Clinical Targets for Continuous Glucose Monitoring Data Interpretation: Recommendations From the International Consensus on Time in Range

A combined diabetes and continuous glucose monitoring education program for adults with type 2 diabetes

Objective

The lack of descriptions for education programs in studies evaluating the efficacy of continuous glucose monitoring (CGM) compared to blood glucose monitoring (BGM) for individuals with T2DM makes it difficult to compare results across trials. This study aimed to develop and evaluate a new education program for adults with insulin-treated T2DM and HbA1c ≥58 mmol/mol (7.5 %) initiating CGM.

Methods

A 3-h education program was created to provide information on diabetes self-management and CGM or BGM based on international guidelines and a pre-evaluation based on user needs assessment. Questionnaires were used to post-evaluate participant-rated benefits from the program.

Results

Seven individuals attended a user needs assessment of the program and 96 participated in the final education program (61.5 % men, mean age 61 (59.5;63) years, mean diabetes duration 18.2 (16.9;19.5) years, and median HbA1c 69 (63-78)mmol/mol (8.5 (7.9-9.3)%). Benefit from this program was rated good/very good by 95.5 % with no statistically significant difference between glucose monitoring groups.

Conclusions

This study presents a new well-received education program for T2DM for both the CGM and BGM group.

Innovation

The description of the development process and the education provided for both glucose monitoring groups may be useful for CGM initiation in clinics and trials.

Excellence in the management of Advanced Hybrid Closed-Loop Systems: Lessons from the Polish cohort

BACKGROUND

The aim of the study was to analyze the real-world performance of MiniMed 780G (MM780G) Advanced Hybrid Closed Loop (AHCL) system users from Poland (PL) and compare it to the European region excluding Poland (EU-PL) in order to identify factors contributing to potential differences. The former achieved some of the best Time in Range (TIR) results globally using this technology.

METHODS

CareLink Personal data uploaded by MM780G system users from August 2020 to December 2022 were analyzed.

RESULTS

The Polish users (N=1304) on average reached to TIR of 79.1 ± 8.7 % (vs 73.0 ± 10.0 % for EU-PL, N=55659), a TBR<54 mg/dL of 0.6 ± 0.7 % (vs 0.4 ± 0.6 %) and a TBR<70 mg/dL of 2.9 ± 2.1 % (vs 2.1 ± 1.8 %). The adoption rate of optimal settings (i.e, GT=100 mg/dL, AIT=2hr) in PL was high (19.7 % vs 6.3 %), and filtering on optimal setting users led to less pronounced differences in glycemic control between PL and EU-PL. A univariable analysis with post-AHCL TIR showed that geography itself (PL vs EU-PL) is not a significant contributor to a high post-AHCL TIR (p = 0.15), and that much of the Polish post-AHCL TIR can be explained by the high pre-AHCL TIR.

CONCLUSION

The Polish MM780G users achieved better glycemic control than the general European population (excluding Poland). This is largely attributable to the adoption of optimal settings in Poland and the already high glycemic outcomes at system start. As these characteristics can be implemented elsewhere, we believe this outstanding result can be obtained in other countries as well.

The potential of glucose management indicator for the estimation of glucose disposal rate in people with type 1 diabetes

BACKGROUND AND AIMS

Insulin resistance is a growing feature in type 1 diabetes (T1D). It can be quantified by calculating the estimated glucose disposal rate (eGDR) with the Epstein's formula, which includes laboratory-measured glycated hemoglobin (HbA1c). We aimed the current research to assess the agreement between the conventional eGDR formula and an alternative one (eGDR-GMI) incorporating the glucose management indicator (GMI) derived from continuous glucose monitoring (CGM). We also explored the relationship between eGDR-GMI, cardiovascular risk factors, and the prevalence of diabetes-related complications.

METHODS AND RESULTS

We designed a cross-sectional study that included adults with T1D. eGDR-GMI and eGDR (mg/kg/min) were calculated using GMI or HbA1c, waist circumference, and hypertensive state. Clinical data were collected from electronic medical records. The analyses encompassed 158 participants with a mean age of 39 ± 13 years. The Bland-Altman analysis showed a good agreement between eGDR-GMI and eGDR. When we divided participants in eGDR-GMI tertiles we found a higher prevalence of diabetes-related complications and a less favorable metabolic profile in the lowest eGDR-GMI tertile. The relative risk of retinopathy, nephropathy, and neuropathy significantly increased by approximately 1 unit with each decrease in eGDR-GMI, regardless of age, sex, disease duration, lipids, and smoking habit.

CONCLUSIONS

eGDR-GMI represents a valid and robust alternative to the eGDR to assess insulin resistance in T1D. Low eGDR-GMI is associated with diabetes complications and a less favorable metabolic profile. Incorporating the eGDR-GMI into clinical practice can enhance the characterization of T1D people and allow for a more personalized treatment approach.

Validation and verification framework and data integration of biosensors and in vitro diagnostic devices: a position statement of the IFCC Committee on Mobile Health and Bioengineering in Laboratory Medicine (C-MBHLM) and the IFCC Scientific Division

Advances in technology have transformed healthcare and laboratory medicine. Biosensors have emerged as a promising technology in healthcare, providing a way to monitor human physiological parameters in a continuous, real-time, and non-intrusive manner and offering value and benefits in a wide range of applications. This position statement aims to present the current situation around biosensors, their perspectives and importantly the need to set the framework for their validation and safe use. The development of a qualification framework for biosensors should be conceptually adopted and extended to cover digitally measured biomarkers from biosensors for advancing healthcare and achieving more individualized patient management and better patient outcome.

Effect of Real-Time Continuous Glucose Monitoring Versus Flash Glucose Monitoring on Glycemic Control in Adults with Type 1 Diabetes Mellitus: A Systematic Review and Meta-Analysis

Objective: This meta-analysis aimed to compare the effect of the real-time continuous glucose monitoring (rt-CGM) and flash glucose monitoring (FGM) on glycemic control in adults with type 1 diabetes mellitus (T1DM). Methods: A systematic literature search of all relevant studies comparing the clinical effectiveness of rt-CGM and FGM in adults with T1DM on Cochrane Library, PubMed, Embase, Web of Science, and Scopus from January 2015 to June 2023 was performed. The primary endpoints were glycated hemoglobin (HbA1c) and TIR (time in range). Secondary endpoints included time below range [TBR (<3.9 mmol/L) and (<3.0 mmol/L)], time above range [TAR (>10.0 mmol/L) and (>13.9 mmol/L)], mean glucose, and glycemic variability (GV) [standard deviations (SD) and coefficient of variation (CV)]. Results: Six studies with 1516 TIDM patients, including three randomized controlled trials and three observational studies, were enrolled in this meta-analysis. Compared to FGM, rt-CGM led to greater glycemic control, represented by higher TIR (%, 3.9 ∼ 10 mmol/L) (SMD = 0.59, 95%CI: 0.37 ∼ 0.81, p < 0.001), decreased TBR (%, <3.9 mmol/L) (SMD = -1.45, 95%CI: -2.33 ∼ -0.57, p = 0.001), decreased TAR [(%, >10.0 mmol/L) (SMD = -0.38, 95%CI: -0.71 ∼ -0.04, p = 0.03) and (%, >13.9 mmol/L) (SMD = -0.42, 95%CI: -0.79 ∼ -0.04, p = 0.03), respectively], lower mean glucose (SMD = -0.18, 95%CI: -0.31 ∼ -0.06, p = 0.003), decreased SD (SMD = -0.70, 95%CI: -1.09 ∼ -0.31, p < 0.001), and decreased CV (SMD = -0.76, 95%CI: -1.05 ∼ -0.47, p < 0.001). However, there was no difference in lowering HbA1c and TBR (%, <3.0 mmol/L) between groups. Conclusion: The rt-CGM outperformed FGM in improving several key CGM metrics among adults with T1DM, but there is no significant difference in HbA1c and TBR (<3.0 mmol/L).

Long-Term Glycemic Control Improvement After the Home and Self-Care Program for Patients With Type 1 Diabetes: Real-World-Based Cohort Study

BACKGROUND

The prevalence of type 1 diabetes (T1D) is increasing worldwide, with a much higher proportion of adult patients. However, achieving stable glycemic control is difficult in these patients.

OBJECTIVE

After periodic implementation of structured education for patients with T1D through the Home and Self-Care Program, a pilot home health care project promoted by the Korean government, we evaluated the program's effects on glycemic control.

METHODS

This study was conducted from April 2020 to March 2023. We analyzed 119 participants with T1D aged >15 years. Nursing and nutrition education were provided separately up to 4 times per year, with physician consultation up to 6 times per year. A distinguishing feature of this study compared with previous ones was the provision of remote support using a general-purpose smartphone communication app offered up to 12 times annually on an as-needed basis to enhance the continuity of in-person education effects. Patients were followed up on at average intervals of 3 months for up to 24 months. The primary end point was the mean difference in glycated hemoglobin (HbA1c) at each follow-up visit from baseline. For continuous glucose monitoring (CGM) users, CGM metrics were also evaluated.

