Use of FreeStyle Libre Flash Monitor Register in the Netherlands (FLARE-NL1): Patient Experiences, Satisfaction, and Cost Analysis

Use of continuous glucose monitoring and point-of-care glucose testing in hospitalized patients with diabetes mellitus in non-intensive care unit settings: A systematic review and meta-analysis of randomized controlled trials

The benefits of using continuous glucose monitoring (CGM) in hospitalized patients with diabetes remain uncertain. Point-of-care (POC) glucose testing is the standard of care in this setting. We compared the effect of adding CGM to POC testing versus POC testing alone on glycemic outcomes in this population. We have searched the Cochrane Library, Embase, and MEDLINE databases and relevant conferences up to May 2024. We have included six randomized controlled trials (n = 979 patients) comparing CGM plus POC testing to POC testing alone in non-pregnant, non-critically ill hospitalized adults with diabetes. The addition of CGM improved time in range (mean difference [MD] + 7.24 %; 95 % confidence interval [CI]: +5.06, +9.42; P < 0.00001; I2 = 35 %), reduced time below range < 70 mg/dL (MD: -1.23 %; 95 %CI: -2.27, -0.18; P = 0.02; I2 = 64 %) and < 54 mg/dL (MD: -0.95 %; 95 %CI: -1.19, -0.70; P < 0.00001; I2 = 0 %), and time above range > 250 mg/dL (MD: -3.70 %; 95 %CI: -6.10, -1.29; P = 0.003; I2 = 39 %) compared to POC testing alone. We observed no statistically significant differences in glycemic variability or insulin doses. In non-critically ill, hospitalized adults with diabetes, the addition of CGM to POC testing for insulin dosing resulted in superior glycemic control and reduction of hypoglycemia compared to POC testing alone.

High-Carbohydrate Energy Intake During a Round of Golf-Maintained Blood Glucose Levels, Inhibited Energy Deficiencies, and Prevented Fatigue: A Randomized, Double-Blind, Parallel Group Comparison Study

OBJECTIVES

This study primarily aimed to examine the optimal amount of carbohydrates in the effects of high-isomaltulose and high-sucrose ingestion compared with low-sucrose ingestion on blood glucose levels. The secondary objective was to assess the changes in blood glucose levels that may impact golf-related performance.

METHODS

This study included 29 healthy male competitive golfers playing 18 holes. These participants were randomly assigned to the low-sucrose (LSUC, 30.9 g/h of carbohydrates), high-sucrose (HSUC, 44.2 g/h of carbohydrates), and high-isomaltulose (HISO, 44.5 g/h of carbohydrates) groups. They were required to continuously consume the test food during the round. Assessment items included blood glucose, golf performance, urinary urea nitrogen, subjective ratings (concentration, fatigue, and relaxation), and anxiety ratings. A main effect of the test meal of changes in interstitial glucose concentration was determined.

RESULTS

The HSUC had significantly more interstitial glucose than the HISO and LSUC, while the HISO group had a much lower decrease in urine urea nitrogen than the LSUC group. In subjective fatigue, the main effect of the test diet was observed, and the HSUC and HISO showed significantly lower values than the LSUC after 18 h.

CONCLUSIONS

Compared with low-carbohydrate intake, high-carbohydrate intake during a round of golf-maintained the blood glucose levels and prevented fatigue. Therefore, this study indicates that competitive golfers need a high-carbohydrate intake of approximately 44 g/h for energy intake during a round of golf.

Effects of Continuous Carbohydrate Intake with Gummies during the Golf Round on Interstitial Glucose, Golf Performance, and Cognitive Performance of Competitive Golfers: A Randomized Repeated-Measures Crossover Design

