Clinical Approach to Flash Glucose Monitoring: An Expert Recommendation

Current landscape and comprehensive management of glycemic variability in diabetic retinopathy

Diabetic retinopathy (DR), a well-known microvascular complication of diabetes mellitus, remains the main cause of vision loss in working-age adults worldwide. Up to now, there is a shortage of information in the study regarding the contributing factors of DR in diabetes. Accumulating evidence has identified glycemic variability (GV), referred to fluctuations of blood glucose levels, as a risk factor for diabetes-related complications. Recent reports demonstrate that GV plays an important role in accounting for the susceptibility to DR development. However, its exact role in the pathogenesis of DR is still not fully understood. In this review, we highlight the current landscape and relevant mechanisms of GV in DR, as well as address the mechanism-based therapeutic strategies, aiming at better improving the quality of DR management in clinical practice.

Mixed methods study on the feasibility of implementing periodic continuous glucose monitoring among individuals with type 2 diabetes mellitus in a primary care setting

Background

Health care professionals (HCPs) play a central role in leveraging technologies to support individuals with diabetes. This mixed-method study was completed to determine the feasibility of implementing periodic continuous glucose monitoring (CGM) in a primary care setting.

Aim

This study aimed to evaluate and describe the experiences of using periodic CGM with data visualization tools in patients with type 2 diabetes to foster a person-centered approach in a primary care setting.

Methods

Fifty outpatients aged ≥18 years, diagnosed with type 2 diabetes, and with a disease duration of at least 2 years were included in this study. Data were collected from April 2021 to January 2022. Patients completed a single period of sensor measurements for 28 days and a diabetes questionnaire about feelings and experiences of health care. HbA1c was also measured. A focus group interview was conducted to evaluate and describe the HCPs experiences of using periodic CGM.

Results

Patients reported to HCPs that the CGM device was comfortable to wear and noted that LibreView was easy to use when scanning the sensor to obtain and visualize the glucose levels and trends. Data availability of CGM data was >70 %.Clinical observations revealed a mean reduction in HbA1c, mmol/mol from 60.06 [7.65 %] at baseline to 55.42 [7.20 %] after 4 weeks (p < 0.001). Two categories were identified: 1) Fostering dialogue on self-care and 2) Promoting understanding.

Conclusions

The HCPs and participants in this study had a positive experience or viewed the implementation of periodic CGM with data visualization tools as a positive experience and appeared to be feasible for implementation in a primary care setting.

Flash Glucose Monitoring in Croatia: The Optimal Number of Scans per Day to Achieve Good Glycemic Control in Type 1 Diabetes

Background and Objectives: The purpose of this study is to determine the optimal number of scans per day required for attaining good glycemic regulation. Materials and Methods: The association of scanning frequency and glucometrics was analyzed according to bins of scanning frequency and bins of time in range (TIR) in the Croatian population of type 1 diabetes (T1DM) patients. Results: Intermittently scanned continuous glucose monitoring (isCGM) Libre users in Croatia performed on average 13 ± 7.4 scans per day. According to bins of scanning frequency, bin 5 with 11.2 ± 02 daily scans was sufficient for achieving meaningful improvements in glycemic regulation, while decreasing severe hypoglycemia required an increasing number of scans up to bin 10 (31 ± 0.9), yet with no effect on TIR improvement. When data were analyzed according to bins of TIR, an average of 16.3 ± 10.5 scans daily was associated with a TIR of 94.09 ± 3.49% and a coefficient of variation (CV) of 22.97 ± 4.94%. Improvement was shown between each successive bin of TIR but, of notice, the number of scans performed per day was 16.3 ± 10.5 according to TIR-based analysis and 31.9 ± 13.5 in bin 10 according to scan frequency analysis. Conclusions: In conclusion, an optimal average number of scans per day is 16.3 in order to achieve glucose stability and to minimize the burden associated with over-scanning.

To evaluate the use and clinical effect of intermittently scanned continuous glucose monitoring in adults with type 1 diabetes: Results of a multicentre study

AIM

To evaluate the use and clinical effect of intermittently scanned continuous glucose monitoring (isCGM) in adults with type 1 diabetes (T1D) in a public health service scenario.

METHOD

Cross-sectional retrospective analysis of all patients with T1D and medical indication for isCGM use from a cohort followed since 2010 at Castilla-La Mancha Public Health Service (Spain). Primary outcome was HbA1c change during the first year of follow-up after isCGM initiation. Secondary outcomes included evaluation of self-monitoring of blood glucose (SMBG), isCGM and insulin use, along with glycometric indexes.

