Translating glycated hemoglobin A1c into time spent in glucose target range: A multicenter study

Sustained Effectiveness of an Advanced Hybrid Closed-Loop System in a Cohort of Children and Adolescents With Type 1 Diabetes: A 1-Year Real-World Study

OBJECTIVE

To investigate glucose metrics and identify potential predictors of the achievement of glycemic outcomes in children and adolescents during their first 12 months of MiniMed 780G use.

RESEARCH DESIGN AND METHODS

This multicenter, longitudinal, real-world study recruited 368 children and adolescents with type 1 diabetes (T1D) starting SmartGuard technology between June 2020 and June 2022. Ambulatory glucose profile data were collected during a 15-day run-in period (baseline), 2 weeks after automatic mode activation, and every 3 months. The influence of covariates on glycemic outcomes after 1 year of MiniMed 780G use was assessed.

RESULTS

After 15 days of automatic mode use, all glucose metrics improved compared with baseline (P < 0.001), except for time below range (P = 0.113) and coefficient of variation (P = 0.330). After 1 year, time in range (TIR) remained significantly higher than at baseline (75.3% vs. 62.8%, P < 0.001). The mean glycated hemoglobin (HbA1c) over the study duration was lower than the previous year (6.9 ± 0.6% vs. 7.4 ± 0.9%, P < 0.001). Time spent in tight range (70-140 mg/dL) was 51.1%, and the glycemia risk index was 27.6. Higher TIR levels were associated with a reduced number of automatic correction boluses (P < 0.001), fewer SmartGuard exits (P = 0.021), and longer time in automatic mode (P = 0.030). Individuals with baseline HbA1c >8% showed more relevant improvement in TIR levels (from 54.3% to 72.3%).

CONCLUSIONS

Our study highlights the sustained effectiveness of MiniMed 780G among youth with T1D. Findings suggest that even children and adolescents with low therapeutic engagement may benefit from SmartGuard technology.

During an 18-month course of automated insulin delivery treatment, children aged 2 to 6 years achieve and maintain a higher time in tight range

AIMS

To investigate whether the positive effects on glycaemic outcomes of 3-month automated insulin delivery (AID) achieved in 2- to 6-year-old children endure over an extended duration and how AID treatment affects time in tight range (TITR), defined as 3.9-7.8 mmol/L.

RESEARCH DESIGN AND METHODS

We analysed 18 months of follow-up data from a non-randomized, prospective, single-arm clinical trial (n = 35) conducted between 2021 and 2023. The main outcome measures were changes in time in range (TIR), glycated haemoglobin (HbA1c), time above range (TAR), TITR, and mean sensor glucose (SG) value during follow-up visits (at 0, 6, 12 and 18 months). The MiniMed 780G AID system in SmartGuard Mode was used for 18 months. Parental diabetes distress was evaluated at 3 and 18 months with the validated Problem Areas in Diabetes-Parent, revised (PAID-PR) survey.

RESULTS

Between 0 and 6 months, TIR and TITR increased, and HbA1c, mean SG value and TAR decreased significantly (p < 0.001); the favourable effect persisted through 18 months of follow-up. Between 3 and 18 months, PAID-PR score declined significantly (0 months: mean score 37.5; 3 months: mean score 28.6 [p = 0.06]; 18 months: mean score 24.6 [p < 0.001]).

CONCLUSIONS

Treatment with AID significantly increased TITR and TIR in young children. The positive effect of AID on glycaemic control observed after 6 months persisted throughout the 18 months of follow-up. Similarly, parental diabetes distress remained reduced during 18 months follow-up. These findings are reassuring and suggest that AID treatment improves glycaemic control and reduces parental diabetes distress in young children over an extended 18-month follow-up.

Utility of time in tight range (TITR) in evaluating metabolic control in pediatric and adult patients with type 1 diabetes in treatment with advanced hybrid closed-loop systems

PURPOSE

To analyze the time in tight range (TITR), and its relationship with other glucometric parameters in patients with type 1 diabetes (T1D) treated with advanced hybrid closed-loop (AHCL) systems.

METHODS

A prospective observational study was conducted on pediatric and adult patients with T1D undergoing treatment with AHCL systems for at least 3 months. Clinical variables and glucometric parameters before and after AHCL initiation were collected.

RESULTS

A total of 117 patients were evaluated. Comparison of metabolic control after AHCL initiation showed significant improvements in HbA1c (6.9 ± 0.9 vs. 6.6 ± 0.5%, p < 0.001), time in range (TIR) (68.2 ± 11.5 vs. 82.5 ± 6.9%, p < 0.001), TITR (43.7 ± 10.8 vs. 57.3 ± 9.7%, p < 0.001), glucose management indicator (GMI) (6.9 ± 0.4 vs. 6.6 ± 0.3%, p < 0.001), time below range (TBR) 70-54 mg/dl (4.3 ± 4.5 vs. 2.0 ± 1.4%, p < 0.001), and time above range (TAR) > 180 mg/dl (36.0 ± 7.6 vs. 15.1 ± 6.4%, p < 0.001). Coefficient of variation (CV) also improved (36.3 ± 5.7 vs. 30.6 ± 3.7, p < 0.001), while time between 140-180 mg/dl remained unchanged. In total, 76.3% achieved TITR > 50% (100% pediatric). Correlation analysis between TITR and TIR and GRI showed a strong positive correlation, modified by glycemic variability.

CONCLUSIONS

AHCL systems achieve significant improvements in metabolic control (TIR > 70% in 93.9% patients). The increase in TIR was not related to an increase in TIR 140-180 mg/dl. Despite being closely related to TIR, TITR allows for a more adequate discrimination of the achieved control level, especially in a population with good initial metabolic control. The correlation between TIR and TITR is directly influenced by the degree of glycemic variability.

