Real-World Hypoglycemia Avoidance With a Predictive Low Glucose Alert Does Not Depend on Frequent Screen Views

Background: Frequent real-time continuous glucose monitoring (rtCGM) data viewing has been associated with reduced mean glucose and frequent scanning of an intermittently scanned continuous glucose monitoring (isCGM) system has been associated with reduced hypoglycemia for patients with diabetes. However, requiring patients to frequently interact with their glucose monitoring devices to detect actual or impending hypoglycemia is burdensome. We hypothesized that a predictive low glucose alert, which forecasts glucose ≤55 mg/dL within 20 minutes and is included in a new rtCGM system, could mitigate hypoglycemia without requiring frequent device interaction. Methods: We analyzed estimated glucose values (EGVs) from an anonymized convenience sample of 15,000 patients who used Dexcom G6 (Dexcom, Inc, San Diego, CA, USA) and its mobile app for at least 30 days with or without the “Urgent Low Soon” alert (ULS) enabled. Screen view frequency was determined as the frequency with which the trend screen was accessed on the app. Multiple screen views within any 5-minute interval were counted as one. Hypoglycemia exposure for patients in the top and bottom quartiles of screen view frequency (>8.25 and <3.30 per day, respectively) was calculated as the percentage of EGVs below various thresholds. Results: Over 93% of users enabled the ULS alert; its use was associated with significantly reduced hypoglycemia <55 and <70 mg/dL, independent of screen view frequency. Conclusion: Use of the G6 ULS alert may disencumber rtCGM users by promoting significant reductions in hypoglycemia without requiring frequent device interactions.

Download Full-text

The Use of HbA1c, Glycated Albumin and Continuous Glucose Monitoring to Assess Glucose Control in the Chronic Kidney Disease Population Including Dialysis

Nephron ◽

10.1159/000511614 ◽

2020 ◽

Vol 145 (1) ◽

pp. 14-19

Author(s):

Tobias Bomholt ◽

Therese Adrian ◽

Kirsten Nørgaard ◽

Ajenthen G. Ranjan ◽

Thomas Almdal ◽

...

Keyword(s):

Glycemic Control ◽

Continuous Glucose Monitoring ◽

Glycated Albumin ◽

Glucose Monitoring ◽

Glucose Variability ◽

Glycated Haemoglobin ◽

Time Data ◽

Precise Estimation ◽

Patients With Diabetes ◽

Mean Glucose

Background: Glycated haemoglobin A1c (HbA1c) has limitations as a glycemic marker for patients with diabetes and CKD and for those receiving dialysis. Glycated albumin is an alternative glycemic marker, and some studies have found that glycated albumin more accurately reflects glycemic control than HbA1c in these groups. However, several factors are known to influence the value of glycated albumin including proteinuria. Continuous glucose monitoring (CGM) is another alternative to HbA1c. CGM allows one to assess mean glucose, glucose variability, and the time spent in hypo-, normo-, and hyperglycemia. Currently, several different CGM models are approved for use in patients receiving dialysis; CKD (not on dialysis) is not a contraindication in any of these models. Some devices are for blind recording, while others provide real-time data to patients. Small studies suggest that CGM could improve glycemic control in hemodialysis patients, but this has not been studied for individual CKD stages. Summary: Glycated albumin and CGM avoid the pitfalls of HbA1c in CKD and dialysis populations. However, the value of glycated albumin may be affected by several factors. CGM provides a precise estimation of the mean glucose. Here, we discuss the strengths and limitations for using HbA1c, glycated albumin, or CGM in CKD and dialysis population. Key Messages: Glycated albumin is an alternative glycemic marker but is affected by proteinuria. CGM provides a precise estimation of mean glucose and glucose variability. It remains unclear if CGM improves glycemic control in the CKD and dialysis populations.

Download Full-text

Measures of Accuracy for Continuous Glucose Monitoring and Blood Glucose Monitoring Devices

Journal of Diabetes Science and Technology ◽

10.1177/1932296818812062 ◽

2018 ◽

Vol 13 (3) ◽

pp. 575-583 ◽

Cited By ~ 6

Author(s):

Guido Freckmann ◽

Stefan Pleus ◽

Mike Grady ◽

Steven Setford ◽

Brian Levy

Keyword(s):

Blood Glucose ◽

Continuous Glucose Monitoring ◽

Measurement Accuracy ◽

Glucose Monitoring ◽

Blood Glucose Monitoring ◽

Glucose Measurement ◽

Bias Analysis ◽

Patients With Diabetes ◽

Monitoring Devices ◽

Error Grid

Currently, patients with diabetes may choose between two major types of system for glucose measurement: blood glucose monitoring (BGM) systems measuring glucose within capillary blood and continuous glucose monitoring (CGM) systems measuring glucose within interstitial fluid. Although BGM and CGM systems offer different functionality, both types of system are intended to help users achieve improved glucose control. Another area in which BGM and CGM systems differ is measurement accuracy. In the literature, BGM system accuracy is assessed mainly according to ISO 15197:2013 accuracy requirements, whereas CGM accuracy has hitherto mainly been assessed by MARD, although often results from additional analyses such as bias analysis or error grid analysis are provided. The intention of this review is to provide a comparison of different approaches used to determine the accuracy of BGM and CGM systems and factors that should be considered when using these different measures of accuracy to make comparisons between the analytical performance (ie, accuracy) of BGM and CGM systems. In addition, real-world implications of accuracy and its relevance are discussed.

Download Full-text