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

Diabetes and Glucose Management in People on Hemodialysis

Diabetes is a major cause of end-stage kidney disease (ESKD). Glycemic management is challenging in this population, and A1C, commonly used for monitoring glycemic control, is unreliable. Continuous glucose monitoring indices can be used for glycemic monitoring in people with ESKD. Dipeptidyl peptidase 4 inhibitors, incretin mimetic agents (glucagon-like peptide 1 and glucose-dependent insulinotropic peptide receptor agonists), and insulin using an automated insulin delivery system are preferred to manage diabetes in people with ESKD on hemodialysis.

Consensus Report on the Use of Continuous Glucose Monitoring in Chronic Kidney Disease and Diabetes

This report represents the conclusions of 15 experts in nephrology and endocrinology, based on their knowledge of key studies and evidence in the field, on the role of continuous glucose monitors (CGMs) in patients with diabetes and chronic kidney disease (CKD), including those receiving dialysis. The experts discussed issues related to CGM accuracy, indications, education, clinical outcomes, quality of life, research gaps, and barriers to dissemination. Three main goals of management for patients with CKD and diabetes were identified: (1) greater use of CGMs for better glycemic monitoring and management, (2) further research evaluating the accuracy, feasibility, outcomes, and potential value of CGMs in patients with end-stage kidney disease (ESKD) on hemodialysis, and (3) equitable access to CGM technology for patients with CKD. The experts also developed 15 conclusions regarding the use of CGMs in this population related to CGMs' unique delivery of both real-time information that can guide monitoring and management of glycemia and continuous and predictive data in this population, which is at higher risk for hypoglycemia and hyperglycemia. The group noted three major clinical gaps: (1) CGMs are not routinely prescribed for patients with diabetes and CKD; (2) CGMs are not approved by the United States Food and Drug Administration (FDA) for patients with diabetes who are on dialysis; and (3) CGMs are not routinely available to all of those who need them because of structural barriers in the health care system. These gaps can be improved with greater stakeholder collaboration, education, and awareness brought to the use of CGM technology in CKD.

Diabetes technology in people with diabetes and advanced chronic kidney disease

Diabetes is the leading cause and a common comorbidity of advanced chronic kidney disease. Glycaemic management in this population is challenging and characterised by frequent excursions of hypoglycaemia and hyperglycaemia. Current glucose monitoring tools, such as HbA1c, fructosamine and glycated albumin, have biases in this population and provide information only on mean glucose exposure. Revolutionary developments in glucose sensing and insulin delivery technology have occurred in the last decade. Newer factory-calibrated continuous glucose monitors provide real-time glucose data, with predictive alarms, allowing improved assessment of glucose excursions and preventive measures, particularly during and between dialysis sessions. Furthermore, integration of continuous glucose monitors and their predictive alerts with automated insulin delivery systems enables insulin administration to be decreased or stopped proactively, leading to improved glycaemic management and diminishing glycaemic fluctuations. While awaiting regulatory approval, emerging studies, expert real-world experience and clinical guidelines support the use of diabetes technology devices in people with diabetes and advanced chronic kidney disease.

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.

Breaking through diabetes management barriers: Assessing the accuracy of Freestyle Libre Pro flash continuous glucose monitoring in diabetes patients with myocardial infarction

Purpose

The objective of this study was to assess the accuracy of FreeStyle Libre Pro (FSL-Pro) flash continuous glucose monitoring (CGM) in patients with type 2 diabetes mellitus (T2DM) and acute myocardial infarction (AMI).

Methods

A single-arm, single-center prospective study was conducted in the cardiac care unit from January 2021 to September 2023. Patients underwent finger-prick blood glucose (FPBG) testing before breakfast (6:00 am) and after meals (at 9:00, 13:00, 19:00 pm), along with CGM during their hospitalization. Statistical analyses included mean differences (MDs), mean absolute relative difference (MARDs) of blood glucose levels, and hypoglycemia occurrences. A Bland-Altman plot analysis and Pearson correlation were performed.