This study examined the effects of continuous carbohydrate intake during a golf round on interstitial glucose, golf performance, and the cognitive performance of competitive golfers. Eleven competitive golfers participated and played 18 holes of golf in this study. Participants were randomly assigned to the group indicated to consume the test food (CHO intake) or the group required to not consume it (NOT intake). Here, gummies were used as the test food, and the amount of carbohydrates was 30 g per h. Blood glucose levels were evaluated using interstitial glucose. Golf performance was measured in five tests, including scores, 2.5 m putting test, club head speed, driving distance, and accuracy. Cognitive performance was measured in three tests, including self-perceived levels of fatigue (PLF), self-perceived levels of concentration (PLC), and self-perceived levels of relaxation (PLR). Interstitial glucose (p < 0.001) and PLF (p < 0.001) were significantly reduced in the CHO intake compared with that in the NOT intake from the sixth hole. PLC was significantly higher in the CHO intake than in the NOT intake on all 18 holes (p = 0.032). These findings suggest that continuous carbohydrate intake may be effective in reducing fatigue and maintaining the performance of competitive golfers.

Commencement of flash glucose monitoring is associated with a decreased rate of depressive disorders among persons with diabetes (FLARE-NL7)

INTRODUCTION

Depressive disorders are more common among persons with diabetes, as compared with persons without diabetes. The burden of glucose management is known to associate with depressive symptoms. This study aims to assess the effects of commencement of FreeStyle Libre flash glucose monitoring (FSL-FGM) on the mental health status of persons with diabetes.

RESEARCH DESIGN AND METHODS

Post-hoc analysis of data from a 1-year prospective nationwide FSL-FGM registry. Participants who used FSL-FGM for 12 months and completed the 12-Item Short Form Health Survey version 2 (SF-12^v2) questionnaires at baseline, 6 and 12 months were included. An SF-12^v2 Mental Component Score (MCS) of ≤45 was used as a cut-off to discriminate between persons with and without a depressive disorder.

RESULTS

A total of 674 patients were included with a mean age of 48.2 (±15.8) years, 51.2% men, 78.2% type 1 diabetes and baseline HbA1c 62.8 (±13.4) mmol/mol (7.9±1.2%). At baseline, 235 (34.9%) persons had an SF-12 MCS ≤45 while after 6 and 12 months these numbers decreased: 202 (30.0%, p<0.01) and 173 (25.7%, p<0.01). Overall, MCS improved from 48.5 at baseline to 50.7 after 6 months and 51.3 after 12 months. In multivariable regression analysis, age and MCS at baseline were associated with improvement of MCS after 12 months of FSL-FGM use.

CONCLUSIONS

This analysis suggests that use of FSL-FGM is associated with a decreased rate of depressive disorders among persons with diabetes. Future studies are needed to corroborate these findings.

Landscape of Continuous Glucose Monitoring (CGM) and Integrated CGM: Accuracy Considerations

Continuous glucose monitoring devices have significantly improved in many respects compared with earlier versions. As sensor accuracy improved, U.S. Food and Drug Administration approved a nonadjunctive indication for use that no longer required confirmatory blood glucose monitoring. This article discusses the performance characteristics and regulatory classifications for the current systems that are relevant to informed clinical decision-making.

Two-year use of flash glucose monitoring is associated with sustained improvement of glycemic control and quality of life (FLARE-NL-6)

INTRODUCTION

The FreeStyle Libre (FSL) is a flash glucose monitoring (FGM) system. The Flash Monitor Register in the Netherlands (FLARE-NL-4) study previously demonstrated the positive effects of FSL-FGM use during 1 year on glycemic control, quality of life and disease burden among persons with diabetes mellitus (DM). The present follow-up study assesses the effects of FSL-FGM after 2 years.

RESEARCH DESIGN AND METHODS

Patients included in the FLARE-NL-4 study who continued FSL-FGM during the 1-year study period were invited to participate (n=687). Data were collected using questionnaires (the 12-Item Short Form Health Survey version 2 (SF-12^v2) and the EuroQol 5-Dimension 3-Level (EQ-5D-3L) for quality of life), including self-reported hemoglobin A1c (HbA1c).

