Time in range centered diabetes care

Impact of Continuous Glucose Monitoring and its Glucometrics in Clinical Practice in Spain and Future Perspectives: A Narrative Review

INTRODUCTION

Continuous glucose monitoring (CGM) devices allow for 24-h real-time measurement of interstitial glucose levels and have changed the interaction between people with diabetes and their health care providers. The large amount of data generated by CGM can be analyzed and evaluated using a set of standardized parameters, collectively named glucometrics. This review aims to provide a summary of the existing evidence on the use of glucometrics data and its impact on clinical practice based on published studies involving adults and children with type 1 diabetes (T1D) in Spain.

METHODS

The PubMed and MEDES (Spanish Medical literature) databases were searched covering the years 2018-2022 and including clinical and observational studies, consensus guidelines, and meta-analyses on CGM and glucometrics conducted in Spain.

RESULTS

A total of 16 observational studies were found on the use of CGM in Spain, which have shown that cases of severe hypoglycemia in children with T1D were greatly reduced after the introduction of CGM, resulting in a significant reduction in costs. Real-world data from Spain shows that CGM is associated with improved glycemic markers (increased time in range, reduced time below and above range, and glycemic variability), and that there is a relationship between glycemic variability and hypoglycemia. Also, CGM and analysis of glucometrics proved highly useful during the COVID-19 pandemic. New glucometrics, such as the glycemic risk index, or new mathematical approaches to the analysis of CGM-derived glucose data, such as "glucodensities," could help patients to achieve better glycemic control in the future.

CONCLUSION

By using glucometrics in clinical practice, clinicians can better assess glycemic control and a patient's individual response to treatment.

'We're taught green is good': Perspectives on time in range and time in tight range from youth with type 1 diabetes, and parents of youth with type 1 diabetes

AIMS

Continuous glucose monitoring (CGM) systems are standard of care for youth with type 1 diabetes with the goal of spending >70% time in range (TIR; 70-180 mg/dL, 3.9-10 mmol/L). We aimed to understand paediatric CGM user experiences with TIR metrics considering recent discussion of shifting to time in tight range (TITR; >50% time between 70 and 140 mg/dL, 3.9 and 7.8 mmol/L).

METHODS

Semi-structured interviews and focus groups with adolescents with type 1 diabetes and parents of youth with type 1 diabetes focused on experiences with TIR goals and reactions to TITR. Groups and interviews were audio-recorded, transcribed and analysed using content analysis.

RESULTS

Thirty participants (N = 19 parents: age 43.6 ± 5.3 years, 79% female, 47% non-Hispanic White, 20 ± 5 months since child's diagnosis; N = 11 adolescents: age 15.3 ± 2 years, 55% female, 55% non-Hispanic White, 16 ± 3 months since diagnosis) attended. Participants had varying levels of understanding of TIR. Some developed personally preferred glucose ranges. Parents often aimed to surpass 70% TIR. Many described feelings of stress and disappointment when they did not meet a TIR goal. Concerns about TITR included increased stress and burden; risk of hypoglycaemia; and family conflict. Some participants said TITR would not change their daily lives; others said it would improve their diabetes management. Families requested care team support and a clear scientific rationale for TITR.

CONCLUSIONS

The wealth of CGM data creates frequent opportunities for assessing diabetes management and carries implications for management burden. Input from people with type 1 diabetes and their families will be critical in considering a shift in glycaemic goals and targets.

Assessing the feasibility of time in tight range (TITR) targets with advanced hybrid closed loop (AHCL) use in children and adolescents: A single-centre real-world study

AIMS

Time in Tight Range (TITR) is a novel glycaemic metric in monitoring type 1 diabetes (T1D) management. The aim of this study was to assess the attainability of the TITR target in children and adolescents using the advanced hybrid closed loop (AHCL).

METHODS

The 2128-day CGM data from 56 children and adolescents with T1D using AHCL (Minimed-780G) were analysed. Time in Range (TIR) (3.9-10 mmol/L), TITR (3.9-7.7 mmol/L), and other glycaemic parameters were separately analysed in terms of whole day, daytime (06.00-23:59), and nighttime (00.00-05.59) results. The participants were divided into two groups by autocorrection rate where Group 1 had a rate of <30% and Group 2 had a rate of ≥30.

RESULTS

All glycaemic parameters indicated a better glycaemic outcome in the nighttime with higher TIR and TITR values compared with daytime (for TIR 87.5 ± 9.5% vs. 78.8 ± 8%, p < 0.001, and TITR 68.2 ± 13.5% vs. 57.5 ± 8.8%, p < 0.001). The rates of TITR >50% and >60% were 87% and 52%, respectively. When those with TITR >60% (n: 29) and those without (n: 27) were evaluated in terms of hypoglycaemia, no statistically significant difference was found in time below range (TBR) 3-3.9 mmol/L (0.3% vs. 2.1%, p: 0.084) and TBR < 3 mmol/L (0.47% vs. 0.3%, p: 0.298). Group 1 had a significantly higher TIR and TITR compared to Group 2 (82.6 ± 6.1% vs. 75.6 ± 8.6%, p: 0.008 and 62.1 ± 7.5% vs. 53.8 ± 7.5%, p: 0.002, respectively).

CONCLUSIONS

Most children and adolescents on AHCL achieved the 50% target for TITR whereas more than half achieved the >60% target. A target of >50% for TITR seems realistic in children with T1D using AHCL.

A comparison of the usage of an open-source automated insulin delivery system and the MiniMed™ 780 G system in children and adolescents with type 1 diabetes in real-world settings: the AWeSoMe study group

PURPOSE

In recent years there has been a noticeable increase in the use of advanced hybrid closed-loop systems (AHCLs) for managing type 1 diabetes (T1D) among youth. However, there is a lack of comparison between the open-source automated insulin delivery (AID) system and the MiniMed™ 780 G system (780 G).