RESULTS

The mean HbA1c level of study participants was 8.6% at baseline (mean duration of T1D 10.02, SD 16.10 y). The HbA1c level reduction in participants who received at least 1 structured educational session went from 1.63% (SD 2.03%; P<.001; adjustment model=1.69%, 95% CI 1.24%-2.13% at the first follow-up visit) to 1.23% (SD 1.31%; P=.01; adjustment model=1.28%, 95% CI 0.78%-1.79% at the eighth follow-up visit). In the adjustment model, the actual mean HbA1c values were maintained between a minimum of 7.33% (95% CI 7.20%-7.46% at the first follow-up visit) and a maximum of 7.62% (95% CI 7.41%-7.82% at the sixth follow-up visit). Among CGM users, after at least 1 session, the mean time in the target range was maintained between 61.59% (adjusted model, 95% CI 58.14%-65.03% at the second follow-up visit) and 54.7% (95% CI 50.92%-58.48% at the eighth follow-up visit), consistently staying above 54.7% (corresponding to an HbA1c level of <7.6%). The mean time below the target range (TBR) also gradually improved to the recommended range (≤4% for TBR of <70 mg/dL and ≤1% for TBR of <54 mg/dL).

CONCLUSIONS

The Home and Self-Care Program protocol for glycemic control in patients with T1D is effective, producing significant improvement immediately and long-term maintenance effects, including on CGM indexes.

Impact of blood glucose on cognitive function in insulin resistance: novel insights from ambulatory assessment

BACKGROUND/OBJECTIVES

Insulin resistance (IR)-related disorders and cognitive impairment lead to reduced quality of life and cause a significant strain on individuals and the public health system. Thus, we investigated the effects of insulin resistance (IR), and blood glucose fluctuations on cognitive function under laboratory and free-living conditions, using ecological momentary assessment (EMA).

SUBJECTS/METHODS

Baseline assessments included neuropsychological tests and blood analysis. Individuals were classified as either insulin-sensitive (<2) or insulin-resistant (≥2), based on their Homeostatic Model Assessment (HOMA-IR) values. Continuous glucose monitoring (CGM) using a percutaneous sensor was performed for 1 week. Using multiple linear regression, we examined the effects of HOMA-IR and CGM metrics on cognitive domains. Working memory (WM) performance, which was assessed using EMA, 4 times a day for 3 consecutive days, was matched to short-term pre-task CGM metrics. Multilevel analysis was used to map the within-day associations of HOMA-IR, short-term CGM metrics, and WM.

RESULTS

Analyses included 110 individuals (mean age 48.7 ± 14.3 years, 59% female, n = 53 insulin-resistant). IR was associated with lower global cognitive function (b = -0.267, P = 0.027), and WM (b = -0.316; P = 0.029), but not with executive function (b = -0.216; P = 0.154) during baseline. EMA showed that higher HOMA-IR was associated with lower within-day WM performance (β = -0.20, 95% CI -0.40 to -0.00). CGM metrics were not associated with cognitive performance.

CONCLUSIONS

The results confirm the association between IR and decrements in global cognitive functioning and WM, while no effects of CGM metrics were observed, making IR a crucial time point for intervention. Targeting underlying mechanisms (e.g., inflammation) in addition to glycemia could be promising to minimize adverse cognitive effects. Registered under https://drks.de/register/de identifier no. DRKS00022774.

Effectiveness and safety of glucose-lowering drugs as an adjunct to insulin therapy in Chinese patients with type 1 diabetes: a retrospective, observational study

AIM

To assess the real-world impact of glucose-lowering drugs (GLDs) as an adjunct to insulin in Chinese patients with type 1 diabetes (T1DM).

METHODS

This dual-center, observational, retrospective study included 121 T1DM patients receiving GLDs as adjuncts and 56 participants with insulin-only drugs as comparators. Glycated hemoglobin A1c (HbA1c), daily insulin dosage, fasting blood glucose (FBG), postprandial blood glucose (PBG), nocturnal blood glucose (NBG) and the difference in trough and peak blood glucose levels on the same day (Δ TP) were assessed at baseline and at the end of the study.

RESULTS

In total, HbA1c decreased by 1.14% in the GLD+insulin group (p < 0.0001) and 0.36% in the insulin-only group (p = 0.0423, mean adjusted difference, -0.09% [95% CI, -0.55 to 0.37]). The total daily insulin concentration was reduced by 7.34 U per day in the GLD+insulin group vs. 5.55 U per day in the insulin-only group (mean adjusted difference, -2.32 U [95% CI, -4.97 to 0.33]). In particular, among patients with fasting C-peptide levels < 17 pmol/L, the total daily insulin concentration was significantly reduced by 9.22 U vs. 5.09 U per day (mean adjusted difference, -3.84 [95% CI, -6.85-0.84]; p = 0.0129). There were no notable differences in the other glycemic indices between the two groups. A gradual downward trend in changes in glycemic outcomes was observed among patients treated with various combinations of metformin, acarbose, and dipeptidyl peptidase 4 inhibitor (DPP-4i). Similar reductions in the daily insulin dose were also detected in most of the GLD+insulin group in addition to the DPP-4i-only group. No severe hypoglycemia was induced by additional GLDs.

CONCLUSIONS

The use of additional GLDs tends to improve glycemic outcomes and reduce insulin requirements in patients with T1DM. These results indicate that the use of GLDs as an adjunctive therapy may have been an effective treatment strategy among adults with T1DM in China.

Time-in-range derived from self-measured blood glucose in people with type 2 diabetes advancing to iGlarLixi: A participant-level pooled analysis of three phase 3 LixiLan randomized controlled trials

AIM

To evaluate the efficacy of a fixed-ratio combination of insulin glargine 100 U/mL plus lixisenatide (iGlarLixi) in people with type 2 diabetes (T2D) using derived time-in-range (dTIR).

METHODS

Participant-level data from LixiLan-L, LixiLan-O and LixiLan-G were pooled and dTIR (70-180 mg/dL), derived time-above-range (> 180 mg/dL) and derived time-below-range (dTBR; < 70 mg/dL) were calculated from participant seven-point self-monitored blood glucose profiles.

RESULTS

This pooled analysis included data from 2420 participants receiving iGlarLixi (n = 1093), iGlar (n = 836), Lixi (n = 234) or a glucagon-like peptide-1 receptor agonist (GLP-1 RA) (n = 257). Numerically greater improvements in least square (LS) means dTIR were seen from baseline to end of treatment (EOT) with iGlarLixi (25.7%) versus iGlar (15.8%), Lixi (11.7%) or GLP-1 RA (16.2%). At EOT, the mean (standard deviation) dTBR was 0.71% ± 3.4%, 0.61% ± 3.2%, 0.08% ± 1.0% and 0.0% ± 0.0% for iGlarLixi, iGlar, Lixi and GLP-1 RA, respectively. In a subgroup analysis, participants aged younger than 65 years (n = 1690) and 65 years or older (n = 713) showed numerically greater improvements in LS means dTIR from baseline to EOT with iGlarLixi versus iGlar, Lixi or GLP-1 RA.

CONCLUSIONS

iGlarLixi achieved improvements in dTIR, with low dTBR values, providing further evidence to inform clinical outcomes with the use of iGlarLixi.

Effect of Body Weight on Glycaemic Indices in People with Type 1 Diabetes Using Continuous Glucose Monitoring

Background/Objectives: Obesity and overweight have become increasingly prevalent in different populations of people with type 1 diabetes (PwT1D). This study aimed to assess the effect of body weight on glycaemic indices in PwT1D. Methods: Adult PwT1D using continuous glucose monitoring (CGM) and followed up at a regional academic diabetes centre were included. Body weight, body mass index (BMI), waist circumference, glycated haemoglobin (HbA1c), and standard CGM glycaemic indices were recorded. Glycaemic indices were compared according to BMI, and correlation and linear regression analysis were performed to estimate the association between measures of adiposity and glycaemic indices. Results: A total of 73 PwT1D were included (48% normal weight, 33% overweight, and 19% obese). HbA1c was 7.2% (5.6-10), glucose management indicator (GMI) 6.9% (5.7-8.9), coefficient of variation (CV) for glucose 39.5% ± 6.4, mean glucose 148 (101-235) mg/dL, TIR (time in range, glucose 70-180 mg/dL) 66% (25-94), TBR70 (time below range, 54-69 mg/dL) 4% (0-16), TBR54 (<54 mg/dL) 1% (0-11), TAR180 (time above range, 181-250 mg/dL) 20% ± 7, and TAR250 (>250 mg/dL) 6% (0-40). Glycaemic indices and achievement (%) of optimal glycaemic targets were similar between normal weight, overweight, and obese patients. BMI was associated negatively with GMI, mean glucose, TAR180, and TAR250 and positively with TIR; waist circumference was negatively associated with TAR250. Conclusions: CGM-derived glycaemic indices were similar in overweight/obese and normal weight PwT1D. Body weight and BMI were positively associated with better glycaemic control. PwT1D should receive appropriate ongoing support to achieve optimal glycaemic targets whilst maintaining a healthy body weight.

Cost-effectiveness of the tandem t: Slim X2 with control-IQ technology automated insulin delivery system in children and adolescents with type 1 diabetes in Sweden

AIMS

The present analysis estimated the cost-effectiveness of treatment with the Tandem t: slim X2 insulin pump with Control IQ technology (CIQ) in children with type 1 diabetes in Sweden.