RESULTS

A total of 342 patients agreed to participate: mean age 48.0 (±15.6) years, 52% men and 79.5% with type 1 DM. HbA1c decreased from 60.7 (95% CI 59.1 to 62.3) mmol/mol before use of FSL-FGM to 57.3 (95% CI 55.8 to 58.8) mmol/mol after 1 year and 57.8 (95% CI 56.0 to 59.5) mmol/mol after 2 years. At the end of the 2-year follow-up period, 260 (76%) persons were still using the FSL-FGM and 82 (24%) had stopped. The main reason for stopping FSL-FGM was financial constraints (55%). Concerning the whole 2-year period, there was a significant decrease in HbA1c among persons who continued use of FSL-FGM (-3.5 mmol/mol, 95% CI -6.4 to -0.7), while HbA1c was unaltered compared with baseline among persons who stopped FSL-FGM (-2.4 mmol/mol, 95% CI -7.5 to 2.7): difference between groups 2.2 (95% CI -1.3 to 5.8) mmol/mol. After 2 years, persons who continued use of FSL-FGM had higher SF-12 mental component score and higher EQ-5D Dutch tariff score and felt less often anxious or depressed compared with persons who discontinued FSL-FGM.

CONCLUSIONS

Although the considerable number of non-responders limits generalizability, this study suggests that persons who continue to use FSL-FGM for 2 years may experience sustained improvement in glycemic control and quality of life.

Just Because You Can, Doesn't Mean You Should … Now. A Practical Approach to Counseling Persons with Diabetes on Use of Optional CGM Alarms

Advances in glucose monitoring technologies have led to the development of different types of continuous glucose monitoring (CGM) platforms: traditional CGM and flash CGM. Both platforms provide critical glucose data that enable persons with diabetes (PwDs) to make more informed decisions in their self-management. Until recently, a key advantage of traditional CGM over flash CGM was the availability of automatic alarms that warn users about current or impending hypoglycemia and hyperglycemia. However, with the introduction of the FreeStyle Libre 2 (FSL2) system (Abbott Diabetes Care, Alameda, CA), PwD can now utilize flash CGM with the option to set low and high glycemic thresholds and receive alarms when these thresholds are crossed. In addition, having the option to use or not use the alarms may attract previous traditional CGM users who grew fatigued by constant alarms. However, despite the additional layer of safety that alarms provide, many PwD are reluctant to switch from self-monitoring of blood glucose to CGM due to concerns about how alarms could impact the quality of their daily lives. This reluctance is heightened by their perceptions that use of alarms is mandatory. Because the functionality of the FSL2 alarms differs from current traditional CGM devices, it is important that clinicians become familiar with these differences. Moreover, clinicians will be challenged to help PwD overcome their concerns about the use of alarms. This article presents a comprehensive description of the FSL2 alarms function and provides guidance to clinicians when counseling PwDs about the strengths, limitations, and various ways that the FSL2 alarms can be used in daily diabetes self-management.

Evolving Use of Continuous Glucose Monitoring Beyond Intensive Insulin Treatment

Numerous studies have demonstrated the clinical benefits of continuous glucose monitoring (CGM) use in individuals with type 1 diabetes and type 2 diabetes (T2D) who are treated with intensive insulin therapy. A growing body of evidence suggests that CGM use may also confer similar glycemic benefits in T2D individuals who are treated with less-intensive therapies. Investigators are also exploring the potential use of CGM as an aid in weight management. This article reviews the continuing evolution of CGM, focusing on how CGM may be used to improve glycemic control and promote adoption of desired health behaviors within broader T2D and prediabetes populations.

Contribution of Solid Food to Achieve Individual Nutritional Requirement during a Continuous 438 km Mountain Ultramarathon in Female Athlete

Background: Races and competitions over 100 miles have recently increased. Limited information exists about the effect of multiday continuous endurance exercise on blood glucose control and appropriate intake of food and drink in a female athlete. The present study aimed to examine the variation of blood glucose control and its relationship with nutritional intake and running performance in a professional female athlete during a 155.7 h ultramarathon race with little sleep. Methods: We divided the mountain course of 438 km into 33 segments by timing gates and continuously monitored the participant’s glucose profile throughout the ultramarathon. The running speed in each segment was standardized to the scheduled required time-based on three trial runs. Concurrently, the accompanying runners recorded the participant’s food and drink intake. Nutrient, energy, and water intake were then calculated. Results: Throughout the ultramarathon of 155.7 h, including 16.0 h of rest and sleep, diurnal variation had almost disappeared with the overall increase in blood glucose levels (25–30 mg/dL) compared with that during resting (p < 0.0001). Plasma total protein and triglyceride levels were decreased after the ultramarathon. The intake of protein and fat directly or indirectly contributed to maintaining blood glucose levels and running speed as substrates for gluconeogenesis or as alternative sources of energy when the carbohydrate intake was at a lower recommended limit. The higher amounts of nutrient intakes from solid foods correlated with a higher running pace compared with those from liquids and gels to supply carbohydrates, protein, and fat. Conclusion: Carbohydrate, protein, and fat intake from solid foods contributed to maintaining a fast pace with a steady, mild rise in blood glucose levels compared with liquids and gels when female runner completed a multiday continuous ultramarathon with little sleep.