Results

Ninety-seven T2DM and AMI patients underwent CGM for up to 72 h (1142 monitoring point). Mean daily BG, Fasting plasma glucose (FPG) and mean postprandial plasma glucose (PPG) were significantly lower by CGM than by FPBG with an estimated MD of -0.89 mmol/L in BG, -0.88 mmol/L in FPG, and -0.90 mmol/L in PPG, respectively. The maximum effect was mainly in the first day and then the difference was gradually declined (falling range, Day1, -1.24; Day 2, -0.70; Day 3, -0.68, mmol/L, respectively). The incidence rates of hypoglycemia and potential hypoglycemia was 1.57% and 8.5% higher, respectively, in CGM than in FBPG. A Bland-Altman Plot revealed some variability and bias between the two methods of measurement of glucose monitoring (p < .001). Pearson's correlation coefficient demonstrated a significant correlation between the mean BG, FPG, and PPG of CGM and FBPG (Pearson's coefficient: 0.92, 0.87, 0.92, respectively, p < .001).

Conclusion

Compared with FPBG, FSL Pro-CGM showed lower mean glucose and higher hypoglycemia detection in T2DM and AMI patients, especially in the first 24 h.

Discordance Between Glycated Hemoglobin A1c and the Glucose Management Indicator in People With Diabetes and Chronic Kidney Disease

INTRODUCTION

Assessment of glucose exposure via glycated hemoglobin A1c (HbA1c) has limitations for interpretation in individuals with diabetes and chronic kidney disease (CKD). The glucose management indicator (GMI) derived from continuous glucose monitoring (CGM) data could be an alternative. However, the concordance between HbA1c measured in laboratory and GMI (HbA1c-GMI) is uncertain in individuals with CKD. The purpose of this study is to analyze this discrepancy.

MATERIAL AND METHOD

We performed a multicentric, retrospective, observational study. A group of individuals with diabetes and CKD (n = 170) was compared with a group of individuals with diabetes without CKD (n = 185). All individuals used an intermittently scanned continuous glucose monitoring (isCGM). A comparison of 14-day and 90-day glucose data recorded by the isCGM was performed to calculate GMI and the discordance between lab HbA1c and GMI was analyzed by a Bland-Altman method and linear regression.

RESULTS

HbA1c-GMI discordance was significantly higher in the CKD group versus without CKD group (0.78 ± 0.57 [0.66-0.90] vs 0.59 ± 0.44 [0.50-0.66]%, P < .005). An absolute difference >0.5% was found in 68.2% of individuals with CKD versus 42.2% of individuals without CKD. We suggest a new specific formula to estimate HbA1c from the linear regression between HbA1c and mean glucose CGM, namely CKD-GMI = 0.0261 × 90-day mean glucose (mg/L) + 3.5579 (r2 = 0.59).

CONCLUSIONS

HbA1c-GMI discordance is frequent and usually in favor of an HbA1c level higher than the GMI value, which can lead to errors in changes in glucose-lowering therapy, especially for individuals with CKD. This latter population should benefit from the CGM to measure their glucose exposure more precisely.

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.

Apple preload increased postprandial insulin sensitivity of a high glycemic rice meal only at breakfast

PURPOSE

The possible impact of preload food on insulin sensitivity has yet been reported. This study aimed to investigate the glycemic and insulinemic effect of an apple preload before breakfast, lunch and early supper, based on high glycemic index (GI) rice meals.

METHODS

Twenty-three healthy participants in Group 1 and 14 participants in Group 2 were served with the reference meal (white rice containing 50 g of available carbohydrate) or experimental meals (apple preload and rice, each containing 15 and 35 g of available carbohydrate). The meals were either served at 8:00 for breakfast, 12:30 for lunch or 17:00 for early supper to explore the possible effect of time factor. The group 1 assessed the postprandial and subsequent-meal glycemic effect of the test meals by continuous glucose monitoring (CGM), along with subjective appetite; The group 2 further investigated the glycemic and insulin effect by blood collection.

RESULTS

The apple preload lowered the blood glucose peak value by 33.5%, 31.4% and 31.0% in breakfast, lunch and supper, respectively, while increased insulin sensitivity by 40.5% only at breakfast, compared with the rice reference. The early supper resulted significantly milder glycemic response than its breakfast and lunch counterparts did. The result of CGM tests was consistent with that of the fingertip blood tests.

