The Relationship of Hemoglobin A1C to Time-in-Range in Patients with Diabetes

Limitations of 14-Day Continuous Glucose Monitoring Sampling for Assessment of Hypoglycemia and Glycemic Variability in Type 1 Diabetes

Continuous glucose monitoring (CGM) has become the standard of care in diabetes management with the recent advances in technology and accessibility in the last decade. An International Consensus was established to define CGM metrics and its goals in diabetes care. The 2019 International Consensus suggested 14 days of CGM sampling for the assessment of CGM metrics stating the limitations that may occur for hypoglycemia and glycemic variability metrics. Since then, several studies assessed the correlation between CGM metrics and duration of the sampling period. This review summarized the studies that investigated the relationship between 14-day CGM sampling to 90-day CGM data in >70% CGM users for all CGM metrics and highlighted possible solutions for more accurate CGM sampling durations in type 1 diabetes (T1D). Accumulating evidence showed that 14-day CGM sampling correlates well with 90-day CGM data for mean glucose, time in 70-180 mg/dL, and hyperglycemia metrics; however, it correlates weakly for hypoglycemia and glycemic variability metrics. In the studies included in this review, in adults with T1D, minimum sampling duration was 14 days for mean glucose, time in 70-180 mg/dL, and time in hyperglycemia (>180 and >250 mg/dL); however, minimum sampling duration varied between 21 to 30 days for time <70 mg/dL, 30 to 35 days for time <54 mg/dL, and 28 to 35 days for coefficient of variation. Longer than 14 days of CGM, sampling was required to properly assess hypoglycemia and glycemic variability in T1D.

Diabetic peripheral neuropathy and glycemic variability assessed by continuous glucose monitoring: A systematic review and meta-analysis

Continuous glucose monitoring (CGM)-derived metrics have been used to accurately assess glycemic variability (GV) to facilitate management of diabetes mellitus, yet their relationship with diabetic peripheral neuropathy (DPN) is not fully understood. We performed a systematic review and meta-analysis to evaluate the association between GV metrics and the risk of developing DPN. Nine studies totaling 3,649 patients with type 1 and type 2 diabetes mellitus were included. A significant association was found between increased GV, as indicated by metrics including standard deviation (SD) with OR and 95% CI of 2.58 (1.45-4.57), mean amplitude of glycemic excursions (MAGE) with OR and 95% CI of 1.90 (1.01-3.58), mean of daily difference (MODD) with OR and 95% CI of 2.88 (2.17-3.81) and the incidence of DPN. Our findings support a link between higher GV and an increased risk of DPN in patients with diabetes. These findings highlight the potential of GV metrics as indicators for the development of DPN, advocating for their inclusion in diabetes management strategies to potentially mitigate neuropathy risk. Longitudinal studies with longer observation periods and larger sample sizes are necessary to validate these associations across diverse populations.

Metabolic dysfunction-associated steatotic liver disease is associated with worse time in ranges in type 1 diabetes

AIM

To investigate the relationship between continuous glucose monitoring (CGM)-derived glucometrics and metabolic dysfunction-associated steatotic liver disease (MASLD) in type 1 diabetes (T1D).

METHODS

A cross-sectional study collecting data on anthropometrics, glucometrics and MASLD in adults with T1D using a CGM device was conducted. MASLD was assessed by abdominal ultrasound and the presence of at least one cardiometabolic criterion. Backward multivariable logistic regression models were applied to define variables independently associated with MASLD.

RESULTS

A total of 302 consecutive participants were included (median age 49 [34-61] years, male sex 58%, median diabetes duration 29 [17-38] years, mean time in range [TIR] 55% ± 16%). MASLD was present in 17% of cases, and 32% had metabolic syndrome (MetS). MetS was significantly more prevalent in the MASLD group (65% vs. 25%, P < .0001). TIR (P = .038) and time below range (TBR) (P = .032) were lower and time above range (TAR) was higher (P = .006), whereas HbA1c did not reach significance (P = .068). No differences were found for the glycaemia risk index. TIR (P = .028), TAR (P = .007), TBR (P = .036), waist circumference (P < .001) and systolic blood pressure (P = .029) were independently associated with MASLD, while sex, age, aspartate aminotransferase/alanine aminotransferase ratio, gamma-glutamyl transferase, high-density lipoprotein cholesterol and triglycerides were not.

CONCLUSIONS

TIR, TAR, TBR, waist circumference and systolic blood pressure were independently associated with MASLD.

Glycemic variability through the perspective of the glycemia risk index and time in range and their association with glycated hemoglobin A1c in pediatric patients on sensor-augmented pump therapy

Introduction

From the introduction of continuous glucose monitoring (CGM) in treatments of type 1 diabetes, particularly its integration with insulin pumps, there has been a quest for new parameters that describe optimal glycemic control. As of the consensus reached in 2019, the ambulatory glucose profile (AGP) has become the standard, with time in range (TIR) emerging as a fundamental parameter for metabolic control assessment. However, with technological advancements, new parameters, such as the glycemia risk index (GRI), have been introduced and clinically utilized. Therefore, exploring the relationships between traditional and novel parameters to understand metabolic control comprehensively is imperative.

Materials and methods

This study was conducted at the Pediatric Clinic of the University Hospital of the Republic of Srpska Banja Luka between January and July 2023. The participants were randomly selected, with the inclusion criteria specifying an age greater than eight years and a diabetes type 1 duration exceeding two years. All participants were required to use a sensor-augmented insulin pump for the next three months (90 days), irrespective of prior use, with the suspend-before-low option activated.

Results

Of the 35 participants, 30 completed the study, 14 (46.7%) of whom were male. The mean age of the subjects was 14.90 ± 2.88 years, and the mean duration of diabetes was 7.83 ± 4.76 years. Over the 90-day period, HbA1c increased to an average of 7.31%. The analysis revealed significant effects of TIR (β=-0.771) and GRI (β=0.651) on HbA1c. Furthermore, GRI and TIR strongly correlated (β=-0.953).

Discussion and conclusion

New parameters generated from the ambulatory glucose profile (AGP) can help clinicians create a complete picture of a patient's metabolic control in relation to HbA1c levels. Additionally, the GRI is a mathematically tailored parameter that incorporates all components of the ambulatory glucose profile and demonstrates strong correlations with laboratory-measured HbA1c and TIR. The GRI potentially can become a valuable statistical parameter for evaluating and managing patients in routine clinical practice.

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.

