The increasing prevalence of diabetes has led to a growing population of end-stage kidney disease (ESKD) patients with diabetes. Currently, kidney transplantation is the best treatment option for ESKD patients; however, it is limited by the lack of donors. Therefore, dialysis has become the standard treatment for ESKD patients. However, the optimal dialysis method for diabetic ESKD patients remains controversial. ESKD patients with diabetes often present with complex conditions and numerous complications. Furthermore, these patients face a high risk of infection and technical failure, are more susceptible to malnutrition, have difficulty establishing vascular access, and experience more frequent blood sugar fluctuations than the general population. Therefore, this article reviews nine critical aspects: Survival rate, glucose metabolism disorder, infectious complications, cardiovascular events, residual renal function, quality of life, economic benefits, malnutrition, and volume load. This study aims to assist clinicians in selecting individualized treatment methods by comparing the advantages and disadvantages of hemodialysis and peritoneal dialysis, thereby improving patients' quality of life and survival rates.

Continuous glucose monitoring in people with diabetes and end-stage kidney disease-review of association studies and Evidence-Based discussion

Diabetic nephropathy is currently the leading cause of end-stage kidney disease. The present methods of assessing diabetes control, such as glycated hemoglobin or self-monitoring of blood glucose, have limitations. Over the past decade, the field of continuous glucose monitoring has been greatly improved and expanded. This review examines the use of continuous glucose monitoring in people with end-stage kidney disease treated with hemodialysis (HD), peritoneal dialysis (PD), or kidney transplantation. We assessed the use of both real-time continuous glucose monitoring and flash glucose monitoring technology in terms of hypoglycemia detection, glycemic variability, and efficacy, defined as an improvement in clinical outcomes and diabetes control. Overall, the use of continuous glucose monitoring in individuals with end-stage kidney disease may improve glycemic control and detection of hypoglycemia. However, most of the published studies were observational with no control group. Moreover, not all studies used the same assessment parameters. There are very few studies involving subjects on peritoneal dialysis. The small number of studies with limited numbers of participants, short follow-up period, and small number of manufacturers of continuous glucose monitoring systems are limitations of the review. More studies need to be performed to obtain more reliable results.

Evaluating glucose variability through OGTT in early pregnancy and its association with hypertensive disorders of pregnancy in non-diabetic pregnancies: a large-scale multi-center retrospective study

BACKGROUND

Recent evidence suggests increased glucose variability (GV) causes endothelial dysfunction, a central pathology of hypertensive disorders of pregnancy (HDP). We aimed to investigate the association between GV in early pregnancy and subsequent HDP development among non-diabetes mellitus (DM) pregnancies.

METHODS

This multicenter retrospective study used data from singleton pregnancies between 2009 and 2019. Among individuals who had 75 g-OGTT before 20 weeks of gestation, we evaluated GV by 75 g-OGTT parameters and examined its relationship with HDP development, defining an initial-increase from fasting-plasma glucose (PG) to 1-h-PG and subsequent-decrease from 1-h-PG to 2-h-PG.

RESULTS

Approximately 3.0% pregnancies (802/26,995) had 75 g-OGTT before 20 weeks of gestation, and they had a higher prevalence of HDP (14.3% vs. 7.5%). The initial-increase was significantly associated with overall HDP (aOR 1.20, 95% CI 1.02-1.42), and the subsequent-decrease was associated with decreased and increased development of early-onset (EoHDP: aOR 0.56, 95% CI 0.38-0.82) and late-onset HDP (LoHDP: aOR 1.38, 95% CI 1.11-1.73), respectively.

CONCLUSIONS

A pattern of marked initial-increase and minor subsequent-decrease (i.e., sustained hyperglycemia) was associated with EoHDP. Contrarily, the pattern of marked initial-increase and subsequent-decrease (i.e., increased GV) was associated with LoHDP. This provides a new perspective for future study strategies.

Glucagon-like peptide 1 receptor agonists in end-staged kidney disease and kidney transplantation: A narrative review

AIMS

Glucagon-like peptide 1 receptor agonists (GLP-1RA) improve glycemic control and promote weight loss in type 2 diabetes (DM2) and obesity. We identified studies describing the metabolic benefits of GLP-1RA in end-staged kidney disease (ESKD) and kidney transplantation.

DATA SYNTHESIS

We searched for randomized controlled trials (RCTs) and observational studies that investigated the metabolic benefits of GLP-1RA in ESKD and kidney transplantation. We summarized the effect of GLP-1RA on measures of obesity and glycemic control, examined adverse events, and explored adherence with therapy. In small RCTs of patients with DM2 on dialysis, liraglutide for up to 12 weeks lowered HbA1c by 0.8%, reduced time in hyperglycemia by ∼2%, lowered blood glucose by 2 mmol/L and reduced weight by 1-2 kg, compared with placebo. In prospective studies inclusive of ESKD, 12 months of semaglutide reduced HbA1c by 0.8%, and contributed to weight losses of 8 kg. In retrospective cohort studies in DM2 and kidney transplantation, 12 months of GLP-1RA lowered HbA1c by 2%, and fasting glucose by ∼3 mmol/L compared with non-use, and in some reports, weight losses of up to 4 kg were described. Gastrointestinal (GI) side effects were most commonly reported, with hypoglycemia described with GLP-1RA in hemodialysis, particularly in those using insulin.

CONCLUSIONS

GLP-1RA are growing in popularity in those with DM2 and obesity. In small RCTs and observational cohort studies modest glycemic and weight benefits have been described in ESKD and transplantation, but GI side effects may limit adherence. Larger and longer term studies of GLP-1RA remain important.

Glucose variability in maintenance hemodialysis patients with type 2 diabetes: Comparison of dialysis and nondialysis days

INTRODUCTION

Hemodialysis (HD) induces several physiological changes that can affect plasma glucose levels in patients with diabetes and in turn their glycemic control. Studies using continuous glucose monitoring (CGM) to assess glucose variations on dialysis days compared with nondialysis days report conflicting results. Here, we used CGM to examine glucose variations induced by HD in patients with type 2 diabetes.

METHODS

Patients with type 2 diabetes undergoing maintenance HD were included. CGM (Ipro2®, Medtronic) was performed at baseline and Week 4, 8, 12, and 16 for up to 7 days at each visit. CGM profiles on days where participants received HD were compared with days without HD using a linear mixed model.