METHODS

A four-state Markov model and probabilistic sensitivity analyses (PSA) were used to assess the cost-effectiveness of CIQ use compared with treatment with multiple daily insulin injections (MDI) or continuous subcutaneous insulin infusion (CSII) in conjunction with CGM. Data sources included clinical input data from a recent retrospective, observational study, cost data from local diabetes supply companies and government agencies, and published literature. Outcomes measures were quality adjusted life years (QALYs) at 10, 20 and 30-year time horizons based on cost per QALY and incremental cost-effectiveness ratio (ICER).

RESULTS

A total of 84 type 1 diabetes children were included (CIQ, n = 37; MDI, n = 19; CSII, n = 28). For all time horizons, the use of CIQ was a dominant strategy (e.g. more effective and less costly) compared with MDI or CSII use: 10-year ICER, SEK -88,010.37 and SEK -91,723.92; 20-year ICER, SEK -72,095.33 and SEK -87,707.79; and 30-year ICER, SEK -65,573.01 and SEK -85,495.68, respectively. PSA confirmed that CIQ use was less costly compared with MDI and CSII.

CONCLUSIONS

Initiation of CIQ use in children with type 1 diabetes is cost-saving, besides previously shown improved glycaemic control, and increased quality of life. Further investigations are needed to more fully elucidate the cost-effectiveness of these technologies in different countries with existing differences in payment models.

Is there a target value for time in tight range for individuals with type 1 diabetes on MDI? Data from masked CGM

OBJECTIVE

Time in Tight Range (TITR), defined as the percentage of time within the glucose range of 70 to 140 mg/dL, is anticipated to be challenging to maintain without causing hypoglycemia, especially in individuals with type 1 diabetes (T1D). This study aimed to investigate the TITR target value in individuals with T1D on multiple daily injections (MDI).

METHODS

The study included 101 individuals with T1D on MDI aged 15 to 75 who were hospitalized at Jikei University School of Medicine from September 2006 to November 2013 to conduct Continuous Glucose Monitoring (CGM). The cutoff values of TITR for predicting the attainment of GMI < 7.0%, and TBR < 4% were determined using Receiver Operating Characteristic (ROC) curves.

RESULTS

The TITR cutoff value was calculated to be 41% (sensitivity 81%, specificity 88%) and 40% (54%,72%) for predicting GMI < 7.0% and TBR < 4%.

CONCLUSIONS

In individuals with T1D on MDI without devices capable of preventing hypoglycemia, it is recommended to target TITR at 40% to address the risk of increased hypoglycemia sufficiently.

Investigation of Glucose Metabolism by Continuous Glucose Monitoring and Validation of Dipeptidyl Peptidase 4 Inhibitor Use in Patients with Myotonic Dystrophy Type 1

Objectives: We characterized blood glucose fluctuations in patients with myotonic dystrophy type 1 (DM1). After confirming the incretin secretion capacity of patients with DM1, we intended to clarify whether dipeptidyl peptidase 4 (DPP-4) inhibitor administration was appropriate in cases of DM1 with diabetes mellitus. Methods: A 48 h continuous glucose monitoring (CGM) was performed in 29 Japanese patients with DM1. An oral glucose tolerance test (OGTT) was performed in patients with DM1 and five disease controls, and levels of blood glucose, insulin, and incretin (glucagon-like peptide-1 and gastric inhibitory polypeptide) were measured. DPP-4 inhibitors were administered to patients with diabetes mellitus complicated by DM1, and the CGM results were compared. Results: The CGM showed distinct patterns of blood glucose variability among patients classified by an OGTT pattern with significant differences in glucose parameters such as time above 140 mg/dL and mean amplitude of glycemic excursions between the groups. High sensor glucose values were observed in a certain number of patients who were classified as having normal or impaired glucose tolerance by the OGTT. The CGM confirmed the presence of low glucose levels in several patients. Incretin secretion, the target of DPP-4 inhibitors, was preserved in patients with DM1. DPP-4 inhibitor treatment resulted in lower glucose levels and improved insulin secretion in some patients. Conclusions: This is the first CGM study for DM1 patients. The CGM identified potential early abnormalities in glucose metabolism in DM1. In the future, it will be crucial to explore effective methods for harnessing CGM and assessing it quantitatively in DM1.

Development of a three-dimensional scoring model for the assessment of continuous glucose monitoring data in type 1 diabetes

INTRODUCTION

Despite the improvements in diabetes management by continuous glucose monitoring (CGM) it is difficult to capture the complexity of CGM data in one metric. We aimed to develop a clinically relevant multidimensional scoring model with the capacity to identify the most alarming CGM episodes and/or patients from a large cohort.

RESEARCH DESIGN AND METHODS

Retrospective CGM data from 2017 to 2020 available in electronic medical records were collected from n=613 individuals with type 1 diabetes (total 82 114 days). A scoring model was developed based on three metrics; glycemic variability percentage, low blood glucose index and high blood glucose index. Values for each dimension were normalized to a numeric score between 0-100. To identify the most representative score for an extended time period, multiple ways to combine the mean score of each dimension were evaluated. Correlations of the scoring model with CGM metrics were computed. The scoring model was compared with interpretations of a clinical expert board (CEB).

RESULTS

The dimension of hypoglycemia must be weighted to be representative, whereas the other two can be represented by their overall mean. The scoring model correlated well with established CGM metrics. Applying a score of ≥80 as the cut-off for identifying time periods with a 'true' target fulfillment (ie, reaching all targets for CGM metrics) resulted in an accuracy of 93.4% and a specificity of 97.1%. The accuracy of the scoring model when compared with the CEB was high for identifying the most alarming CGM curves within each dimension of glucose control (overall 86.5%).

CONCLUSIONS

Our scoring model captures the complexity of CGM data and can identify both the most alarming dimension of glycemia and the individuals in most urgent need of assistance. This could become a valuable tool for population management at diabetes clinics to enable healthcare providers to stratify care to the patients in greatest need of clinical attention.

Clinical significance of coefficient of variation in continuous glucose monitoring for glycemic management in children and adolescents with type 1 diabetes

AIMS/INTRODUCTION

Coefficient of variation (CV) is an indicator for glucose variability in continuous glucose monitoring (CGM), and the target threshold of %CV in type 1 diabetes is proposed to be ≤36%. This study aimed to evaluate the clinical significance of CV in children and adolescents with type 1 diabetes.

MATERIALS AND METHODS

Participants included 66 children with type 1 diabetes. A total of 48 participants were treated with multiple daily injections of insulin, and 18 with continues subcutaneous insulin infusion, using intermittently scanned CGM. The frequencies of the CGM metrics and glycosylated hemoglobin values were examined, and the significance of a threshold %CV of 36% was evaluated.

RESULTS

The mean frequencies in time in range (TIR), time below range, %CV and the mean glycosylated hemoglobin value were 59.3 ± 16.1, 4.0 ± 3.5, 39.3 ± 6.2 and 7.3 ± 0.8%, respectively. The frequencies of participants who achieved a TIR >70% and a %CV of ≤36% were 24.1 and 27.3%, respectively. A total of 18 participants with a %CV of ≤36% had significantly higher TIR, lower time below range and lower glycosylated hemoglobin than the 48 with a %CV of >36% (72.6 ± 12.6 vs 52.4 ± 13.6, 2.4 ± 1.9 vs 4.6 ± 3.6, 6.9 ± 0.8 vs 7.4 ± 0.7%, respectively).

CONCLUSIONS

Children and adolescents with type 1 diabetes using intermittently scanned CGM had difficulties in achieving the recommended targets of TIR and CV. However, the target %CV of ≤36% seems to be an appropriate indicator for assessing glycemic control and risk of hypoglycemia in pediatric patients with type 1 diabetes with any treatment.

Low-carbohydrate diet in children and young people with type 1 diabetes: A randomized controlled trial with cross-over design

AIMS

We investigated whether a short period of tightly controlled low-carbohydrate diet (LCD) leads to higher time in range without increasing the associated risks in children and young people with diabetes (CYPwD).

METHODS

Thirty-five (CYPwD) were recruited into this randomized controlled cross-over study (20 female; 20 CSII; age 14.5 ± 2.9 years; HbA1c 48.9 ± 9.4 mmol/mol). The interventions were five and five weeks of ready-made food box deliveries of isocaloric diets in random order: either LCD (94.5 ± 4.7 g/day) or recommended carbohydrate diet (RCD) (191 ± 19.2 g/day). The outcomes were continuous glucose monitoring parameters, anthropometric, laboratory and quality of life (QoL) data.

RESULTS

Time in range was significantly higher in the LCD than in the RCD period (77.1 % vs. 73.8 %, P=0.008). Times in hyperglycemia and average glycaemia were significantly lower in the LCD. There was no difference between the diets in time in hypoglycemia or glycemic variability. The subjects' body weight and BMI were significantly lower during the LCD. There was no significant difference in the LDL-cholesterol levels. No significant differences were observed in the self-assessed QoL.

CONCLUSIONS

Short-term LCD led to an improvement of glycemic parameters without increasing time in hypoglycemia, disturbing the lipid profile or negatively affecting the quality of life of CYPwD.

Neuropathy of diabetes following initiation of a low-carbohydrate diet: Case report

Introduction

This case study portrays an unusual case of treatment-induced neuropathy of diabetes (TIND) in a patient with uncontrolled type 2 diabetes (T2D) who achieved rapid improvement in glucose control primarily with dietary intervention. Initial presentation was 50-year-old white male with a long-standing history of obesity and a family history of T2D with a screening glucose level >500mg/dL by glucometer, HbA1c of 14.9%, and initial weight 213 lbs.