CONCLUSION

Apple preload performed the best at breakfast in terms of enhancing the insulin sensitivity. The preload treatment could effectively attenuate postprandial GR without increasing the area under insulin response curve in any of the three meals.

The Accuracy of Continuous Glucose Sensors in People with Diabetes Undergoing Haemodialysis (ALPHA Study)

OBJECTIVES

Real-time and intermittently scanned continuous glucose monitoring are increasingly used for glucose monitoring in people with diabetes requiring renal replacement therapy, with limited data reporting their accuracy in this cohort. We evaluated the accuracy of Dexcom G6 and Abbott Freestyle Libre 1 glucose monitoring systems in people with diabetes undergoing haemodialysis.

METHODS

Participants on haemodialysis with diabetes (on insulin or sulfonylureas) were recruited. Paired sensor glucose from Dexcom G6 and Freestyle Libre 1 were recorded with plasma glucose analysed using the YSI (Yellow Springs Instrument) method at frequent intervals during haemodialysis. Analysis of accuracy metrics included mean absolute relative difference (MARD), Clarke Error Grid (CEG) analysis and proportion of CGM values within 15 and 20% or 15 and 20mg/dL of YSI reference values for blood glucose >100 mg/dL or ≤100 mg/dL, respectively (% 15/15, % 20/20).

RESULTS

Forty adults (median age 64.7 (60.2-74.4) years) were recruited. Overall MARD for Dexcom G6 was 22.7% (2,656 matched glucose pairs), and 11.3% for Libre 1 (n=2,785). The proportions of readings meeting %15/15 and %20/20 were 29.1% and 45.4% for Dexcom G6, respectively, and 73.5% and 85.6% for Libre 1. CEG analysis showed 98.9% of all values in zones A and B for Dexcom G6 and 99.8% for Libre 1.

CONCLUSIONS

Our results indicate Freestyle Libre 1 is a reliable tool for glucose monitoring in adults on haemodialysis. Further studies are required to evaluate Dexcom G6 accuracy in people on haemodialysis. Small molecule interferents may affect electrochemical glucose sensors in end-stage kidney disease.

Accuracy of Flash Glucose Monitoring in Hemodialysis Patients With and Without Diabetes Mellitus

AIMS

Glucose and insulin metabolism are altered in hemodialysis patients, and diabetes management is difficult in these patients. We aimed to validate flash glucose monitoring (FGM) in hemodialysis patients with and without diabetes mellitus as an attractive option for glucose monitoring not requiring regular self-punctures.

METHODS

We measured interstitial glucose using a FreeStyle Libre device in eight hemodialysis patients with and seven without diabetes mellitus over 14 days and compared the results to simultaneously performed self-monitoring of capillary blood glucose (SMBG).

RESULTS

In 720 paired measurements, mean flash glucose values were significantly lower than self-measured capillary values (6.17±2.52 vs. 7.15±2.41 mmol/L, p=1.3 E-86). Overall, the mean absolute relative difference was 17.4%, and the mean absolute difference was 1.20 mmol/L. The systematic error was significantly larger in patients without vs. with diabetes (- 1.17 vs. - 0.82 mmol/L) and on dialysis vs. interdialytic days (-1.09 vs. -0.90 mmol/L). Compared to venous blood glucose (72 paired measurements), the systematic error of FGM was even larger (5.89±2.44 mmol/L vs. 7.78±7.25 mmol/L, p=3.74E-22). Several strategies to reduce the systematic error were evaluated, including the addition of +1.0 mmol/L as a correction term to all FGM values, which significantly improved accuracy.

CONCLUSIONS

FGM systematically underestimates blood glucose in hemodialysis patients but, taking this systematic error into account, the system may be useful for glucose monitoring in hemodialysis patients with or without diabetes.