FINDINGS

Twenty-seven patients were included. The median number of CGM days performed was 8 (interquartile range [IQR] 6-10) for dialysis days and 16 (IQR 12-17) for nondialysis days. The median sensor glucose was 9.4 (95% confidence interval [CI] 8.8-10.2) mmol/L on dialysis days compared with 9.5 (95% CI 8.9-10.2) mmol/L on nondialysis days (p = 0.58). Nocturnal mean sensor glucose was higher on dialysis days compared with nondialysis days: 8.8 (95% CI 8.0-9.6) mmol/L versus 8.4 (95% CI 7.7-9.2) mmol/L (p = 0.029).

DISCUSSION

Similar median sensor glucose values were found for days on and off HD. Nocturnal glucose levels were modestly increased on dialysis days. Our findings indicate that antidiabetic treatment does not need to be differentiated on dialysis versus nondialysis days in patients with type 2 diabetes undergoing maintenance HD.

Novel clinical relationships between time in range and microangiopathies in people with type 2 diabetes mellitus on hemodialysis

AIMS/HYPOTHESIS

We investigated associations among glucose time in range (TIR, 70-180 mg/dL), glycemic markers and prevalence of diabetic microangiopathy in people with diabetes undergoing hemodialysis (HD).

METHODS

A total of 107 people with type 2 diabetes undergoing HD (HbA_1c 6.4 %; glycated albumin [GA] 20.6 %) using continuous glucose monitoring were analyzed in this observational and cross-sectional study.

RESULTS

HbA_1c and GA levels significantly negatively correlated with TIR, and positively correlated with time rate of hyperglycemia, but not with time rate of hypoglycemia. TIR of 70 % corresponded to HbA_1c of 6.5 % and GA of 21.2 %. The estimated HbA_1c level corresponding to TIR of 70 % in this study was lower than that previously reported in people with diabetes without HD. The prevalence of diabetic neuropathy was not significantly different between people with TIR ≥ 70 % and those with TIR < 70 % (P = 0.1925), but the prevalence of diabetic retinopathy in people with TIR ≥ 70 % was significantly lower than in those with TIR < 70 % (P = 0.0071).

CONCLUSION/INTERPRETATION

TIR correlated with HbA_1c and GA levels in people with type 2 diabetes on HD. Additionally, a higher TIR resulted in a lower rate of diabetic retinopathy.

RESEARCH IN CONTEXT

What is already known about this subject? What is the key question? What are the new findings? How might this impact on clinical practice in the foreseeable future?

Continuous Glucose Monitoring to Optimize Management of Diabetes in Patients with Advanced CKD

Treatment of patients with diabetes and CKD includes optimizing glycemic control using lifestyle modifications and drugs that safely control glycemia and improve clinical kidney and cardiovascular disease outcomes. However, patients with advanced CKD, defined as eGFR <30 ml/min per 1.73 m2 or kidney disease treated with dialysis, have limitations to the use of some preferred glucose-lowering medications, are often treated with insulin, and experience high rates of severe hypoglycemia. Moreover, hemoglobin A1c accuracy decreases as GFR deteriorates. Hence, there is a need for better glycemic monitoring tools. Continuous glucose monitoring allows for 24-hour glycemic monitoring to understand patterns and the effects of lifestyle and medications. Real-time continuous glucose monitoring can be used to guide the administration of insulin and noninsulin therapies. Continuous glucose monitoring can overcome the limitations of self-monitored capillary glucose testing and hemoglobin A1c and has been shown to prevent hypoglycemic excursions in some populations. More data are needed to understand whether similar benefits can be obtained for patients with diabetes and advanced CKD. This review provides an updated approach to management of glycemia in advanced CKD, focusing on the role of continuous glucose monitoring in this high-risk population.

Making sense of glucose sensors in end-stage kidney disease: A review

Diabetes mellitus remains the leading cause of end-stage kidney disease worldwide. Inadequate glucose monitoring has been identified as one of the gaps in care for hemodialysis patients with diabetes, and lack of reliable methods to assess glycemia has contributed to uncertainty regarding the benefit of glycemic control in these individuals. Hemoglobin A1c, the standard metric to evaluate glycemic control, is inaccurate in patients with kidney failure, and does not capture the full range of glucose values for patients with diabetes. Recent advances in continuous glucose monitoring have established this technology as the new gold standard for glucose management in diabetes. Glucose fluctuations are uniquely challenging in patients dependent on intermittent hemodialysis, and lead to clinically significant glycemic variability. This review evaluates continuous glucose monitoring technology, its validity in the setting of kidney failure, and interpretation of glucose monitoring results for the nephrologist. Continuous glucose monitoring targets for patients on dialysis have yet to be established. While continuous glucose monitoring provides a more complete picture of the glycemic profile than hemoglobin A1c and can mitigate high-risk hypoglycemia and hyperglycemia in the context of the hemodialysis procedure itself, whether the technology can improve clinical outcomes merits further investigation.

Flash glucose monitoring system in special situations

The management of diabetes mellitus (DM) requires maintaining glycemic control, and patients must keep their blood glucose levels close to the normal range to reduce the risk of microvascular complications and cardiovascular events. While glycated hemoglobin (A1C) is currently the primary measure for glucose management and a key marker for long-term complications, it does not provide information on acute glycemic excursions and overall glycemic variability. These limitations may even be higher in some special situations, thereby compromising A1C accuracy, especially when wider glycemic variability is expected and/or when the glycemic goal is more stringent. To attain adequate glycemic control, continuous glucose monitoring (CGM) is more useful than self-monitoring of blood glucose (SMBG), as it is more convenient and provides a greater amount of data. Flash Glucose Monitoring (isCGM /FGM) is a widely accepted option of CGM for measuring interstitial glucose levels in individuals with DM. However, its application under special conditions, such as pregnancy, patients on hemodialysis, patients with cirrhosis, during hospitalization in the intensive care unit and during physical exercise has not yet been fully validated. This review addresses some of these specific situations in which hypoglycemia should be avoided, or in pregnancy, where strict glycemic control is essential, and the application of isCGM/FGM could alleviate the shortcomings associated with poor glucose control or high glycemic variability, thereby contributing to high-quality care.

Targeting Predialysis Glucose up to 180 mg/dl Reduces Glycemic Variability in End Stage Diabetic Nephropathy

Context

Glycemic variability plays a major role in the development as well as the progression of cardiovascular disease in diabetes.

Aims

We compared the mean plasma glucose and glycemic variability (GV) parameters on and off hemodialysis (HD) in patients with End-Stage Diabetic Nephropathy (ESDN) and End-Stage Renal Disease (ESRD).

