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

The futility of post-haemodialysis blood glucose levels: A retrospective cohort study

BACKGROUND

Frequent blood glucose tests are performed for people with diabetes receiving haemodialysis.

OBJECTIVES

To determine the rate of out-of-range post-haemodialysis blood glucose levels that are clinically acted upon, the intervention and outcome of each intervention, and the associations between post-haemodialysis blood glucose levels and relevant clinical predictors.

DESIGN

12-month retrospective cohort medical record review in one Australian haemodialysis centre. Post-haemodialysis blood glucose levels, prehaemodialysis blood glucose levels, time of treatment, diabetes medications, intradialytic fluid removal, dialysate dextrose concentration, clinical actions, interventions, and outcomes on out-of-range blood glucose levels were retrieved.

PARTICIPANTS

22 participants with a median time receiving dialysis 3.1 years (interquartile range 2.3-4.7).

MEASUREMENTS AND RESULTS

The proportion of out-of-range post-haemodialysis blood glucose levels was 87.3% (95% confidence interval, 86.1%-88.5%). No out-of-range post-haemodialysis blood glucose levels were clinically acted upon. Out-of-range post-haemodialysis blood glucose levels were 4.6 times more likely if a higher dextrose bath was used (95% confidence interval: 3.3; 6.3. p < 0.001). The odds of the post-haemodialysis blood glucose levels increased by each 1 mmol/L. Intradialytic fluid removal, dialysate dextrose concentration, sex, dialysis time, anti-hyperglycaemic agents were also associated with out-of-range post-haemodialysis blood glucose levels.

CONCLUSION

Routine post-haemodialysis blood glucose levels testing has limited clinical utility in care for people with diabetes receiving maintenance haemodialysis. Higher dextrose dialysate may require individual titration depending on prehaemodialysis blood glucose levels.

Accuracy of Continuous Glucose Monitoring in Hemodialysis Patients With Diabetes

OBJECTIVE

In the general population, continuous glucose monitoring (CGM) provides convenient and less-invasive glucose measurements than conventional self-monitored blood glucose and results in reduced hypoglycemia and hyperglycemia and increased time in target glucose range. However, accuracy of CGM versus blood glucose is not well established in hemodialysis patients.

RESEARCH DESIGN AND METHODS

Among 31 maintenance hemodialysis patients with diabetes hospitalized from October 2020 to May 2021, we conducted protocolized glucose measurements using Dexcom G6 CGM versus blood glucose, with the latter measured before each meal and at night, plus every 30-min during hemodialysis. We examined CGM-blood glucose correlations and agreement between CGM versus blood glucose using Bland-Altman plots, percentage of agreement, mean and median absolute relative differences (ARDs), and consensus error grids.

RESULTS

Pearson and Spearman correlations for averaged CGM versus blood glucose levels were 0.84 and 0.79, respectively; Bland-Altman showed the mean difference between CGM and blood glucose was ∼+15 mg/dL. Agreement rates using %20/20 criteria were 48.7%, 47.2%, and 50.2% during the overall, hemodialysis, and nonhemodialysis periods, respectively. Mean ARD (MARD) was ∼20% across all time periods; median ARD was 19.4% during the overall period and was slightly lower during nonhemodialysis (18.2%) versus hemodialysis periods (22.0%). Consensus error grids showed nearly all CGM values were in clinically acceptable zones A (no harm) and B (unlikely to cause significant harm).

CONCLUSIONS

In hemodialysis patients with diabetes, although MARD values were higher than traditional optimal analytic performance thresholds, error grids showed nearly all CGM values were in clinically acceptable zones. Further studies are needed to determine whether CGM improves outcomes in hemodialysis patients.

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.

Residual Kidney Function in Hemodialysis: Its Importance and Contribution to Improved Patient Outcomes

Individuals afflicted with advanced kidney dysfunction who require dialysis for medical management exhibit different degrees of native kidney function, called residual kidney function (RKF), ranging from nil to appreciable levels. The primary focus of this manuscript is to delve into the concept of RKF, a pivotal yet under-represented topic in nephrology. To begin, we unpack the definition and intrinsic nature of RKF. We then juxtapose the efficiency of RKF against that of hemodialysis in preserving homeostatic equilibrium and facilitating physiological functions. Given the complex interplay of RKF and overall patient health, we shed light on the extent of its influence on patient outcomes, particularly in those living with advanced kidney dysfunction and on dialysis. This manuscript subsequently presents methodologies and measures to assess RKF, concluding with the potential benefits of targeted interventions aimed at preserving RKF.