RESULTS

A total of 945 T1D patients were analyzed. Median age was 49.5 years (IQ range 19.0 years) and T1D duration of 28.9 years (IQ range 14.0 years). The most frequent insulin therapy alternatives were multiple daily injections (85%) followed by insulin pump (11%). Eighty percent of the patients were active isCGM users with a 90% of adherence to the device. Patients showed a mean daily scan frequency of 10.1±6.4scans/day. Daily SMBG reduced by -3.5 test/day [95% CI -3.7, -3.2; P<0.001]. We detected an HbA1c reduction of -0.3% (-4mmol/mol) [95% CI -0.2, -0.4 (-3, -5); P<0.001] at the end of the follow-up. An inverse correlation between HbA1c levels at the end of the follow-up and daily frequency of isCGM scanning (R=-0.34, P<0.001) was observed. Dropout rate was 4%, and 4% of patients were not willing to use isCGM.

CONCLUSIONS

Adult patients with T1D improved glycaemic control after isCGM initiation in a public health service scenario. Despite described clinical benefits, a higher than expected percentage of patients were not using isCGM technology. NCT05095610.

Effectiveness of a flash glucose monitoring systems implementation program through a group and telematic educational intervention in adults with type 1 diabetes

OBJECTIVES

Verifying the clinical effectiveness and the impact on quality-of-life parameters, fear of hypoglycaemia and satisfaction with the treatment obtained with a flash glucose monitoring (MFG) devices implantation program that includes a telematic and group educational intervention in adults with type 1 diabetes.

PATIENTS AND METHODS

Prospective quasi-experimental study, carried out during the COVID-19 pandemic period with a 9-month follow-up at the Virgen Macarena University Hospital, Sevilla.

RESULTS

Eighty-eight participants were included (men: 46.6%; mean age (years) 38.08, SD: 9.38); years of DM1 evolution: 18.4 (SD: 10.49); treatment with multiple doses insulin (MDI) 70.5% vs 29.5% subcutaneous insulin infusion therapy (CSII)). Baseline HbA1c was 7.74% (1.08). After the intervention, the global decrease in HbA1c was -0.45% (95% CI [-0.6, -0.25], P < 0.01), increasing to -1.08% in the group that started with HbA1c ≥ 8% (P < 0.01). A mean decrease in the Fear of Hypoglycemia 15 (FH15) test score of -6.5 points was observed (P < 0.01). In the global score of the Spanish version of Diabetes Quality Of Life (DQOL-s) test, the decrease was -8.44 points (P < 0.01). In Diabetes Treatment Satisfaction Questionnaire test (DTQ-s), global score increased in + 4 points (P < 0.01).

CONCLUSIONS

The incorporation of an educational program in group and telematic format within the development of MFG devices implantation strategies is an effective option, with associated benefits in quality of life and fear of hypoglycemia in adult patients with DM1. This option can be implemented in usual clinical practice.

Effects of flash glucose monitoring on glycemic control in participants with diabetes mellitus: A meta-analysis of randomized controlled trials

BACKGROUND

With the introduction of flash glucose monitoring (FGM) into the international market in 2014, academics worldwide are exploring whether this device improves glycemic control in participants with diabetes mellitus.

OBJECTIVE

A study was conducted in which participants were evaluated to determine the effect of FGM on glycemic control.

METHODS

From inception to April 9, 2022, we searched the Cochrane Library, PubMed, SinoMed, Embase, Web of Science, MEDLINE, CNKI, Wan Fang Data, and VIP databases to collect randomized controlled trials (RCTs) related to the effect of FGM on glycemic control in participants with diabetes mellitus. Outcomes included glycated hemoglobin, the occurrence of hypoglycemic events, fasting plasma glucose (FPG), and 2-h postprandial glucose (2hPG) levels. The statistical analysis was performed using R 4.1.3 software.

RESULTS

We included 19 studies involving 2013 participants, all of which were RCTs. Meta-analysis results revealed that compared to self-monitoring of blood glucose (SMBG), FGM significantly reduced glycated hemoglobin levels in participants with type 2 diabetes mellitus [mean difference = -0.74 [95 % CI-1.16, -0.32], P < 0.01] and type 1 diabetes mellitus combined with type 2 diabetes mellitus [mean difference = -1.14 [95 % CI-3.14, 0.87], P < 0.01], with a greater effect in participants aged ≤65 years with type 2 diabetes mellitus (mean difference = -1.38 [95 % CI-2.05, -0.72], P < 0.01). However, there was no effect of FGM on the improvement of glycated hemoglobin levels in patients with type 1 diabetes mellitus [P = 0.45]. Furthermore, fasting plasma glucose levels and 2-h postprandial glucose levels were significantly lower in FGM than SMBG, and the number of hypoglycemic events was also significantly lower.