Settings and Design

Cross-sectional study.

Methods and Material

We included 23 ESDN and 6 ESRD patients who underwent continuous glucose monitoring (CGM) (iPro2) for 6 days and a glucose-free dialysate for 4 hours thrice weekly. EasyGV software was used to calculate the variability parameters {mean glucose, Time in range (TIR), Time above and below range (TAR/TBR), CV (Coefficient of Variation) and MAGE}.

Statistical Analysis Used

The quantitative data variables were expressed by using mean and SD. Unpaired t-test was used to compare the two groups. P value <0.05 was considered significant.

Results

In the ESDN group, TIR was significantly lower whereas TAR and TBR were significantly higher on HD day. MAGE (101.88 ± 40.5 v/s 89.46 ± 30.0, P < 0.007) and CV (29.41% v/s 21.67%) were higher on HD day. Subjects with pre-HD glucose values ≥180 mg/dl (Group B, n = 24) had a rapid drop with a delayed higher rise in glucose values than those with pre-HD glucose values <180 mg/dl (Group A, n = 27). Ten patients had 13 episodes of hypoglycemia. The CGM parameters were not different in the ESRD group.

Conclusions

Targeting a pre- HD glucose value <180 mg/dl could be a good strategy to prevent larger fluctuation during and post HD.

Blood Glucose Fluctuation in Older Adults with Diabetes Mellitus and End-Stage Renal Disease on Maintenance Hemodialysis: An Observational Study

INTRODUCTION

Patients with diabetes mellitus and end-stage renal disease are at a high risk of developing coronary, cerebrovascular, and peripheral vascular diseases. This study aimed to characterize hypoglycemia and blood glucose fluctuations associated with maintenance hemodialysis in older adult patients with diabetes mellitus and end-stage renal disease using a continuous glucose monitoring system.

METHODS

Seven patients were enrolled in this study, and 13 pairs of continuous glucose monitoring system data were collected. Each pair included data of 1 dialysis-on day and 1 dialysis-off day. Information on basic patient characteristics, including age, diabetes mellitus duration, hemodialysis duration, and proportions of hemoglobin A1c and glycated albumin, were collected. Differences in blood glucose fluctuation were compared between dialysis-on days and dialysis-off days.

RESULTS

The mean blood glucose on dialysis-on days (6.96 ± 2.57 mmol/L) was significantly lower than that on dialysis-off days (7.68 ± 2.31 mmol/L; P < 0.05). In contrast, the following parameters had significantly higher values (all P < 0.05) on dialysis-on days compared to dialysis-off days: large amplitude of glycemic excursion level (5.82 ± 2.86 mmol/L versus 4.21 ± 1.71 mmol/L), large amplitude of glycemic excursion level from 8 a.m. to 2 p.m. (3.6 ± 1.74 mmol/L versus 2.8 ± 1.33 mmol/L), mean amplitude of glycemic excursion level (4.78 ± 1.68 mmol/L versus 3.89 ± 1.67 mmol/L), mean amplitude of glycemic excursion level from 8 a.m. to 2 p.m. (4.01 ± 1.03 mmol/L versus 3.12. ± 0.97 mmol/L), standard deviation of blood glucose (1.55 ± 0.89 mmol/L versus 1.03 ± 0.4 mmol/L), and time below a target glucose range of less than 3.9 mmol/L (8.27% versus 4.25%).

CONCLUSION

Fluctuations in blood glucose levels were larger on dialysis-on days, particularly from the start of hemodialysis to 2 h post-hemodialysis, than on dialysis-off days. Hypoglycemia, as indicated by the time below a target glucose range of less than 3.9 mmol/L, occurred more frequently on dialysis-on days than on dialysis-off days.

Use of a Continuous Glucose Monitoring System in High Risk Hospitalized Non-critically ill Patients with Diabetes after Cardiac Surgery and during their Transition of Care from the Intensive Care Unit during Covid-19-A Pilot Study

OBJECTIVE

Continuous glucose monitoring (CGM) has demonstrated benefits in managing inpatient diabetes. We initiated this single-arm pilot feasibility study during the COVID-19 pandemic in 11 patients to determine the feasibility and accuracy of real-time CGM in cardiac surgery patients with diabetes after their transition of care from the intensive care unit(ICU).

METHODS

Clarke Error Grid(CEG) analysis was used to compare CGM and point-of-care(POC) measurements. Mean absolute relative difference(MARD) of the paired measurements was calculated to assess the accuracy of the CGM for glucose measurements during the first 24 hours on CGM, the remainder of time on the CGM as well as for different chronic kidney disease(CKD) strata.

RESULTS

Overall MARD between POC and CGM measurements was 14.80%. MARD for patients without CKD IV and V with eGFR < 20 ml/min/1.73m² was 12.13%. Overall, 97% of the CGM values were within the no-risk zone of the CEG analysis. For the first 24 hours, a sensitivity analysis of the overall MARD for all subjects and for those with eGFR > 20 ml/min/1.73m² was 15.42% (+/- 14.44) and 12.80% (+/- 7.85) respectively. Beyond the first 24 hours, overall MARD for all subjects and for those with eGFR > 20 ml/min/1.73m² was 14.54% (+/- 13.21) and 11.86% (+/- 7.64) respectively.

CONCLUSIONS

CGM has great promise to optimize inpatient diabetes management in the noncritical care setting and after the transition of care from the ICU with high clinical reliability, and accuracy. More studies are needed to further assess CGM in patients with advanced CKD.

Use of Continuous Glucose Monitoring in the Assessment and Management of Patients With Diabetes and Chronic Kidney Disease