Methods

The initial intervention included a low-carbohydrate diet, metformin, and a continuous glucose monitor (CGM). Semaglutide was added after seven days.

Results

His glycemia was within the target range within three weeks. Four weeks after initiation of therapy, he developed TIND symptoms consisting of burning, tightness, and numbness of bilateral feet along with 10/10 pain. At three months, his HbA1c dropped to 6.9% and his weight to 195 lbs. Treatment of his TIND reduced his pain from 10/10 to 2/10.

Conclusion

Whereas TIND is commonly associated with the use of insulin or sulfonylureas, this study adds evidence to the paucity of literature regarding TIND precipitated by dietary intervention.

Diagnosis and Treatment of Hyperglycemia in Pregnancy: Type 2 Diabetes Mellitus and Gestational Diabetes

Hyperglycemia in pregnancy due to pre-existing Type 2 diabetes mellitus (T2DM) and gestational diabetes mellitus (GDM) is rising globally with increasing rates of risk factors for metabolic disease. This review summarizes current evidence and recommendations from national and international guidelines for diagnosis and management of T2DM and GDM to optimize maternal and neonatal outcomes.

Differences in glycemic trends due to reconstruction methods after proximal gastrectomy from the perspective of continuous glucose-monitoring

PURPOSE

In recent years, clinicians have focused on the importance of preventing hypoglycemia. We evaluated the impact of different reconstruction procedures after proximal gastrectomy on glycemic variability in non-diabetic patients with gastric cancer.

METHODS

This prospective observational study was conducted between April 2020 and March 2023. Flash continuous glucose-monitoring, a novel method for assessing glycemic control, was used to evaluate the glycemic profiles after gastrectomy. A flash continuous glucose-monitoring sensor was placed subcutaneously at the time of discharge, and glucose trends were evaluated for 2 weeks.

RESULTS

The anastomotic methods for proximal gastrectomy were esophagogastrostomy in 10 patients and double-tract reconstruction in 10 patients. The time below this range (glucose levels < 70 mg/dL) was significantly higher in the double-tract reconstruction group than in the esophagogastrostomy group (p = 0.049). A higher nocturnal time below this range was significantly correlated with an older age and double-tract reconstruction (p = 0.025 and p = 0.025, respectively).

CONCLUSION

These findings provide new insights into reconstruction methods after proximal gastrectomy by assessing postoperative hypoglycemia in non-diabetic patients with gastric cancer.

Use of Continuous Glucose Monitoring in Pump Therapy Sensor Augmented Pump or Automated Insulin Delivery in Different Age Groups (0.5 to <26 Years) With Type 1 Diabetes From 2018 to 2021: Analysis of the German/Austrian/Swiss/Luxemburg Diabetes Prospective Follow-up Database Registry

AIM

Insulin pump, continuous glucose monitoring (CGM), and sensor augmented pump (SAP) technology have evolved continuously leading to the development of automated insulin delivery (AID) systems. Evaluation of the use of diabetes technologies in people with T1D from January 2018 to December 2021.

METHODS

A patient registry (Diabetes Prospective Follow-up Database [DPV]) was analyzed for use of SAP (insulin pump + CGM ≥90 days, no automated dose adjustment) and AID (HCL or LGS/PLGS). In total 46,043 people with T1D aged 0.5 to <26 years treated in 416 diabetes centers (Germany, Austria, Luxemburg, and Switzerland) were included and stratified into 4 groups A-D according to age. Additionally, TiR and HbA1c were analyzed.

RESULTS

From 2018 to 2021, there was a significant increase from 28.7% to 32.9% (sensor augmented pump [SAP]) and 3.5% to 16.6% (AID) across all age groups, with the most frequent use in group A (<7 years, 38.8%-40.2% and 10.3%-28.5%). A similar increase in SAP and AID use was observed in groups B (7 to <11 years) and C (11 to <16 years): B: +15.8 PP, C: +15.9 PP. HbA1c improved significantly in groups C and D (16 to <26 years) (both P < .01). Time in range (TiR) increased in all groups (A: +3 PP; B: +5 PP; C: +5 PP; D: +5 PP; P < 0.01 for each group). Insulin pumps (61.0% versus 53.4% male) and SAP (33.5% versus 28.9% male) are used more frequently in females.

CONCLUSION

In recent years, we found an increasing use of new diabetes technologies and an improvement in metabolic control (TiR) across all age groups.

Characteristics of Nocturnal Hypoglycaemic Events and Their Impact on Glycaemia

BACKGROUND

Nocturnal hypoglycaemia is a burden for people with diabetes, particularly when treated with multiple daily injections (MDI) therapy. However, the characteristics of nocturnal hypoglycaemic events in this patient group are only poorly described in the literature.

METHOD

Continuous glucose monitoring (CGM) data from 185 study participants with type 1 diabetes using MDI therapy were collected under everyday conditions for up to 13 weeks. Hypoglycaemic events were identified as episodes of consecutive CGM readings <70 mg/dl or <54 mg/dl for at least 15 minutes. Subsequently, the time <54 mg/dl (TB54), time below range (TBR), time in range (TIR), time above range (TAR), glucose coefficient of variation (CV), and incidence of hypoglycaemic events were calculated for diurnal and nocturnal periods. Furthermore, the effect of nocturnal hypoglycaemic events on glucose levels the following day was assessed.

RESULTS

The incidence of hypoglycaemic events <70 mg/dl was significantly lower during the night compared to the day, with 0.8 and 3.8 events per week, respectively, while the TBR, TB54, and incidence of events with CGM readings <54 mg/dl was not significantly different. Nocturnal hypoglycaemic events <70 mg/dl were significantly longer (60 vs 35 minutes) and enveloped by less rapidly changing glucose levels. On days following nights containing hypoglycaemic events, there was a decrease in TAR, mean CGM glucose level and morning glucose levels and an increase in TB54, TBR, and CV.

CONCLUSIONS

The results showed that nocturnal hypoglycaemic events are a common occurrence in persons with type 1 diabetes using MDI with significant differences between the characteristics of nocturnal and diurnal events.

Highly Miniaturized, Low-Power CMOS ASIC Chip for Long-Term Continuous Glucose Monitoring

BACKGROUND

The objective of this work is to develop a highly miniaturized, low-power, biosensing platform for continuous glucose monitoring (CGM). This platform is based on an application-specific integrated circuit (ASIC) chip that interfaces with an amperometric glucose-sensing element. To reduce both size and power requirements, this custom ASIC chip was implemented using 65-nm complementary metal oxide semiconductor (CMOS) technology node. Interfacing this chip to a frequency-counting microprocessor with storage capabilities, a miniaturized transcutaneous CGM system can be constructed for small laboratory animals, with long battery life.

METHOD

A 0.45 mm × 1.12 mm custom ASIC chip was first designed and implemented using the Taiwan Semiconductor Manufacturing Company (TSMC) 65-nm CMOS technology node. This ASIC chip was then interfaced with a multi-layer amperometric glucose-sensing element and a frequency-counting microprocessor with storage capabilities. Variation in glucose levels generates a linear increase in frequency response of this ASIC chip. In vivo experiments were conducted in healthy Sprague Dawley rats.

RESULTS

This highly miniaturized, 65-nm custom ASIC chip has an overall power consumption of circa 36 µW. In vitro testing shows that this ASIC chip produces a linear (R2 = 99.5) frequency response to varying glucose levels (from 2 to 25 mM), with a sensitivity of 1278 Hz/mM. In vivo testing in unrestrained healthy rats demonstrated long-term CGM (six days/per charge) with rapid glucose response to glycemic variations induced by isoflurane anesthesia and tail vein injection.

CONCLUSIONS

The miniature footprint of the biosensor platform, together with its low-power consumption, renders this CMOS ASIC chip a versatile platform for a variety of highly miniaturized devices, intended to improve the quality of life of patients with type 1 and type 2 diabetes.

Advanced Hybrid Closed Loop in Adult Population With Type 1 Diabetes: A Substudy From the ADAPT Randomized Controlled Trial in Users of Real-Time Continuous Glucose Monitoring

BACKGROUND

This analysis reports the findings from a predefined exploratory cohort (cohort B) from the ADAPT (ADvanced Hybrid Closed Loop Study in Adult Population with Type 1 Diabetes) study. Adults with type 1 diabetes (T1D) with suboptimal glucose control were randomly allocated to an advanced hybrid closed-loop (AHCL) system or multiple daily injections of insulin (MDI) plus real-time continuous glucose monitoring (RT-CGM).

METHODS

In this prospective, multicenter, exploratory, open-label, randomized controlled trial, 13 participants using MDI + RT-CGM and with HbA1c ≥8.0% were randomized to switch to AHCL (n = 8) or continue with MDI + RT-CGM (n = 5) for six months. Prespecified endpoints included the between-group difference in mean change from baseline in HbA1c, CGM-derived measures of glycemic control, and safety.

RESULTS

The mean HbA1c level decreased by 1.70 percentage points in the AHCL group versus a 0.60 percentage point decrease in the MDI + RT-CGM group, with a model-based treatment effect of -1.08 percentage points (95% confidence interval [CI] = -2.17 to 0.00 percentage points; P = .0508) in favor of AHCL. The percentage of time spent with sensor glucose levels between 70 and 180 mg/dL in the study phase was 73.6% in the AHCL group and 46.4% in the MDI + RT-CGM group; model-based between-group difference of 28.8 percentage points (95% CI = 12.3 to 45.3 percentage points; P = .0035). No diabetic ketoacidosis or severe hypoglycemia occurred in either group.