The association of chronic complications with time in tight range and time in range in people with type 1 diabetes: a retrospective cross-sectional real-world study

AIMS/HYPOTHESIS

The aim of this study was to evaluate the association of chronic complications with time in tight range (TITR: 3.9-7.8 mmol/l) and time in range (TIR: 3.9-10.0 mmol/l) in people with type 1 diabetes.

METHODS

The prevalence of microvascular complications (diabetic retinopathy, diabetic nephropathy and diabetic peripheral neuropathy [DPN]) and macrovascular complications according to sensor-measured TITR/TIR was analysed cross-sectionally in 808 adults with type 1 diabetes. Binary logistic regression was used to evaluate the association between TITR/TIR and the presence of complications without adjustment, with adjustment for HbA1c, and with adjustment for HbA1c and other confounding factors (sex, age, diabetes duration, BMI, BP, lipid profile, smoking, and use of statins and renin-angiotensin-aldosterone system inhibitors).

RESULTS

The mean TITR and TIR were 33.9 ± 12.8% and 52.5 ± 15.0%, respectively. Overall, 46.0% had any microvascular complication (34.5% diabetic retinopathy, 23.8% diabetic nephropathy, 16.0% DPN) and 16.3% suffered from any macrovascular complication. The prevalence of any microvascular complication, diabetic retinopathy, diabetic nephropathy and a cerebrovascular accident (CVA) decreased with increasing TITR/TIR quartiles (all ptrend<0.05). Each 10% increase in TITR was associated with a lower incidence of any microvascular complication (OR 0.762; 95% CI 0.679, 0.855; p<0.001), diabetic retinopathy (OR 0.757; 95% CI 0.670, 0.856; p<0.001), background diabetic retinopathy (OR 0.760; 95% CI 0.655, 0.882; p<0.001), severe diabetic retinopathy (OR 0.854; 95% CI 0.731, 0.998; p=0.048), diabetic nephropathy (OR 0.799; 95% CI 0.699, 0.915; p<0.001), DPN (OR 0.837; 95% CI 0.717, 0.977; p=0.026) and CVA (OR 0.651; 95% CI 0.470, 0.902; p=0.010). The independent association of TITR with any microvascular complication (OR 0.867; 95% CI 0.762, 0.988; p=0.032), diabetic retinopathy (OR 0.837; 95% CI 0.731, 0.959; p=0.010), background diabetic retinopathy (OR 0.831; 95% CI 0.705, 0.979; p=0.027) and CVA (OR 0.619; 95% CI 0.426, 0.899; p=0.012) persisted after adjustment for HbA1c. Similar results were obtained when controlling for HbA1c and other confounding factors.

CONCLUSIONS/INTERPRETATION

TITR and TIR are inversely associated with the presence of microvascular complications and CVA in people with type 1 diabetes. Although this study was not designed to establish a causal relationship, this analysis adds validity to the use of TITR and TIR as key measures in glycaemic management.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02601729 and NCT02898714.

Time in Tight Glucose Range in Type 1 Diabetes: Predictive Factors and Achievable Targets in Real-World Users of the MiniMed 780G System

OBJECTIVE

We studied time in tight range (TITR) (70-140 mg/dL) in real-world users of the MiniMed 780G system (MM780G).

RESEARCH DESIGN AND METHODS

CareLink Personal data were extracted (August 2020 to December 2022) to examine TITR and its relationship with time in range (TIR; 70-180 mg/dL), factors predicting higher TITR, and which TITR target is a reasonable treatment goal.

RESULTS

The 13,461 users (3,762 age ≤15 years and 9,699 age >15 years) showed an average TITR of 48.9% in those age ≤15 years and 48.8% in the older group (vs. TIR 71.2% and 73.9%, respectively). Consistent use of a glucose target (GT) of 100 mg/dL and active insulin time (AIT) of 2 h were the most relevant factors predicting higher TITR (P < 0.0001). In users consistently applying these optimal settings, TITR was 56.7% in those age ≤15 years and 57.0% in the older group, and the relative impact of these settings on TITR was 60% and 86% greater than that on TIR, respectively. TITRs of ∼45% (age ≤15 years 46.3% and older group 45.4%), ∼50% (50.7% and 50.7%) and ∼55% (56.4% and 58.0%) were best associated with glucose management indicators <7.0%, <6.8%, and <6.5%, respectively. TITRs of >45%, >50%, and >55% were achieved in 91%, 74%, and 55% of those age ≤15 years and 93%, 81%, and 57% of older group users, respectively, at optimal settings.

CONCLUSIONS

This study demonstrates that 1) mean TIR is high with a high mean TITR in MM780G users (>48%), 2) consistent use of optimal GT/AIT improves TITR (>56%), 3) the impact of these settings on TITR is larger than on TIR, and 4) a TITR target >50% is our suggested treatment goal.

The Relationship Between Glycated Hemoglobin and Time in Range in a Pediatric Population

In adults with type 1 diabetes (T1D), time in range (TIR) [70-180 mg/dL] has been proposed as an additional metric besides glycated hemoglobin (HbA1c). This retrospective monocentric cohort study determined the correlation between HbA1c and TIR during the 2, 4, and 12 weeks (TIR2w, TIR4w, and TIR12w) before consultation in a pediatric T1D population. A total of 168 children with T1D were included. Continuous glucose monitoring data, HbA1c, and demographic variables were collected. We found strong linear correlations between HbA1c and TIR2w (R = -0.571), HbA1c and TIR4w (R = -0.603), and between HbA1c and TIR12w (R = -0.624). A strong correlation exists between TIR2w and TIR12w, HbA1c and time above range (TAR), and between TIR and TAR at different time points. In conclusion, a strong correlation was found between HbA1c and TIR, making TIR a potentially complementary metric to HbA1c. TIR2w seems a viable alternative to TIR12w. TAR also seems promising in assessing glycemic control.