Uninterrupted continuous glucose monitoring access is associated with a decrease in HbA1c in youth with type 1 diabetes and public insurance

OBJECTIVE

Continuous glucose monitor (CGM) use is associated with improved glucose control. We describe the effect of continued and interrupted CGM use on hemoglobin A1c (HbA1c) in youth with public insurance.

METHODS

We reviewed 956 visits from 264 youth with type 1 diabetes (T1D) and public insurance. Demographic data, HbA1c and two-week CGM data were collected. Youth were classified as never user, consistent user, insurance discontinuer, and self-discontinuer. Visits were categorized as never-user visit, visit before CGM start, visit after CGM start, visit with continued CGM use, visit with initial loss of CGM, visit with continued loss of CGM, and visit where CGM is regained after loss. Multivariate regression adjusting for age, sex, race, diabetes duration, initial HbA1c, and body mass index were used to calculate adjusted mean and delta HbA1c.

RESULTS

Adjusted mean HbA1c was lowest for the consistent user group (HbA1c 8.6%;[95%CI 7.9,9.3]). Delta HbA1c (calculated from visit before CGM start) was lower for visit after CGM start (-0.39%;[95%CI -0.78,-0.02]) and visit with continued CGM use (-0.29%;[95%CI -0.61,0.02]), whereas it was higher for visit with initial loss of CGM (0.40%;[95%CI -0.06,0.86]), visit with continued loss of CGM (0.46%;[95%CI 0.06,0.85]), and visit where CGM is regained after loss (0.57%;[95%CI 0.06,1.10]).

CONCLUSIONS

Youth with public insurance using CGM have improved HbA1c, but only when CGM use is uninterrupted. Interruptions in use, primarily due to gaps in insurance coverage of CGM, were associated with increased HbA1c. These data support both initial and ongoing coverage of CGM for youth with T1D and public insurance.

Continuous Glucose Monitors and Automated Insulin Dosing Systems in the Hospital Consensus Guideline

This article is the work product of the Continuous Glucose Monitor and Automated Insulin Dosing Systems in the Hospital Consensus Guideline Panel, which was organized by Diabetes Technology Society and met virtually on April 23, 2020. The guideline panel consisted of 24 international experts in the use of continuous glucose monitors (CGMs) and automated insulin dosing (AID) systems representing adult endocrinology, pediatric endocrinology, obstetrics and gynecology, advanced practice nursing, diabetes care and education, clinical chemistry, bioengineering, and product liability law. The panelists reviewed the medical literature pertaining to five topics: (1) continuation of home CGMs after hospitalization, (2) initiation of CGMs in the hospital, (3) continuation of AID systems in the hospital, (4) logistics and hands-on care of hospitalized patients using CGMs and AID systems, and (5) data management of CGMs and AID systems in the hospital. The panelists then developed three types of recommendations for each topic, including clinical practice (to use the technology optimally), research (to improve the safety and effectiveness of the technology), and hospital policies (to build an environment for facilitating use of these devices) for each of the five topics. The panelists voted on 78 proposed recommendations. Based on the panel vote, 77 recommendations were classified as either strong or mild. One recommendation failed to reach consensus. Additional research is needed on CGMs and AID systems in the hospital setting regarding device accuracy, practices for deployment, data management, and achievable outcomes. This guideline is intended to support these technologies for the management of hospitalized patients with diabetes.