Applications of continuous glucose monitoring across settings and populations: Report from the 23rd Hong Kong diabetes and cardiovascular risk factors-East meets west symposium

Continuous glucose monitoring (CGM) is now an integral part of glycaemic management in people with type 1 diabetes and those with insulin-treated type 2 diabetes. Immediate access to information on CGM glucose levels and trends helps to inform food choices, titration and timing of insulin doses and prompts corrective actions in the event of impending hypo- or hyperglycaemia. Although glycated haemoglobin (HbA1c) remains an important measure of the average of glucose, CGM metrics including time-in-range (TIR) and other metrics on glycaemic variability and hypoglycaemia are strongly endorsed by people with diabetes as impacting their daily lives. There is growing consensus on definitions and targets of CGM metrics with an increasing number of studies demonstrating correlations between CGM metrics and incident complications of diabetes. Implementation of new technologies needs to take into consideration factors such as cost-effectiveness, accessibility as well as acceptability of the person with diabetes and healthcare professional. The United Kingdom is one of the few countries that have developed clinical pathways for integrating CGM into the routine care of people with type 1 diabetes. Besides type 1 diabetes, special groups such as people with impaired kidney function and women during pregnancy may derive additional benefits from CGM.

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.

Impact of super energy-dense oral nutritional supplementation (SED ONS) on glycemic variability and food intake postoperatively in gastric cancer patients

PURPOSE

Adherence to oral nutritional supplements (ONS) to prevent weight loss after gastrectomy is problematic. The present study evaluated the impact of super energy-dense ONS (SED ONS; 4 kcal/mL) on glycemic change and energy intake after gastrectomy.

METHODS

Gastrectomy patients were placed on continuous glucose monitoring for a 3-day observation period after food intake had been stabilized postoperatively. In addition, they were given 0, 200, and 400 kcal/day of SED ONS on Days 1, 2, and 3, respectively. The primary outcome was the area under the curve < glucose 70 mg/dL (AUC < 70). The secondary outcomes were other indices of glucose fluctuation and the amount of food and SED ONS intake.

RESULTS

Seventeen patients were enrolled. The AUC < 70 did not differ significantly with or without SED ONS over the observation period. SED ONS did not cause postprandial hypoglycemia and prevented nocturnal hypoglycemia. The mean dietary intake did not change significantly during the observation period, and the total energy intake increased significantly according to the amount of SED ONS provided.

CONCLUSION

SED ONS after gastrectomy increased the total energy intake without dietary reduction and it did not result in hypoglycemia.

Intradialytic parenteral nutrition using a standard amino acid solution not for renal failure in maintenance hemodialysis patients with malnutrition: a multicenter pilot study

Background

Standard amino acid solutions have recently been removed from the contraindications for use in dialysis patients in Japan. However, the details of their safety and efficacy in these patients are still not known. In this study, we investigated the safety and efficacy of intradialytic parenteral nutrition (IDPN) using ENEFLUID® injection containing standard amino acids, glucose, electrolytes, fats, and water-soluble vitamins in maintenance hemodialysis patients with malnutrition.

Methods

This clinical trial was designed as a multicenter, prospective, non-randomized, open-label, single-arm, observational pilot study. The participants were patients on maintenance hemodialysis who were in the nutritional high-risk group according to the Nutritional Risk Index for Japanese Hemodialysis Patients. One bag of ENEFLUID® injection was administered during every hemodialysis session for 12 weeks. The primary endpoint was change in serum transthyretin levels between before and after the 12-week period. As safety endpoints, we evaluated changes in body fluid volume and blood biochemical tests, including blood urea nitrogen and electrolytes, as well as blood glucose variability using flash glucose monitoring (FGM).

Results

The mean age and body mass index of the 13 participants were 79.0 ± 10.7 years and 18.0 ± 1.7 kg/m2, respectively. No significant changes were observed in nutritional parameters, including serum transthyretin, between before and after the start of the study. After IDPN initiation, there was no obvious fluid overload or significant changes in blood biochemical tests, including electrolytes, and the treatment could be safely continued for 12 weeks. In the FGM analysis, asymptomatic hypoglycemia during hemodialysis was observed at the beginning of the study, but there was a trend toward improvement after 12 weeks (area over the curve < 70 mg/dl per dialysis session: 747.5 ± 1333.9 to 21.6 ± 54.3, P = 0.09).

Conclusions

IDPN using ENEFLUID® injection can be safely continued, although it does not significantly improve markers of nutritional status. It also showed the potential to ameliorate asymptomatic hypoglycemia during hemodialysis sessions. More detailed studies of the improvement in nutritional indicators are needed.

Trial registration: This study was registered with the University Hospital Medical Information Network-Clinical Trials Registry (UMIN-CTR) on May 9, 2021 (registration ID, UMIN000044051).