METHODS

In this multi-center study, we retrospectively compared selected glycemic ranges of 26 individuals who used open-source AID and 20 individuals who used 780 G (age 11.3 years [IQR 9.3, 12.9] and 13.4 years [IQR 10.9, 16.5], respectively, p = 0.069) from system initiation to the most recent visit.

RESULTS

At baseline, the median HbA1c was significantly lower and the time below range (TBR)<54mg/dL was significantly higher in the open-source AID group compared to the 780 G group (6.8% [IQR 6.4, 7.1] vs. 7.4% [IQR 6.9, 8.6], p = 0.006 and (1.0% [IQR 0.5, 2.8] vs. 0.0% [0.0, 1.0], p = 0.014), respectively; the median time in range (TIR70-180mg/dL) was similar (p = 0.068). After a median duration of 10.9 months on AHCLs the reduction of HbA1c was similar ( ~ 0.3%). The time spent in the hypoglycemic ranges was longer among users of the open-source AID compared to 780 G (TBR54-70mg/dL 4.2% [IQR 2.6, 7.3] vs. 2.0% [1.0, 4.0], p = 0.005) and TBR<54mg/dL 1.1% [IQR 0.4, 2.3] vs. 0.0 [0.0, 1.0], p = 0.001).

CONCLUSIONS

Both AHCLs similarly improved HbA1c and TIR70-180mg/dL. The open-source AID youth had better glycemic control but spent longer time in the hypoglycemic range. These findings must be considered when choosing the use of AHCL technologies.

Q-Score Complements the Time in Range in the Evaluation of Short-Term Glycemic Control

BACKGROUND AND AIMS

The Q-Score is a single-number composite metric that is constructed based on the following components: central glycemic tendency, hyperglycemia, hypoglycemia, and intra- and interday variability. Herein, we refined the Q-Score for the screening and analysis of short-term glycemic control using continuous glucose monitoring (CGM) profiles.

METHODS

Continuous glucose monitoring profiles were obtained from noninterventional, retrospective cross-sectional studies. The upper limit of the Q-Score component hyperglycemia' that is, the time above target range (TAR), was adjusted from 8.9 to 10 mmol/L (n = 1562 three-day-sensor profiles). A total of 302 people with diabetes mellitus treated with intermittent CGM for ≥14 days were enrolled. The time to stability was determined via correlation-based analysis.

RESULTS

There was a strong correlation between the Q-Scores of the two TARs, that is, 8.9 and 10 mmol/L (Q-ScoreTAR10 = -0.03 + 1.00 Q-ScoreTAR8.9, r = .997, p < .001). The times to stability of the Q-Score and TIR were 10 and 12 days, respectively. The Q-Score was correlated with fructosamine concentrations, the glucose management indicator (GMI), the time in range (TIR), and the glycemic risk index (GRI) (r = .698, .887, -.874, and .941), respectively. The number of Q-Score components above the target increased as the TIR decreased, from two (1.7 ± 0.9) in CGM profiles with a TIR between 70% and 80% to four (3.9 ± 0.5) in the majority of the CGM profiles with a TIR below 50%. A conversion matrix between the Q-Score and glycemic indices was developed.

CONCLUSIONS

The Q-Score is a tool for assessing short-term glycemic control. The Q-Score can be translated into clinician opinion using the GRI.

Association of scan frequency with CGM-derived metrics and influential factors in adults with type 1 diabetes mellitus

Introduction

This study aimed to investigate the association between scan frequency and intermittently scanned continuous glucose monitoring (isCGM) metrics and to clarify the factors affecting scan frequency in adults with type 1 diabetes mellitus (T1D).

Methods

We enrolled adults with T1D who used FreeStyle® Libre. Scan and self-monitoring of blood glucose (SMBG) frequency and CGM metrics from the past 90-day glucose data were collected. The receiver operating characteristic curve was plotted to obtain the optimal cutoff values of scan frequency for the target values of time in range (TIR), time above range (TAR), and time below range (TBR).

Results

The study was conducted on 211 adults with T1D (mean age, 50.9 ± 15.2 years; male, 40.8%; diabetes duration, 16.4 ± 11.9 years; duration of CGM use, 2.1 ± 1.0 years; and mean HbA1c, 7.6 ± 0.9%). The average scan frequency was 10.5 ± 3.3 scan/day. Scan frequency was positively correlated with TIR and negatively correlated with TAR, although it was not significantly correlated with TBR. Scan frequency was positively correlated with the hypoglycemia fear survey-behavior score, while it was negatively correlated with some glycemic variability metrics. Adult patients with T1D and good exercise habits had a higher scan frequency than those without exercise habits. The AUC for > 70% of the TIR was 0.653, with an optimal cutoff of 11 scan/day.

Conclusions

In real-world conditions, frequent scans were linked to improved CGM metrics, including increased TIR, reduced TAR, and some glycemic variability metrics. Exercise habits and hypoglycemia fear-related behavior might affect scan frequency. Our findings could help healthcare professionals use isCGM to support adults with T1D.Clinical Trial Registry No. UMIN000039376.

Insulin Therapy for the Management of Diabetes Mellitus: A Narrative Review of Innovative Treatment Strategies

The discovery of insulin was presented to the international medical community on May 3, 1922. Since then, insulin has become one of the most effective pharmacological agents used to treat type 1 and type 2 diabetes mellitus. However, the initiation and intensification of insulin therapy is often delayed in people living with type 2 diabetes due to numerous challenges associated with daily subcutaneous administration. Reducing the frequency of injections, using insulin pens instead of syringes and vials, simplifying treatment regimens, or administering insulin through alternative routes may help improve adherence to and persistence with insulin therapy among people living with diabetes. As the world commemorates the centennial of the commercialization of insulin, the aims of this article are to provide an overview of insulin therapy and to summarize clinically significant findings from phase 3 clinical trials evaluating less frequent dosing of insulin and the non-injectable administration of insulin.