Continuous Glucose Monitoring-Derived Glucometrics in Adults with Type 1 Diabetes When Switching Basal Insulins

Context: Limited evidence is available on the real-world effect of insulin degludec (IDeg) in type 1 diabetes (T1D), using continuous glucose monitoring (CGM)-derived metrics. Objective: To assess the real-world effect of switching to IDeg from other long-acting insulins on time in ranges (TIRs) measured by CGM, metabolic control, and insulin dose for people with T1D. Design: This retrospective multicenter study encompassed five time points during a 12-month pre-switch of IDeg and a 12-month follow-up period. For each visit, clinical and CGM data were collected to evaluate temporal trends in glycemic outcomes. Participants: Of 753 persons with T1D who were assessed for eligibility, 486 persons were included, mostly men (61.5%), 47.4 (16.9) years old and diabetes duration of 23.8 (14.2) years at IDeg-initiation. Main Outcome Measure: Primary outcome was the evolution of percent TIR (70-180 mg/dL or 3.9-10.0 mmol/L, TIR) before versus after switch to IDeg. Results: TIR over 24 h increased at 12 months versus baseline (56.7% vs. 52.3%, P < 0.001), mostly during daytime. Time <54 mg/dL (<3.0 mmol/L) over 24 h decreased at 12 months versus baseline (2.02% vs. 2.86%, P < 0.001), mostly during nighttime. Glycated hemoglobin (7.9% vs. 8.1%, P < 0.001) and coefficient of variation (40.0% vs. 41.5%, P < 0.001) improved at 12 months versus baseline. Mean daily basal, bolus and total insulin doses decreased at 12 months (P < 0.001 for all vs. baseline). Conclusions: This retrospective real-world study reports that switching basal insulin significantly improved time spent in glucometric ranges and glycemic variability in the studied population of people with T1D. Clinical Trial Registration number: NCT05434559.

Future of Time-in-Range Goals in the Era of Advanced Hybrid Closed-Loop Automated Insulin Delivery Systems

The concept of maintaining blood glucose levels within the 70-180 mg/dL range, known as time-in-range, has raised questions regarding its representation of true physiological euglycemia. Some have speculated that focusing on the time spent within the 70-140 mg/dL range, introduced as time in tight range (TITR) through the International Consensus statement, could serve as a more precise metric for assessing normoglycemia in individuals with type 1 diabetes. This article delves into the current status of TITR as an emerging marker and explores how advanced hybrid closed-loop systems may offer a promising avenue for achieving this higher level of glycemic control.

Aiming for the Best Glycemic Control Beyond Time in Range: Time in Tight Range as a New Continuous Glucose Monitoring Metric in Children and Adolescents with Type 1 Diabetes Using Different Treatment Modalities

Introduction: To evaluate time in tight range (TITR) 70-140 mg/dL (3.9-7.8 mmol/L), its correlation with standard continuous glucose monitoring (CGM) metrics and the clinical variables that possibly have a substantial impact on its value, in a large cohort of pediatric subjects using different treatment strategies. Materials and Methods: A total of 854 children and adolescents with type 1 diabetes were consecutively recruited in this real world, dual center, cross-sectional study. Participants were categorized into four treatment groups (multiple daily injections [MDI] + real-time CGM, MDI + intermittently scanned CGM, sensor augmented pump, and hybrid closed loop [HCL]). Demographical and clinical data, including CGM data, were collected and analyzed. Results: The overall study population exhibited an average TITR of 36.4% ± 12.8%. HCL users showed higher TITR levels compared to the other treatment groups (P < 0.001). A time in range (TIR) cut-off value of 71.9% identified subjects achieving a TITR ≥50% (area under curve [AUC] 0.98; 95% confidence interval 0.97-0.99, P < 0.001), and a strong positive correlation between these two metrics was observed (r = 0.95, P < 0.001). An increase in TIR of 1% was associated with 1.84 (R2 Nagelkerke = 0.35, P < 0.001) increased likelihood of achieving TITR ≥50%. Use of HCL systems (B = 7.78; P < 0.001), disease duration (B = -0.26, P = 0.006), coefficient of variation (B = -0.30, P = 0.004), and glycated hemoglobin (B = -8.82; P < 0.001) emerged as significant predictors of TITR levels. Conclusions: Our study highlights that most children and adolescents with type 1 diabetes present TITR levels below 50%, except those using HCL. Tailored interventions and strategies should be implemented to increase TITR.

14. Children and Adolescents: Standards of Care in Diabetes-2024

The American Diabetes Association (ADA) "Standards of Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, an interprofessional expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations and a full list of Professional Practice Committee members, please refer to Introduction and Methodology. Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

Correlation between time on target and glycated hemoglobin in people with diabetes mellitus: systematic review

to analyze the correlation between time on target and glycated hemoglobin in people living with diabetes mellitus and carrying out continuous blood glucose monitoring or self-monitoring of capillary blood glucose.

systematic review of etiology and risk based on JBI guidelines and reported according to Preferred Reporting Items for Systematic Reviews and Meta- Analyses, covering six databases and grey literature. The sample included 16 studies and methodological quality was assessed using JBI tools. Protocol registered in the Open Science Framework, available at https://doi.org/10.17605/OSF.IO/NKMZB.

time on target (70-180 mg/dl) showed a negative correlation with glycated hemoglobin, while time above target (>180 mg/dl) showed a positive correlation. Correlation coefficients ranged between -0.310 and -0.869 for time on target, and between 0.66 and 0.934 for time above target. A study was carried out on a population that performed self-monitoring.

there is a statistically significant correlation between time on target and time above target with glycated hemoglobin. The higher the proportion in the adequate glycemic range, the closer to or less than 7% the glycated hemoglobin will be. More studies are needed to evaluate this metric with data from self-monitoring of blood glucose.

14. Children and Adolescents: Standards of Care in Diabetes-2023

The American Diabetes Association (ADA) "Standards of Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, a multidisciplinary expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations and a full list of Professional Practice Committee members, please refer to Introduction and Methodology. Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

Correlation between glucose measurement parameters of continuous flash monitoring and HbA1c. Real life experience in Asturias

INTRODUCTION

Despite continuous glucose monitoring having been proven useful in patients with type 1 diabetes mellitus, A1C remains the gold standard for assessing disease management.