CONCLUSION

Comparing SMBG with FGM indicated that FGM improves fasting plasma glucose levels, 2-h postprandial glucose levels, and glycated hemoglobin levels, and it reduces the number of hypoglycemic events.

Longitudinal study of the flash glucose monitoring system in type 1 diabetics: An mHealth ally in times of COVID-19

AIMS AND OBJECTIVES

The aim of this study was to assess the effect of the FreeStyle Libre device implantation in adult type 1 diabetics in a Health Area of Castilla La Mancha (Spain) during the COVID-19 pandemic.

BACKGROUND

FreeStyle Libre is a so-called mHealth device that supports health care. During COVID-1 confinement, diabetic patients could have improved their glycaemic monitoring thanks to these devices, although health care in these patients may have been limited due to confinement.

METHODS

A 12-month longitudinal study in which a total of 206 type I diabetics participated, belonging to a single health area. Sociodemographic and analytical data and the Self Care Inventory Revised questionnaire (SCI-R) were collected. STROBE checklist was followed.

RESULTS

The analysis showed differences related to the use of the sensor. After the study period, patients obtained better levels of basal glucose, glycosylated haemoglobin, creatinine, cholesterol, triglycerides and LDL. In addition, a significant increase in the total score of the SCI-R questionnaire was observed after the use of the monitor (MD -7.77; 95% CI -10.43, -8.29). The same occurred with different SCI-R items such as diet (MD -2.995; 95% CI -3.24, -2.57), glucose determination (MD -3.21; 95% CI -3.52, -2.91), medication administration (MD -2.58; 95% CI -2.53, -1.96) and hypoglycaemic episodes (MD -1.07; 95% CI -1.21, -0.93). In the analysis by groups, worse values of glycosylated haemoglobin and adherence to treatment (p < .05) were observed in overweight/obese subjects versus those with normal weight after one year of study.

CONCLUSION

The use of flash monitoring is related to better adherence to most of the recommended habits in diabetes. Nevertheless, there seems to be no relationship with an improvement in physical exercise and preventive aspects of diabetes. A good nursing intervention to support physical exercise and the use of mHealth devices could improve the control of diabetic patients.

RELEVANCE TO CLINICAL PRACTICE

The use of this mHealth device has shown positive results and reduced complications. Despite less contact with healthcare facilities due to the pandemic, type 1 diabetic patients have improved their blood results and adherence after using the device for one year. Nursing staff should focus on promoting physical activity and routine disease care in type 1 diabetics.

Use of continuous glucose monitoring trend arrows in the younger population with type 1 diabetes

Early control of glycaemia is key to reduce vascular complications in individuals with Type 1 diabetes. Therefore, encouraging children and adolescents with T1DM to take responsibility for controlling glucose levels is an important yet a challenging task. The rapid expansion of continuous glucose monitoring (CGM) systems has allowed for more comprehensive analysis of glycaemia in T1D. Moreover, CGM devices have the ability to calculate rate of change in glucose levels and display the information as trend arrows. In turn, this can help to take evasive actions to return glucose levels to near physiological glycaemia, which can be highly motivating for young people with T1DM. In the absence of standardised, evidence-based guidance, this consensus document, generated by experts from the Arab Society of Paediatric Endocrinology and Diabetes and international advisors, summarises recent literature on the use of trend arrows in young people with T1DM. The use of trend arrows in different CGM systems is reviewed and their clinical significance is highlighted. Adjusting insulin doses according to trend arrows is discussed while also addressing special situations, such as exercise, fasting, nocturnal hypoglycaemia and menstruation. Adequate understanding of trend arrows should facilitate optimisation of glycaemic control in the T1D population.

Flash glucose monitoring system: impact on glycemic control and body mass index in type 1 diabetes mellitus

OBJECTIVE

Flash glucose monitoring (FGM) is increasingly used in type 1 diabetes mellitus (T1D) management. This study aimed to assess glycated hemoglobin (HbA1c) and body mass index (BMI) in the first year of FGM use in patients with T1D and to identify predictive factors of benefit associated with its use.

METHODS

Retrospective study of T1D patients, using FGM for ≥ 6 months and under intensive insulin therapy with multiple daily injections.