Determinants of HbA1c reduction with FreeStyle Libre flash glucose monitoring (FLARE-NL 5)

Aims

To identify factors predicting HbA1c reduction in patients with diabetes mellitus (DM) using FreeStyle Libre Flash Glucose Monitoring (FSL-FGM).

Methods

Data from a 12-month prospective nation-wide FSL registry were used and analysed with multivariable regression. For the present study we included patients with hypoglycaemia unawareness or unexpected hypoglycaemias (n = 566) and persons who did not reach acceptable glycaemic control (HbA1c > 70 mmol/mol (8.5%)) (n = 294). People with other indications for use, such as sensation loss of the fingers or individuals already using FSL-FGM or rtCGM, were excluded (37%).

Results

Eight hundred and sixty persons (55% male with a mean age of 46.7 (±16.4) years) were included. Baseline HbA1c was 65.1 (±14.5) mmol/mol (8.1 ± 1.3%), 75% of the patients had type 1 DM and 37% had microvascular complications. Data concerning HbA1c was present for 482 (56.0%) at 6 months and 423 (49.2%) persons at 12 months. A significant reduction in HbA1c (≥5 mmol/mol (0.5%)) was present in 187 (22%) persons. For these persons, median HbA1c reduction was −9.0 [−13.0, −4.0] mmol/mol (−0.82 [−1.19, −0.37]%) at 6 months and −9.0 [−15.0, −7.0] mmol/mol (−0.82 [−1.37, −0.64]%) at 12 months. In multivariable regression analysis with age, gender and SF-12 physical and mental component scores as covariates, only baseline HbA1c was significant: −0.319 (SE 0.025; p < 0.001; R² = 0.240 for the model). In exploratory analysis among subgroups with different indications for FSL-FGM use (hypoglycaemia unawareness or persistently high HbA1c) and persons with a significant HbA1c decrease over the study period, baseline HbA1c remained the only significant predictor.

Conclusions

Among the variables we analysed in the present study, only high HbA1c at baseline predicts significant HbA1c reduction during FSL-CGM use.

Effect of Flash Glucose Monitoring on Glycemic Control, Hypoglycemia, Diabetes-Related Distress, and Resource Utilization in the Association of British Clinical Diabetologists (ABCD) Nationwide Audit

OBJECTIVE

The FreeStyle Libre (FSL) flash glucose-monitoring device was made available on the U.K. National Health Service (NHS) drug tariff in 2017. This study aims to explore the U.K. real-world experience of FSL and the impact on glycemic control, hypoglycemia, diabetes-related distress, and hospital admissions.

RESEARCH DESIGN AND METHODS

Clinicians from 102 NHS hospitals in the U.K. submitted FSL user data, collected during routine clinical care, to a secure web-based tool held within the NHS N3 network. The t and Mann-Whitney U tests were used to compare the baseline and follow-up HbA_1c and other baseline demographic characteristics. Linear regression analysis was used to identify predictors of change in HbA_1c following the use of FSL. Within-person variations of HbA_1c were calculated using [Formula: see text].

RESULTS

Data were available for 10,370 FSL users (97% with type 1 diabetes), age 38.0 (±18.8) years, 51% female, diabetes duration 16.0 (±49.9) years, and BMI of 25.2 (±16.5) kg/m² (mean [±SD]). FSL users demonstrated a -5.2 mmol/mol change in HbA_1c, reducing from 67.5 (±20.9) mmol/mol (8.3%) at baseline to 62.3 (±18.5) mmol/mol (7.8%) after 7.5 (interquartile range 3.4-7.8) months of follow-up (n = 3,182) (P < 0.0001). HbA_1c reduction was greater in those with initial HbA_1c ≥69.5 mmol/mol (>8.5%), reducing from 85.5 (±16.1) mmol/mol (10%) to 73.1 (±15.8) mmol/mol (8.8%) (P < 0.0001). The baseline Gold score (score for hypoglycemic unawareness) was 2.7 (±1.8) and reduced to 2.4 (±1.7) (P < 0.0001) at follow-up. A total of 53% of those with a Gold score of ≥4 at baseline had a score <4 at follow-up. FSL use was also associated with a reduction in diabetes distress (P < 0.0001). FSL use was associated with a significant reduction in paramedic callouts and hospital admissions due to hypoglycemia and hyperglycemia/diabetic ketoacidosis.