MATERIAL AND METHODS

Descriptive, retrospective study which included 252 patients, 40.5% male, mean age 44.91±14.57 years, mean duration of diabetes 22.21±13.12 years, 88.1% on basal-bolus insulin therapy and 11.9% users of continuous subcutaneous insulin infusion. Glucose measurement, analytical and anthropometric data were obtained.

RESULTS

The mean time in range was 60.18±15.60% and was associated with A1C after adjusting for age, gender, duration of diabetes, BMI, insulin regimen, %CV and time below range (ß: -0.548; p<0.01). The glucose management indicator (GMI) was 7.19±0.69% and was also associated with A1C (ß: 0.957; p<0.01) regardless of age, gender, duration of diabetes, BMI, insulin treatment, %CV and time in range. The average difference between A1C and GMI was 0.17±0.65% (-2.70-3.40%), being higher as A1C increased, in a linear and significant manner, without being influenced by the duration of diabetes or CV.

CONCLUSIONS

Although we found a positive correlation between continuous glucose monitoring glucose measurement parameters and A1C, there is still not enough evidence to replace one parameter with another.

Glycemic Metrics Derived From Intermittently Scanned Continuous Glucose Monitoring

BACKGROUND

Glucose data from intermittently scanned continuous glucose monitoring (isCGM) is a combination of scanned and imported glucose values. The present knowledge of glycemic metrics originate mostly from glucose data from real-time CGM sampled every five minutes with a lack of information derived from isCGM.

METHODS

Glucose data obtained with isCGM and hemoglobin A1c (HbA1c) were obtained from 169 patients with type 1 diabetes. Sixty-one patients had two observations with an interval of more than three months.

RESULTS

The best regression line of HbA1c against mean glucose was observed from 60 days prior to HbA_1c measurement as compared to 14, 30, and 90 days. The difference between HbA1c and estimated HbA1c (=glucose management indicator [GMI]) first observed correlated with the second observation (R2 0.61, P < .001). Time in range (TIR, glucose between 3.9 and 10 mmol/L) was significantly related to GMI (R2 0.87, P < .001). A TIR of 70% corresponded to a GMI of 6.8% (95% confidence interval, 6.3-7.4). The fraction of patients with the optimal combination of TIR >70% and time below range (TBR) <4% was 3.6%. The fraction of patients with TBR>4% was four times higher for those with high glycemic variability (coefficient of variation [CV] >36%) than for those with lower CV.

CONCLUSION

The individual difference between HbA1c and GMI was reproducible. High glycemic variability was related to increased TBR. A combination of TIR and TBR is suggested as a new composite quality indicator.

14. Children and Adolescents: Standards of Medical Care in Diabetes-2022

The American Diabetes Association (ADA) "Standards of Medical Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, a multidisciplinary expert committee (https://doi.org/10.2337/dc22-SPPC), are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations, please refer to the Standards of Care Introduction (https://doi.org/10.2337/dc22-SINT). Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

Achieving the HbA1c Target Requires Longer Time in Range in Pregnant Women With Type 1 Diabetes

CONTEXT

Continuous glucose monitoring (CGM) overcomes the limitations of glycated hemoglobin (HbA1c).

OBJECTIVE

This study aimed to investigate the relationship between CGM metrics and laboratory HbA1c in pregnant women with type 1 diabetes.

METHODS

An observational study enrolled pregnant women with type 1 diabetes who wore CGM devices during pregnancy and postpartum from 11 hospitals in China from January 2015 to June 2019. CGM data were collected to calculate time in range (TIR), time above range (TAR), time below range (TBR), and glycemic variability parameters. Relationships between the CGM metrics and HbA1c were explored. Linear and curvilinear regressions were conducted to investigate the best-fitting model to clarify the influence of HbA1c on the TIR-HbA1c relationship during pregnancy.

RESULTS

A total of 272 CGM data and corresponding HbA1c from 98 pregnant women with type 1 diabetes and their clinical characteristics were analyzed in this study. Mean HbA1c and TIR were 6.49 ± 1.29% and 76.16 ± 17.97% during pregnancy, respectively. HbA1c was moderately correlated with TIR3.5-7.8(R = -0.429, P = .001), mean glucose (R = 0.405, P = .001) and TAR7.8 (R = 0.435, P = .001), but was weakly correlated with TBR3.5 (R = 0.034, P = .001) during pregnancy. On average, a 1% (11 mmol/mol) decrease in HbA1c corresponded to an 8.5% increase in TIR3.5-7.8. During pregnancy, HbA1c of 6.0%, 6.5%, and 7.0% were equivalent to a TIR3.5-7.8 of 78%, 74%, and 69%, respectively.

CONCLUSION

We found there was a moderate correlation between HbA1c and TIR3.5-7.8 during pregnancy. To achieve the HbA1c target of less than 6.0%, pregnant women with type 1 diabetes should strive for a TIR3.5-7.8 of greater than 78% (18 hours 43 minutes) during pregnancy.

Glucose Regulation Beyond HbA1c in Type 2 Diabetes Treated With Insulin: Real-World Evidence From the DIALECT-2 Cohort

OBJECTIVE

To investigate glucose variations associated with glycated hemoglobin (HbA1c) in insulin-treated patients with type 2 diabetes.

RESEARCH DESIGN AND METHODS

Patients included in Diabetes and Lifestyle Cohort Twente (DIALECT)-2 (n = 79) were grouped into three HbA1c categories: low, intermediate, and high (≤53, 54-62, and ≥63 mmol/mol or ≤7, 7.1-7.8, and ≥7.9%, respectively). Blood glucose time in range (TIR), time below range (TBR), time above range (TAR), glucose variability parameters, day and night duration, and frequency of TBR and TAR episodes were determined by continuous glucose monitoring (CGM) using the FreeStyle Libre sensor and compared between HbA1c categories.