In developed countries, diabetes is the leading cause of chronic kidney disease (CKD) and accounts for 50% of incidence of end stage kidney disease. Despite declining prevalence of micro- and macrovascular complications, there are rising trends in renal replacement therapy in diabetes. Optimal glycemic control may reduce risk of progression of CKD and related death. However, assessing glycemic control in patients with advanced CKD and on dialysis (G4-5) can be challenging. Laboratory biomarkers, such as glycated haemoglobin (HbA_1c), may be biased by abnormalities in blood haemoglobin, use of iron therapy and erythropoiesis-stimulating agents and chronic inflammation due to uraemia. Similarly, glycated albumin and fructosamine may be biased by abnormal protein turnover. Patients with advanced CKD exhibited heterogeneity in glycemic control ranging from severe insulin resistance to 'burnt-out' beta-cell function. They also had high risk of hypoglycaemia due to reduced renal gluconeogenesis, frequent use of insulin and dysregulation of counterregulatory hormones. Continuous glucose monitoring (CGM) systems measure glucose in interstitial fluid every few minutes and provide an alternative and more reliable method of glycemic assessment, including asymptomatic hypoglycaemia and hyperglycaemic excursions. Recent international guidelines recommended use of CGM-derived Glucose Management Index (GMI) in patients with advanced CKD although data are scarce in this population. Using CGM, patients with CKD were found to experience marked glycemic fluctuations with hypoglycemia due to loss of glucose and insulin during haemodialysis (HD) followed by hyperglycemia in the post-HD period. On the other hand, during peritoneal dialysis, patients may experience glycemic excursions with influx of glucose from dialysate solutions. These undesirable glucose exposure and variability may accelerate decline of residual renal function. Although CGM may improve the quality of glycemic monitoring and control in populations with CKD, further studies are needed to confirm the accuracy, optimal mode and frequency of CGM as well as their cost-effectiveness and user-acceptability in patients with advanced CKD and dialysis.

Association of glycemic variability and hypoglycemia with distal symmetrical polyneuropathy in adults with type 1 diabetes

Previous studies exploring the influence of glycemic variability (GV) on the pathogenesis of distal symmetrical polyneuropathy (DSPN) in type 1 diabetes (T1DM) produced conflicting results. The aim of this study was to assess the relationship between GV and DSPN in T1DM. Adults with T1DM were included in this cross-sectional study and asked to undergo 3-day CGM. GV quantified by coefficient of variation (CV) and mean amplitude of glucose excursions (MAGE) were obtained from CGM. Clinical characteristics and biochemical assessments were collected for analysis. The study comprised 152 T1DM patients (53.9% males) with mean age of 44.2 year. Higher levels of age and duration of diabetes and lower levels of total cholesterol, LDL, fasting C-peptide and postprandial C-peptide were observed in DSPN subjects. DSPN groups displayed a higher blood glucose between 00:00 and 12:59 according to the CGM profile. Higher MAGE and CV were associated with increased risk of DSPN in the fully adjusted model. Meanwhile, a significant association between measurements of hypoglycemia, especially nocturnal hypoglycemia, and DSPN was found after multiple tests. CGM parameters describing the glycemic variability and hypoglycemia were potential risk factors for DSPN in adults with T1DM.

Continuous glucose monitoring in patients with type 2 diabetes on hemodialysis

Diabetic kidney disease is the leading cause of end-stage kidney disease in high-income countries. The strict control of glycemic oscillations is the principal therapeutic target, but this could be hard to achieve in uremic patients due to their unpredictable insulin sensitivity. Currently, the evaluation of the glycemic profile relies on serum markers (glycated hemoglobin HbA1c, glycated albumin, and fructosamine), capillary glucose blood control (self-monitoring of blood glucose), and interstitial glucose control (continue glucose monitoring). We conducted a systematic review of published articles on continue glucose monitoring in hemodialysis patients with type 2 diabetes, which included 12 major articles. Four studies found significant fluctuations in glucose levels during hemodialysis sessions. All studies reported a higher mean amplitude of glucose variations on the hemodialysis day. Three studies agreed that continue glucose monitoring is better than glycated hemoglobin in detecting these abnormalities. Moreover, continue glucose monitoring was more accurate and perceived as easier to use by patients and their caregivers. In patients with type 2 diabetes on hemodialysis, glucose levels show different variation patterns than the patients on hemodialysis without diabetes. Considering manageability, accuracy, and cost-effectiveness, continue glucose monitoring could be the ideal diagnostic tool for the patient with diabetes on hemodialysis.

Prevalence of glycemic variability and factors associated with the glycemic arrays among end-stage kidney disease patients on chronic hemodialysis

Glycemic variability (GV) confers a significantly higher risk of diabetic-related complications, especially cardiovascular. Despite extensive research in this area, data on end-stage kidney disease (ESKD) patients on chronic hemodialysis are scarce. This study aims to determine the magnitude of GV among ESKD (diabetic vs nondiabetic) patients and its associated factors on hemodialysis days (HDD) and non-hemodialysis days (NHDD) where postulation of a higher GV observed among diabetic on HDD.We recruited 150 patients on hemodialysis, 93 patients with type 2 diabetic (DM-ESKD), and 57 with nondiabetic (NDM-ESKD). The GV indices (standard deviation [SD] and percentage coefficient variant [%CV]) were obtained from 11-point and 7-point self-monitoring blood glucose (fasting to post-meal) (SMBG) profiles on HDD and NHDD. The GV indices and its associated factors of both DM-ESKD and NDM-ESKD were analyzed to compare HDD vs NHDD.Mean blood glucose on HDD was 9.33 [SD 2.7, %CV 30.6%] mmol/L in DM-ESKD compared with 6.07 [SD 0.85, %CV 21.3%] mmol/L in NDM-ESKD (P = <.01). The DM-ESKD group experienced significantly above target GV indices compared to NDM-ESKD on both HDD and NHDD, particularly in the subgroup with HbA1c 8-10% (P = <.01). Presence of diabetes, older age, hyperlipidemia, HbA1c, ferritin levels, and albumin were identified as factors associated with GV.DM-ESKD patients have above-target GV indices, especially on HDD, therefore increasing their risk of developing future complications. We identified high HbA1c, older age group, presence of hyperlipidemia, ferritin levels, and albumin as factors associated with GV indices that may be used as surrogate markers for GV. Since these groups of patients are vulnerable to CVD mortality, urgent attention is needed to rectify it.

Flash Glucose Monitoring to Assess Glycemic Control and Variability in Hemodialysis Patients: The GIOTTO Study

Background: Flash glucose monitoring (FGM) is a technology with considerable differences compared to continuous glucose monitoring (CGM), but it has been scarcely studied in hemodialysis patients. Thus, we aimed assessing the performance of FGM in such patients by comparison to self-monitoring of blood glucose (SMBG). We will also focus on estimation of glycemic control and variability, and their relationships with parameters of glucose homeostasis.

Methods: Thirty-one patients (20 with type 2 diabetes, T2DM, 11 diabetes-free, NODM) collected readings by FGM and SMBG for about 12 days on average. Readings by FGM and SMBG were compared by linear regression, Clarke error grid, and Bland-Altman analyses. Several indices of glycemic control and variability were computed. Ten patients also underwent oral glucose tolerance test (OGTT) for assessment of insulin sensitivity/resistance and insulin secretion/beta-cell function.

