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

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.

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.

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?

Performance of Dexcom G5 and FreeStyle Libre sensors tested simultaneously in people with type 1 or 2 diabetes and advanced chronic kidney disease

BACKGROUND

Advanced chronic kidney disease (CKD) is a common complication for people with type 1 and 2 diabetes and can often lead to glucose instability. Continuous glucose monitoring (CGM) helps users monitor and stabilize their glucose levels. To date, CGM and intermittent scanning CGM are only approved for people with diabetes but not for those with advanced CKD.

AIM

To compare the performance of Dexcom G5 and FreeStyle Libre sensors in adults with type 1 or 2 diabetes and advanced CKD.

METHODS

This was a non-randomized clinical trial that took place in two outpatient clinics in western Sweden. All patients with type 1 or 2 diabetes and an estimated glomerular filtration rate (eGFR) of < 30 mL/min per 1.73 m² were invited to participate. Forty patients (full analysis set = 33) carried the Dexcom G5 sensor for 7 d and FreeStyle Libre sensor for 14 d simultaneously. For referencing capillary blood glucose (SMBG) was measured with a high accuracy glucose meter (HemoCue^®) during the study period. At the end of the study, all patients were asked to answer a questionnaire on their experience using the sensors.

RESULTS

The mean age was 64.1 (range 41-77) years, hemoglobin A1c was 7.0% [standard deviation (SD) 3.2], and diabetes duration was 28.5 (SD 14.7) years. A total of 27.5% of the study population was on hemodialysis and 22.5% on peritoneal dialysis. The mean absolute relative difference for Dexcom G5 vs SMBG was significantly lower than that for FreeStyle Libre vs SMBG [15.2% (SD 12.2) vs 20.9% (SD 8.6)], with a mean difference of 5.72 [95% confidence interval (CI): 2.11-9.32; P = 0.0036]. The mean absolute difference was also significantly lower for Dexcom G5 than for FreeStyle Libre, 1.21 mmol/L (SD 0.78) and 1.76 mmol/L (SD 0.78), with a mean diffrenec of 0.55 (95%CI: 0.27-0.83; P = 0.0004).The mean difference (MD) was -0.107 mmol/L and -1.10 mmol/L (P = 0.0002), respectively. In all, 66% of FreeStyle Libre values were in the no risk zone on the surveillance error grid compared to 82% of Dexcom G5 values.

CONCLUSION

Dexcom G5 produces more accurate sensor values than FreeStyle Libre in people with diabetes and advanced CKD and is likely safe to be used by those with advanced CKD.

Clinical feasibility of remote intermittently scanned continuous glucose monitoring in coronavirus disease 2019 patients with and without diabetes during dexamethasone therapy

The clinical utility of intermittently scanned continuous glucose monitoring (isCGM) in patients with coronavirus disease 2019 (COVID-19) is unclear. Hence, we investigated the accuracy of isCGM in COVID-19 patients during dexamethasone therapy. We evaluated the accuracy of the FreeStyle Libre via smartphone isCGM device compared to point-of-care (POC) fingerstick glucose level monitoring in 16 patients with COVID-19 (10 with and 6 without diabetes, 13 men; HbA1c 6.9 ± 1.0%). Overall, isCGM correlated well with POC measurements (46.2% and 53.8% within areas A and B of the Parkes error grid, respectively). The overall mean absolute relative difference (MARD) for isCGM compared to POC measurements was 19.4%. The MARDs were 19.8% and 19.7% for POC blood glucose measurements ranging from 70 to 180 mg/dL and >180 mg/dL, respectively. When divided according to the presence and absence of diabetes, both groups of paired glucose measurements showed a good correlation (56.3% and 43.7%, and 27.1% and 72.9% within the A and B areas in patients with and without diabetes, respectively), but the MARD was not significant but higher in patients without diabetes (16.5% and 24.2% in patients with and without diabetes). In conclusion, although isCGM may not be as accurate as traditional blood glucose monitoring, it has good reliability in COVID-19 patients with and without diabetes during dexamethasone therapy.

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.

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.

Diabetes Technology Meeting 2020

Diabetes Technology Society hosted its annual Diabetes Technology Meeting on November 12 to November 14, 2020. This meeting brought together speakers to cover various perspectives about the field of diabetes technology. The meeting topics included artificial intelligence, digital health, telemedicine, glucose monitoring, regulatory trends, metrics for expressing glycemia, pharmaceuticals, automated insulin delivery systems, novel insulins, metrics for diabetes monitoring, and discriminatory aspects of diabetes technology. A live demonstration was presented.

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.