CONCLUSIONS

In people with T1D with HbA1c ≥8.0%, the use of AHCL resulted in improved glycemic control relative to MDI + RT-CGM. The scale of improvement suggests that AHCL should be considered as an option for people not achieving good glycemic control on MDI + RT-CGM.

Adolescent-Preferred financial incentives to promote type 1 diabetes Self-Care: A discrete choice experiment

AIMS

This study aimed to quantify preferences for the characteristics of a financial incentives program that would motivate adolescent engagement in type 1 diabetes (T1D) self-care.

METHOD

We performed a discrete choice experiment with 12-18 year-olds with T1D from two pediatric hospital endocrinology clinics (n = 317). We identified key attributes of incentives: (1) monthly value of the reward, (2) payment structure, and (3) difficulty of incentivized behaviors. In twelve choice questions, adolescents chose the incentive option from a pair of profiles that was more likely to motivate them to increase adherence to recommended self-care. Options presented were tailored to adolescents' T1D technology use and perceived difficulty of completing each behavior. We analyzed data using a conditional logit model.

RESULTS

The value of the reward accounted for 60.8% of preferences. Adolescents were willing to accept lower value rewards when incentive payments used positive vs. negative reinforcement (-$10.88 (95% CI: -$12.60, -9.24)) and preferred higher incentives for performing hard vs. easier behaviors (+$14.92 (95% CI: +$12.66, +$17.28)).

CONCLUSIONS

Stated preferences can inform intervention design. Future research will evaluate the external validity of the discrete choice experiment-informed intervention design by assessing adolescent health and behavioral outcomes in a randomized controlled trial.

Newer Outpatient Diabetes Therapies and Technologies

New diabetes drugs such as glucagon-like peptide-1 receptor agonists (GLP-1 RAs) and glucose-dependent insulinotropic peptide/GLP-1 RAs have emerged to show hemoglobin A1c (HbA1c) reduction, weight loss, and cardiovascular benefits. Similarly, sodium-glucose cotransporter 2 inhibitors' benefits span from HbA1c decrease to cardiovascular and renoprotective effects. Diabetes technology has expanded to include type 2 diabetes mellitus, with literature supporting its use in T2DM on any insulin regimen. Connected insulin pens and insulin delivery devices have opened new solutions to insulin users and automated insulin delivery systems have become the standard of care therapy for type 1 diabetes mellitus.

Extended-Release Versus Immediate-Release Triamcinolone Acetonide in Patients Who Have Knee Osteoarthritis and Type 2 Diabetes Mellitus

BACKGROUND

Intra-articular corticosteroid injections may cause hyperglycemia (glucose level >180 mg/dL). In a phase 2 study of 33 patients who had osteoarthritis of the knee and type 2 diabetes mellitus, triamcinolone acetonide extended-release (TA-ER) was associated with minimal glycemic control disruption compared with triamcinolone acetonide immediate-release (TA-IR). This post hoc analysis characterizes the clinical relevance of these results.

METHODS

Patients who had symptomatic osteoarthritis of the knee for ≥6 months, type 2 diabetes mellitus for ≥1 year, and hemoglobin A1c ≥6.5 and ≤9.0% were randomized to receive an intra-articular injection of either TA-ER or TA-IR. Changes in continuous glucose monitor daily glucose level, percentage of time in or above the target glucose range (>70 to 180 mg/dL), time to glucose level 250 mg/dL and maximum glucose level >250 mg/dL, and glycemic variability were evaluated.

RESULTS

Across postinjection days 1 to 3, the TA-ER group (n = 18) had a lower median change from baseline in maximum glucose level (92.3 versus 169.1 mg/dL), a reduced percentage of time with a glucose level >250 mg/dL (12 versus 26%), a smaller proportion of patients who had a maximum glucose level >250 mg/dL (50 versus 93%), and a greater percentage of time in the target glucose range (62 versus 48%) versus the TA-IR group (n = 15). There was less glycemic variability and lower glucose spikes in the TA-ER versus TA-IR group. Median times to glucose level 250 mg/dL (44 versus 6 hours) and maximum glucose level (34 versus 13 hours) were significantly longer in the TA-ER versus TA-IR group.

CONCLUSIONS

Use of TA-ER was associated with a clinically meaningful reduction in hyperglycemia versus TA-IR.

Glycemia Risk Index Assessment in a Pediatric and Adult Patient Cohort With Type 1 Diabetes Mellitus

BACKGROUND

To evaluate the glycemia risk index (GRI) as a new glucometry in pediatric and adult populations with type 1 diabetes (T1D) in clinical practice.

METHODS

A cross-sectional study of 202 patients with T1D receiving intensive treatment with insulin (25.2% continuous subcutaneous insulin infusion [CSII]) and intermittent scanning (flash) glucose monitoring (isCGM). Clinical and glucometric isCGM data were collected, as well as the component of hypoglycemia (CHypo) and component of hyperglycemia (CHyper) of the GRI.

RESULTS

A total of 202 patients (53% males and 67.8% adults) with a mean age of 28.6 ± 15.7 years and 12.5 ± 10.9 years of T1D evolution were evaluated.Adult patients (>19 years) presented higher glycated hemoglobin (HbA1c) (7.4 ± 1.1 vs 6.7 ± 0.6%; P < .01) and lower time in range (TIR) (55.4 ± 17.5 vs 66.5 ± 13.1%; P < .01) values than the pediatric population, with lower coefficient of variation (CV) (38.6 ± 7.2 vs 42.4 ± 8.9%; P < .05). The GRI was significantly lower in pediatric patients (48.0 ± 22.2 vs 56.8 ± 23.4; P < .05) associated with higher CHypo (7.1 ± 5.1 vs 5.0 ± 4.5; P < .01) and lower CHyper (16.8 ± 9.8 vs 26.5 ± 15.1; P < .01) than in adults.When analyzing treatment with CSII compared with multiple doses of insulin (MDI), a nonsignificant trend to a lower GRI was observed in CSII (51.0 ± 15.3 vs 55.0 ± 25.4; P= .162), with higher levels of CHypo (6.5 ± 4.1 vs 5.4 ± 5.0; P < .01) and lower CHyper (19.6 ± 10.6 vs 24.6 ± 15.2; P < .05) compared with MDI.

CONCLUSIONS

In pediatric patients and in those with CSII treatment, despite a better control by classical and GRI parameters, higher overall CHypo was observed than in adults and MDI, respectively. The present study supports the usefulness of the GRI as a new glucometric parameter to evaluate the global risk of hypoglycemia-hyperglycemia in both pediatric and adult patients with T1D.

Design of a Real-Time Physical Activity Detection and Classification Framework for Individuals With Type 1 Diabetes

BACKGROUND

Managing glycemia during and after exercise events in type 1 diabetes (T1D) is challenging since these events can have wide-ranging effects on glycemia depending on the event timing, type, intensity. To this end, advanced physical activity-informed technologies can be beneficial for improving glucose control.

METHODS

We propose a real-time physical activity detection and classification framework, which builds upon random forest models. This module automatically detects exercise sessions and predicts the activity type and intensity from tri-axial accelerometer, heart rate, and continuous glucose monitoring records.

RESULTS

Data from 19 adults with T1D who performed structured sessions of either aerobic, resistance, or high-intensity interval exercise at varying times of day were used to train and test this framework. The exercise onset and completion were both predicted within 1 minute with an average accuracy of 81% and 78%, respectively. Activity type and intensity were identified within 2.38 minutes and from the exercise onset. On participants assigned to the test set, the average accuracy for activity type and intensity classification was 74% and 73%, respectively, if exercise was announced. For unannounced exercise events, the classification accuracy was 65% for the activity type and 70% for its intensity.

CONCLUSIONS

The proposed module showed high performance in detection and classification of exercise in real-time within a minute of exercise onset. Integration of this module into insulin therapy decisions can help facilitate glucose management around physical activity.

Performance of Continuous Glucose Monitoring in Patients With Acute Respiratory Failure: A Prospective, Single-Center Observational Study

OBJECTIVE

Continuous glucose monitoring (CGM) may have benefits in achieving glycemic control in critically ill patients. The aim of this study was to assess the accuracy of the Freestyle Libre H (professional version similar to the Libre Pro) in patients with acute respiratory failure (ARF) in the intensive care unit (ICU).

METHODS

Fifty-two adult patients with ARF were selected. The performance of CGM was evaluated using the arterial blood glucose (aBG) and point-of-care (POC) glucose levels as the reference values. Numerical accuracy was evaluated by the mean absolute relative difference, Bland-Altman analysis, %15/15 (the percentage of CGM values within 15 mg/dL or 15% of reference values <100 or >100 mg/dL, respectively), %20/20, and %30/30. Clinical accuracy was assessed using the Clarke error grid analysis.

RESULTS

A total of 519 and 1504 pairs of aBG/CGM and POC/CGM glucose values were analyzed. The mean absolute relative difference values were 13.8% and 14.7%, respectively. The mean deviations of the Bland-Altman analysis were 0.82 mmol/L and 0.81 mmol/L. The proportions of CGM values within %15/15, %20/20, and %30/30 of the aBG values were 62.6%, 75.5%, and 92.4%, respectively; those within %15/15, %20/20, and %30/30 of the POC values were 57.1%, 72.9%, and 88.7%, respectively. The Clarke error grid analysis showed that 97.8% and 99.3% of the values were located in zone A + B. Additionally, the accuracy of CGM was not affected by general patient factors.