Continuous Glucose Monitoring Metrics and Hemoglobin A1c Relationship in Patients with Type 2 Diabetes Treated by Hemodialysis

Background:There is a need for accurate glycemic control metrics in patients with diabetes and end-stage kidney disease (ESKD). Hence, we assessed the relationship of continuous glucose monitoring (CGM) metrics and laboratory-measured hemoglobin A1c (HbA1c) in patients with type 2 diabetes (T2D) treated by hemodialysis. Methods: This prospective observational study included adults (age 18-80 years) with T2D (HbA1c 5%-12%), treated by hemodialysis (for at least 90 days). Participants used a Dexcom G6 Pro CGM for 10 days. Correlation analyses between CGM metrics [mean glucose, glucose management indicator (GMI), and time-in-range (TIR 70-180 mg/dL)] and HbA1c were performed. Results: Among 59 participants (mean age was 57.7 ± 9.3 years, 58% were female, 86% were non-Hispanic blacks), the CGM mean glucose level was 188.9 ± 45 mg/dL (95% CI: 177.2, 200.7), the mean HbA1c and GMI were 7.1% ± 1.3% and 7.8% ± 1.1%, respectively (difference 0.74% ± 0.95). GMI had a strong negative correlation with TIR 70-180 mg/dL (r = -0.96). The correlation between GMI and HbA1c (r = 0.68) was moderate. Up to 29% of participants had a discordance between HbA1c and GMI of <0.5%, with 22% having a discordance between 0.5% and 1%, and 49% having a discordance of >1%. Conclusions: In patients with diabetes and ESKD treated by hemodialysis, the GMI has a strong correlation with TIR, while HbA1c underestimated the average glucose and GMI. Given the limitations of HbA1c in this population, GMI or mean glucose and TIR may be considered as more appropriate glucose control markers.

Assessing Patterns of Continuous Glucose Monitoring Use and Metrics of Glycemic Control in Type 1 Diabetes and Type 2 Diabetes Patients in the Veterans Health Care System: Integrating Continuous Glucose Monitoring Device Data with Electronic Health Records Data

Objective: To integrate long-term daily continuous glucose monitoring (CGM) device data with electronic health records (EHR) for patients with type 1 and type 2 diabetes (T1D and T2D) in the national Veterans Affairs Healthcare System to assess real-world patterns of CGM use and the reliability of EHR-based CGM information. Research Design and Methods: This observational study used Dexcom CGM device data linked with EHR (from 2015 to 2020) for a large national cohort of patients with diabetes. We tracked the initiation and consistency of CGM use, assessed concordance of CGM use and measures of glucose control between CGM device data and EHR records, and examined results by age, ethnicity, and diabetes type. Results: The time from pharmacy release of CGM to patients to initiation of uploading CGM data to Dexcom servers averaged 3 weeks but demonstrated wide variation among individuals; importantly, this delay decreased markedly over the later years. The average daily wear time of CGM exceeded 22 h over nearly 3 years of follow-up. Patterns of CGM use were generally consistent across age, race/ethnicity groups, and diabetes type. There was strong concordance between EHR-based estimates of CGM use and Dexcom CGM wear time and between estimates of glucose control from both sources. Conclusions: The study demonstrates our ability to reliably integrate CGM devices and EHR data to provide valuable insights into CGM use patterns. The results indicate in the real-world environment that CGM is worn consistently over many years for both patients with T1D and T2D within the Veterans Affairs Healthcare System and is similar across major race/ethnic groups and age-groups.

Associations Between HbA1c and Glucose Time in Range Using Continuous Glucose Monitoring in Type 1 Diabetes: Cross-Sectional Population-Based Study

INTRODUCTION

Continuous glucose monitoring (CGM) introduces novel indicators of glycemic control.

METHODS

This cross-sectional study, based on the Swedish National Diabetes Register, examines 27,980 adults with type 1 diabetes. It explores the relationships between HbA1c (glycated hemoglobin) and various CGM-derived metrics, including TIR (time in range, representing the percentage of time within the range of 4-10 mmol/l for 2 weeks), TAR (time above range), TBR (time below range), mean glucose, standard deviation (SD), and coefficient of variation (CV). Pearson correlation coefficients and linear regression models were utilized for estimation.

RESULTS

The analysis included 46% women, 30% on insulin pump, 7% with previous coronary heart disease and 64% with retinopathy. Mean ± SD values were age 48 ± 18 years, diabetes duration 25 ± 16 years, HbA1c 58.8 ± 12.8 mmol/mol, TIR 58.8 ± 19.0%, TAR 36.3 ± 20.0%, TBR 4.7 ± 5.4%, mean sensor glucose 9.2 ± 2.0 mmol/l, SD 3.3 ± 1.0 mmol/l, and CV 36 ± 7%. The overall association between HbA1c and TIR was - 0.71 (Pearson's r), with R2 0.51 in crude linear regression and 0.57 in an adjusted model. R2 values between HbA1c and CGM mean glucose were 0.605 (unadjusted) 0.619 (adjusted) and TAR (unadjusted 0.554 and fully adjusted 0.568, respectively), while fully adjusted R2 values were 0.458, 0.175 and 0.101 between HbA1c and CGM SD, CGM CV and TBR, respectively.

CONCLUSIONS

This descriptive study demonstrates that the degree of association between HbA1c and new and readily available CGM-derived metrics, i.e., time in range (TIR), time above range (TAR), and CGM mean glucose, is robust in assessing the management of individuals with type 1 diabetes in clinical settings. Metrics from CGM that pertain to variability and hypoglycemia exhibit only weak correlations with HbA1c.

Association between continuous glucose monitoring metrics and clinical outcomes in adults with type 1 diabetes in a real-world setting

AIMS

Continuous glucose monitoring (CGM) metrics can assist diabetes management. Consensus statements recommend > 70 % time in range (TIR) and ≤ 36 % glucose coefficient of variation (CV). However, how these targets perform in clinical practice is unknown. This retrospective, longitudinal cohort study analyzed relationships between TIR, CV, glycated hemoglobin (HbA1c), and hypoglycemia in a real-world setting.

METHODS

Data of 542 adults with type 1 diabetes who used CGM (January 2014-July 2020) were analyzed. Associations between TIR and HbA1c at the same and subsequent visits, incidence rate ratios (IRRs) for hypoglycemia at different CVs, and number of hypoglycemic events at cross-sections of HbA1c and CV were estimated by regression.

RESULTS

TIR was inversely related to HbA1c; for every 10 % increase in TIR, HbA1c was significantly reduced by 0.34 % (4 mmol/mol) and 0.20 % (2 mmol/mol) at the same and subsequent visits, respectively. Level 2 hypoglycemia was significantly reduced at CV < 30 %, 30-33 %, 33.1-36 %, and 36.1-40 %: adjusted IRRs vs CV ≥ 40.1 % of 0.14, 0.28, 0.32, and 0.50, respectively. Hypoglycemic events were reduced at lower CV across HbA1c levels and at higher HbA1c across CV levels.

CONCLUSION

This study quantifies HbA1c improvements with increased TIR and hypoglycemia reductions with improved CV in clinical practice.

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.