RESULTS

In 179 patients with a median (Md) age of 43.0 years (P25 31.0; P75 52.0) and disease duration of 18.0 years (P25 10.0; P75 28.0), initial HbA1c was 7.9% (P25 7.2; P75 8.8) and initial BMI was 24.0 kg/m2 (P25 21.9; P75 26.2). With FGM, HbA1c improved significantly to 7.6% (P25 7.0; P75 8.3) at 6 months and 7.7% (P25 6.95; P75 8.5) at 12 months (p < 0.05), with more patients with HbA1c < 7% (16.1% vs 22.5%) and fewer patients with HbA1c ≥ 8% (49.1% vs 35.8%) (p < 0.05). Initial HbA1c 8.0-8.9% (HR 1.886; 95% CI 1.321-2.450) and ≥ 9.0% (HR 3.108, 95% CI 2.454-3.761) predicted greater HbA1c reduction. BMI increased significantly, especially between 6 and 12 months (BMI Md 23.8 [P25 21.9; P75 26.2] kg/m2 and 24.0 [P25 22.0; P75 26.2] kg/m2, respectively) (p < 0.05). Overweight (HR 4.319, 95% CI 3.185-5.453) and obesity (HR 8.112, 95% CI 3.919-12.306) predicted greater weight gain.

CONCLUSION

FGM use was associated with significant improvement in HbA1c, mainly in patients with worse previous glycemic control. It was also associated with increased BMI, especially if baseline BMI ≥ 25 kg/m2, so weight control strategies should be emphasized.

Use of ambulatory glucose monitoring and analysis of ambulatory glucose profile in clinical practice for diabetes management; a position statement of the Arab Society of Paediatric Endocrinology and diabetes

BACKGROUND AND AIM

Diabetes mellitus imposes a significant burden around the world generally and in the Middle East and North Africa specifically. Glucose monitoring is a cornerstone of diabetes management.

METHODS

Glycated haemoglobin has always been the main metric for assessing glycaemic control, but its use is linked with multiple pitfalls. As an alternative, continuous glucose monitoring is becoming a standard of care in many countries. Intermittent scanning glucose monitoring (isCGM) has acquired a worldwide popularity and has been proven to improve glycaemic control, hypoglycaemia detection and prevention, and quality of life.

RESULTS

The most recent International Society of Paediatric and Adolescent Diabetes practice. guidelines recommended its use in young people with diabetes observing Ramadan to ensure safe fasting. At a meeting in Abu Dhabi in November 2019, the Arab Society for Paediatric. Endocrinology and Diabetes brought together a number of regional diabetes experts, patient. representatives and international expert advisors to review the evidence for isCGM and propose. guidelines for its use in the Middle East and North Africa region.

CONCLUSION

In this paper, the authors strongly recommend the use of isCGM for patients in MENA and present general recommendations and compressive specific guidance for physicians and patients, which they believe will also have wider resonance.

Susceptibility for Some Infectious Diseases in Patients With Diabetes: The Key Role of Glycemia

Uncontrolled diabetes results in several metabolic alterations including hyperglycemia. Indeed, several preclinical and clinical studies have suggested that this condition may induce susceptibility and the development of more aggressive infectious diseases, especially those caused by some bacteria (including Chlamydophila pneumoniae, Haemophilus influenzae, and Streptococcus pneumoniae, among others) and viruses [such as coronavirus 2 (CoV2), Influenza A virus, Hepatitis B, etc.]. Although the precise mechanisms that link glycemia to the exacerbated infections remain elusive, hyperglycemia is known to induce a wide array of changes in the immune system activity, including alterations in: (i) the microenvironment of immune cells (e.g., pH, blood viscosity and other biochemical parameters); (ii) the supply of energy to infectious bacteria; (iii) the inflammatory response; and (iv) oxidative stress as a result of bacterial proliferative metabolism. Consistent with this evidence, some bacterial infections are typical (and/or have a worse prognosis) in patients with hypercaloric diets and a stressful lifestyle (conditions that promote hyperglycemic episodes). On this basis, the present review is particularly focused on: (i) the role of diabetes in the development of some bacterial and viral infections by analyzing preclinical and clinical findings; (ii) discussing the possible mechanisms by which hyperglycemia may increase the susceptibility for developing infections; and (iii) further understanding the impact of hyperglycemia on the immune system.

Comprehensive elaboration of glycemic variability in diabetic macrovascular and microvascular complications

Diabetes mellitus is the major risk factor for the development of macrovascular and microvascular complications. It is increasingly recognized that glycemic variability (GV), referring to oscillations in blood glucose levels and representing either short-term or long-term GV, is involved in the pathogenesis of diabetic complications and has emerged as a possible independent risk factor for them. In this review, we summarize the metrics and measurement of GV in clinical practice, as well as comprehensively elaborate the role and related mechanisms of GV in diabetic macrovascular and microvascular complications, aiming to provide the mechanism-based therapeutic strategies for clinicians to manage diabetes mellitus.