RESULTS

CGM was performed for a median (interquartile range) of 10 (7-12) days/patient. TIR was not different for low and intermediate HbA1c categories (76.8% [68.3-88.2] vs. 76.0% [72.5.0-80.1]), whereas in the low category, TBR was higher and TAR lower (7.7% [2.4-19.1] vs. 0.7% [0.3-6.1] and 8.2% [5.7-17.6] vs. 20.4% [11.6-27.0], respectively, P < 0.05). Patients in the highest HbA1c category had lower TIR (52.7% [40.9-67.3]) and higher TAR (44.1% [27.8-57.0]) than the other HbA1c categories (P < 0.05), but did not have less TBR during the night. All patients had more (0.06 ± 0.06/h vs. 0.03 ± 0.03/h; P = 0.002) and longer (88.0 [45.0-195.5] vs. 53.4 [34.4-82.8] minutes; P < 0.001) TBR episodes during the night than during the day.

CONCLUSIONS

In this study, a high HbA1c did not reduce the occurrence of nocturnal hypoglycemia, and low HbA1c was not associated with the highest TIR. Optimal personalization of glycemic control requires the use of newer tools, including CGM-derived parameters.

Assessment of metabolic control and use of flash glucose monitoring systems in a cohort of pediatric, adolescents, and adults patients with Type 1 diabetes

PURPOSE

Flash glucose monitoring (FGM) in patients with type 1 diabetes (DM1) provides glucometric data that allow assessing glycemic control beyond HbA1c. The objective of this study was to evaluate metabolic control and use of FGM in a cohort of the pediatric and adult population with DM1.

MATERIAL AND METHODS

A cross-sectional study of patients with DM1 and FGM. Data on the use of the system and metabolic control were evaluated, carrying out a comparative study between different age ranges, ≤12 years; 13-19 years, 20-25 years, and ≥26 years.

RESULTS

One hundred and ninety-five patients have included: 35.9% children and adolescents (≤19 years), 42.6% female, 26.2% in treatment with an insulin pump. Mean age was 28.5 ± 15.9 years, mean duration of diabetes 13.7 ± 11.0 years, and mean HbA1c 7.1 ± 0.9% (54 ± 6 mmol/l). Average daily FGM scans were 11.1 ± 6.7. Mean glucose was 162 ± 35 mg/dl, mean standard deviation (SD) 66.1 ± 20.4 mg/dl, mean coefficient of variation 41.4 ± 7.9%, mean time in range (TIR) 58.8 ± 17.0%, mean time above range 33.7 ± 17.6% and mean time below range 7.5 ± 5.8%. The pediatric group showed higher TIR, lower HbA1c, lower glycemic variability, lower mean glucose, and higher use of the device than the adult population. In the entire cohort, the device scans showed a negative quadratic correlation with HbA1c, mean glucose, SD, and age and a positive quadratic correlation with TIR.

CONCLUSIONS

Children under 12 years showed the best metabolic control and the most frequent use of the device. Metabolic control deteriorates with age. The greater number of device scans was in correlation with better metabolic control in all age groups.

Relationships between HbA1c and continuous glucose monitoring metrics of glycaemic control and glucose variability in a large cohort of children and adolescents with type 1 diabetes

AIMS

To evaluate the relationships between HbA1c and Continuous Glucose Monitoring (CGM) metrics in children/adolescents with Type 1 Diabetes (T1D).

METHODS

HbA1c and real-life CGM data of the 12 weeks preceding its measurement were retrospectively collected from 654 children/adolescents with T1D. The relationships between HbA1c and CGM metrics were assessed by Spearman correlation coefficient. Participants were categorized into groups based on HbA1c and CGM metrics values. ANOVA was run across HbA1c and CGM metrics groups in the entire study population and in subjects stratified by CGM type, insulin therapy, age and puberty.

RESULTS

HbA1c was positively correlated with mean glucose, SD, %TAR > 180 mg/dL, %TAR > 250 mg/dL, HBGI and negatively with %TIR, %TBR and %time < 54 mg/dL. HbA1c-based groups were significantly associated with these metrics, but for each group their value widely ranged with a substantial overlap between them. HbA1c and HbA1c-based groups were not associated with %CV and LBGI, as well as %CV and LBGI-based groups had not significantly different HbA1c. Comparable results were found analysing subjects according to age, type of CGM, insulin therapy and puberty.

CONCLUSIONS

The relationships between HbA1c and CGM metrics described in this cohort of paediatric subjects with T1D support the importance of the evaluation of these metrics, in particular %CV and LBGI, independently of HbA1c value.

Exploring the inter-subject variability in the relationship between glucose monitoring metrics and glycated hemoglobin for pediatric patients with type 1 diabetes

OBJECTIVES

Despite the widespread diffusion of continuous glucose monitoring (CGM) systems, which includes both real-time CGM (rtCGM) and intermittently scanned CGM (isCGM), an effective application of CGM technology in clinical practice is still limited. The study aimed to investigate the relationship between isCGM-derived glycemic metrics and glycated hemoglobin (HbA1c), identifying overall CGM targets and exploring the inter-subject variability.

METHODS

A group of 27 children and adolescents with type 1 diabetes under multiple daily injection insulin-therapy was enrolled. All participants used the isCGM Abbott's FreeStyle Libre system on average for eight months, and clinical data were collected from the Advanced Intelligent Distant-Glucose Monitoring platform. Starting from each HbA1c exam date, windows of past 30, 60, and 90 days were considered to compute several CGM metrics. The relationships between HbA1c and each metric were explored through linear mixed models, adopting an HbA1c target of 7%.

RESULTS

Time in Range and Time in Target Range show a negative relationship with HbA1c (R²>0.88) whereas Time Above Range and Time Severely Above Range show a positive relationship (R²>0.75). Focusing on Time in Range in 30-day windows, random effect represented by the patient's specific intercept reveals a high variability compared to the overall population intercept.