Optimal Coefficient of Variance Threshold to Minimize Hypoglycemia Risk in Individuals with Well-Controlled Type 1 Diabetes Mellitus

BACKGRUOUND

This study investigated the optimal coefficient of variance (%CV) for preventing hypoglycemia based on real-time continuous glucose monitoring (rt-CGM) data in people with type 1 diabetes mellitus (T1DM) already achieving their mean glucose (MG) target.

METHODS

Data from 172 subjects who underwent rt-CGM for at least 90 days and for whom 439 90-day glycemic profiles were available were analyzed. Receiver operator characteristic analysis was conducted to determine the cut-off value of %CV to achieve time below range (%TBR)<54 mg/dL <1 and =0.

RESULTS

Overall mean glycosylated hemoglobin was 6.8% and median %TBR<54 mg/dL was 0.2%. MG was significantly higher and %CV significantly lower in profiles achieving %TBR<54 mg/dL <1 compared to %TBR<54 mg/dL ≥1 (all P<0.001). The cut-off value of %CV for achieving %TBR<54 mg/dL <1 was 37.5%, 37.3%, and 31.0%, in the whole population, MG >135 mg/dL, and ≤135 mg/dL, respectively. The cut-off value for %TBR<54 mg/dL=0% was 29.2% in MG ≤135 mg/dL. In profiles with MG ≤135 mg/dL, 94.2% of profiles with a %CV <31 achieved the target of %TBR<54 mg/dL <1, and 97.3% with a %CV <29.2 achieved the target of %TBR<54 mg/ dL=0%. When MG was >135 mg/dL, 99.4% of profiles with a %CV <37.3 achieved %TBR<54 mg/dL <1.

CONCLUSION

In well-controlled T1DM with MG ≤135 mg/dL, we suggest a %CV <31% to achieve the %TBR<54 mg/dL <1 target. Furthermore, we suggest a %CV <29.2% to achieve the target of %TBR<54 mg/dL =0 for people at high risk of hypoglycemia.

Beyond HbA1c: Identifying Gaps in Glycemic Control Among Children and Young People with Type 1 Diabetes Using Continuous Glucose Monitoring

OBJECTIVES

To describe continuous glucose monitoring (CGM) derived glycemic variables, and study their association with HbA1c and socio-economic factors in young people with Type 1 diabetes mellitus (T1DM).

METHODS

Ninety-two participants [age 15.7 ± 5.0 y (mean ± SD), HbA1c 8.0 ± 1.5% (mean ± SD)] wore a professional CGM sensor for 14 d.

RESULTS

Median (IQR) time in range (TIR) was 41 (18)%. Participants spent 41 ± 20% of their day in hyperglycemia (>180 mg/dl), and 14 (13)% in hypoglycemia (<70 mg/dl). High glycemic variability (percent CV >36%) was seen in 92% participants. Older age at diagnosis was associated with higher TIR (β = 0.267, p = 0.01), lower time above range (TAR) (β = -0.352, p <0.001), but higher time below range (TBR) (β = 0.274, p = 0.006). The use of NPH vs. glargine basal insulin was associated with higher TBR (β = -0.262, p = 0.009) but lower TAR (β = 0.202, p = 0.041). HbA1c showed negative correlation with TIR (r = -0.449, p <0.001) and TBR (r = -0.466, p <0.001) and positive correlation with TAR (r = 0.580, p <0.001) and mean glucose (r = 0.589, p <0.001).

CONCLUSIONS

These data demonstrate wide gaps between the recommended vs. real world glycemic variables in patients with T1DM in this region on multiple daily insulin injections. CGM identifies glycemic variability and complements HbA1c in improving glycemic control.

Association between continuous glucose monitoring-derived glycemic control indices and urinary biomarkers of diabetic kidney disease: Hyogo Diabetes Hypoglycemia Cognition Complications study

AIMS

Glomerular damage and proximal tubular damage play an important role in the pathogenesis of diabetic kidney disease. This study aimed to investigate the relationship between the urinary markers of proximal tubular injury, including urinary liver-type fatty acid-binding protein-to-creatinine ratio (uL-FABP/Cr) and urinary N-acetyl-β-D-glucosaminidase-to-creatinine ratio (uNAG/Cr), and glycemic control status.

METHODS

This cross-sectional study included 245 and 39 patients with type 2 diabetes mellitus (T2DM) and non-T2DM (NDM), respectively. The participants of this study were fitted with retrospective CGM, and glycemic control indices, such as time in range (TIR) and glycemia risk index (GRI), were calculated.

RESULTS

The results were presented as medians (interquartile ranges). The uL-FABP/Cr was significantly higher in the microalbuminuria than in the normo-albuminuria group [4.2 (2.7-7.1) and 2.2 (1.4-3.4) μg/gCr, respectively, P < 0.001], while the uNAG/Cr in the normo-albuminuria group [6.3 (4.5-10.1) U/gCr] was significantly higher than that in the NDM group [5.3 (3.8-6.3) U/gCr, P = 0.048] but significantly lower than that in the microalbuminuria group [9.2 (6.4-11.1) U/gCr, P = 0.004]. The multivariate logistic regression analysis indicated that CGM-derived TIR was significantly associated with the urinary albumin-to-creatinine ratio [uAlb/Cr, odds ratio (OR) 0.985, 95% confidence interval (CI) 0.971-0.998, P = 0.029] and uNAG/Cr (OR 0.973, 95% CI 0.957-0.989, P = 0.001) independent of renal function. GRI was similarly associated with uAlb/Cr and uNAG/Cr.

CONCLUSION

The findings of this study indicated that uNAG/Cr was elevated before albuminuria development and was associated with CGM-derived TIR and GRI.

Short-term recovery of insulin secretion in response to a meal is associated with future glycemic control in type 2 diabetes patients

AIMS/INTRODUCTION

Endogenous insulin secretion could be recovered by improving hyperglycemia in patients with type 2 diabetes. This study aimed to investigate the association between short-term recovery of insulin secretion during hospitalization and clinical background or future glycemic control in patients with type 2 diabetes.

MATERIALS AND METHODS

A total of 127 patients with type 2 diabetes were included. The recovery of endogenous insulin secretion was determined using the following indices: index A: fasting C-peptide index (CPI) at discharge - fasting CPI on admission; index B: postprandial CPI at discharge - postprandial CPI on admission; and index C: Δ C-peptide immunoreactivity (CPR) (postprandial CPR - fasting CPR) at discharge - ΔCPR on admission. We examined the associations of each index with clinical background and future glycemic control measured by glycosylated hemoglobin and continuous glucose monitoring.