Resistance to data loss from the Freestyle Libre: impact on glucose variability indices and recommendations for data analysis

Like many wearables, flash glucose monitoring relies on user compliance and is subject to missing data. As recent research is beginning to utilise glucose technologies as behaviour change tools, it is important to understand whether missing data are tolerable. Complete Freestyle Libre data files were amputed to remove 1-6 h of data both at random and over mealtimes (breakfast, lunch, and dinner). Absolute percent errors (MAPE) and intraclass correlation coefficients (ICC) were calculated to evaluate agreement and reliability. Thirty-two (91%) participants provided at least 1 complete day (24 h) of data (age: 44.8 ± 8.6 years, female: 18 (56%); mean fasting glucose: 5.0 ± 0.6 mmol/L). Mean and continuous overall net glycaemic action (CONGA) (60 min) were robust to data loss (MAPE ≤3%). Larger errors were calculated for standard deviation, coefficient of variation (CV) and mean amplitude of glycaemic excursions (MAGE) at increasing missingness (MAPE: 2%-10%, 2%-9%, and 4%-18%, respectively). ICC decreased as missing data increased, with most indicating excellent reliability (>0.9) apart from certain MAGE ICCs, which indicated good reliability (0.84-0.9). Researchers and clinicians should be aware of the potential for larger errors when reporting standard deviation, CV, and MAGE at higher rates of data loss in nondiabetic populations. But where mean and CONGA are of interest, data loss is less of a concern. Novelty: As research now utilises flash glucose monitoring as behavioural change tools in nondiabetic populations, it is important to consider the influence of missing data. Glycaemic variability indices of mean and CONGA are robust to data loss, but standard deviation, CV, and MAGE are influenced at higher rates of missingness.

Glycemic variability: adverse clinical outcomes and how to improve it?

Glycemic variability (GV), defined as an integral component of glucose homoeostasis, is emerging as an important metric to consider when assessing glycemic control in clinical practice. Although it remains yet no consensus, accumulating evidence has suggested that GV, representing either short-term (with-day and between-day variability) or long-term GV, was associated with an increased risk of diabetic macrovascular and microvascular complications, hypoglycemia, mortality rates and other adverse clinical outcomes. In this review, we summarize the adverse clinical outcomes of GV and discuss the beneficial measures, including continuous glucose monitoring, drugs, dietary interventions and exercise training, to improve it, aiming at better addressing the challenging aspect of blood glucose management.

Flash glucose monitoring reduces glycemic variability and hypoglycemia: real-world data from Spain

OBJECTIVE

Observations in real-world settings support and extend findings demonstrated in randomized controlled trials that show flash glucose monitoring improves glycemic control. In this study, Spain-specific relationships between testing frequency and glycemic parameters were investigated under real-world settings.

RESEARCH DESIGN AND METHODS

Deidentified glucose and user scanning data were analyzed and readers were rank ordered into 20 equal sized groups by daily scan frequency. Glucose parameters were calculated for each group: estimated HbA1c, time below range (<70 and ≤54 mg/dL), within range (70-180 mg/dL), and above range (>180 mg/dL). Glycemic variability (GV) metrics were described and data obtained from sensors in Spain and worldwide were compared.

RESULTS

Spanish users (n=22 949) collected 37.1 million glucose scans, 250 million automatically recorded glucose readings, and checked glucose values via a mean of 13 scans/day. Estimated HbA1c, time below 70 mg/dL, at or below 54 mg/dL, above 180 mg/dL, and GV metrics were significantly lower in the highest compared with lowest scan rate group (39.6 to 3.9 scans/day). Time-in-range was higher for the highest versus lowest scan rate group at 15.6 vs 11.5 hours/day, respectively. GV metrics correlated positively with time below 70 mg/dL, at or below 54 mg/dL, above 180 mg/dL, and negatively with time-in-range. The relationship between glucose metrics and scan rate was similar in Spain and worldwide. However, time in hypoglycemia in Spain was higher in the groups with lower scan rates.

CONCLUSIONS

As seen in clinical trials, flash glucose monitoring in real-world settings allows frequent glucose checks. High scan rates are associated with the favorable glycemic markers of increased time-in-range and reduced time in hyperglycemia and hypoglycemia, and GV. The same trends, with unique nuances, are observed in both Spanish and global data.