CONCLUSION

This study demonstrated that the accuracy of CGM in patients with ARF is lower than that in most outpatients and it is not affected by general patient factors. Whether CGM is beneficial to glucose management in the intensive care unit needs further evaluation.

An automated insulin delivery system from pregestational care to postpartum in women with type 1 diabetes. Preliminary experience with telemedicine in 6 patients

INTRODUCTION

The use of most commercially available automated insulin delivery (AID) systems is off-label in pregnancy. However, an increasing number of women with type 1 diabetes (T1D) use such devices throughout pregnancy and delivery. We analysed the data of six women with T1D from a single centre (Diabetology Outpatient Clinic of District-63/Asl Salerno, Italy) who were able to start and maintain AID therapy with the MiniMed™ 780G (Medtronic, Minneapolis, MN, USA) throughout the pregestational care period, pregnancy, delivery, and postpartum.

METHODS

We retrospectively collected data from six patients with T1D who received training and initiation on use of the MiniMed™ 780G and attended follow-up visits throughout pregnancy (these visits were virtual because of the COVID-19 pandemic). All patients maintained their devices in the closed-loop setting throughout pregnancy and during labour and delivery. We analysed data from the pregestational phase to the first 30 days postpartum.

RESULTS

All patients achieved the recommended metabolic goals before conception [median time in range (TIR) of 88% for 70-180 mg/dL; median pregnancy-specific TIR 63-140 mg/dL (ps-TIR) of 66% and maintained the ps-TIR until delivery (median ps-TIR 83%). All patients had slightly better metrics during the night than during the day, with a very low time below range of < 63 mg/dL. Optimal glycaemic values were also maintained on the day of labour and delivery (median ps-TIR 92.5%) and in the first 30 days postpartum, with no severe hypoglycaemia. The only neonatal complications were jaundice in one child and an interatrial defect in another child.

CONCLUSION

In our well-selected and trained patients, use of the MiniMed™ 780G helped to achieve and maintain ps-metrics from the pregestational period to delivery despite the fact that the algorithm is not set to achieve the ambitious glycaemic values recommended for pregnancy.

Innovative solution or cause for concern? The use of continuous glucose monitors in people not living with diabetes: A narrative review

AIMS

Continuous glucose monitors (CGMs) have expanded their scope beyond indicated uses for diabetes management and are gaining traction among people not living with diabetes (PNLD). CGMs track in time glucose levels and are proposed as tools for the early detection of abnormal glucose and a potential solution for its normalisation through behavioural change, particularly, diet personalisation and motivation of physical activity. This becomes relevance given the growing incidence of metabolic conditions, such as type 2 diabetes mellitus (T2DM). Clinical guidelines, however, do not recommend CGMs in contexts outside type 1 diabetes (T1DM) or insulin-treated T2DM. Therefore, there is a visible disconnect between the indicated and real-world usage of these medical devices. While the commercial market for CGMs in PNLD is expanding rapidly, a comprehensive and evidence-based evaluation of the devices' utility in this population has not been done. Therefore, this review aims to formulate a working model for CGM utility in PNLD as proposed by the 'health and wellness' market that advertises and distributes it to these individuals.

METHODS

We aim to critically analyse the available research addressing components of the working model, that is (1) detection of abnormal glucose; (2) behavioural change, and (3) metabolic health improvement.

RESULTS

We find a lack of consistent and high-quality evidence to support the utility of CGMs for these purposes. We identify significantly under-reserved areas including clinical benchmarks and scoring procedures for CGM measures, device acceptability, and potential adverse effects of CGMs on eating habits in PNLD. We also raise concerns about the robustness of available CGM research.

CONCLUSION

In the face of these research gaps, we urge for the commercial claims suggesting the utility of the device in PNLD to be labelled as misleading. We argue that there is a regulatory inadequacy that fuels 'off-label' CGM distribution and calls for the strengthening of post-market clinical follow-up oversight for CGMs. We hope this will help to avert the continued misinformation risk to PNLD and 'off-label' exacerbation of health disparities.

Effectiveness of the flash glucose monitoring system in preventing severe hypoglycemic episodes and in improving glucose metrics and quality of life in subjects with type 1 diabetes at high risk of acute diabetes complications

AIMS

To assess the effectiveness of the intermittent-scanned continuous glucose monitoring (isCGM) system in preventing severe hypoglycemic episodes and in improving glucose parameters and quality of life.

METHODS

Four hundred T1D individuals were enrolled in a prospective real-word study with an intermittently scanned continuous glucose monitoring device during the 12-months follow-up. The primary endpoint was the incidence of severe hypoglycemic events.

RESULTS

82% of subjects were naïve to the use of the device (group A) and 18% were already wearing the system (group B). The cumulative incidence of severe hypoglycemia (SH) at 12 months was 12.06 per 100 person-year (95% CI: 8.35-16.85) in group A and 10.14 (95% CI: 4.08-20.90) in group B without inter-group differences. In group A there was a significant decrease in SH at 12 months compared to 3 months period (p = 0.005). Time in glucose range significantly increased in both groups accompanied with a significant decrease in glucose variability. HbA1c showed a progressive significant time-dependent decrease in group A. The use of the device significantly improved the perceived quality of life.

CONCLUSION

This study confirmed the effectiveness of the isCGM in reducing hypoglycemic risk without glucose deterioration, with potential benefits on adverse outcomes in T1D individuals.

TRIAL REGISTRATION

ClinicalTrials.gov registration no. NCT04060732.

Updates in the Management of Type 1 Diabetes in Pregnancy

The care of pregnant individuals with type 1 diabetes mellitus has experienced significant advancements in recent years. Preconception counseling has re-emerged as a core dimension of management. Continuous glucose monitoring plays an increasingly useful and beneficial role in gestational glycemic monitoring, a practice informed by improved maternofetal outcomes. While studies have not shown that continuous subcutaneous insulin infusion is superior to multiple daily injections of insulin for glycemic control, recent work has signaled that hybrid closed-loop systems with pregnancy-specific targets could meaningfully improve glycemic control and potentially ameliorate maternofetal outcomes while reducing self-care burden.

Evaluation of folliculogenesis and oxidative stress parameters in type 1 diabetes mellitus women with different glycemic profiles

BACKGROUND

Despite enormous advances in diabetes treatment, women with type 1 diabetes mellitus (DM) still experience delayed menarche, menstrual irregularities, fewer pregnancies, and a higher rate of stillbirths compared to women without the disease. Due to the fact that type 1 DM occurs at a young age, the preservation of reproductive health is one of the most important goals of treatment.

AIMS

The aim of this study was to evaluate the relationship between different glycemic profiles and changes in the pro-oxidant-antioxidant balance and ovarian follicular apparatus in reproductive-age patients with type 1 DM.

METHODS

We examined 50 reproductive-age (19-38 years) women with type 1 DM with a disease duration of at least ten years. Carbohydrate metabolism was assessed with the continuous glucose monitoring (CGM) system and glycated hemoglobin (HbA1c) concentration measurement. CGM was performed using the FreeStyle Libre flash glucose monitoring system (Abbott Diabetes Care, Witney, UK). In each patient, malondialdehyde level, catalase activity and 3-nitrotyrosine level in the blood serum were determined. To assess the ovarian function, we measured the ovarian volume, the antral follicle count, and the serum levels of anti-Müllerian hormone and follicle-stimulating hormone. All patients were divided into four groups (glucotypes) based on the CGM results. Group 1 included type 1 DM patients with satisfactory compensation of carbohydrate metabolism; group 2 consisted of patients with frequent hypoglycemic conditions and pathological glucose variability; group 3 included individuals with prolonged hyperglycemic conditions and maximum HbA1c levels; and group 4 comprised patients with the glycemic profile characterized by all the presented types of dysglycemia (intermittent glycemia).

RESULTS

We revealed a negative correlation between serum catalase activity and time of hypoglycemic conditions in patients with type 1 DM based on the CGM results (rs = -0.47, p < 0.01). In group 4 (intermittent glycemia), patients demonstrated the lowest serum catalase activity and increased serum 3-nitrotyrosine level, while in group 3, women with chronic hyperglycemia (HbA1c 8.4 [8.1; 9.9]%; 68 [65; 85] mmol/mol) had a moderate change in antioxidant defense and oxidative stress parameters. Correlation analysis of ovarian volume, the antral follicle count, and the serum anti-Müllerian hormone level in type 1 DM women with different glycemic profiles established a negative relationship (rs = -0.82, p < 0.05) between the antral follicle count and glucose variability in group 1, a positive relationship (rs = 0.68, p < 0.05) between ovarian volume and glucose variability in group 2, and a positive relationship (rs = 0.88, p < 0.05) between ovarian volume and time of hypoglycemic conditions, which, according to the CGM results, amounted to a critical value of 57.5 [40.0; 82.0]%.

CONCLUSIONS

The data obtained indicate the relationship between the ovarian volume, serum anti-Müllerian hormone level, the antral follicle count and oxidative stress parameters not only in patients with hyperglycemia, but also in those with hypoglycemic conditions, as well as with pathological glucose variability.