CONCLUSIONS

We show that the use of FSL was associated with significantly improved glycemic control and hypoglycemia awareness and a reduction in hospital admissions.

Continuous Glucose Monitoring in Adults with Type 1 Diabetes: Real-World Data from the German/Austrian Prospective Diabetes Follow-Up Registry

Background: To analyze key indicators of metabolic control in adults with type 1 diabetes (T1D) using real-time or intermittent scanning continuous glucose monitoring (rtCGM/iscCGM) during real-life care, based on the German/Austrian/Swiss Prospective Diabetes Follow-up (DPV) registry. Methods: Cross-sectional analysis including 233 adults with T1D using CGM. We assessed CGM metrics by gender, age group (18 to <30 years vs. ≥30 years), insulin delivery method (multiple daily injections vs. continuous subcutaneous insulin infusion [CSII]) and sensor type (iscCGM vs. rtCGM), working days versus weekends, and daytime versus night-time using multivariable linear regression models (adjusted for demographic variables) or Wilcoxon signed-rank test. Results: Overall, 79/21% of T1D patients used iscCGM/rtCGM. Those aged ≥30 years spent more time in range (TIR [70-180 mg/dL] 54% vs. 49%) and hypoglycemic range <70 mg/dL (7% vs. 5%), less time in hyperglycemic range >180 mg/dL (38% vs. 46%) and had a lower glucose variability (coefficient of variation [CV] 36% vs. 37%) compared with adults aged <30 years. We found no significant differences between genders. Multivariable regression models revealed the highest Time In Range (TIR) and lowest time with sensor glucose >250 mg/dL, CV and daytime-night-time differences in those treated with CSII and rtCGM. Glucose profiles were slightly more favorable on working days. Conclusions: In our real-world data, rtCGM versus iscCGM was associated with a higher percentage of TIR and improved metabolic stability. Differences in ambulatory glucose profiles on working and weekend days may indicate lifestyle habits affecting glycemic stability. Real-life CGM results should be included in benchmarking reports in addition to hemoglobin A1c (HbA1c) and history of hypoglycemia.

Application of Continuous Glucose Monitoring for Assessment of Individual Carbohydrate Requirement during Ultramarathon Race

Background: The current study intended to evaluate the feasibility of the application of continuous glucose monitoring to guarantee optimal intake of carbohydrate to maintain blood glucose levels during a 160-km ultramarathon race. Methods: Seven ultramarathon runners (four male and three female) took part in the study. The glucose profile was monitored continuously throughout the race, which was divided into 11 segments by timing gates. Running speed in each segment was standardized to the average of the top five finishers for each gender. Food and drink intake during the race were recorded and carbohydrate and energy intake were calculated. Results: Observed glucose levels ranged between 61.9–252.0 mg/dL. Average glucose concentration differed from the start to the end of the race (104 ± 15.0 to 164 ± 30.5 SD mg/dL). The total amount of carbohydrate intake during the race ranged from 0.27 to 1.14 g/kg/h. Glucose concentration positively correlated with running speeds in segments (P < 0.005). Energy and carbohydrate intake positively correlated with overall running speed (P < 0.01). Conclusion: The present study demonstrates that continuous glucose monitoring could be practical to guarantee optimal carbohydrate intake for each ultramarathon runner.

Practical guidance for using the FreeStyle Libre flash continuous glucose monitoring in primary care

Use of continuous glucose monitoring (CGM) improves clinical outcomes in type 1 diabetes, and significant benefits been demonstrated in patients with type 2 diabetes, including improved glycemic control, better treatment adherence, and an increased understanding of their treatment regimens. Currently, there are two types of CGM systems: real-time CGM (rtCGM) and flash CGM (FCGM). Retrospective analysis of CGM data allows patients and their clinicians to identify glycemic patterns that support and facilitate informed therapy decisions. With the increasing prevalence of diabetes, primary care physicians will be compelled to take on more responsibility for managing patients with diabetes. This article focuses on practical approaches and decision-making strategies for utilizing FCGM in primary care settings.