MiniMed 780G™ advanced hybrid closed-loop system performance in Egyptian patients with type 1 diabetes across different age groups: evidence from real-world users

BACKGROUND

Advanced hybrid closed loop (AHCL) system provides both automated basal rate and correction boluses to keep glycemic values in a target range.

OBJECTIVES

To evaluate the real-world performance of the MiniMed™ 780G system among different age groups of Egyptian patients with type 1diabetes.

METHODS

One-hundred seven AHCL system users aged from 3 to 71 years were enrolled. Data uploaded by patients were aggregated and analyzed. The mean glucose management indicator (GMI), percentage of time spent within glycemic ranges (TIR), time below range (TBR) and time above range (TAR) were determined.

RESULTS

Six months after initiating Auto Mode, patients spent a mean of 85.31 ± 22.04% of the time in Auto Mode (SmartGuard) and achieved a mean GMI of 6.95 ± 0.58% compared with 7.9 ± 2.1% before AHCL initiation (p < 0.001). TIR 70-180 mg/dL was increased post-AHCL initiation from 63.48 ± 10.14% to 81.54 ± 8.43% (p < 0.001) while TAR 180-250 mg/dL, TAR > 250 mg/dL, TBR < 70 mg/dL and TBR < 54 mg/dL were significantly decreased (p < 0.001). After initiating AHCL, TIR was greater in children and adults compared with adolescents (82.29 ± 7.22% and 83.86 ± 9.24% versus 78.4 ± 7.34%, respectively; p < 0.05). The total daily dose of insulin was increased in all age groups primarily due to increased system-initiated insulin delivery including auto correction boluses and basal insulin.

CONCLUSIONS

MiniMed™ 780G system users across different age groups achieved international consensus-recommended glycemic control with no serious adverse effects even in challenging age group as children and adolescents.

Post-Exercise Protein Intake May Reduce Time in Hypoglycemia Following Moderate-Intensity Continuous Exercise among Adults with Type 1 Diabetes

Little is known about the role of post-exercise protein intake on post-exercise glycemia. Secondary analyses were conducted to evaluate the role of post-exercise protein intake on post-exercise glycemia using data from an exercise pilot study. Adults with T1D (n = 11), with an average age of 33.0 ± 11.4 years and BMI of 25.1 ± 3.4, participated in isoenergetic sessions of high-intensity interval training (HIIT) or moderate-intensity continuous training (MICT). Participants completed food records on the days of exercise and provided continuous glucose monitoring data throughout the study, from which time in range (TIR, 70-180 mg/dL), time above range (TAR, >180 mg/dL), and time below range (TBR, <70 mg/dL) were calculated from exercise cessation until the following morning. Mixed effects regression models, adjusted for carbohydrate intake, diabetes duration, and lean mass, assessed the relationship between post-exercise protein intake on TIR, TAR, and TBR following exercise. No association was observed between protein intake and TIR, TAR, or TBR (p-values ≥ 0.07); however, a borderline significant reduction of -1.9% (95% CI: -3.9%, 0.0%; p = 0.05) TBR per 20 g protein was observed following MICT in analyses stratified by exercise mode. Increasing post-exercise protein intake may be a promising strategy to mitigate the risk of hypoglycemia following MICT.

The Advanced Hybrid Closed Loop Improves Glycemia Risk Index, Continuous Glucose Monitoring Index, and Time in Range in Children with Type 1 Diabetes: Real-World Data from a Single Center Study

Introduction: The Glycemia Risk Index (GRI) and Continuous Glucose Monitoring Index (COGI) are newly defined composite metric parameters derived from continuous glucose monitoring (CGM) data. GRI is divided into five separate risk zones (from lowest to highest: A-E). In this study, the effect of the advanced hybrid closed loop (AHCL) system on GRI and COGI in children with type 1 diabetes was evaluated. Materials and Methods: Forty-five children who had started using the AHCL and whose baseline and sixth-month CGM data were available were analyzed in terms of achievement of CGM consensus goals and changes in GRI scores and zones. The paired t-test was used for the analyses. Results: The mean age and duration of diabetes of the participants were 10.95 ± 3.41 and 3.85 ± 2.67 years, respectively. The mean GRI score significantly decreased from 35.66 ± 17.46 at baseline to 22.83 ± 9.08 at 6 months (P < 0.001). Although the proportion of those in the A zone was 20% at baseline, it increased to 42% at 6 months. AHCL also improved COGI from 72.59 ± 12.44 to 82.90 ± 7.72 (P < 0.001). Time in range (TIR) increased significantly from 70.54% to 80.51% (P < 0.001) at 6 months. Conclusion: AHCL provides not only an improvement in TIR but also a significant improvement in both GRI and COGI at 6 months. The incorporation of GRI and COGI alongside TIR may enhance the assessment of the glycemic profile by providing a more comprehensive and in-depth analysis.

Real-World User and Clinician Perspective and Experience with MiniMed™ 780G Advanced Hybrid Closed Loop System

INTRODUCTION

The advanced hybrid closed loop (AHCL) MiniMed™ 780G system changes basal insulin delivery every 5 min and auto bolus in response to sensor glucose values. We assessed the performance of the AHCL system in real-world settings for individuals with type 1 diabetes (T1DM) as well as user and clinician perspectives and satisfaction.

METHODS

We held two peer group discussions: one having adults with T1DM/parents of children and adolescents with T1DM to understand their experiences with the AHCL system and another with healthcare providers (HCPs). Responses from the discussions were analyzed and categorized into themes by two independent researchers, with any inconsistencies resolved by consensus. We also analyzed data from the system uploaded to CareLink personal software. Glycemic outcomes, including time in range (TIR), time below range (TBR), time above range (TAR), mean sensor glucose (SG) levels, glucose management indicator (GMI), sensor use, and percentage of time spent in AHCL, were determined.