Results: Flash glucose monitoring and SMBG readings showed very good agreement in both T2DM and NODM (on average, 97 and 99% of readings during hemodialysis in A+B Clarke regions, respectively). Some glycemic control and variability indices were similar by FGM and SMBG (p = 0.06–0.9), whereas others were different (p = 0.0001–0.03). The majority of control and variability indices were higher in T2DM than in NODM, according to both FGM and SMBG (p = 0.0005–0.03). OGTT-based insulin secretion was inversely related to some variability indices according to FGM (R < −0.72, p < 0.02).

Conclusions: Based on our dataset, FGM appeared acceptable for glucose monitoring in hemodialysis patients, though partial disagreement with SMBG in glycemic control/variability assessment needs further investigations.

Hemodialysis-Related Glycemic Disarray Proven by Continuous Glucose Monitoring; Glycemic Markers and Hypoglycemia

OBJECTIVE

There is a high risk of asymptomatic hypoglycemia associated with hemodialysis (HD) using glucose-free dialysate; therefore, the inclusion of glucose in the dialysate is believed to prevent intradialytic hypoglycemia. However, the exact glycemic fluctuation profiles and frequency of asymptomatic hypoglycemia using dialysates containing >100 mg/dL glucose have not been determined.

RESEARCH DESIGN AND METHODS

We evaluated the glycemic profiles of 98 patients, 68 of whom were men, with type 2 diabetes undergoing HD (HbA_1c 6.4 ± 1.2%; glycated albumin 20.8 ± 6.8%) with a dialysate containing 100, 125, or 150 mg/dL glucose using continuous glucose monitoring.

RESULTS

Sensor glucose level (SGL) showed a sustained decrease during HD, irrespective of the dialysate glucose concentration, and reached a nadir that was lower than the dialysate glucose concentration in 49 participants (50%). Twenty-one participants (21%) presented with HD-related hypoglycemia, defined by an SGL <70 mg/dL during HD and/or between the end of HD and their next meal. All these hypoglycemic episodes were asymptomatic. Measures of glycemic variability calculated using the SGL data (SD, coefficient of variation, and range of SGL) were higher and time below range (<70 mg/dL) was lower in participants who experienced HD-related hypoglycemia than in those who did not, whereas time in range between 70 and 180 mg/dL, time above range (>180 mg/dL), HbA_1c, and glycated albumin of the two groups were similar.

CONCLUSIONS

Despite the use of dialysate containing 100-150 mg/dL glucose, patients with diabetes undergoing HD experienced HD-related hypoglycemia unawareness frequently. SGL may fall well below the dialysate glucose concentration toward the end of HD.

Intermittent Use of Continuous Glucose Monitoring: Expanding the Clinical Value of CGM

In addition to the continuous use, the intermittent use of continuous glucose monitoring (CGM) is an application of CGM, expanding the typical medical use cases. There are a variety of reasons and occasions that speak in favor of using CGM only for a limited time. To date, these circumstances have not been sufficiently discussed. In this article, we define discontinuous or intermittent CGM use, provide reasons for using it, and expand on the benefits and possibilities of using CGM on a temporary basis. We aim to draw attention to this important topic in the discussion of CGM use and give examples for a different method of CGM use. As well, we would like to foster the allocation of CGM to the right patient groups and indications, especially in cases of limited resources. From a global point of view, intermittent CGM use is more likely to occur than continuous use, primarily for economic reasons.

Analysis of Glycemic Improvement in Hemodialysis Patients Based on Time in Range, Assessed by Flash Glucose Monitoring

INTRODUCTION

This study aimed to investigate the application value of "time in ranges (TIRs)" in dialysis patients with diabetes and summarize the experience of optimizing glycemic control by flash glucose monitoring (FGM) system.

METHODS

In this monocentric 2-week pilot study, FGM was applied for 14 days in 57 type 2 diabetes mellitus medically stable patients under maintenance hemodialysis to determine their glycemic improvement. The diagnostic value of TIR versus HbA1c in detecting glucose fluctuations and levels was evaluated using receiver operating characteristic analysis.

RESULTS

Average glucose exhibited stronger association with TIR (r = -0.785, p < 0.001) than HbA1c (r = 0.644, p < 0.001), and mean amplitude of glycemic excursion (MAGE) had the same conclusion (r = -0.568, p < 0.001 for TIR vs. r = 0.423, p = 0.016 for HbA1c). TIR exhibited a higher area under curve than HbA1c in detecting significant derangements in glucose fluctuation, using a 14-day average FGM-derived coefficient of variation >36% as the reference standard (difference between areas: 0.237; 95% CI 0.092-0.383, p = 0.001). We found a significant improvement in TIR (58.38 ± 19.42 vs. 46.45 ± 24.42 mmol/L, p < 0.001) and a significant decline in MAGE (median 5.64 vs.7.42 mmol/L, p < 0.001) compared to the baseline without deterioration of time spent in hypoglycemia.

CONCLUSION

TIR seems to be feasible and clinically useful for AGP analysis in dialysis patients with diabetes, and FGM can be used to improve glycemic control.

Current concepts and clinical importance of glycemic variability

BACKGROUND AND AIMS

Evolving evidence indicate that variations in blood glucose levels are likely to be an important factor in developing diabetic complications. Monitoring glucose fluctuations in patients remains as a therapeutic challenge and more evidence needs to be created in order to bring GV into limelight. This review encapsulates the most important findings conducted and discusses on them to provide readers a better understanding on this emerging subject.

METHODS

Keyword-based comprehensive desktop search was conducted to gather the relevant literature. Triple-stage cascade type content analysis of the literature was conducted to draw relevant themes of discussions.

RESULTS

High glycemic variability is associated with an increased risk of development of diabetic complications especially in cardiac conditions. The widely used and accepted metrics to determine the variations in blood glucose are Standard deviation (SD), MAGE (Mean amplitude of glycemic excursions) and MODD (Mean of daily differences). Occurrence of blood glucose variations affects at a molecular level thereby causing more harm than the occurrence of hyperglycemia alone.

CONCLUSION

Available data suggest that Glycemic Variability should be used as an additional marker of glycemia. Additional research globally, and in India are required.