Useful of proximal gastrectomy with double-tract reconstruction in preventing glucose spikes

BACKGROUND

Volatile glucose levels after gastrectomy induce dumping syndrome, which adversely affects patient quality of life. This study aimed to evaluate the glycemic variability of proximal gastrectomy with double-tract reconstruction (PGDTR) as a function-preserving procedure.

METHODS

This study used a continuous glucose monitoring (CGM) system to record glycemic profiles of patients who underwent PGDTR or total gastrectomy (TG) and compared them. Moreover, this study evaluated postgastrectomy syndrome, including dumping symptoms, between the PGDTR and TG groups using the 37-item Postgastrectomy Syndrome Assessment Scale (PGSAS-37) questionnaire.

RESULTS

Of note, 44 patients underwent PGDTR, and 42 patients underwent TG, which included more advanced cases. CGM results showed that the SD, relative SD, and maximum drop in glucose level between 30 min and 2 h after a meal were smaller in the PGDTR group than in the TG group (14.81 vs 22.40 mg/dL [P < .001], 0.14 vs 0.20 mg/dL [P < .001], and 42.06 vs 117.67 mg/dL [P < .001], respectively). For nocturnal glucose levels, SD and percentage time below the range were smaller in the PGDTR group than in the TG group (11.76 vs 15.16 mg/dL [P = .005] and 11.25% vs 35.27% [P < .001]). The PGDTR group generally performed better than the TG group on all the PGSAS-37 questionnaire items. Patients in the PGDTR group without food inflow into the remnant stomach showed similar CGM results as those in the TG group but with stronger dumping symptoms.

CONCLUSION

Food inflow into the remnant stomach is essential for PGDTR to be a function-preserving procedure as it leads to the control of dumping symptoms and lower glucose level spikes.

Diabetes Technology Meeting 2023

Diabetes Technology Society hosted its annual Diabetes Technology Meeting from November 1 to November 4, 2023. Meeting topics included digital health; metrics of glycemia; the integration of glucose and insulin data into the electronic health record; technologies for insulin pumps, blood glucose monitors, and continuous glucose monitors; diabetes drugs and analytes; skin physiology; regulation of diabetes devices and drugs; and data science, artificial intelligence, and machine learning. A live demonstration of a personalized carbohydrate dispenser for people with diabetes was presented.

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.

AGATA: A Toolbox for Automated Glucose Data Analysis

BACKGROUND

Analyzing continuous glucose monitoring (CGM) data is a mandatory step for multiple purposes spanning from reporting clinical trial outcomes to developing new algorithms for diabetes management. This task is repetitive, and scientists struggle in computing literature glucose control metrics and waste time in reproducing possibly complex plots and reports. For this reason, to provide the diabetes technology community a unified tool, here we present Automated Glucose dATa Analysis (AGATA), an automated glucose data analysis toolbox developed in MATLAB/Octave.

METHODS

Automated Glucose dATa Analysis is an open-source software program to visualize and preprocess CGM data, compute glucose control metrics, detect adverse events, evaluate the effectiveness of users' prediction algorithms, and compare study arms. Automated Glucose dATa Analysis can be used as a standalone computer application accessible through a dedicated graphical user interface, particularly suitable for clinicians, or by integrating its functionalities in user-defined MATLAB/Octave scripts, which fits the need of researchers and developers. To demonstrate its features, we used AGATA to analyze CGM data of two subjects extracted from a publicly available data set of individuals with type one diabetes. Finally, AGATA's features are compared against those of 12 noncommercial software programs for CGM data analysis.

RESULTS

Using AGATA, we easily preprocessed, analyzed, and visualized CGM data in a handy way, in compliance with the requirements and the standards defined in the literature. Compared to the other considered software programs, AGATA offers more functionalities and capabilities.

CONCLUSION

Automated Glucose dATa Analysis is easy to use and reduces the burden of CGM data analysis. It is freely available in GitHub at https://github.com/gcappon/agata.

Impact of an Advanced Hybrid Closed-Loop System on Glycemic Control Throughout the Menstrual Cycle in Women with Type 1 Diabetes Prone to Hypoglycemia

This study aimed to evaluate the impact of advanced hybrid closed loop (AHCL) on glycemic control throughout the menstrual cycle (MC) in women with type 1 diabetes. We included 39 pairs of spontaneous MCs from 13 participants, before and after switching from sensor-augmented pump to AHCL. Baseline time below range <70 mg/dL (TBR <70) was significantly higher during the midfollicular phase than during late luteal phase (5.7% ± 5.0% vs. 4.1% ± 3.0%), but similar time in range 70-180 mg/dL (TIR) was observed throughout the MC. After switching to AHCL, a reduction in TBR <70 and an increase in TIR were observed in all phases. Phase-dependent changes in insulin infusion were detected and pre-existing differences in TBR <70 were eradicated (3.5% ± 3.2% vs. 3.0% ± 3.0%). However, TIR became significantly higher during the early follicular phase than during the late luteal phase (79.1% ± 9.3% vs. 74.5% ± 10.0%). In conclusion, AHCL improved glycemic control throughout the MC, but performance differed according to phase.

Predicting Glucose Values: A New Era for Continuous Glucose Monitoring

The last 25 years of CGM have been characterized above all by providing better and more accurate glucose values in real time and analyzing the measured glucose values. Trend arrows are the only way to look into the future, but they are often too imprecise for therapy adjustment. While AID systems provide algorithms to use glucose values for glucose control, this has not been possible with stand-alone CGM systems, which are most used by people with diabetes. By analyzing the measured values with algorithms, often supported by AI, this should be possible in the future. This provides the user with important information about the further course of the glucose level, such as during the night. Predictive approaches can be used by next-generation CGM systems. These systems can proactively prevent glucose events such as hypo- or hyperglycemia. With the Accu-Chek® SmartGuide Predict app, an integral part of a novel CGM system, and the Glucose Predict (GP) feature, people with diabetes have the first commercially available CGM system with predictive algorithms. It characterizes the CGM systems of the future, which not only analyze past values and current glucose values in the future, but also use these values to predict future glucose progression.

Glycemic Risk Index Profiles and Predictors Among Diverse Adults With Type 1 Diabetes

BACKGROUND

The Glycemia Risk Index (GRI) was introduced as a single value derived from the ambulatory glucose profile that identifies patients who need attention. This study describes participants in each of the five GRI zones and examines the percentage of variation in GRI scores that is explained by sociodemographic and clinical variables among diverse adults with type 1 diabetes.

METHODS

A total of 159 participants provided blinded continuous glucose monitoring (CGM) data over 14 days (mean age [SD] = 41.4 [14.5] years; female = 54.1%, Hispanic = 41.5%). Glycemia Risk Index zones were compared on CGM, sociodemographic, and clinical variables. Shapley value analysis examined the percentage of variation in GRI scores explained by different variables. Receiver operating characteristic curves examined GRI cutoffs for those more likely to have experienced ketoacidosis or severe hypoglycemia.

RESULTS

Mean glucose and variability, time in range, and percentage of time in high, and very high, glucose ranges differed across the five GRI zones (P values < .001). Multiple sociodemographic indices also differed across zones, including education level, race/ethnicity, age, and insurance status. Sociodemographic and clinical variables collectively explained 62.2% of variance in GRI scores. A GRI score ≥84.5 reflected greater likelihood of ketoacidosis (area under the curve [AUC] = 0.848), and scores ≥58.2 reflected greater likelihood of severe hypoglycemia (AUC = 0.729) over the previous six months.

CONCLUSIONS

Results support the use of the GRI, with GRI zones identifying those in need of clinical attention. Findings highlight the need to address health inequities. Treatment differences associated with the GRI also suggest behavioral and clinical interventions including starting individuals on CGM or automated insulin delivery systems.

Real-world glycaemic outcomes of automated insulin delivery in type 1 diabetes: A meta-analysis

AIM

To evaluate the real-world effectiveness of automated insulin delivery (AID) systems in patients with type 1 diabetes (T1D).

MATERIALS AND METHODS

PubMed, Embase, the Cochrane Library, and ClinicalTrials.gov were searched for studies published up until 2 March 2024. We included pragmatic randomized controlled trials (RCTs), cohort studies, and before-after studies that compared AID systems with conventional insulin therapy in real-world settings and reported continuous glucose monitoring outcomes. Percent time in range (TIR; 3.9-10 mmol/L), time below range (TBR; <3.9 mmol/L), time above range (TAR; >10 mmol/L), and glycated haemoglobin (HbA1c) level were extracted. Data were summarized as mean differences (MDs) with 95% confidence interval.

RESULTS

A total of 23 before-after studies (101 704 participants) were included in the meta-analysis. AID systems were associated with an increased percentage of TIR (11.61%, 10.47 to 12.76; p < 0.001). The favourable effect of AID systems was consistently observed when used continuously for 6 (11.76%) or 12 months (11.33%), and in both children (12.16%) and adults (11.04%). AID systems also showed favourable effects on TBR (-0.53%, -0.63 to -0.42), TAR (-9.65%, -10.63 to -8.67) and HbA1c level (-0.42%, -0.47 to -0.37) when compared with previous treatments.

CONCLUSIONS

Similar improvements in glycaemic parameters were observed in real-world settings in RCTs using AID systems in T1D. AID systems benefit both children and adults by increasing TIR for both short- and long-term interventions.