RESULTS

The peer group discussions revealed numerous key themes and issues for each group, such as the significance of setting reasonable expectations, carbohydrate counting and bolus dosing, technical difficulties, and overall user experience. The users (n = 25; T1DM; 17 female; age 13.8 ± 7.49 years; A1C 6.54 ± 0.45%; duration of diabetes 6 ± 6.78 years) were very satisfied with the system. Most users experienced consistent blood glucose values with very few hypoglycemic episodes. However, there were a few limitations reported, such as hyperglycemic episodes caused by inaccuracies in carb counting, issues with sensor connectivity, and cannula blockages or kinking for those using insulin Fiasp. Users achieved a mean GMI of 6.4 ± 0.26%, TIR of 83.0 ± 8.12%, TBR (54-70 mg/dL) of 2.0 ± 0.81%, TBR* (< 54 mg/dL) of 0%. All of the users achieved a TIR of > 70%.

CONCLUSION

The use of the AHCL system in T1DM resulted in robust glycemic control, minimizing hypoglycemia. Providing training to both users and HCPs can help them use the system effectively.

Effects of steroid stewardship on glycemic control in acute exacerbations of chronic obstructive pulmonary disease patients

INTRODUCTION

The adverse effects of corticosteroids are dose-dependent, and guidance is to use the lowest effective dose in most disease states. The study facility recently reported a steroid stewardship program that reduced steroid dosing in acute exacerbations of chronic obstructive pulmonary disease (AECOPD) patients by 50%. The purpose of this post-hoc analysis was to evaluate the effect of this intervention on glycemic control in hospitalized AECOPD before and after cohorts.

METHODS

This was a retrospective post-hoc review of hospitalized patients in a before and after study design (n = 27 in each group). The primary endpoint was the proportion of glucose readings >180 mg/dL. Baseline characteristics, mean glucose levels, and corrective insulin were also collected. Continuous variables were compared with a Student's t-test (or Mann-Whitney U where appropriate) and nominal variables with a chi-square test in R Studio.

RESULTS

There was a significantly higher proportion of glucose >180 mg/dL readings in the pre-intervention cohort: 38% vs. 25% (p = 0.007). The mean glucose levels were numerically lower post-intervention but did not reach statistical significance (160 mg/dL vs. 145 mg/dL, p = 0.27) both in diabetics (192 mg/dL vs. 181 mg/dl, p = 0.69) and non-diabetics (142 mg/dL vs. 125 mg/dL, p = 0.08). The use of correctional insulin was similar: a median of 25 units vs. 24.5 units (p = 0.92).

CONCLUSION

A stewardship program focused on steroid reduction in AECOPD significantly lowered the proportion of hyperglycemic readings but did not significantly affect mean glucose and corrective insulin usage while hospitalized.

Metformin Sustained-Release and Vildagliptin Fixed-Dose Combination for Optimizing Glycemic Control: A Review with Real-World Case Reports

(1) Background: There is a high burden of poor glycemic control in the Indian population with type 2 diabetes mellitus (T2DM). Currently, the use of metformin sustained-release (SR)–vildagliptin fixed-dose combination (FDC) is very low as compared to metformin immediate-release (IR)–vildagliptin FDC which is associated with higher adverse events (AEs). Here, we present real-world effectiveness of metformin SR–vildagliptin FDC treatment in patients with T2DM; (2) Methods: This retrospective analysis was carried out from the medical records of adult T2DM patients visiting a single study center in India (December 2020–February 2021). A total of 10 patients (aged ≥20 years) were treated with vildagliptin 50 mg and metformin SR 500 mg FDC for 15 days. The treatment response was assessed by the percentage of time spent in the target glucose range (TIR at baseline and 15 days after treatment); (3) Results: The glycated hemoglobin (HbA1c) levels at baseline varied between 6.5% to 12%. The glycemic control improved in 70% of patients (mean increase in TIR: 18.9%). Treatment adherence was 100%. No gastrointestinal symptoms or AEs were reported; (4) Conclusions: Early intervention with metformin SR–vildagliptin FDC in patients with T2DM can ensure therapy compliance in terms of superior efficacy along with safety and tolerability. Key summary points: Early initiation of combination therapy helps in early achievement of glycemic goals; Early initiation of metformin and vildagliptin FDC results in significant glycemic control with good tolerability and compliance; Metformin SR–vildagliptin FDC has lower adverse events, compared to metformin IR–vildagliptin FDC; A case series of ten patients with T2DM treated with metformin SR–vildagliptin FDC is presented to assess the real-world effectiveness of this combination.

Expert Consensus Recommendations on Time in Range for Monitoring Glucose Levels in People with Diabetes: An Indian Perspective

Keeping up with the global scenario, diabetes prevalence is on rise in India. Inadequate glycemic control is a major cause of diabetes-related morbidity and mortality. The conventional standards of care (SOC) in diabetes, including self-monitoring of blood glucose and measurement of glycated hemoglobin, have supported achievement of glycemic control, yet there are a few limitations. With the use of current technologies and metrics, such as continuous glucose monitoring (CGM) and standardized CGM data reporting, the continuous real-time glucose levels can be measured, and importantly, the percentage of time above, below, and within the target glucose range can be calculated, which facilitates patient-centric care, a current goal in diabetes management. International consensus recommendations endorse the incorporation of CGM and CGM data reporting in SOC for diabetes management. The guidelines provide time in range (TIR) thresholds for different patient populations and different types of diabetes. However, extrapolation of these global guidelines does not aptly cover the Indian population, which has diverse diet, culture, and religious practices. In this context, a consensus meeting was held in India in 2021 with experts in the field of diabetes care. The purpose of the meeting was to develop consensus recommendations for TIR thresholds for different patient profiles in India. Those expert recommendations, together with an evidence-based review, are reported here. The aim of this agreement is to aid clinicians across India to routinely use CGM and CGM data reports for optimizing individualized diabetes care, by implementing clinical targets for TIR.