CONCLUSIONS

This study confirms the relationship between several CGM metrics and HbA1c; it also highlights the importance of an individualized interpretation of the CGM data.

Beyond A1C: A Practical Approach to Interpreting and Optimizing Continuous Glucose Data in Youth

Despite significant pharmacological and technological advances in the treatment of type 1 diabetes, the majority of youth in the United States do not meet the American Diabetes Association's recommended A1C goal. Understanding and managing glycemic variability is important in children and adolescents. Because A1C provides an incomplete picture of day-to-day glycemic fluctuations, continuous glucose monitoring (CGM)-derived metrics are a promising addition to address glycemic management challenges in youth with diabetes. In this article, we discuss how to develop practical strategies to optimize the use of CGM in the pediatric population, interpret the valuable data it provides, and develop personalized and actionable treatment goals.

Systematic Review on Human Skin-Compatible Wearable Photoplethysmography Sensors

The rapid advances in human-friendly and wearable photoplethysmography (PPG) sensors have facilitated the continuous and real-time monitoring of physiological conditions, enabling self-health care without being restricted by location. In this paper, we focus on state-of-the-art skin-compatible PPG sensors and strategies to obtain accurate and stable sensing of biological signals adhered to human skin along with light-absorbing semiconducting materials that are classified as silicone, inorganic, and organic absorbers. The challenges of skin-compatible PPG-based monitoring technologies and their further improvements are also discussed. We expect that such technological developments will accelerate accurate diagnostic evaluation with the aid of the biomedical electronic devices.

Efficacy of a glucose meter connected to a mobile app on glycemic control and adherence to self-care tasks in patients with T1DM and LADA: a parallel-group, open-label, clinical treatment trial

Objective

The main aim of the study was to evaluate the patients' glycemic control and adherence to self-care tasks.

Methods

Patients with type 1 diabetes mellitus (T1DM) or latent autoimmune diabetes of the adult (LADA) using a multiple daily injection (MDI) regimen with carbohydrate counting (n = 25, Subgroup B) or fixed insulin dose (n = 25, Subgroup C) were allocated to use the application (app) for 12 weeks. Both subgroups were compared with each other and against a control group (n = 25, Group A) comprising patients with T1DM or LADA treated with continuous subcutaneous insulin infusion (CSII) in a parallel-group, open-label, clinical treatment trial. All patients had glycated hemoglobin (A1C) levels measured and were asked to fill out the Diabetes Self-Management Profile (DSMP) questionnaire at study start and end. The patients were instructed to measure capillary glucose six times daily in study weeks 4, 8, and 12.

Results

Mean A1C levels decreased 0.725% in Subgroup C in intragroup analysis (p = 0.0063), and had a mean variation of 0.834% compared with Group A (p = 0.003). Mean DSMP scores increased 5.77 points in Subgroup B in intragroup analysis (p = 0.0004) and increased by a mean of 6.815 points in relation to Group A (p = 0.002).

Conclusion

OneTouch Reveal improved both A1C levels and DSMP scores in patients with T1DM or LADA compared with standard treatment (CSII).

Relationship of continuous glucose monitoring-related metrics with HbA1c and residual β-cell function in Japanese patients with type 1 diabetes

The targets for continuous glucose monitoring (CGM)-derived metrics were recently set; however, studies on CGM data over a long period with stable glycemic control are limited. We analyzed 194,279 CGM values obtained from 19 adult Japanese patients with type 1 diabetes. CGM data obtained during stable glycemic control over four months were analyzed. CGM-related metrics of different durations “within 120, 90, 60, 30, and 7 days” were calculated from baseline. Time in range (TIR; glucose 70–180 mg/dL), time above range (TAR; glucose ≥ 181 mg/dL), and average glucose levels, but not time below range (TBR; glucose ≤ 69 mg/dL), strongly correlated with glycated hemoglobin (HbA1c) values (P < 0.0001). TBR correlated with glucose coefficient of variation (CV) (P < 0.01). Fasting serum C-peptide levels negatively correlated with glucose CV (P < 0.01). HbA1c of approximately 7% corresponded to TIR of 74% and TAR of 20%. The shorter the CGM period, the weaker was the relationship between HbA1c and CGM-related metrics. TIR, TAR, and average glucose levels accurately reflected HbA1c values in Japanese patients with type 1 diabetes with stable glycemic control. Glucose CV and TBR complemented the limitation of HbA1c to detect glucose variability and hypoglycemia. Stable glycemic control with minimal hypoglycemia depended on residual β-cell function.

Individualizing Time-in-Range Goals in Management of Diabetes Mellitus and Role of Insulin: Clinical Insights From a Multinational Panel

Diabetes mellitus is a global health concern associated with significant morbidity and mortality. Inadequate control of diabetes leads to chronic complications and higher mortality rates, which emphasizes the importance of achieving glycemic targets. Although glycated hemoglobin (HbA_1c) is the gold standard for measuring glycemic control, it has several limitations. Therefore, in recent years, along with the emergence of continuous glucose monitoring (CGM) technology, glycemic control modalities have moved beyond HbA_1c. They encompass modern glucometrics, such as glycemic variability (GV) and time-in-range (TIR). The key advantage of these newer metrics over HbA_1c is that they allow personalized diabetes management with person-centric glycemic control. Basal insulin analogues, especially second-generation basal insulins with properties such as longer duration of action and low risk of hypoglycemia, have demonstrated clinical benefits by reducing GV and improving TIR. Therefore, for more effective and accurate diabetes management, the development of an integrated approach with second-generation basal insulin and glucometrics involving GV and TIR is the need of the hour. With this objective, a multinational group of endocrinologists and diabetologists reviewed the existing recommendations on TIR, provided their clinical insights into the individualization of TIR targets, and elucidated on the role of the second-generation basal insulin analogues in addressing TIR.