RESULTS

Using index A and B, the age was significantly younger, whereas BMI and visceral fat area were significantly higher in the high-recovery group than in the low-recovery group. Changes in glycosylated hemoglobin levels were significantly greater at 6 and 12 months in the high-recovery group in the analysis of index C. The receiver operating characteristic curve analysis identified the index B and index C as indicators to predict glycosylated hemoglobin <7.0% at 6 months after discharge. Furthermore, index C was positively correlated with the time in the target glucose range, and inversely correlated with the standard deviation of glucose at 3 and 12 months after discharge.

CONCLUSIONS

Short-term recovery of insulin secretion in response to a meal during hospitalization, evaluated with the index-C, might predict future glycemic control.

Determination of Time in Range Associated With HbA1c ≤7% in a Prospective Cohort of Patients With Type 1 Diabetes Using Continuous Glucose Monitoring for Three Months

INTRODUCTION

Finding a goal of time in range (%TIR) that defines good glycemic control is necessary. Previous retrospective studies suggest good concordance between HbA1c ≤7% with a TIR >70%; however, the studies that included the largest number of patients used blood glucose measurement data with a follow-up time of less than 90 days. This study defined the TIR value that best discriminates HbA1c ≤7%.

METHODS

We performed a prospective study of diagnostic tests based on a cohort of patients with type 1 diabetes (T1D) treated with a hybrid closed loop (HCL) followed for three months. The ability of %TIR to distinguish patients with HbA1c ≤7% was evaluated through receiver operating characteristic curve analysis. We determined the %TIR cutoff point with the best operating characteristics.

RESULTS

A total of 118 patients were included (58.1% women, 47% overweight or obese, and 33% with high glycemic variability). A moderate negative correlation (R = -.54, P < .001) was found between %TIR and HbA1c. The discrimination ability was moderate, with an area under the curve of 0.7485 (95% confidence interval = 0.6608-0.8363). The cutoff point that best predicted HbA1c ≤7% was %TIR ≥75.5 (sensitivity 70%, specificity 67%). The findings were similar among those with a coefficient of variation (CV%) ≥36%.

CONCLUSIONS

Our data suggest that the %TIR adequately identifies patients with HbA1c ≤7%. A target of TIR ≥75%, rather than the currently recommended TIR ≥70%, may be a more suitable value for optimal glycemic control.

Scans per day as predictors of optimal glycemic control in people with type 1 diabetes mellitus using flash glucose monitoring: what number of scans per day should raise a red flag?

AIMS

This study aimed to determine the minimum frequency of flash glucose monitoring (FGM) scans necessary for optimal glycemic control in patients with type 1 diabetes (T1D).

METHODS

Data were collected from 692 patients (47.5% female, with a median age of 47.4 years) who used FGM systems daily and recorded their clinical variables and device data.

RESULTS

Logistic regression models showed that performing more than 12 scans per day was associated with improved T1D control (OR = 4.22, p < 0.001) and a reduction in HbA1c (7.6 vs 7.0%, 60-53 mmol/mol p < 0.001). However, those performing less than 6 scans showed no improvement in HbA1c (7.9 vs 7.8%, 63-61 mmol/mol p = 0.514). Thirteen daily scans were determined as the optimal cutoff point for predicting optimal glycemic control using a maximally selected rank algorithm. Significant reductions were observed in mean glucose (< 0.001), coefficient of variation (< 0.001), HbA1c (< 0.001), and an increase in TIR (< 0.001) in patients who performed more than 12 daily scans.

CONCLUSIONS

The results suggest that a higher frequency of daily scans by T1D patients using FGM systems leads to improved chronic glycemic control. The minimum recommended frequency for optimal control is 13 scans per day, and more than 6 daily scans are needed to improve HbA1c.

Optimizing Glycemic Outcomes for Children with Type 1 Diabetes

Changes in physical growth, neurocognitive development, and pubertal maturation are some of the challenges to achieving blood glucose targets in children with type 1 diabetes mellitus. To optimize glycemic outcomes, a comprehensive approach is crucial to address psychosocial needs, expand the use of diabetes technology, and diminish health inequities.

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.

The Health Economics of Automated Insulin Delivery Systems and the Potential Use of Time in Range in Diabetes Modeling: A Narrative Review

Intensive therapy with exogenous insulin is the treatment of choice for individuals living with type 1 diabetes (T1D) and some with type 2 diabetes, alongside regular glucose monitoring. The development of systems allowing (semi-)automated insulin delivery (AID), by connecting glucose sensors with insulin pumps and algorithms, has revolutionized insulin therapy. Indeed, AID systems have demonstrated a proven impact on overall glucose control, as indicated by effects on glycated hemoglobin (HbA1c), risk of severe hypoglycemia, and quality of life measures. An alternative endpoint for glucose control that has arisen from the use of sensor-based continuous glucose monitoring is the time in range (TIR) measure, which offers an indication of overall glucose control, while adding information on the quality of control with regard to blood glucose level stability. A review of literature on the health-economic value of AID systems was conducted, with a focus placed on the growing place of TIR as an endpoint in studies involving AID systems. Results showed that the majority of economic evaluations of AID systems focused on individuals with T1D and found AID systems to be cost-effective. Most studies incorporated HbA1c, rather than TIR, as a clinical endpoint to determine treatment effects on glucose control and subsequent quality-adjusted life year (QALY) gains. Likely reasons for the choice of HbA1c as the chosen endpoint is the use of this metric in most validated and established economic models, as well as the limited publicly available evidence on appropriate methodologies for TIR data incorporation within conventional economic evaluations. Future studies could include the novel TIR metric in health-economic evaluations as an additional measure of treatment effects and subsequent QALY gains, to facilitate a holistic representation of the impact of AID systems on glycemic control. This would provide decision makers with robust evidence to inform future recommendations for health care interventions.

Early Real-World Performance of the MiniMed™ 780G Advanced Hybrid Closed-Loop System and Recommended Settings Use in the United States

Background: The MiniMed™ 780G system (MM780G) with Guardian™ 4 sensor includes a 100 mg/dL glucose target (GT) and automated insulin corrections up to every 5 min and was recently approved for use in the United States. In the present study, early real-world MM780G performance and the use of recommended system settings (100 mg/dL GT with an active insulin time of 2 h), by individuals with type 1 diabetes, were evaluated. Methods: CareLink™ personal data uploaded between the launch of the MM780G to August 22, 2023 were aggregated and underwent retrospective analysis (based on user consent) and if users had ≥10 days of continuous glucose monitoring (CGM) data. The 24-h day CGM metrics, including mean glucose, percentage of time spent in (%TIR), above (%TAR), and below (%TBR) target range (70-180 mg/dL), in addition to delivered insulin and closed-loop (CL) exits, were compared between an overall group (n = 7499) and individuals who used recommended settings (each, for >95% of the time). An analysis of the same metrics for MiniMed™ 770G system (MM770G) users (n = 3851) who upgraded to the MM780G was also conducted (paired t-test or Wilcoxon signed-rank test, P < 0.05 considered statistically significant). Results: For MM780G users, CGM use, and time in CL were >90% and all MM780G CGM metrics exceeded consensus-recommended goals. With recommended settings (22% of all users), mean %TIR and %TITR (70-140 mg/dL) were 81.4% and 56.4%, respectively. For individuals who upgraded from the MM770G, %TIR and %TITR increased from 73.2% to 78.3% and 45.8% to 52.6%, respectively, while %TAR reduced from 25.1% to 20.2% (P < 0.001, for all three). CL exits/week averaged <1, for all MM780G users. Conclusions: Early real-world MM780G use in the United States demonstrated a high percentage of time in range with low time above and below range. These outcomes are similar to those observed for real-world MM780G use in other countries.