Continuous glucose monitoring metrics (Mean Glucose, time above range and time in range) are superior to glycated haemoglobin for assessment of therapeutic efficacy

AIM

To evaluate continuous glucose monitoring (CGM) metrics for use as alternatives to glycated haemoglobin (HbA1c) to evaluate therapeutic efficacy.

METHODS

We re-analysed correlations among CGM metrics from studies involving 545 people with type 1 diabetes (T1D), 5910 people with type 2 diabetes (T2D) and 98 people with T1D during pregnancy and the postpartum period.

RESULTS

Three CGM metrics, interstitial fluid Mean Glucose level, proportion of time above range (%TAR) and proportion of time in range (%TIR), were correlated with HbA1c and provided metrics that can be used to evaluate therapeutic efficacy. Mean Glucose showed the highest correlation with %TAR (r = 0.98 in T1D, 0.97 in T2D) but weaker correlations with %TIR (r = -0.92 in T1D, -0.83 in T2D) or with HbA1c (r = 0.78 in T1D). %TAR and %TIR were highly correlated (r = -0.96 in T1D, -0.91 in T2D). After 6 months of use of real-time CGM by people with T1D, changes in Mean Glucose level were more highly correlated with changes in %TAR (r = 0.95) than with changes in %TIR (r = -0.85) or with changes in HbA1c level (r = 0.52). These metrics can be combined with metrics of hypoglycaemia and/or glycaemic variability to provide a more comprehensive assessment of overall quality of glycaemic control.

CONCLUSION

The CGM metrics %TAR and %TIR show much higher correlations with Mean Glucose than with HbA1c and provide sensitive indicators of efficacy. Mean glucose may be the best metric and shows consistently higher correlations with %TAR than with %TIR.

Comparative assessment of modern parameters of glycemic control in children with type 1 diabetes after switching to fast-acting insulin aspart using Flash Glucose Monitoring in real clinical practice

BACKGROUND: Postprandial hyperglycaemia contributes significantly to the lack of glycaemic control in patients with type 1 diabetes mellitus (DM1). At least a quarter of patients forget to inject insulin before meals once a week, and more than 40% of them inject bolus insulin immediately before meals, which does not correspond to the pharmacokinetic effects of ultrashort insulins and determines the need to use insulins with better imitations of physiological insulin secretion.

AIM: To assess the effect of fast acting insulin aspart (FIAsp) on the current parameters of glycaemic control in children with DM1 after switching from insulin Asp (iAsp) using continuous glucose monitoring.

MATERIALS AND METHODS: A multicenter observational 12-week prospective open-label uncontrolled comparative study was initiated. A group of insufficiently controlled patients were identified (n = 48) including a group on multiple insulin injections therapy (MII) (insulin degludec and IAsp) and a group on continuous subcutaneous insulin infusion (CSII) of iAsp. Three 14-day flash glucose monitoring (FMG) were performed: before transferring patients to FiAsp and after 2 and 12 weeks of the transfer. Key endpoints: HbA1c after 2 and 12 weeks on FiAsp relative to baseline, analysis of 5 FMG target glucose ranges, presented as an ambulatory glycemic profile. Additional indicators: dynamics of insulin daily dose, frequency of glucose self- monitoring, the number of severe hypoglycemia, adverse events that occurred during treatment.

RESULTS: 2 weeks after the transfer from IAsp to FIAsp, TIR increased in the entire group of patients: from 53% [44.3; 66.5] to 57% [47.4; 71.0] (p-value = 0.010) and TAR decreased from 38% [24.8; 50.2] to 30.5% [22.0; 45, 0] (p-value = 0.0124). Maintaining and increase time spent in the target glucose ranges during a 12-week observation period, in parallel with a significant decrease in hypoglycemic episodes <3.9 mmol / L per week, on FIAsp therapy naturally leads to an improvement in diabetes control: a decrease in HbA1c from 8.15% up to 7.75% (p-value = 0.0224), more pronounced in the group of patients on CSII — from 7.9% to 7.5% (p-value = 0.028).

CONCLUSION: Switching from IAsp to BDIAsp in routine clinical practice in the MII and CSII regimen in children and adolescents with type 1 diabetes allows achieving better glycemic control compared to the previous generation prandial insulin analog Iasp. The better diabetes control is associated with an increase or a trend towards an increase in TIR and a decrease or a trend towards a decrease in TAR and TBR, as well as a significant decrease in episodes of hypoglycemia.

Association between high levels of physical activity and improved glucose control on active days in youth with type 1 diabetes

BACKGROUND

Sixty minutes per day of at least moderate to vigorous physical activity (MVPA) is recommended for children for a variety of physical and psychological reasons. Adherence to these guidelines is confounded by challenges with glucose control during exercise in type 1 diabetes (T1D).

OBJECTIVES

This study examined the potential association between physical activity level on active days and glucose control in youth with T1D.

METHODS

Blinded continuous glucose monitors (CGM: Abbott Libre Pro) and physical activity data as measured from a body monitor patch (Metria IH1) were collected for up to 3 weeks in youth aged 9-17 years with T1D. The association between physical activity levels, expressed as mean active metabolic equivalent minutes (MET-minutes) per day, with CGM-based mean glucose, percent time in range (TIR: 70-180 mg/dl), % time above range (TAR) and % time below range (TBR) were assessed using a linear regression model adjusted for age, gender, and baseline HbA1c.

RESULTS

Study participants were deemed physically active, as defined by at least 10 min of continuous moderate-to-vigorous activity, on 5.2 ± 1.9 days per week, with a median accumulated physical activity time of 61 [IQR: 37-145] minutes per day. Higher physical activity levels were associated with lower mean glucose levels (r = -0.36; p = 0.02) and lower TAR (r = -0.45; p = 0.002) on active days. Higher activity levels were also associated with greater TIR (r = 0.54; p < 0.001) without being associated with more, or less, TBR.