Effects of DPP-4 Inhibitors on Blood Glucose Variability in Japanese Patients with Type 2 Diabetes on Maintenance Hemodialysis: A Prospective Observational Exploratory Study

INTRODUCTION

The precise blood glucose (BG) profile of hemodialysis patients is unclear, as is the effectiveness of dipeptidyl peptidase-4 (DPP-4) inhibitors in hemodialysis patients with type 2 diabetes. Here, we used continuous glucose monitoring (CGM) to evaluate BG variability in these patients and to assess the efficacy of DPP-4 inhibitors, particularly during hemodialysis sessions and at nighttime (UMIN000012638).

METHODS

We examined BG profiles using CGM in 31 maintenance hemodialysis patients with type 2 diabetes. Differences between patients with and without DPP-4 inhibitors (n = 15 and 16, respectively) were analyzed using a linear mixed-effects model to assess changes in glucose levels in 5-min intervals.

RESULTS

The model revealed that DPP-4 inhibitor use was significantly associated with suppression of a rapid drop in glucose levels, both with and without adjustment for BG levels at the start of hemodialysis. Moreover, the model revealed that the two groups differed significantly in the pattern of changes in BG levels from 0:00 to 6:55 am. DPP-4 inhibitors suppressed the tendency for subsequent nocturnal hypoglycemia.

CONCLUSIONS

This prospective observational exploratory study showed that DPP-4 inhibitors could suppress BG variability during hemodialysis sessions as well as subsequent nocturnal changes in patients with type 2 diabetes.

TRIAL REGISTRATION

ClinicalTrials.gov identifier, UMIN000012638.

Comparison of Interstitial Fluid Glucose Levels Obtained by Continuous Glucose Monitoring and Flash Glucose Monitoring in Patients With Type 2 Diabetes Mellitus Undergoing Hemodialysis

BACKGROUND

The accuracy of flash glucose monitoring (FGM, FreeStyle Libre Pro [FSL-Pro]) remains unclear in patients with type 2 diabetes mellitus (T2DM) undergoing hemodialysis.

METHODS

We assessed 13 patients with T2DM undergoing hemodialysis. They simultaneously underwent FGM, continuous glucose monitoring (CGM, iPro2), and self-monitoring blood glucose (SMBG).

RESULTS

Parkes error grid analysis against SMBG showed that 49.0% and 51.0% of interstitial fluid glucose (ISFG) levels measured using FGM and 93.3% and 6.7% of those measured using CGM fell into zones A and B, respectively. Mean absolute relative difference (MARD) against SMBG for FGM was significantly higher than that for CGM (19.5% ± 13.2% vs 8.1% ± 7.6%, P < .0001). Parkes error grid analysis of 2496 paired ISFG levels between FGM and CGM showed that 53.6%, 46.2%, and 0.2% of the plots fell into zones A, B, and C, respectively. Mean ISFG levels were lower with FGM than with CGM (143.7 ± 67.2 mg/dL vs 164.6 ± 58.5 mg/dL; P < .0001). Mean absolute relative difference of ISFG levels between FGM and CGM was 19.2% ± 13.8%. Among three groups classified according to CGM ISFG levels (hypoglycemia, <70 mg/dL; euglycemia, 70-180 mg/dL; and hyperglycemia, >180 mg/dL), the MARDs for hypoglycemia (31.9% ± 25.0%) and euglycemia (22.8% ± 14.6%) were significantly higher than MARD for hyperglycemia (13.0% ± 8.5%) (P < .0001 in both).

CONCLUSIONS

Flash glucose monitoring may be clinically acceptable. Average ISFG levels were lower with FGM than with CGM, and MARDs were higher for hypoglycemia and euglycemia in patients with T2DM undergoing hemodialysis.

Comparison of accuracy between flash glucose monitoring and continuous glucose monitoring in patients with type 2 diabetes mellitus undergoing hemodialysis

INTRODUCTION

We evaluated the accuracy and clinical utility of flash glucose monitoring (FGM) in comparison with continuous glucose monitoring (CGM) and self-monitoring blood glucose (SMBG) in patients with type 2 diabetes (T2D) undergoing hemodialysis (HD).

METHODS

Simultaneous FGM (FreeStyle LibrePro), CGM (iPro2) and SMBG were performed on 13 T2D research subjects.

RESULTS

There were good overall correlations between SMBG and FGM (64.7% and 30.8% within the A and B of Parkes Error Grid, respectively) and between SMBG and CGM (87.9% and 11.0% within the A and B, respectively). However, during HD, correlations between SMBG and FGM were only 49.7% and 37.2% within the A and B, respectively, while correlations of SMBG and CGM were 72.8% and 22.2% within the A and B, respectively. The percentage of FGM not in Zone A + B was more than 4 times higher than for CGM. The overall mean absolute relative difference (MARD) for FGM was 18.2%, this significantly higher than 11.2% for CGM. During HD, MARD for FGM was 22.8%, significantly higher than 15.0% for CGM.

CONCLUSION

FGM has good clinical agreement in T2D patients undergoing HD. However, the accuracy of FGM relative to SMBG was worse than that of CGM.

The Glycemic Effect of Liraglutide Evaluated by Continuous Glucose Monitoring in Persons with Type 2 Diabetes Receiving Dialysis

AIMS

The aim of this study was to evaluate the effect of liraglutide treatment on glucose variability and the risk of hypoglycemia by continuous glucose monitoring (CGM) in persons with type 2 diabetes (T2D) and dialysis-dependent end-stage renal disease (ESRD).

MATERIALS AND METHODS

We assessed CGM data from a previous trial where 24 persons with T2D and dialysis-dependent ESRD were allocated (1:1) to 12 weeks of double-blinded treatment with liraglutide (titrated to maximum tolerable dose up to 1.8 mg) or placebo as an add-on to preexisting antidiabetic treatment. CGM (Ipro2®; Medtronic) was performed for up to 7 days at baseline and at weeks 2, 6, and 10. A linear mixed model was used to compare the 2 study arms.

RESULTS

A CGM was worn at baseline by 12 persons in the liraglutide group and 10 in the placebo group (7 and 9 completed week 10, respectively). Glycated hemoglobin A1c (p = 0.81) and glucose variability was similar between the groups (standard deviation, p = 0.33; coefficient of variation, p = 0.16). Comparing baseline and week 10, the number of hypoglycemic events (glucose values between <3.9 and 3.0 mmol/L) increased in the liraglutide group compared with the placebo group (p = 0.02). The occurrence of hypoglycemic events below 3.0 mmol/L was similar between the groups (p = 0.36).

CONCLUSIONS

In the present cohort of persons with T2D and dialysis-dependent ESRD, liraglutide treatment increased the risk of hypoglycemic events as compared to placebo (no difference was found for hypoglycemic events below 3.0 mmol/L). The majority of participants were co-treated with insulin.