Time in range centered diabetes care

Optimal glycemic control remains challenging and elusive for many people with diabetes. With the comprehensive clinical evidence on safety and efficiency in large populations, and with broader reimbursement, the adoption of continuous glucose monitoring (CGM) is rapidly increasing. Standardized visual reporting and interpretation of CGM data and clear and understandable clinical targets will help professionals and individuals with diabetes use diabetes technology more efficiently, and finally improve long-term outcomes with less everyday disease burden. For the majority of people with type 1 or type 2 diabetes, time in range (between 70 and 180 mg/dL, or 3.9 and 10 mmol/L) target of more than 70% is recommended, with each incremental increase of 5% towards this target being clinically meaningful. At the same time, the goal is to minimize glycemic excursions: a recommended target for a time below range (< 70 mg/dL or < 3.9 mmol/L) is less than 4%, and time above range (> 180 mg/dL or 10 mmol/L) less than 25%, with less stringent goals for older individuals or those at increased risk. These targets should be individualized: the personal use of CGM with the standardized data presentation provides all necessary means to accurately tailor diabetes management to the needs of each individual with diabetes.

13. Children and Adolescents: Standards of Medical Care in Diabetes-2021

The American Diabetes Association (ADA) "Standards of Medical Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, a multidisciplinary expert committee (https://doi.org/10.2337/dc21-SPPC), are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations, please refer to the Standards of Care Introduction (https://doi.org/10.2337/dc21-SINT). Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

Time in range-A1c hemoglobin relationship in continuous glucose monitoring of type 1 diabetes: a real-world study

INTRODUCTION

The availability of easily accessible continuous glucose monitoring (CGM) metrics can improve glycemic control in diabetes, and they may even become a viable alternative to hemoglobin A1c (HbA1c) laboratory tests in the next years. The REALISM-T1D study (REAl-Life glucoSe Monitoring in Type 1 Diabetes) was aimed at contributing, with real-world data, to a deeper understanding of these metrics, including the time in range (TIR)-HbA1c relationship, to facilitate their adoption by diabetologists in everyday practice.

RESEARCH DESIGN AND METHODS

70 adults affected by type 1 diabetes were monitored for 1 year by means of either flash (FGM) or real-time (rtCGM) glucose monitoring devices. Follow-up visits were performed after 90, 180 and 365 days from baseline and percentage TIR^70-180 evaluated for the 90-day time period preceding each visit. HbA1c tests were also carried out in the same occasions and measured values paired with the corresponding TIR data.

RESULTS

A monovariate linear regression analysis confirms a strong correlation between TIR and HbA1c as found in previous studies, but leveraging more homogeneous data (n=146) collected in real-life conditions. Differences were determined between FGM and rtCGM devices in Pearson's correlation (r_FGM=0.703, r_rtCGM=0.739), slope (β_1,FGM=-11.77, β_1,rtCGM=-10.74) and intercept (β_0,FGM=141.19, β_0,rtCGM=140.77) coefficients. Normality of residuals and homoscedasticity were successfully verified in both cases.

CONCLUSIONS

Regression lines for two patient groups monitored through FGM and rtCGM devices, respectively, while confirming a linear relationship between TIR and A1c hemoglobin (A1C) in good accordance with previous studies, also show a statistically significant difference in the regression intercept, thus suggesting the need for different models tailored to device characteristics. The predictive power of A1C as a TIR estimator also deserves further investigations.

Individualization of recommendations from the international consensus on continuous glucose monitoring-derived metrics in Japanese children and adolescents with type 1 diabetes

We assessed the significance of recommendations from the international consensus on continuous glucose monitoring (CGM)-derived metrics in Japanese children and adolescents with type 1 diabetes. Eighty-five patients (age, 13.5 ± 4.7 years) who wore the FreeStyle^® Libre for a 28-day period were enrolled in this study. Seventy-three patients were treated with multiple daily injections of insulin and 12 with insulin pump therapy without using a sensor-augmented pump or a predictive low-glucose suspend-function pump. We evaluated the relationship between CGM-derived metrics: time in range (TIR: 70-180 mg/dL), time below range (TBR: <70 mg/dL), and time above range (TAR: >180 mg/dL), and laboratory-measured HbA1c and estimated HbA1c (eA1c) levels calculated from the mean glucose values. The TIR was 50.7 ± 12.2% (23-75%), TBR was 11.8 ± 5.8% (2-27%), and TAR was 37.5 ± 13.5% (9-69%). The TIR was highly correlated with HbA1c level, eA1c level, and TAR, but not with TBR. An HbA1c level of 7.0% corresponded to a TIR of 55.1% (95% CI: 53.7-56.5%), whereas a TIR of 70% corresponded to an HbA1c level of 6.1% (95% CI: 5.9-6.3%). The results of eA1c levels were similar to those observed for HbA1c levels. From these findings, we conclude that low rates of a recommended TIR of 70% may be due to less use of advanced technology and insufficient comprehensive diabetes care. Ethnic characteristics including lifestyle and eating customs may have contributed to the result. CGM-derived targets must be individualized based on ethnic characteristics, insulin treatment and diabetes care, and needs of individuals with diabetes.

Time spent outside of target glucose range for young children with type 1 diabetes: a continuous glucose monitor study

AIM

To assess the associations between demographic and clinical characteristics and sensor glucose metrics in young children with type 1 diabetes, using masked, continuous glucose monitoring data from children aged 2 to < 8 years.

RESEARCH DESIGN AND METHODS

The analysis included 143 children across 14 sites in the USA, enrolled in a separate clinical trial. Eligibility criteria were: age 2 to <8 years; type 1 diabetes duration ≥3 months; no continuous glucose monitoring use for past 30 days; and HbA_1c concentration 53 to <86 mmol/mol (7.0 to <10.0%). All participants wore masked continuous glucose monitors up to 14 days.