CONCLUSIONS

Higher amounts of physical activity are associated with improvements in TIR without significantly increasing TBR. These data suggest that youth ages 9-17 years with T1D can benefit from a high level of physical activity without undue fear of hypoglycemia.

Comparison Between Continuous Versus Flash Glucose Monitoring in Children, Adolescents, and Young Adults with Type 1 Diabetes: An 8-Week Prospective Randomized Trial

INTRODUCTION

To assess the impact of real-time continuous glucose monitoring (RT-CGM) instead of first-generation flash glucose monitoring (FGM) on hypoglycaemia in children and adolescents with type 1 diabetes.

METHODS

In this randomized controlled interventional study, young individuals with type 1 diabetes used RT-CGM or FGM for 8 weeks. We evaluated changes in time below range (TBR), severe hypoglycaemia (SH), HbA1c, glycaemic variability, and impaired awareness of hypoglycaemia with RT-CGM (intervention group) in comparison with FGM.

RESULTS

We randomly assigned 37 participants to either the intervention group (n = 19) or the control group (n = 18). At 8 weeks, we did not find a decrease in TBR in either group, but there was a significant reduction in SH in the intervention group. For participants with TBR ≥ 5% at baseline, we observed significant reductions in 24-h TBR, wake TBR, sleep TBR, and glucose variability at 8 weeks in the intervention group.

CONCLUSIONS

The use of RT-CGM versus FGM decreased SH in young individuals with type 1 diabetes, and TBR and glucose variability in patients with a higher TBR at baseline. The patient's history should be taken into account when advising on the method of blood glucose monitoring, as RT-CGM could be more effective in younger patients at high risk for SH.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04249102.

A computational framework for discovering digital biomarkers of glycemic control

Digital biomarkers can radically transform the standard of care for chronic conditions that are complex to manage. In this work, we propose a scalable computational framework for discovering digital biomarkers of glycemic control. As a feasibility study, we leveraged over 79,000 days of digital data to define objective features, model the impact of each feature, classify glycemic control, and identify the most impactful digital biomarkers. Our research shows that glycemic control varies by age group, and was worse in the youngest population of subjects between the ages of 2–14. In addition, digital biomarkers like prior-day time above range and prior-day time in range, as well as total daily bolus and total daily basal were most predictive of impending glycemic control. With a combination of the top-ranked digital biomarkers, we achieved an average F1 score of 82.4% and 89.7% for classifying next-day glycemic control across two unique datasets.

A guide for the use of LibreView digital diabetes platform in clinical practice: Expert paper of the Italian Working Group on Diabetes and Technology

Wider access to continuous glucose monitoring systems, including flash glucose monitoring, has enabled people with diabetes to achieve lower HbA1c levels and reduce the amount of time they spend in hypoglycaemia or hyperglycaemia, and has improved their quality of life. An International Consensus Panel proposed different target glucose ranges and recommendations according to different ages and situations (adults, young people and children with type 1 or type 2 diabetes, as well as elderly people who are at higher risk of hypoglycaemia, and women with diabetes during pregnancy). In this expert opinion, we interpret the international recommendations in the context of established clinical practice for diabetes care, and propose three different step-by-step algorithms to help the healthcare professionals use the most innovative glucose metrics, including time in glucose ranges, glucose management indicator, coefficient of variation, and ambulatory glucose profile. In detail, we focus on glucose metrics as measured by the FreeStyle Libre system and as visualized on the LibreView digital diabetes platform to support appropriate interpretation of flash glucose monitoring data. This is specifically structured for healthcare professionals and general practitioners who may have a low level of confidence with diabetes technology, with the aim of optimizing diabetes management, ensuring effective use of healthcare resources and to maximise outcomes for people with diabetes.

Frequent scanning using flash glucose monitoring contributes to better glycemic control in children and adolescents with type 1 diabetes

AIMS/INTRODUCTION

We examined the impact of scanning frequency with flash glucose monitoring on glycemic control in children and adolescents with type 1 diabetes.

MATERIALS AND METHODS

The study included 85 patients, aged 14.0 ± 0.5 years, with type 1 diabetes. The median time in the target glucose range (TIR) and glycosylated hemoglobin (HbA1c) values were 50.0 ± 1.4% and 7.5 ± 0.1%, respectively.

RESULTS

The median scanning frequency using flash glucose monitoring was 12.0 ± 0.4 times/day. Scanning frequency showed a significant positive correlation with TIR and an inverse correlation with HbA1c. Scanning frequency was identified to be the determinant of TIR and HbA1c by using multivariate analysis. The participants whose scanning frequency was <12 times/day were categorized as the low-frequency group (n = 40), and those who carried out the scanning >12 times/day were categorized as the high-frequency group (n = 45). Patients in the high-frequency group were more likely to be treated with insulin pumps compared with those in the low-frequency group; however, this difference was not significant (21.3 vs 5.3%, P = 0.073). The high-frequency group showed significantly greater TIR than the low-frequency group (57 ± 1.6 vs 42 ± 1.7%, P = 0.002). Furthermore, the high-frequency group showed significantly lower HbA1c levels than the low-frequency group (6.8 ± 0.1 vs 8.0 ± 0.1%, P < 0.001).

CONCLUSIONS

These findings showed that patients with a higher scanning frequency had better glycemic control, with greater TIRs and lower HbA1c levels, compared with those with a lower scanning frequency. Scanning frequency of >12 times/day might contribute to better glycemic outcomes in real-world practice in children with type 1 diabetes.