Application and management of continuous glucose monitoring in diabetic kidney disease

Diabetic kidney disease (DKD) is a common complication of diabetes mellitus that contributes to the risk of end-stage kidney disease (ESKD). Wide glycemic var-iations, such as hypoglycemia and hyperglycemia, are broadly found in diabetic patients with DKD and especially ESKD, as a result of impaired renal metabolism. It is essential to monitor glycemia for effective management of DKD. Hemoglobin A1c (HbA1c) has long been considered as the gold standard for monitoring glycemia for > 3 months. However, assessment of HbA1c has some bias as it is susceptible to factors such as anemia and liver or kidney dysfunction. Continuous glucose monitoring (CGM) has provided new insights on glycemic assessment and management. CGM directly measures glucose level in interstitial fluid, reports real-time or retrospective glucose concentration, and provides multiple glycemic metrics. It avoids the pitfalls of HbA1c in some contexts, and may serve as a precise alternative to estimation of mean glucose and glycemic variability. Emerging studies have demonstrated the merits of CGM for precise monitoring, which allows fine-tuning of glycemic management in diabetic patients. Therefore, CGM technology has the potential for better glycemic monitoring in DKD patients. More research is needed to explore its application and management in different stages of DKD, including hemodialysis, peritoneal dialysis and kidney transplantation.

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.

Accuracy of Continuous Glucose Monitoring in an Insulin-Treated Population Requiring Haemodialysis

BACKGROUND

Continuous glucose monitoring (CGM) is revolutionizing diabetes care by giving both patients and the healthcare professionals unprecedented insights into glucose variability and patterns. It is established in National Institute for Health and Care Excellence (NICE) guidance as a standard of care for type 1 diabetes and diabetes in pregnancy under certain conditions. Diabetes mellitus (DM) is recognized as an important risk factor for chronic kidney disease (CKD). Around a third of patients receiving in-center haemodialysis as renal replacement therapy (RRT) have diabetes, either as a direct cause of renal failure or as an additional co-morbidity. Evidence of poor compliance with the current standard of care (self-monitoring of blood glucose [SMBG]) and overall greater morbidity and mortality, suggests this patient population as an ideal target group for CGM. However, there exists no strong published evidence showing the validity of CGM devices in insulin-treated diabetes patients requiring haemodialysis.

METHODS

We applied a Freestyle Libre Pro sensor to 69 insulin-treated diabetes haemodialysis (HD) patients on a dialysis day. Interstitial glucose levels were obtained, and time matched within 7 minutes to capillary blood glucose testing and any plasma blood glucose levels sent. Data cleansing techniques were applied to account for rapidly correcting hypoglycaemia and poor SMBG technique.

RESULTS

Clarke-error grid analysis showed 97.9% of glucose values in an acceptable range of agreement (97.3% on dialysis days and 99.1% on non-dialysis days).

CONCLUSIONS

We conclude that the Freestyle Libre sensor is accurate in measuring glucose levels when compared to glucose as measured by capillary SMBG testing and laboratory obtained serum glucose in patients on HD.

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.

Neuromuscular Electrical Stimulation during Hemodialysis Suppresses Postprandial Hyperglycemia in Patients with End-Stage Diabetic Kidney Disease: A Crossover Controlled Trial

Hemodialysis patients with diabetic kidney disease (DKD) experience blood glucose fluctuations owing to insulin removal. We evaluated the effects of single and long-term application of neuromuscular electrical stimulation (NMES) during hemodialysis on glycemic control. This trial was conducted in two stages: Stage 1, following a crossover design and 4 week washout period, eleven outpatients with DKD either underwent a single bout of NMES for 30 min (NMES period) or rested (control period) after receiving nutritional support during hemodialysis; Stage 2, following a crossover design and 4 week washout period, each participant received the intervention for 12 weeks. NMES was administered for 30 min at the maximum tolerable intensity. The mean subcutaneous glucose concentration and mean amplitude of glycemic excursion (MAGE) were determined by flash glucose monitoring for 24 h. Changes in glycoalbumin and MAGE before and after NMES initiation were evaluated. The mean blood glucose level and MAGE after a single bout of NMES were significantly lower than those after rest. Glycoalbumin levels and echo intensity of the rectus femoris tended to decrease, but not significantly by ANOVA due to a lack in statistical power after the dropout of three patients. NMES in end-stage DKD decreased blood glucose levels during and after hemodialysis.

Evaluation of the relationship between hemodialysis-related glycemic variability and hormonal profiles in patients with type 2 diabetes on hemodialysis: a pilot study

Background

The number of dialysis patients with diabetes is currently increasing in Japan and a similar proportion worldwide. It was suggested that approximately 20% of these patients had hypoglycemia after dialysis session and most of these hypoglycemia were unconscious. Furthermore, it was suggested that glucose variabilities induced by hemodialysis may be related to insulin and insulin-counter hormones, such as glucagon, adrenocorticotropic hormone (ACTH), and cortisol and growth hormone, but conclusive evidence has not still been obtained.

Methods

We investigated in detail the glucose and hormonal profiles in 7 patients with type 2 diabetes on hemodialysis (all male, HbA1c 6.8 ± 2.1%, glycated albumin 24.7 ± 10.2%). All participants were attached continuous glucose monitoring (iPro2®). Blood glucose level, C-peptide immunoreactivity, plasma glucagon, ACTH, cortisol and growth hormone were measured by 7 points blood tests at before breakfast, after breakfast (predialysis), 2 h and 4 h after starting dialysis, after lunch and before/after dinner on the dialysis day and 6 points at before/after each meal on the non-dialysis day, and these relationship with blood glucose dynamics were examined. The meal contents were set to the indicated energy amount, and the same menu was served daily for breakfast, lunch, and dinner on dialysis and non-dialysis days of this study period. In addition, the start time of lunch on non-dialysis day was the same as the start time of lunch on the dialysis day.