Comparative study on the efficacy of peritoneal dialysis and hemodialysis in patients with end-stage diabetic nephropathy

Objective

Diabetic nephropathy is a serious threat to human health, and its incidence is on the rise. End-stage diabetic nephropathy (ESDN) requires extra investigation due to its complexity and severity, as well as serious concurrent diseases. Our objective was to compare the efficacy of hemodialysis (HD) and peritoneal dialysis (PD) in the treatment of ESDN.

Methods

Clinical data of 84 patients with ESDN admitted to our hospital from June 2016 to June 2018 were retrospectively analyzed. The patients were divided into an HD group that received hemodialysis and a PD group that received peritoneal dialysis. Their general conditions, biochemical indicators, residual renal function and incidence of complications were recorded and compared between the two groups.

Results

(1) No significant difference in diastolic blood pressure, systolic blood pressure, body weight, or urine output was detected between the two groups at the beginning of dialysis (P>0.05). (2) Compared to the PD group, the HD group had significantly lower total cholesterol (TC) and triglyceride (TG) (P<0.05), and significantly higher total protein (TP) and albumin (ALB) after treatment (P<0.05). (3) The two groups also showed significant difference in residual renal function after treatment (P<0.05). (4) The HD group had significantly higher systolic pressure than the PD group after treatment (P<0.05). And more cases of infection were observed in the PD group than the HD group (P<0.05).

Conclusion

Both HD and PD are used for treatment of ESDN, and can achieve similar calcium and phosphorus control. Compared to HD, PD has less adverse effect on hemodynamics and better preserves residual renal function, but is more likely to cause malnutrition and disorders of lipid metabolism. Therefore, choice of dialysis method should be based on specific conditions of each patient.

Molecular Mechanisms of Glucose Fluctuations on Diabetic Complications

Accumulating evidence indicates the occurrence and development of diabetic complications relates to not only constant high plasma glucose, but also glucose fluctuations which affect various kinds of molecular mechanisms in various target cells and tissues. In this review, we detail reactive oxygen species and their potentially damaging effects upon glucose fluctuations and resultant downstream regulation of protein signaling pathways, including protein kinase C, protein kinase B, nuclear factor-κB, and the mitogen-activated protein kinase signaling pathway. A deeper understanding of glucose-fluctuation-related molecular mechanisms in the development of diabetic complications may enable more potential target therapies in future.

Comparison of Glycemic Variability in Chinese T2DM Patients Treated with Exenatide or Insulin Glargine: A Randomized Controlled Trial

INTRODUCTION

Increasing the frequency of blood glucose monitoring aids the evaluation of glycemic variability and blood glucose control by antidiabetic drugs. It remains unclear, however, whether GLP-1 receptor agonists or basal insulin has a better effect on glycemic variability in type 2 diabetes mellitus (T2DM) patients who are inadequately controlled by metformin. We used a continuous glucose monitoring system (CGMS) to compare patients on a GLP-1 receptor agonist with patients on basal insulin in terms of glycemic variability.

METHODS

This prospective randomized study assigned T2DM patients treated with metformin (N = 39) to either exenatide treatment or insulin glargine treatment for 16 weeks. Glycemic variability was assessed using a CGMS; hemoglobin A1c (HbA1c), β-cell function, weight, body mass index (BMI), and waist circumference were also evaluated.

RESULTS

Mean blood glucose level, continuous overlapping net glycemic action, mean amplitude of glycemic excursions, percentage of the time that the blood glucose value was > 10.0 mmol/L, and highest blood glucose level (P  < 0.01-0.05) significantly decreased in both groups. Standard deviation of the mean glucose value, largest amplitude of glycemic excursions, and waist circumference significantly decreased for those treated with exenatide (P  < 0.05), while no changes were observed with insulin glargine treatment. Percentage of the time that the blood glucose value was > 7.8 mmol/L decreased after insulin glargine use (P  < 0.05) but not with the exenatide intervention. Similar decreases in fasting blood glucose and HbA1c and increases in the 1/homeostasis model assessment of insulin resistance, disposition index 30, and disposition index 120 were observed in both groups (P  < 0.01-0.05). Reductions in weight and BMI were greater with exenatide than with insulin glargine treatment (P  < 0.05).

CONCLUSIONS

In overweight and obese patients with T2DM inadequately controlled by metformin, exenatide and insulin glargine have similar efficacies in terms of glycemic variability, HbA1c alleviation, and β-cell function, but exenatide has a greater effect on body weight and BMI.

Managing Diabetes and Cardiovascular Risk in Chronic Kidney Disease Patients

We discuss mechanisms of increased cardiovascular disease (CVD) in patients with chronic kidney disease (CKD) and strategies for managing cardiovascular (CV) risk in these patients. Our focus was mainly on decreasing CV events and progression of microvascular complications by reducing levels of glucose and lipids. We searched PubMed with no limit on the date of the article. All articles were discussed among all authors. We chose pertinent articles, and searched their references in turn for additional relevant publications.

Association between circulating fibroblast growth factor 21 and mortality in end-stage renal disease

Fibroblast growth factor 21 (FGF21) is an endocrine factor that regulates glucose and lipid metabolism. Circulating FGF21 predicts cardiovascular events and mortality in type 2 diabetes mellitus, including early-stage chronic kidney disease, but its impact on clinical outcomes in end-stage renal disease (ESRD) patients remains unclear. This study enrolled 90 ESRD patients receiving chronic hemodialysis who were categorized into low- and high-FGF21 groups by the median value. We investigated the association between circulating FGF21 levels and the cardiovascular event and mortality during a median follow-up period of 64 months. A Kaplan-Meier analysis showed that the mortality rate was significantly higher in the high-FGF21 group than in the low-FGF21 group (28.3% vs. 9.1%, log-rank, P = 0.034), while the rate of cardiovascular events did not significantly differ between the two groups (30.4% vs. 22.7%, log-rank, P = 0.312). In multivariable Cox models adjusted a high FGF21 level was an independent predictor of all-cause mortality (hazard ratio: 3.98; 95% confidence interval: 1.39–14.27, P = 0.009). Higher circulating FGF21 levels were associated with a high mortality rate, but not cardiovascular events in patient with ESRD, suggesting that circulating FGF21 levels serve as a predictive marker for mortality in these subjects.