The automated pancreas: A review of technologies and clinical practice

Insulin pumps and glucose sensors are effective in improving diabetes therapy and reducing acute complications. The combination of both devices using an algorithm-driven interoperable controller makes automated insulin delivery (AID) systems possible. Many AID systems have been tested in clinical trials and have proven safety and effectiveness. However, currently, none of these systems are available for routine use in children younger than 6 years in Europe. For continued use, both users and prescribers must have sound knowledge of the features of the individual AID systems. Presently, all systems require various user interactions (e.g. meal announcements) because fully automated systems are not yet developed. Open-source systems are non-regulated variants to circumvent existing regulatory conditions. There are risks here for both users and prescribers. To evaluate AID therapy, the metric data of the glucose sensors, 'time in target range' and 'glucose management index', are novel recognized and suitable parameters allowing a consultation based on real glucose and insulin pump download data from the daily life of people with diabetes. Read out via cloud-based software or automatic download of such individual treatment data provides the ideal technical basis for shared decision-making through telemedicine, which must be further evaluated for general use.

Glycaemic management in diabetes: old and new approaches

HbA_1c is the most used parameter to assess glycaemic control. However, evidence suggests that the concept of hyperglycaemia has profoundly changed and that different facets of hyperglycaemia must be considered. A modern approach to glycaemic control should focus not only on reaching and maintaining optimal HbA_1c concentrations as early as possible, but to also do so by reducing postprandial hyperglycaemia, glycaemic variability, and to extend as much as possible the time in range in near-normoglycaemia. These goals should be achieved while avoiding hypoglycaemia, which, should it occur, should be reverted to normoglycaemia. Modern technology, such as intermittently scanned glucose monitoring and continuous glucose monitoring, together with new drug therapies (eg, ultra-fast insulins, SGLT2 inhibitors, and GLP-1 receptor agonists), could help to change the landscape of glycaemia management based on HbA_1c in favour of a more holistic approach that considers all the different aspects of this commonly oversimplified pathophysiological feature of diabetes.

Glucose control using fast-acting insulin aspart in a real-world setting: A 1-year, two-centre study in people with type 1 diabetes using continuous glucose monitoring

AIM

To evaluate the efficacy and safety of switching from traditional mealtime insulins to fast-acting insulin aspart (Fiasp) in a "real-world" clinical practice setting in adult people with type 1 diabetes (PWD1) who were using intermittently scanned or real-time continuous glucose monitoring (isCGM or rtCGM, respectively).

MATERIALS AND METHODS

Data from 438 adult PWD1 (60% men, age 44.6 ± 16.2 years, diabetes duration 21.5 ± 14.0 years, isCGM/rtCGM: 391/47, multiple daily injections/continuous subcutaneous insulin infusion: 409/29), who initiated Fiasp from January 2018 to May 2020, were analysed. The primary objective was the evolution of time in range (TIR; 70-180 mg/dL) at 6 and 12 months. Secondary objectives included change in HbA1c, body mass index (BMI), insulin doses, time below range (<70 and <54 mg/dL), and time above range (>180 and >250 mg/dL).

RESULTS

TIR improved from 50.3% ± 15.6% to 54.3% ± 15.1% at 6 months (n = 425) and to 55.5% ± 15.2% at 12 months (n = 385) (P < .001), corresponding to 57 min/d at 6 months and 75 min/d at 12 months. Time spent below 54 mg/dL evolved from 3.1% ± 3.3% to 3.1% ± 3.7% and 2.5% ± 3.0% at 6 and 12 months, respectively (P = .011). Also, time spent above 180 mg/dL decreased from 42.3% ± 16.7% at start by 4.2% at 6 months and by 4.6% at 12 months (P < .001). The proportion of people reaching TIR more than 70% increased from 11.0% to 14.8% (P = .002), and those spending less than 4% at time less than 70 mg/dL increased from 36.1% to 42.1% (P = .002). After 12 months, HbA1c, insulin doses, and BMI did not change significantly.

CONCLUSIONS

In a Belgian real-world setting of adult PWD1, switching to Fiasp was associated with a 5% increased TIR after 12 months, corresponding to 75 min/d, in combination with less time spent below and above range.

Impact of Custom Features of Do-it-yourself Artificial Pancreas Systems (DIYAPS) on Glycemic Outcomes of People with Type 1 Diabetes

One of the benefits of Do-it-yourself Artificial Pancreas Systems (DIYAPS) over commercially available systems is the high degree of customization possible through various features developed by the community. This paper investigates the impact of thirteen commonly used custom features on the glycemic outcomes of users with type 1 diabetes. Significant differences were observed in the group using the Automated Microbolus, Autotune (automatic), and the Superbolus feature. As many of the features aim to improve not only glycemic outcomes but also reduce the burden of managing diabetes on the user, future studies should investigate the impact of these features on the quality of life of their users.Clinical Relevance-This paper expands the existing knowledge on the DIYAPS for people with type 1 diabetes which have been gaining popularity among the patient population in recent years.

[Individualization of diabetes treatment by automated insulin delivery]

Insulinpumpen und Glucosesensoren haben sich in Registerdaten als effektiv in der Verbesserung der Diabetestherapie und Reduktion akuter Komplikationen gezeigt. In der pädiatrischen Diabetologie ist die Nutzung mindestens eines technischen Geräts Standard. Durch die Kombination beider Systeme ergibt sich Möglichkeit der automatischen Insulinabgabe („automated insulin delivery“, AID).

Viele AID-Systeme sind in klinischen Studien getestet und haben sich als sicher und effektiv erwiesen. Die Versorgungsituation in Deutschland erlaubt es derzeit nur, Mitgliedern der gesetzlichen Krankenversicherungen ein bestimmtes System zu verordnen; dieses ist für Kinder, die jünger als 7 Jahre sind, nicht geeignet. Gründe liegen in gesetzlichen Hürden und mangelnder Zertifizierung durch die Hersteller. Die CE-Zertifikate können Probleme bei der Insulinverordnung mit sich bringen. „Open-source“-Systeme sind Varianten, mit denen bestehende Regularien umgangen werden können. Daraus ergeben sich sowohl für Nutzer wie auch für Verordner Risiken.