Smart connected insulin dose monitoring technologies versus standard of care: a Canadian cost-effectiveness analysis

Aim: There is growing interest in novel insulin management systems that improve glycemic control. This study aimed to evaluate the cost-effectiveness of smart connected insulin re-usable pens or caps for disposable insulin pens versus pens without connected capabilities in the management of adult patients with Type 1 diabetes (T1DM) from a Canadian societal perspective. Materials & methods: The IQVIA Core Diabetes Model was utilized to conduct the analyses. Applying data from a non-interventional study, the connected insulin device arm was assumed to result in greater reductions (-0.67%) in glycated hemoglobin from baseline and fewer non-severe hypoglycemic events (-32.87 events/patient annually). Macro- and micro-vascular risks were predicted using the Epidemiology of Diabetes Interventions and Complications study data. Direct and indirect costs and utilities were sourced from literature. Key model outcomes included life years and quality-adjusted life-years (QALYs). Both costs and effects were annually discounted at 1.5% over a 60-year time horizon. Uncertainty was explored in scenario and probabilistic sensitivity analyses (PSA). Results: The connected insulin pen device was associated with lower mean discounted total costs (CAD221,943 vs 266,199; -CAD44,256), improvement in mean life expectancy (25.78 vs 24.29; +1.49 years) and gains in QALYs (18.48 vs 16.74; +1.75 QALYs) over the patient's lifetime. Most scenario analyses confirmed the base case results. The PSA showed dominance in 99.5% of cases. Conclusion: For adults with T1DM in Canada, a connected insulin pen device is likely to be a cost-effective treatment option associated with greater clinical benefits and lower costs relative to a standard re-usable or disposable pen.

A Systematic Literature Review of Psychological Interventions for Adults with Type 1 Diabetes

INTRODUCTION

The psychological burden of type 1 diabetes mellitus (T1DM) is considerable. The condition affects the daily lives of adults living with T1DM (ALWT1DM) in many ways. International guidelines highlight the importance of providing psychological support to ALWT1DM to improve health outcomes and well-being.

METHODS

We conducted a systematic literature review of randomised controlled trials (RCTs) to identify the evidence on the impact of psychological interventions on glycaemic control and psychological outcomes in ALWT1DM. Literature searches of Medline, Embase, Cochrane Central Register of Controlled Trials, PsycInfo, and the grey literature were performed to identify relevant RCTs, published in English, from 2001 onward. Fourteen RCTs of ten psychological interventions in ALWT1DM were eligible and included in the qualitative synthesis. The studies varied considerably in terms of duration, target population, endpoints, and efficacy.

RESULTS

Overall, psychological interventions did not perform significantly better than control treatments in improving glycaemic control, although selected patient groups did report benefits from some psychological intervention types, such as cognitive behavioural therapy. Although most of the psychological interventions produced small, nonsignificant improvements in self-reported patient functioning, some treatments were effective in reducing diabetes distress and improving mental health, even if no impact on glycaemic control was observed.

DISCUSSION

Current guidelines for the treatment of T1DM recommend access to psychological services; however, there is a paucity of high-quality evidence from clinical trials on the effectiveness or preferred structure of psychological support. There is a clear need for more rigorous, large-scale, international research to address the efficacy of psychological interventions in ALWT1DM.

A Minimized Measurement Scheme for Predicting HbA1c Using Discrete Self-Monitoring Blood Glucose Data Within 4 Weeks for People with Type 2 Diabetes

Objective: To establish an accurate and robust calculation model for predicting hemoglobin A1c (HbA1c) for people with type 2 diabetes (T2D) by using the fewest discrete blood glucose values according to an irregular data set and propose an appropriate cost-effective and scientific scheme for routine blood glucose monitoring. Methods: By using two data sets obtained from 2017 to 2022, which involved 2432 people with T2D, ∼420,000 irregular blood glucose values, and 10,000 HbA1c values, multiple blood glucose monitoring schemes were designed and compared to find the optimal one. The data were structured and then fitted using a regularized extreme learning machine, and the results were evaluated on the basis of indicators such as mean absolute error (MAE), root mean square error, and the relevance analysis (R) value; the optimal scheme for routine blood glucose monitoring was determined by combining the accuracy and the cost and was compared with previous studies in terms of accuracy and stability. Results: Data fitting results for the chosen scheme: R = 0.8029 (P < 0.001), MAE = 0.3181% (95% confidence interval, 0.2666-0.3695%). Within the last 4 weeks before the prediction of HbA1c, a minimum of only seven fasting and seven postprandial blood glucose values are needed, of which are one fasting and one postprandial blood glucose values per 4 days. Compared with previous studies, the prediction model shows better accuracy and stability (P < 0.05), especially under the great glucose fluctuation group. Conclusion: A minimized calculation model for accurately and robustly predicting HbA1c using discrete self-monitoring of blood glucose data within 4 weeks for people with T2D has been established and provides a new reference for the design of a scheme for blood glucose monitoring. The diabetes care clinic of Peking University First Hospital (Registration Number: ChiCTR2300068139).

To What Extent Is HbA1c Associated with Glycemic Variability in Patients with Type 1 Diabetes? A Retrospective, Noninterventional Study

BACKGROUND

Glycemic variability (GV) is a novel parameter used in evaluating the quality of diabetes management. Current guidelines recommend the use of GV indexes alongside the traditional parameter to evaluate glycemic control: hemoglobin A1c (HbA1c). This study aims to evaluate the extent to which HbA1c explains the GV phenomena in patients with Type 1 diabetes (T1DM).

METHODS

In 147 patients with T1DM, associations between HbA1c and several GV indexes were analyzed.

RESULTS

Patients with an HbA1c < 7% had a lower median standard deviation of glycemia (60 vs. 48; p < 0.001), a lower coefficient of variation (34.1 vs. 38.0; p < 0.001), and a significantly increased median time in range (78 vs. 58; p < 0.001). HbA1c was positively correlated with the coefficient of variation (r = 0.349; p < 0.001) and the standard deviation (r = 0.656; p < 0.001) but reversely correlated with a lower time in range (r = -0.637; p < 0.001).