Results

Serum C-peptide level was significantly increased by taking breakfast and lunch on the hemodialysis day, significantly decreased during hemodialysis, and was significantly lower before and after lunch on the hemodialysis day than on the non-hemodialysis day. Plasma glucagon level significantly decreased during hemodialysis and that before lunch on hemodialysis day was significantly lower than on non-hemodialysis day. ACTH, cortisol, and growth hormone did not show any changes related to hemodialysis.

Conclusions

It was suggested that C-peptide and glucagon play an important role in hemodialysis-related glycemic variabilities in patients with type 2 diabetic hemodialysis.

Trial registration UMIN Clinical Trial Registry (Registration Number UMIN000018707). Registered 18 August 2015, https://center6.umin.ac.jp/cgi-open-bin/ctr/ctr.cgi?function=brows&action=brows&type=summary&language=J&recptno=R000021647.

Accuracy of a Factory-Calibrated Continuous Glucose Monitor in Individuals With Diabetes on Hemodialysis

OBJECTIVE

Continuous glucose monitoring (CGM) improves diabetes management, but its reliability in individuals on hemodialysis is poorly understood and potentially affected by interstitial and intravascular volume variations.

RESEARCH DESIGN AND METHODS

We assessed the accuracy of a factory-calibrated CGM by using venous blood glucose measurements (vBGM) during hemodialysis sessions and self-monitoring blood glucose (SMBG) at home.

RESULTS

Twenty participants completed the protocol. The mean absolute relative difference of the CGM was 13.8% and 14.4%, when calculated on SMBG (n = 684) and on vBGM (n = 624), and 98.7% and 100% of values in the Parkes error grid A/B zones, respectively. Throughout 181 days of CGM monitoring, the median time in range (70-180 mg/dL) was 38.5% (interquartile range 29.3-57.9), with 28.7% (7.8-40.6) of the time >250 mg/dL.

CONCLUSIONS

The overall performance of a factory-calibrated CGM appears reasonably accurate and clinically relevant for use in practice by individuals on hemodialysis and health professionals to improve diabetes management.

Peri-dialytic hypoglycaemia with haemodialysis and on-line post-dilutional haemodiafiltration

INTRODUCTION

We wished to determine whether peri-dialytic hypoglycaemia is a clinical risk in contemporary dialysis patients using glucose containing dialysate.

METHODS

We measured blood glucose pre- and post-haemodialysis or haemodiafiltration, using 5.5 mmol/L glucose dialysate, and body composition by bioimpedance.

RESULTS

239 patients were studied, mean age 65±15.4 years, 59.4% male, 46.4% diabetes, 81.6% treated by haemodiafiltration, Five haemodiafiltration patients (2.1%) had hypoglycaemia, with 82 (33%) a blood glucose <5.5 mmol/L, with fewer diabetics (19.8 vs 74.7%, p=0.001, and %body fat 27.7(20.6-32.6) vs 34.7(26.6-42.8)%, p=0.001. Low post-dialysis blood glucose was negatively associated with glycated haemoglobin (OR 0.94 (0.84-0.97), p=0.004), weight (OR 0.94 (0.89-0.98), p=0.009), and % body fat (OR 0.92 (0.86-0.98), p=0.013).

CONCLUSIONS

Although hypoglycaemia occurred in 2%, 33% had a blood glucose below dialysate glucose. Low post-dialysis glucose was associated with lower glycated haemoglobin and body fat, suggesting nutritional status is important in determining the risk of peri-dialytic hypoglycaemia.

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.

Continuous glucose monitoring in an end-stage renal disease patient with diabetes receiving hemodialysis

Diabetes is the leading cause of end-stage renal disease (ESRD) and contributes to heightened morbidity and mortality in dialysis patients. Given that ESRD patients are susceptible to hypoglycemia and hyperglycemia via multiple pathways, adequate glycemic monitoring and control is a cornerstone in diabetic kidney disease management. In ESRD, existing glycemic metrics such as glycated hemoglobin, self-monitored blood glucose, fructosamine, and glycated albumin have limitations in accuracy, convenience, and accessibility. In contrast, continuous glucose monitoring (CGM) provides automated, less invasive glucose measurements and more comprehensive glycemic data versus conventional metrics. Here, we report a 48-year-old male with ESRD due to diabetes receiving thrice-weekly hemodialysis who experienced decreased patient-burden, greater glucose monitoring adherence, improved glycemic parameters, and reduction in hypoglycemia after transitioning to CGM. Through this case, we discuss how CGM is a practical, convenient patient-centered tool that may improve metabolic outcomes and quality of life in ESRD patients with diabetes.