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

Matoba, Kenta; Hayashi, Akinori; Shimizu, Nahoko; Moriguchi, Ibuki; Kobayashi, Naoyuki; Shichiri, Masayoshi

doi:10.1016/j.jdiacomp.2020.107680

Cited by 14 publications

(13 citation statements)

References 22 publications

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“…First, the number of patients included in the study was not large, but this mainly depends on the difficulty in identifying appropriate subjects, i.e., hemodialysis patients matching all the inclusion criteria and willing to participate to the study. It should also be noted that the number of patients of our study was nonetheless typically higher than that of previous relevant studies in the field (7)(8)(9)(10)(11)(12)(13)(14)(15)(16)39), with only a couple of studies having similar or slightly higher number of participants [i.e., 38 and 46 subjects (7, 10)].…”

Section: Discussionmentioning

confidence: 72%

“…Furthermore, similarly to the previously indicated study (7), the assessment of glycemic control and variability was limited. Similar limitations hold also for the other two indicated studies (9,39), with regard to glucose readings duration and study population (thirteen patients with type 2 diabetes, again without non-diabetic patients), though in these studies it has to be appreciated the concomitant use of both FGM and CGM systems, in addition to SMBG monitoring. In our study, CGM system was not used, for reasons of project cost containment, and to limit the burden and discomfort of the study to the patients.…”

Section: Discussionmentioning

confidence: 81%

“…To our knowledge, very few studies used FGM in patients undergoing hemodialysis (7)(8)(9)39). In the first of those studies (7), 32 patients, both with and without diabetes, were studied.…”

Section: Discussionmentioning

confidence: 99%

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

et al. 2021

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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.

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Section: Discussionmentioning

confidence: 72%

Section: Discussionmentioning

confidence: 81%

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

et al. 2021

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“…Performance may vary by glucose levels with higher values leading to more bias and less precision. Areas affecting accuracy and opportunities for improvement include, Preanalytical: such as pressure on sensor site, 130 X Rays, 131 lipohypertrophy, 132 Analytical: Interfering substances, 133,134 end-stage renal disease/dialysis, 135 and Postanalytical: hardware (parakeet, nightrider), software (Nightscout, Looping, tomato), and data analysis (human error). 136,137 Accuracy may even be more important for patients at high risk of hypoglycemia such as those with hypoglycemic unawareness.…”

Section: Consensusmentioning

confidence: 99%

Diabetes Technology Meeting 2020

Shang

Zhang

Bequette

et al. 2021

J Diabetes Sci Technol

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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.

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“…We used a novel sensor-based flash glucose monitoring system (Freestyle Libre TM ; Abbott Diabetes Care, FGM) to improve glycemia. The latest research showed that FGM has good clinical agreement in T2DM patients undergoing HD [8]. There is increasing evidence that FGM use in T2DM improves glycemic control without the risk of hypoglycemia [9], while the currently available evidence is scarce for diabetic dialysis patients.…”

Section: Introductionmentioning

confidence: 99%

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

Peng

et al. 2021

Blood Purif

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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.

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

Cited by 14 publications

References 22 publications

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

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

Diabetes Technology Meeting 2020

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

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