CONCLUSIONS

HbA1c only partially explains the GV phenomena in patients with T1DM. The HbA1c value is associated more strongly with the time in range and standard deviation than with the coefficient of variation.

A novel few shot learning derived architecture for long-term HbA1c prediction

Regular monitoring of glycated hemoglobin (HbA1c) levels is important for the proper management of diabetes. Studies demonstrated that lower levels of HbA1c play an essential role in reducing or delaying microvascular difficulties that arise from diabetes. In addition, there is an association between elevated HbA1c levels and the development of diabetes-related comorbidities. The advanced prediction of HbA1c enables patients and physicians to make changes to treatment plans and lifestyle to avoid elevated HbA1c levels, which can consequently lead to irreversible health complications. Despite the impact of such prediction capabilities, no work in the literature or industry has investigated the futuristic prediction of HbA1c using current blood glucose (BG) measurements. For the first time in the literature, this work proposes a novel FSL-derived algorithm for the long-term prediction of clinical HbA1c measures. More importantly, the study specifically targeted the pediatric Type-1 diabetic population, as an early prediction of elevated HbA1c levels could help avert severe life-threatening complications in these young children. Short-term CGM time-series data are processed using both novel image transformation approaches, as well as using conventional signal processing methods. The derived images are then fed into a convolutional neural network (CNN) adapted from a few-shot learning (FSL) model for feature extraction, and all the derived features are fused together. A novel normalized FSL-distance (FSLD) metric is proposed for accurately separating the features of different HbA1c levels. Finally, a K-nearest neighbor (KNN) model with majority voting is implemented for the final classification task. The proposed FSL-derived algorithm provides a prediction accuracy of 93.2%.

Fasting and postprandial plasma glucose contributions to hemoglobin A1c and time in range in people with diabetes on multiple daily injection insulin therapy: Results from the PRONTO-T1D and PRONTO-T2D clinical trials

AIMS

To investigate contributions of changes in fasting plasma glucose (FPG) and postprandial glucose (PPG) to changes in hemoglobin A1c (HbA1c) and time-in-range (TIR, 70-180 mg/dL) in people with type 1 diabetes (T1D) and type 2 diabetes (T2D) treated with multiple daily injections (MDI) of insulin lispro (rapid/ultra-rapid formulations).

METHODS

Multivariate regression models were used to quantify the contributions of FPG and PPG reductions to change in HbA1c and TIR using data from the PRONTO-T1D (N = 1222) and PRONTO-T2D (N = 673) clinical trials. TIR was derived from 10-point self-monitored blood glucose (SMBG) profiles overall, as well as from continuous glucose monitoring (CGM) in the PRONTO-T1D CGM substudy (n = 269/1222).

RESULTS

A 1 mmol/L FPG reduction corresponded with a 0.09-0.12 % (95 % confidence interval [CI] 0.06-0.15 %) HbA1c reduction in PRONTO-T1D and 0.17-0.26 % (95 % CI 0.13-0.30 %) in PRONTO-T2D (both p < 0.0001). A 1 mmol/L PPG reduction corresponded with a 0.05-0.09 % (95 % CI 0.01-0.12 %) HbA1c reduction in PRONTO-T1D (p < 0.001) and 0.10-0.15 % (95 % CI 0.05-0.19 %) in PRONTO-T2D (p < 0.0001). Reductions in FPG and PPG were significantly associated with increased TIR whether derived from SMBG (7.87-12.95 % [95 % CI 6.81-14.23 %]; all p < 0.0001) or CGM (3.35-4.18 % [95 % CI 2.11-5.39 %]; all p < 0.05).

CONCLUSIONS

FPG and PPG significantly impact HbA1c and TIR. Balanced management of both FPG and PPG is important to achieve glycemic goals for people with diabetes on MDI insulin therapy.

CLINICAL TRIALS REGISTRATION

PRONTO-T1D ClinicalTrials.gov identifier: NCT03214367; PRONTO-T2D ClinicalTrials.gov Identifier: NCT03214380.

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.

6. Glycemic Goals and Hypoglycemia: 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.

How to Measure Glycemic Variability? A Literature Review

Optimal glycemic control without the presence of diabetes-related complications is the primary goal for adequate diabetes management. Recent studies have shown that hemoglobin A1c level cannot fully evaluate diabetes management as glycemic fluctuations are demonstrated to have a major impact on the occurrence of diabetes-related micro- and macroangiopathic comorbidities. The use of continuous glycemic monitoring systems allowed the quantification of glycemic fluctuations, providing valuable information about the patients' glycemic control through various indicators that evaluate the magnitude of glycemic fluctuations in different time intervals. This review highlights the significance of glycemic variability by describing and providing a better understanding of common and alternative indicators available for use in clinical practice.

Technology use and clinical outcomes in a racial-ethnic minority cohort of children and adolescents with type 1 diabetes

OBJECTIVES

Technology use has been shown to improve diabetes control, but minority youths tend to have low rates of technology use and exhibit suboptimal glycemic control. We examined the impact of continuous glucose monitors (CGM) and continuous subcutaneous insulin infusion (CSII) on glycemic control in a racial-ethnic minority cohort of children and adolescents with type 1 diabetes (T1D).

METHODS

A cross-sectional study was conducted among 140 pediatric T1D patients seen at a multidisciplinary clinic. From January to November 2022, data on demographics and glycated hemoglobin (HbA1c) levels were collected. Patients were categorized as technology (CGM, CSII, or both) or non-technology users (finger stick meter (FS) and multiple daily injections (MDI)).

RESULTS

The majority identified as Hispanic (79 %) and had public health insurance (71 %). Sixty-nine percent used technology. Compared with non-technology users, technology users had significantly lower mean HbA1c levels (9.60 vs. 8.40 %, respectively) (p=0.0024), though no group (CGM + CSII, CGM + MDI, FS + CSII, and FS + MDI) achieved a mean HbA1c level of <7.0 %. Regarding minority status, no significant differences in mean HbA1c levels existed between Hispanics and Blacks in the CGM + MDI and FS + CSII groups (p=0.2232 and p=0.9224, respectively). However, there was a significant difference in mean HbA1c levels between Hispanic and Black non-technology users (9.19 vs. 11.26 %, respectively) (p=0.0385).

CONCLUSIONS

Technology users demonstrated better glycemic control than non-technology users. Further research is needed to investigate factors affecting glycemic control in minority youths with T1D.

Impact of glucose variability on the assessment of the glycemia risk index (GRI) and classic glycemic metrics

OBJECTIVE

To evaluate the impact of glucose variability on the relationship between the GRI and other glycemic metrics in a cohort of pediatric and adult patients with type 1 diabetes (T1D) using intermittent scanning continuous glucose monitoring (isCGM).