Two-week continuous glucose monitoring-derived metrics and degree of hepatic steatosis: a cross-sectional study among Chinese middle-aged and elderly participants

BACKGROUND

Continuous glucose monitoring (CGM) devices provide detailed information on daily glucose control and glycemic variability. Yet limited population-based studies have explored the association between CGM metrics and fatty liver. We aimed to investigate the associations of CGM metrics with the degree of hepatic steatosis.

METHODS

This cross-sectional study included 1180 participants from the Guangzhou Nutrition and Health Study. CGM metrics, covering mean glucose level, glycemic variability, and in-range measures, were separately processed for all-day, nighttime, and daytime periods. Hepatic steatosis degree (healthy: n = 698; mild steatosis: n = 242; moderate/severe steatosis: n = 240) was determined by magnetic resonance imaging proton density fat fraction. Multivariate ordinal logistic regression models were conducted to estimate the associations between CGM metrics and steatosis degree. Machine learning models were employed to evaluate the predictive performance of CGM metrics for steatosis degree.

RESULTS

Mean blood glucose, coefficient of variation (CV) of glucose, mean amplitude of glucose excursions (MAGE), and mean of daily differences (MODD) were positively associated with steatosis degree, with corresponding odds ratios (ORs) and 95% confidence intervals (CIs) of 1.35 (1.17, 1.56), 1.21 (1.06, 1.39), 1.37 (1.19, 1.57), and 1.35 (1.17, 1.56) during all-day period. Notably, lower daytime time in range (TIR) and higher nighttime TIR were associated with higher steatosis degree, with ORs (95% CIs) of 0.83 (0.73, 0.95) and 1.16 (1.00, 1.33), respectively. For moderate/severe steatosis (vs. healthy) prediction, the average area under the receiver operating characteristic curves were higher for the nighttime (0.69) and daytime (0.66) metrics than that of all-day metrics (0.63, P < 0.001 for all comparisons). The model combining both nighttime and daytime metrics achieved the highest predictive capacity (0.73), with nighttime MODD emerging as the most important predictor.

CONCLUSIONS

Higher CGM-derived mean glucose and glycemic variability were linked with higher steatosis degree. CGM-derived metrics during nighttime and daytime provided distinct and complementary insights into hepatic steatosis.

Continuous glucose monitoring metrics in people with liver glycogen storage disease and idiopathic ketotic hypoglycemia: A single-center, retrospective, observational study

BACKGROUND

Cohort data on continuous glucose monitoring (CGM) metrics are scarce for liver glycogen storage diseases (GSDs) and idiopathic ketotic hypoglycemia (IKH). The aim of this study was to retrospectively describe CGM metrics for people with liver GSDs and IKH.

PATIENTS AND METHODS

CGM metrics (descriptive, glycemic variation and glycemic control parameters) were calculated for 47 liver GSD and 14 IKH patients, categorized in cohorts by disease subtype, age and treatment status, and compared to published age-matched CGM metrics from healthy individuals. Glycemic control was assessed as time-in-range (TIR; ≥3.9 - ≤7.8 and ≥3.9 - ≤10.0 mmol/L), time-below-range (TBR; <3.0 mmol/L and ≥3.0 - ≤3.9 mmol/L), and time-above-range (TAR; >7.8 and >10.0 mmol/L).

RESULTS

Despite all patients receiving dietary treatment, GSD cohorts displayed significantly different CGM metrics compared to healthy individuals. Decreased TIR together with increased TAR were noted in GSD I, GSD III, and GSD XI (Fanconi-Bickel syndrome) cohorts (all p < 0.05). In addition, all GSD I cohorts showed increased TBR (all p < 0.05). In GSD IV an increased TBR (p < 0.05) and decreased TAR were noted (p < 0.05). In GSD IX only increased TAR was observed (p < 0.05). IKH patient cohorts, both with and without treatment, presented CGM metrics similar to healthy individuals.

CONCLUSION

Despite dietary treatment, most liver GSD cohorts do not achieve CGM metrics comparable to healthy individuals. International recommendations on the use of CGM and clinical targets for CGM metrics in liver GSD patients are warranted, both for patient care and clinical trials.

EXTOD-Immune: a randomised controlled trial to investigate whether a remotely monitored, home-based exercise intervention can reduce disease activity in people with type 1 diabetes

Type 1 diabetes (T1D) is a chronic autoimmune disease in which the adaptive immune system targets insulin-producing β-cells of pancreatic islets, leading to dependence on exogenous insulin therapy. Cytotoxic (CD8+) T-cells specific for islet antigens are major players in T1D autoimmunity. Data indicate that regular exercise may preserve β-cell function in people recently diagnosed with T1D, but the role of islet-reactive CD8+ T-cells is unclear. In a randomised crossover design, this study will determine the impact of a 12-week exercise programme on the frequency and proliferative state of islet-reactive CD8+ T-cells in the peripheral blood of 20 adults diagnosed with T1D within the past 3 years. The exercise intervention will consist of three high-intensity interval training sessions per week (6-10 1 min intervals >80% maximum heart rate, with 1 min rest), the duration of which will incrementally increase from 14 to 22 min. Habitual physical activity and diet will be maintained during control and washout periods. At weeks 0, 12, 24 and 36, a fasting blood sample will be collected to quantify the frequency, phenotype and proliferative activity of islet-reactive CD8+ T-cells (primary outcome) and various clinical parameters. Glycaemic control will also be evaluated using 14-day continuous glucose monitoring at the start and end of each study arm. Findings may provide a rationale for conducting large-scale trials to evaluate the implementation of exercise into routine clinical care, particularly for people recently diagnosed with T1D when maintenance of β-cell function is critical to counteract disease progression. Trial registration number: ISRCTN79006041.

Analysis of Glucose Responsive Glucagon Therapeutics using Computational Models of the Glucoregulatory System

Glucose-responsive glucagon (GRG) therapeutics are a promising technology for reducing the risk of severe hypoglycemia as a complication of diabetes mellitus. Herein, the performance of candidate GRGs in the literature by modeling the kinetics of activation and connecting them as input into physiological glucoregulatory models is evaluated and projected the two distinct GRG designs, experimental results reported in Wu et al. (GRG-I) and Webber et al. (GRG-II) is considered. Both are evaluated using a multi-compartmental glucoregulatory model (IMPACT) and used to compare in-vivo experimental data of therapeutic performance in rats and mice. For GRG-I and GRG-II, the total integrated glucose material balances are overestimated by 41.5% ± 14% and underestimated by 24.8% ± 16% compared to in-vivo time-course data, respectively. These large differences to the relatively simple computational descriptions of glucagon dynamics in the model, which underscores the urgent need for improved glucagon models is attributed. Additionally, therapeutic insulin and glucagon infusion pumps are modeled for type 1 diabetes mellitus (T1DM) human subjects to extend the results to additional datasets. These observations suggest that both the representative physiological and non-physiological models considered in this work require additional refinement to successfully describe clinical data that involve simultaneous, coupled insulin, glucose, and glucagon dynamics.

Integrated Strategies to Support Diabetes Technology in Pregnancy

Managing diabetes in pregnancy can be overwhelming, with numerous dramatic physiologic changes taking place that require constant diligence and attention. Advances in diabetes technology have improved glycemic outcomes, well-being, and quality of life for people with type 1 diabetes of all ages. However, regulatory approval and access to diabetes technology in pregnancy has lagged behind these advancements, leaving many pregnant individuals without tools that could dramatically improve diabetes care before, during, and after gestation. Here, we review the benefits of continuous glucose monitors and automated insulin-delivery systems in pregnancy and highlight specific scientific and structural supports to help implement diabetes technology safely, effectively, and equitably in pregnancy.

From Stability to Variability: Classification of Healthy Individuals, Prediabetes, and Type 2 Diabetes Using Glycemic Variability Indices from Continuous Glucose Monitoring Data

Objective: This study aims to investigate the continuum of glucose control from normoglycemia to dysglycemia (HbA1c ≥ 5.7%/39 mmol/mol) using metrics derived from continuous glucose monitoring (CGM). In addition, we aim to develop a machine learning-based classification model to classify dysglycemia based on observed patterns. Methods: Data from five distinct studies, each featuring at least two days of CGM, were pooled. Participants included individuals classified as healthy, with prediabetes, or with type 2 diabetes mellitus (T2DM). Various CGM indices were extracted and compared across groups. The data set was split 70/30 for training and testing two classification models (XGBoost/Logistic Regression) to differentiate between prediabetes or dysglycemia and the healthy group. Results: The analysis included 836 participants (healthy: n = 282; prediabetes: n = 133; T2DM: n = 432). Across all CGM indices, a progressive shift was observed from the healthy group to those with diabetes (P < 0.001). Statistically significant differences (P < 0.01) were noted in mean glucose, time below range, time above 140 mg/dl, mobility, multiscale complexity index, and glycemic risk index when transitioning from health to prediabetes. The XGBoost models achieved the highest receiver operating characteristic area under the curve values on the test data set ranging from 0.91 [confidence interval (CI): 0.87-0.95] (prediabetes identification) to 0.97 [CI: 0.95-0.98] (dysglycemia identification). Conclusion: Our findings demonstrate a gradual deterioration of glucose homeostasis and increased glycemic variability across the spectrum from normo- to dysglycemia, as evidenced by CGM metrics. The performance of CGM-based indices in classifying healthy individuals and those with prediabetes and diabetes is promising.