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.

Contact dermatitis in children caused by diabetes devices

BACKGROUND

Insulin pump and glucose monitoring devices improve diabetes mellitus (DM) control and enhance patients' quality of life. However, a growing number of adverse cutaneous reactions related to the use of these devices has been reported.

OBJECTIVE

To investigate the culprits of localized contact dermatitis in pediatric patients with diabetes caused by insulin pump and glucose monitoring devices.

METHODS

Retrospective analysis of 15 pediatric patients patch tested as part of a clinical investigation for skin reactions associated with insulin pump and glucose monitoring devices RESULTS: Seven patients had positive patch test reactions to isobornyl acrylate (IBOA) and five had positive reactions to benzoyl peroxide (BP). Positive patch test reactions to materials from the glucose sensor and/or insulin pump were seen in 10 of the 15 patients. Three had positive reactions to adhesive remover wipe from Smith and Nephew Remove and four had reactions to EMLA plaster.

CONCLUSION

A high share of patients showed positive reactions to IBOA and/or their medical devices (insulin pumps or glucose devices). A third of patients showed positive reactions to benzoyl peroxide. The presence of additional unidentified allergens cannot be excluded, highlighting the importance of access to a full description of the chemical composition of the devices. This article is protected by copyright. All rights reserved.

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.

Accuracy of Flash Glucose Monitoring in Patients with Diabetes Mellitus on Hemodialysis and Its Relationship with Hydration Status

BACKGROUND

The use of flash-glucose monitoring system FreeStyle Libre (FSL) has demonstrated benefits in metabolic control and quality of life in different populations with diabetes mellitus (DM), being funded in many countries. Due to this, DM subjects on hemodialysis (HD) are using FSL despite the accuracy in this population being unclear. The aims of the present study are to assess the accuracy of FSL in DM subjects on HD, its relationship to hydration status, and patient satisfaction.

MATERIAL AND METHODS

A prospective study in 16 patients with DM in a chronic HD program was conducted. Interstitial glucose values from FSL during a 14-day period were compared to capillary glucose measurements obtained at the same time. Hydration status was measured via bioimpedance spectroscopy. Satisfaction with FSL was obtained from an ad hoc satisfaction questionnaire.

RESULTS

A total of 766 paired interstitial and capillary glucose levels were analyzed. A correlation coefficient of 0.936 was determined and a mean absolute relative difference (MARD) value of 23%, increasing to 29% during HD. MARD was not related to hydration status. Interstitial glucose values were lower during HD (100.1 ± 17 mg/dL) than within the 12 hours after (125.1 ± 39 mg/dL; P = .012) and the days without HD (134.2 ± 32 mg/dL; P = .001). Subjects showed high satisfaction with FSL.

CONCLUSION

The accuracy of FSL in DM patients on HD is lower than in other populations, especially during HD sessions and is not related with the hydration status. Despite this, the degree of patient satisfaction with FSL is very high.

Use of continuous glucose monitoring system in patients with type 2 mellitus diabetic during hemodialysis treatment

BACKGROUND

Studies highlight the inaccuracy of glycated hemoglobin (HbA1c) for the assessment of glycemic control in dialysis diabetics and suggest the use of continuous glucose monitoring (CGM) as an alternative. Of the CGMs, FreeStyle Libre^® is the most used in worldwide, but there is still no consensus on its use in dialysis.

METHOD

A 3-week prospective study was performed with 12 patients comparing capillary and interstitial glucose during dialysis.

RESULTS

Comparing capillary and interstitial measurements, similar values were observed in pre-dialysis in the 1st week (184.1 ± 69.5 mg/dl and 173.1 ± 78.9 mg/dl, respectively, p = 0.303), in patients with body mass index less than 24.9 kg/m² (214.2 ± 72.2 mg/dl and 201.3 ± 77.0 mg/dl respectively, p = 0.466), in those dialysis fluid loss less than 2 l (185.5 ± 82.6 mg/dl and 183.1 ± 94.0 mg/dl respectively and p = 0.805) and in those with hemoglobin greater than 12 g/dl (152.0 ± 35, 5 mg/dl and 129.5 ± 47.4 mg/dl respectively, p = 0.016). In the correlation of the capillary measurement with the interstitial sensor, it was observed that the proportions in the Clarke Error Grid of zone A, zone B, zone C, zone D and zone E were 62.5%, 27.1%, 0.0%, 10.4% and 0.0% respectively and in the Parkes error grid in zone A, zone B, zone C, zone D and zone E were 80.6%, 9.7%, 9.7% 0.0% and 0.0%, respectively.