METHODS

We performed a cross-sectional study of 202 patients with T1D under intensive insulin treatment (25.2% CSII) using isCGM. Clinical, metabolic, and glycemic metrics were collected, and the GRI was calculated with its hypoglycemia (CHypo) and hyperglycemia (CHyper) components. The correlation between the GRI and other classical glycometrics in relation to the coefficient of variation (CV) was evaluated.

RESULTS

A total of 202 patients were included (53% male; 67.8% adults) with a mean age of 28.6 ± 15.7 years and 12.5 ± 10.9 years of T1D evolution (TIR 59.0 ± 17.0%; CV 39.8 ± 8.0%; GMI 7.3 ± 1.1%). The mean GRI was 54.0 ± 23.3 with a CHypo and CHyper component of 5.7 ± 4.8 and 23.4 ± 14.3, respectively. A strong negative correlation was observed between the GRI and TIR (R = -0.917; R2 = 0.840; p < 0.001), showing differences when dividing patients with low glycemic variability (CV < 36%) (R = -0.974; R2 = 0.948; p < 0.001) compared to those with greater CV instability (≥36%) (R = -0.885; R2 = 0.784; p < 0.001). The relationship of GRI with its two components was strongly positive with CHyper (R = 0.801; R2 = 0.641; p < 0.001) and moderately positive with CHypo (R = 0.398; R2 = 0.158; p < 0.001). When the GRI was evaluated with the rest of the classic glycemic metrics, a strong positive correlation was observed with HbA1c (R = 0.617; R2 = 0.380; p < 0.001), mean glucose (R = 0.677; R2 = 0.458; p < 0.001), glucose standard deviation (R = 0.778; R2 = 0.605; p < 0.001), TAR > 250 (R = 0.801; R2 = 0.641; p < 0.001), and TBR < 54 (R = 0.481; R2 = 0.231; p < 0.001).

CONCLUSIONS

The GRI correlated significantly with all the glycemic metrics analyzed, especially with the TIR. Glycemic variability (GV) significantly affected the correlation of the GRI with other parameters and should be taken into consideration.

Automated Insulin Delivery Systems in Children and Adolescents With Type 1 Diabetes: A Systematic Review and Meta-analysis of Outpatient Randomized Controlled Trials

BACKGROUND

The glycemic control of automated insulin delivery (AID) systems in outpatient children and adolescents with type 1 diabetes (T1D) has not been systematically evaluated.

PURPOSE

To evaluate the efficacy and safety of AID systems in children and adolescents in outpatient settings.

DATA SOURCES

PubMed, Embase, the Cochrane Central Register of Controlled Trials, and ClinicalTrials.gov were searched until 4 May 2023. This study was registered with PROSPERO (2023, CRD42023395252).

STUDY SELECTION

Randomized controlled trials that compared AID systems with conventional insulin therapy in outpatient children and adolescents with T1D and reported continuous glucose monitoring outcomes were selected.

DATA EXTRACTION

Percent time in range (TIR) (3.9-10 mmol/L), time below range (TBR) (<3.9 mmol/L), and time above range (TAR) (>10 mmol/L) were extracted. Data were summarized as mean differences (MDs) with 95% CIs.

DATA SYNTHESIS

Twenty-five trials (1,345 participants) were included in the meta-analysis. AID systems were associated with an increased percentage of TIR (MD, 11.38% [95% CI 9.01-13.76], P < 0.001; high certainty). The favorable effect was consistent whether AID was used over 3 months (10.46% [8.71-12.20]) or 6 months (10.87% [7.11-14.63]). AID systems had a favorable effect on the proportion of TBR (-0.59% [-1.02 to -0.15], P = 0.008; low certainty) or TAR (-12.19% [-14.65 to -9.73], P < 0.001; high certainty) compared with control treatment.

LIMITATIONS

Substantial heterogeneity was observed in most analyses.

CONCLUSIONS

AID systems are more effective than conventional insulin therapy for children and adolescents with T1D in outpatient settings. The favorable effect is consistent both in the short term and long term.

Comparison of Glycemia Risk Index with Time in Range for Assessing Glycemic Quality

Background: The glycemia risk index (GRI) is a novel composite continuous glucose monitoring (CGM) metric that gives greater weight to hypoglycemia than to hyperglycemia and to extreme hypo/hyperglycemia over less extreme hypo/hyperglycemia. This study aimed at validating the effectiveness of GRI and at comparing it with time in range (TIR) in assessing glycemic quality in clinical practice. Methods: A total of 524 ninety-day CGM tracings of 194 insulin-treated adults with diabetes were included in the analysis. GRI was assessed according to standard metrics in ambulatory glucose profiles. Both cross-sectional and longitudinal analyses were performed to compare the GRI and TIR. Results: The GRI was strongly correlated not only with TIR (r = -0.974), but also with the coefficient of variation (r = 0.683). To identify whether the GRI differed by hypoglycemia even with a similar TIR, CGM tracings were grouped according to TIR (50% to <60%, 60% to <70%, 70% to <80%, and ≥80%). In each TIR group, the GRI increased as time below range (TBR)<70 mg/dL increased (P < 0.001 for all TIR groups). In longitudinal analysis, as TBR<70 mg/dL improved, the GRI improved significantly (P = 0.003) whereas TIR did not (P = 0.704). Both GRI and TIR improved as time above range (TAR)>180 mg/dL improved (P < 0.001 for both). The longitudinal change was easily identifiable on a GRI grid. Conclusions: The GRI is a useful tool for assessing glycemic quality in clinical practice and reflects hypoglycemia better than does TIR.

CamAPS FX Hybrid Closed-Loop with Ultra-Rapid Lispro Compared with Standard Lispro in Adults with Type 1 Diabetes: A Double-Blind, Randomized, Crossover Study

Introduction: To evaluate hybrid closed-loop with ultra-rapid insulin lispro (Lyumjev) compared with hybrid closed-loop with standard insulin lispro in adults with type 1 diabetes. Materials and Methods: In a single-center, double-blind, randomized, crossover study, 28 adults with type 1 diabetes (mean ± standard deviation [SD]: age 44.5 ± 10.7 years, glycated hemoglobin (HbA1c) 7.1 ± 0.9% [54 ± 10 mmol/mol]) underwent two 8-week periods comparing hybrid closed-loop with ultra-rapid insulin lispro and hybrid closed-loop with standard insulin lispro in random order. The same CamAPS FX closed-loop algorithm was used in both periods. Results: In an intention-to-treat analysis, the proportion of time sensor glucose was in target range (3.9-10 mmol/L [70-180 mg/dL]; primary endpoint) was greater with ultra-rapid lispro compared with standard insulin lispro (mean ± SD: 78.7 ± 9.8% vs. 76.2 ± 9.6%; mean difference 2.5 percentage points [95% confidence interval 0.8 to 4.2]; P = 0.005). Mean sensor glucose was lower with ultra-rapid lispro compared with standard insulin lispro (7.9 ± 0.8 mmol/L [142 ± 14 mg/dL] vs. 8.1 ± 0.9 mmol/L [146 ± 16 mg/dL]; P = 0.048). The proportion of time with sensor glucose <3.9 mmol/L [70 mg/dL] was similar between interventions (median [interquartile range] ultra-rapid lispro 2.3% [1.3%-2.7%] vs. standard insulin lispro 2.1% [1.4%-3.3%]; P = 0.33). No severe hypoglycemia or ketoacidosis occurred. Conclusions: The use of ultra-rapid lispro with CamAPS FX hybrid closed-loop increases time in range and reduces mean glucose with no difference in hypoglycemia compared with standard insulin lispro in adults with type 1 diabetes. ClinicalTrials.gov: Trial registration number NCT05257460.