Die dauerhafte Nutzung setzt sowohl auf Anwender- als auch auf Behandlerseite die fundierte Kenntnis der Eigenschaften der einzelnen AID-Systeme voraus. Eine vollständige Automatisierung funktioniert noch nicht. Zur Evaluation der AID-Therapie sind die metrischen Daten der Glucosesensoren, die „Zeit im Zielbereich“ und der „Glucose Management Indicator“ anerkannte und geeignete Parameter, da sie eine Beratung auf Basis der reellen Daten aus dem Alltag der Menschen mit Diabetes zulassen.

Da alle Glucosesensoren über Cloud-basierte Software ausgelesen werden oder die Daten automatisch aus einem telefonverbundenen Empfangsgerät beziehen, ist die ideale technische Grundlage für eine telemedizinische Betreuung geschaffen, die noch der Ausgestaltung bedarf.

Time-in-range for monitoring glucose control: Is it time for a change?

The HbA1c value has been the gold standard for evaluating glucose control for decades. However, it has limitations such as the lack of information on glycemic variability or the risk of hypoglycemia. The increasing use of continuous glucose monitoring has provided patients and healthcare professionals with a range of useful metrics for the management of diabetes. Among them, Time in Range (TIR) is a simple and intuitive metric that gives information regarding the quality of glucose control. It is defined as the time spent in an individual's target glucose range. TIR is strongly correlated with HbA1c, and it has been linked to the risk of developing microvascular and macrovascular complications. The International Consensus on Time in Range has recently set targets for different diabetes populations. For the majority of people with type 1 or type 2 diabetes, a TIR (70-180 mg/dL or 3.9-10.0 mmol/L) of >70%, a time below range (TBR) <70 mg/dL (<3.9 mmol/L) of <4% and a TBR <54 (<3.0 mmol/L) of <1% are recommended. In this review, we address the latest evidence for the use of TIR as an essential parameter in the management of diabetes.

AID(„automated insulin delivery“)-Systeme in der Diabetologie

Insulinpumpen und Glukosesensoren können laut Registerdaten die Diabetestherapie verbessern sowie die Rate akuter Komplikationen reduzieren. In der pädiatrischen Diabetologie ist daher die Nutzung mindestens eines dieser technischen Geräte Standard. Deren Kombination macht Systeme zur automatischen Insulinabgabe („automated insulin delivery“ [AID]) möglich. Viele AID-Systeme wurden in klinischen Studien getestet und erwiesen sich als sicher und effektiv. Die Versorgungsituation in Deutschland jedoch lässt derzeit nur ein System als Verordnung bei Versicherten der gesetzlichen Krankenversicherungen zu, und Kinder unter 7 Jahren können damit derzeit nicht versorgt werden. Gründe hierfür sind gesetzliche Hürden und die mangelnde Zertifizierung durch die Hersteller. Die CE-Zertifikate können zudem zu Problemen bei der Insulinverordnung führen. Open-Source-Systeme sind nicht geprüfte Varianten, um bestehende regulatorische Verhältnisse zu umgehen. Deren Anwendung geht mit Risiken sowohl für Nutzer als auch Verordner einher. Für ihren dauerhaften Einsatz müssen sowohl Anwender als auch Behandler über fundierte Kenntnisse der Eigenschaften der einzelnen AID-Systeme verfügen. Zur Evaluation der AID-Therapie sind die metrischen Daten der Glukosesensoren, die „time in range“ und der Glukosemanagementindex die anerkannten und geeigneten Parameter, da sie eine Beratung auf Basis der reellen Werte aus dem Alltag der Menschen mit Diabetes zulassen. Da alle Glukosesensoren über Cloud-basierte Software ausgelesen werden oder die Daten direkt automatisch übermitteln, ist hiermit die ideale technische Grundlage für eine telemedizinische Betreuung geschaffen, die noch der Ausgestaltung bedarf.

Real-world outcomes with different technology modalities in type 1 diabetes

BACKGROUND AND AIMS

Several treatment modalities are available for type 1 diabetes (T1D), including continuous glucose monitoring (CGM) and flash glucose monitoring (FGM) with MDI, sensor-augmented pumps with predictive low-glucose suspend function (SAP-PLGS) and hybrid closed-loop systems (HCL). The aim of the study was to evaluate the real-world benefits obtained with these treatment modalities.

METHODS AND RESULTS

A cross-sectional study was performed, selecting 4 groups of T1D subjects, regarding their treatment modalities, paired by age, sex and diabetes duration. A comparison was performed, concerning time in different glucose ranges in 2-week sensor downloads. Estimated HbA1c, glycaemic variability measures and sensor use were also compared. 302 T1D people were included (age: 39 ± 12 years, 47% male, diabetes duration: 21 ± 10 years, estimated HbA1c: 7.28 ± 0.84% (56 ± 9 mmol/mol), baseline HbA1c: 7.4 ± 1.0% (57 ± 11 mmol/mol), length of use of the device 8 [3-21] months). Group 1 (CGM + MDI) and 2 (FGM + MDI) showed no differences in time in different glucose ranges. Group 4 (HCL) showed a higher time 70-180 mg/dl and a lower time in hypoglycaemia than group 3 (SAP-PLGS). Group 1 and 2 showed lower time 70-180 mg/dl, higher time in hyperglycaemia and higher glycaemic variability measures than group 3. Group 4 was superior to groups 1 and 2 in all the outcomes.

CONCLUSION

Real-life achievements in glycaemic control and glycaemic variability are described. HCL offer the maximum benefit in terms of time in range and hypoglycaemia protection, compared to CGM + MDI, FGM + MDI and SAP-PLGS.