CONCLUSION

The mean absolute relative difference in dialysis patients is higher than the general population without end-stage renal disease. However, clinical decision-making based on the values measured by the system can be made with a good margin based on the correlation between interstitial and capillary measurements.

The Accuracy of Hemoglobin A1c and Fructosamine Evaluated by Long-Term Continuous Glucose Monitoring in Patients with Type 2 Diabetes Undergoing Hemodialysis

INTRODUCTION

The accuracy of hemoglobin A1c (HbA1c) as a glycemic marker in patients with type 2 diabetes (T2D) receiving hemodialysis (HD) remains unknown. To assess accuracy, we compared HbA1c and fructosamine levels with interstitial glucose measured by continuous glucose monitoring (CGM) in patients with T2D receiving HD.

METHODS

Thirty patients in the HD group and 36 patients in the control group (T2D and an estimated glomerular filtration rate >60 mL/min/1.73 m2) completed the study period of 17 weeks. CGM (Ipro2®, Medtronic) was performed 5 times for periods of up to 7 days (with 4-week intervals) during a 16-week period. HbA1c (mmol/mol), the estimated mean plasma glucose from HbA1c (eMPGA1c [mmol/L]) and fructosamine (μmol/L) was measured at week 17 and compared with mean sensor glucose levels from CGM.

FINDINGS

In the HD group, mean sensor glucose was 1.4 mmol/L (95% confidence interval [CI]: 1.0-1.8) higher than the eMPGA1c, whereas the difference for controls was 0.1 mmol/L (95% CI: -0.1-[0.4]; p < 0.001). Adjusted for mean sensor glucose, HbA1c was lower in the HD group (-7.3 mmol/mol, 95% CI: -10.0-[-4.7]) than in the control group (p < 0.001), with no difference detected for fructosamine (p = 0.64).

DISCUSSION

HbA1c evaluated by CGM underestimates plasma glucose levels in patients receiving HD. The underestimation represents a clinical challenge in optimizing glycemic control in the HD population. Fructosamine is unaffected by the factors affecting HbA1c and appears to be more accurate for glycemic monitoring. CGM or fructosamine could thus complement HbA1c in obtaining more accurate glycemic control in this patient group.

Clinical interpretation of the flash continuous glucose monitoring data out of range in type 2 diabetes: A real-world study

AIMS

Flash continuous glucose monitoring system (FCGM) reports nocturnal hypoglycemia with low accuracy in low blood glucose. In our study, we aimed to evaluate the accuracy and clinic profile of FCGM data out of range in T2DM.

METHODS

FCGM data out of range were measured in T2DM patients at eight-time points of a day and compared with fingertip capillary blood glucose levels (REFs) as reference values.

RESULTS

A total of 307 out-of-range cases from 25,886 paired FCGM/REF data from 742 T2DM patients were evaluated. The distribution of "LO" and "HI" cases displayed the significant difference between eight-time points (P < 0.001) with the highest frequency (6.52%) of the "LO" value at 3 AM. The consistency rate between FCGM "LO" readings and REF < 40 mg/dl was far lower than that of FCGM "HI" readings with REF > 500 mg/dl (0.84% vs. 52.2%). In addition, the frequency of some clinical characteristics, including diabetes duration, hypoglycemia, hypertension, HbA1c, and Hb, were higher in patients with FCGM "LO" readings compared to those with "HI" readings.

CONCLUSIONS

These findings suggest the results and treatment regarding FCGM "LO" data should be interpreted with strong caution in the light of the emerging possible adverse measurement in patients.

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.

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.