RESULTS

On average, participants spent the majority (13 h) of the day in hyperglycaemia (>10.0 mmol/l) and a median of ~1 h/day in hypoglycaemia (<3.9 mmol/l). Participants with minority race/ethnicity and higher parent education levels spent more time in target range, 3.9-10.0 mmol/l, and less time in hyperglycaemia. More time in hypoglycaemia was associated with minority race/ethnicity and younger age at diagnosis. Continuous glucose monitoring metrics were similar in pump and injection users.

CONCLUSIONS

Given that both hypo- and hyperglycaemia negatively impact neurocognitive development, strategies to increase time in target glucose range for young children are needed.

Positioning time in range in diabetes management

Recent upswings in the use of continuous glucose monitoring (CGM) technologies have given people with diabetes and healthcare professionals unprecedented access to a range of new indicators of glucose control. Some of these metrics are useful research tools and others have been welcomed by patient groups for providing insights into the quality of glucose control not captured by conventional laboratory testing. Among the latter, time in range (TIR) is an intuitive metric that denotes the proportion of time that a person's glucose level is within a desired target range (usually 3.9-10.0 mmol/l [3.5-7.8 mmol/l in pregnancy]). For individuals choosing to use CGM technology, TIR is now often part of the expected conversation between patient and healthcare professional, and consensus recommendations have recently been produced to facilitate the adoption of standardised TIR targets. At a regulatory level, emerging evidence linking TIR to risk of complications may see TIR being more widely accepted as a valid endpoint in future clinical trials. However, given the skewed distribution of possible glucose values outside of the target range, TIR (on its own) is a poor indicator of the frequency or severity of hypoglycaemia. Here, the state-of-the-art linking TIR with complications risk in diabetes and the inverse association between TIR and HbA_1c are reviewed. Moreover, the importance of including the amount and severity of time below range (TBR) in any discussions around TIR and, by inference, time above range (TAR) is discussed. This review also summarises recent guidance in setting 'time in ranges' goals for individuals with diabetes who wish to make use of these metrics. For most people with type 1 or type 2 diabetes, a TIR >70%, a TBR <3.9 mmol/l of <4%, and a TBR <3.0 mmol/l of <1% are recommended targets, with less stringent targets for older or high-risk individuals and for those under 25 years of age. As always though, glycaemic targets should be individualised and rarely is that more applicable than in the personal use of CGM and the data it provides.

Time in range: a new parameter to evaluate blood glucose control in patients with diabetes

The International Consensus in Time in Range (TIR) was recently released and defined the concept of the time spent in the target range between 70 and 180 mg/dL while reducing time in hypoglycemia, for patients using Continuous Glucose Monitoring (CGM). TIR was validated as an outcome measures for clinical Trials complementing other components of glycemic control like Blood glucose and HbA1c. The challenge is to implement this practice more widely in countries with a limited health public and private budget as it occurs in Brazil. Could CGM be used intermittently? Could self-monitoring blood glucose obtained at different times of the day, with the amount of data high enough be used? More studies should be done, especially cost-effective studies to help understand the possibility of having sensors and include TIR evaluation in clinical practice nationwide.

Patient-Generated Health Data Integration and Advanced Analytics for Diabetes Management: The AID-GM Platform

Diabetes is a high-prevalence disease that leads to an alteration in the patient’s blood glucose (BG) values. Several factors influence the subject’s BG profile over the day, including meals, physical activity, and sleep. Wearable devices are available for monitoring the patient’s BG value around the clock, while activity trackers can be used to record his/her sleep and physical activity. However, few tools are available to jointly analyze the collected data, and only a minority of them provide functionalities for performing advanced and personalized analyses. In this paper, we present AID-GM, a web application that enables the patient to share with his/her diabetologist both the raw BG data collected by a flash glucose monitoring device, and the information collected by activity trackers, including physical activity, heart rate, and sleep. AID-GM provides several data views for summarizing the subject’s metabolic control over time, and for complementing the BG profile with the information given by the activity tracker. AID-GM also allows the identification of complex temporal patterns in the collected heterogeneous data. In this paper, we also present the results of a real-world pilot study aimed to assess the usability of the proposed system. The study involved 30 pediatric patients receiving care at the Fondazione IRCCS Policlinico San Matteo Hospital in Pavia, Italy.

Associations between HbA1c and continuous glucose monitoring-derived glycaemic variables

AIMS

To identify clinically useful associations between HbA_1c levels and various continuous glucose monitoring-derived metrics.

METHODS

We retrospectively analysed end-of-study HbA_1c levels and >2 weeks of continuous glucose monitoring data collected from 530 adults with Type 1 diabetes or insulin-requiring Type 2 diabetes during four randomized trials. Each trial lasted ≥24 weeks and provided central laboratory end-of-study HbA_1c levels and continuous glucose monitoring data from the preceding 3 months. Participants were assigned to groups based on either HbA_1c levels or continuous glucose monitoring-derived glucose values.

RESULTS

HbA_1c was strongly correlated with mean glucose value (r=0.80), time spent with glucose values in the 3.9-10.0 mmol/l range (time in range; r=-0.75) and percentage of glucose values >13.9 mmol/l (r=0.72), but was weakly correlated with the percentage of glucose values <3.9 mmol/l (r=-0.39) or <3.0 mmol/l (r=-0.21). The median percentage of glucose values <3.0 mmol/l was <1.2% (<20 min/day) for all HbA_1c -based groups, but the median percentage of values >13.9 mmol/l varied from 2.5% (0.6 h/day) to 27.8% (6.7 h/day) in the lowest and highest HbA_1c groups, respectively. More than 90% of participants with either <2% of glucose values >13.9 mmol/l, mean glucose <7.8 mmol/l, or time in range >80% had HbA_1c levels ≤53 mmol/mol (≤7.0%). For participants with HbA_1c ≥64 mmol/mol (≥8.0%), the median time in range was 44%, with 90% of participants having a time in range of <59%.

CONCLUSIONS

The associations shown in the present study suggest that continuous glucose monitoring-derived metrics may help guide diabetes therapy intensification efforts in an HbA_1c -independent manner.