Role of continuous glucose monitoring for type 2 in diabetes management and research

The advent of continuous glucose monitoring (CGM) is a significant stride forward in our ability to better understand the glycemic status of our patients. Current clinical practice employs two forms of CGM: professional (retrospective or "masked") and personal (real-time) to evaluate and/or monitor glycemic control. Most studies using professional and personal CGM have been done in those with type 1 diabetes (T1D). However, this technology is agnostic to the type of diabetes and can also be used in those with type 2 diabetes (T2D). The value of professional CGM in T2D for physicians, patients, and researchers is derived from its ability to: (1) to discover previously unknown hyper- and hypoglycemia (silent and symptomatic); (2) measure glycemic control directly rather than through the surrogate metric of hemoglobin A1C (HbA1C) permitting the observation of a wide variety of metrics that include glycemic variability, the percent of time within, below and above target glucose levels, the severity of hypo- and hyperglycemia throughout the day and night; (3) provide actionable information for healthcare providers derived by the CGM report; (4) better manage patients on hemodialysis; and (5) effectively and efficiently analyze glycemic effects of new interventions whether they be pharmaceuticals (duration of action, pharmacodynamics, safety, and efficacy), devices, or psycho-educational. Personal CGM has also been successfully used in a small number of studies as a behavior modification tool in those with T2D. This comprehensive review describes the differences between professional and personal CGM and the evidence for the use of each form of CGM in T2D. Finally, the opinions of key professional societies on the use of CGM in T2D are presented.

Distinct biomarker roles for HbA1c and glycated albumin in patients with type 2 diabetes on hemodialysis

AIMS

HbA_1c and glycated albumin (GA) are used to monitor glycemia, but their accuracy to represent glycemic profiles in hemodialysis remains controversial.

METHODS

Continuous glucose monitoring in 97 patients with type 2 diabetes (41 on hemodialysis [HD] and 56 without nephropathy) was analyzed to evaluate whether HbA_1c and/or GA serve as appropriate glycemic profile markers.

RESULTS

The average glucose significantly correlated with HbA_1c in both HD group and group without nephropathy (r=0.59, P<0.0001; r=0.40, P<0.005). The slopes of linear regression lines were statistically indistinguishable (F=0.30, P=0.744), while the y-intercepts were significantly different (F=57.86, P<0.0001). GA showed strong correlation with the glycemic standard deviation (r=0.68, P<0.0001), and with the average glucose (r=0.42, P<0.001). Least square analysis revealed that only HbA_1c, but not GA, was significantly associated with the average glucose (F=10.20, P<0.0005; F=0.38, P=0.5427), while only GA was significantly associated with the glycemic variability in HD group.

CONCLUSIONS

In HD participants, HbA_1c correlates with the average glucose more than GA, but underestimates it, and a correction formula of HbA1c can be developed as an appreciable marker. GA value itself reflects the average glucose, but less accurately than HbA_1c, while it could serve as an indicator for hyperglycemia/hypoglycemia excursion.

Comparison of intra-individual coefficients of variation on the paired sampling data when inter-individual variations are different between measures

Background

Pain intensities of patients are repeatedly measured by Visual Analog Scale (VAS) and Pain Vision (PV) in a clinical research. Two measurements by VAS and PV are performed at the same time. In order to evaluate within patient consistency, intra-individual coefficient of variations (CVs) are compared between measures assuming that the pain status of each patient is stable during the research period. The correlated samples and different inter-individual variation due to different scales of the measures should be taken into account in statistical analysis. The adjustment of covariates will improve the estimation of population mean values of the measures.

Methods

In this paper, statistical approach to compare the intra-individual CVs is proposed. The approach consists of two steps: (1) estimating population mean values and intra-individual variances of the pain intensities by measure in a mixed effect model framework, (2) computing intra-individual CVs and comparing them between measures. The mixed effect model includes measure and some variables as fixed effects and subject by measure as a random effect. The different inter-individual variations between measures and their covariance reflect the paired sampling in the variance component. The confidence interval of the difference of intra-individual CVs is constructed using the asymptotic normality and the delta method. Bootstrap method is available if sample size is small.

Results

The proposed approach is illustrated using pain research data. Measure (VAS and PV), age and sex are included in the model as fixed effects. The confidence intervals of the difference of intra-individual CVs between measures are estimated by the asymptotic theory and by bootstrap using a subgroup resampling, respectively. Both confidence intervals are similar.

Conclusion

The proposed approach is useful to compare two intra-individual CVs taking it into account to reflect the paired sampling, different inter-individual variations between measures and some covariates. Although the inclusion of covariates did not improve the goodness-of-fit in the illustration, the proposed model with covariates will improve the accuracy and/or precision if covariates truly influence response variable. This approach can be applicable with small modification to various situations.

Electronic supplementary material

The online version of this article (doi:10.1186/s13104-016-1912-y) contains supplementary material, which is available to authorized users.

Bicarbonate dialysis compared to hemodiafiltration on glycemic excursions in patients with end-stage renal disease with and without type 2 diabetes mellitus

AIM

To evaluate the effects on glycemic excursions during bicarbonate dialysis (BHD) compared to hemodiafiltration (HDF) in type 2 diabetic or not diabetic patients affected by end-stage renal disease (ESRD).

MATERIAL AND METHODS

Thirty-six patients (20 affected by type 2 diabetes mellitus, and 16 not diabetic patients) were evaluated and underwent BHD dialysis, followed by HDF dialysis two days later. All patients underwent also glucose continuous monitoring system, using iPro Continuous Glucose Monitor System (Medtronic MiniMed) starting just before the BHD, and ending five days later, two days after the HDF dialysis. Glycemic control was estimated as the mean blood glucose (MBG), the area under the glucose curve above 70mg/dl (AUC>70) or 180mg/dl (AUC>180), and the percentage of time above 70mg/dl (t>70) or 180mg/dl (t>180). Intraday glycemic variability was assessed as the standard deviation (SD), M value, and the mean amplitude of glycemic excursions (MAGE). Day-to-day glycemic variability was assessed as the mean of daily difference (MODD), that is the mean of the absolute difference among glucose values taken on 2 consecutive days at the same time.

RESULTS

glycemic control was better with HDF: MBG, and AUC>180 were lower during HDF compared do BHD. We also observed a significant decrease of glycemic excursions during HDF dialysis: SD, M value, and the MAGE value were lower with HDF. The MODD value was significantly changed in BHD group, while no differences were recorded during HDF.

CONCLUSION

HDF seems to greater reduce glycemic excursions during the treatment compared to BHD.