Glycemic Monitoring and Management in Advanced Chronic Kidney Disease

Glucose and insulin metabolism in patients with diabetes are profoundly altered by advanced chronic kidney disease (CKD). Risk of hypoglycemia is increased by failure of kidney gluconeogenesis, impaired insulin clearance by the kidney, defective insulin degradation due to uremia, increased erythrocyte glucose uptake during hemodialysis, impaired counterregulatory hormone responses (cortisol, growth hormone), nutritional deprivation, and variability of exposure to oral antihyperglycemic agents and exogenous insulin. Patients with end-stage kidney disease frequently experience wide glycemic excursions, with common occurrences of both hypoglycemia and hyperglycemia. Assessment of glycemia by glycated hemoglobin (HbA1c) is hampered by a variety of CKD-associated conditions that can bias the measure either to the low or high range. Alternative glycemic biomarkers, such as glycated albumin or fructosamine, are not fully validated. Therefore, HbA1c remains the preferred glycemic biomarker despite its limitations. Based on observational data for associations with mortality and risks of hypoglycemia with intensive glycemic control regimens in advanced CKD, an HbA1c range of 7% to 8% appears to be the most favorable. Emerging data on the use of continuous glucose monitoring in this population suggest promise for more precise monitoring and treatment adjustments to permit fine-tuning of glycemic management in patients with diabetes and advanced CKD.

Critical discrepancy in blood glucose control levels evaluated by glycated albumin and estimated hemoglobin A1c levels determined from a flash continuous glucose monitoring system in patients with type 2 diabetes on hemodialysis

We aimed to investigate if estimated hemoglobin A1c (eHbA1c) levels determined using a flash continuous glucose monitoring system could be an indicator of glycemic control status in hemodialysis patients with diabetes. Hemodialysis patients with type 2 diabetes were recruited. eHbA1c levels were measured using the FreeStyle Libre Flash Glucose Monitoring System^®. A total of 18 hemodialysis patients with diabetes were included in the study. The eHbA1c^GA – calculated based on glycated albumin level, and body mass index and serum hemoglobin concentration were also included in the formula – was higher than the eHbA1c in most patients. Furthermore, the eHbA1c^GA – eHbA1c values were >2% in all patients with body mass index <18.5 kg/m²; the maximal value was 4.1%. This study shows that eHbA1c can be used as a reliable indicator for evaluating glycemic control and avoiding hypoglycemia in hemodialysis patients with diabetes, particularly those with decreased body mass index.

Exercise improves metformin 72-h glucose control by reducing the frequency of hyperglycemic peaks

PURPOSE

To determine the separated and combined effects of metformin and exercise on insulin sensitivity and free-living glycemic control in overweight individuals with prediabetes/type 2 diabetes (T2DM).

METHODS

We recruited 16 adults with BMI of 32.7 ± 4.3 kg m^-2 and insulin resistance (HOMA-IR 3.2 ± 0.4) under chronic metformin treatment (1234 ± 465 g day^-1) enrolled in a high-intensity interval training (HIIT) program. Participants underwent four 72-h experimental trials in a random-counterbalanced order: (1) maintaining their habitual metformin treatment (MET); (2) replacing metformin treatment by placebo (CON); (3) placebo plus two HIIT sessions (EX + CON), and (4) metformin plus two HIIT sessions (MET + EX). We used intermittently scanned continuous glucose monitoring (isCGM) during 72 h in every trial to obtain interstitial fluid glucose area under the curve (IFG_AUC) and the percentage of measurements over 180 mg dL^-1 (% IFG_PEAKS). Insulin sensitivity was assessed on the last day of each trial with HOMA-IR index and calculated insulin sensitivity (C_SI) from intravenous glucose tolerance test.

RESULTS

IFG_AUC was lower in MET + EX and MET than in CON (P = 0.011 and P = 0.025, respectively). In addition, IFG_AUC was lower in MET + EX than in EX + CON (P = 0.044). %IFG_PEAKS were only lower in MET + EX in relation to CON (P = 0.028). HOMA-IR and C_SI were higher in CON in comparison with MET + EX (P = 0.011 and P = 0.022, respectively) and MET (P = 0.006 and P < 0.001, respectively). IFG_AUC showed a significant correlation with HOMA-IR.

CONCLUSION

Intense aerobic exercise in patients with diabetes and prediabetes under metformin treatment reduces free-living 72-h blood hyperglycemic peaks. This may help to prevent the development of cardiovascular complications associated with diabetes.