Time in range and complications of diabetes: a cross-sectional analysis of patients with Type 1 diabetes

BACKGROUND/ OBJECTIVE

To evaluate the association of CGM parameters and HbA1c with diabetes complications in patients with Type 1 Diabetes (T1D).

METHODS

Patients with T1D using the CGM system Freestyle Libre were included in this analysis. The association of CGM-metrics and HbA1c with diabetes complications (any complication, microvascular complications, or macrovascular complications) was assessed using logistic regression unadjusted and adjusted for age, sex, and diabetes duration (model 1), and further adjusted for hypertension and dyslipidemia (model 2).

RESULTS

One hundred and sixty-one patients with T1D were included. The mean (± SD) age was 37.4 ± 13.4 years old and the median T1D duration was 17.7 ± 10.6 years. Time in range (TIR) was associated with any complication and microvascular complications in the unadjusted model and in the adjusted models. TIR was associated with retinopathy in the unadjusted model as well as in model 1, and was associated with macrovascular complications only in the unadjusted model. HbA1c was associated with any complications, microvascular complications, and retinopathy in the unadjusted model but not in the adjusted models. HbA1c was associated with macrovascular complications in the unadjusted model and in the adjusted model 1.

CONCLUSIONS

In this cross-sectional analysis of patients with T1D using intermittent scanned CGM, TIR, and HbA1c were associated with complications of diabetes. TIR may be a better predictor than HbA1c of any complication and microvascular complications, while HbA1c may be a better predictor of macrovascular complications.

Effects of mulberry twig alkaloids(Sangzhi alkaloids) and metformin on blood glucose fluctuations in combination with premixed insulin-treated patients with type 2 diabetes

Introduction

We aimed to evaluated the effect of premixed insulin (Ins), premixed insulin combined with metformin (Ins+Met) or mulberry twig alkaloids(Ins+SZ-A) on blood glucose fluctuations in patients with type 2 diabetes (T2DM) using continuous glucose monitors (CGM).

Methods

Thirty patients with T2DM and poor blood glucose control using drugs were evaluated for eligibility during the screening period. Subsequently, their original hypoglycemic drugs were discontinued during the lead-in period, and after receiving Ins intensive treatment for 2 weeks, they were randomly assigned to receive either Ins, Ins+Met, or Ins+SZ-A treatment for the following 12 weeks. The main efficacy endpoint comprised changes in their CGM indicators changes (mean blood glucose level [MBG], standard deviation of blood glucose [SDBG], mean amplitude of glycemic excursions [MAGE], postprandial glucose excursions [PPGE], the largest amplitude of glycemic excursions [LAGE], mean of daily difference [MODD], time in range between 3.9-10.0 mmol/L [TIR] and area under the curve for each meal [AUCpp]) during the screening, lead-in, and after 12-week treatment period. Changes in glycosylated hemoglobin (HbA1c), fasting blood glucose (FBG), 1-h postprandial blood glucose (1h-PBG), 2-h postprandial blood glucose (2h-PBG), fasting blood lipids and postprandial blood lipids were also measured at baseline and after 12 weeks of treatment.

Results

The CGM indicators of the three groups during the lead-in period all showed significant improvements compared to the screening period (P<0.05). Compared with those in the lead-in period, all of the CGM indicators improved in the the Ins+Met and Ins+SZ-A groups after 12 weeks of treatment (P<0.05), except for MODD. After 12-week treatment, compared with the Ins group, Ins+Met and Ins+SZ-A groups showed improved MBG, SDBG, TIR, breakfast AUCpp,lunch AUCpp, HbA1c, FBG, 1h-PBG, fasting blood lipid and postprandial blood lipid indicators (P<0.05). Further, the LAGE, PPGE, MAGE, dinner AUCpp and 2h-PBG levels of the Ins+SZ-A group were significantly lower than those of the Ins+Met and Ins groups (P<0.05).

Conclusion

Our findings highlight the efficacy of combination therapy (Ins+SZ-A or Ins+Met) in improving blood glucose fluctuations, as well as blood glucose and lipid levels. Ins+SZ-A reduces postprandial blood glucose fluctuations more than Ins+Met and Ins groups.

Trial registration number

ISRCTN20835488.

Twelve-month results of the ADAPT randomized controlled trial: Reproducibility and sustainability of advanced hybrid closed-loop therapy outcomes versus conventional therapy in adults with type 1 diabetes

AIMS

To reassess the 6-month efficacy and to assess the 12-month sustained efficacy of the MiniMed™ 780G advanced hybrid closed-loop automated insulin delivery (AID) system compared to multiple daily injections plus intermittently scanned glucose monitoring (MDI+isCGM) in people with type 1 diabetes not meeting glucose targets.

METHODS

The ADAPT study was a prospective, multicentre, open-label, randomized control trial in people with type 1 diabetes, with a glycated haemoglobin (HbA1c) concentration of at least 8.0% (64 mmol/mol), on MDI+isCGM therapy. After a 6-month study phase, participants randomized at baseline to MDI+isCGM switched to AID (SWITCH) while the others continued AID therapy (SUSTAIN) for an additional 6 months. The primary endpoint of this continuation phase was the within-group change in mean HbA1c between 6 and 12 months, with superiority in the SWITCH group and noninferiority in the SUSTAIN group (ClinicalTrials.gov: NCT04235504).

RESULTS

A total of 39 SWITCH and 36 SUSTAIN participants entered the continuation phase. In the SWITCH group, HbA1c was significantly decreased by -1.4% (95% confidence interval [CI] -1.7% to -1.1%; P < 0.001) from a mean ± SD of 8.9% ± 0.8% (73.9 ± 8.6 mmol/mol) at 6 months to 7.5% ± 0.6% (58.5 ± 6.9 mmol/mol) at 12 months. Mean HbA1c increased by 0.1% (95% CI -0.05% to +0.25%), from 7.3% ± 0.6% (56.5 ± 6.7 mmol/mol) to 7.4% ± 0.8% (57.7 ± 9.1 mmol/mol) in the SUSTAIN group, meeting noninferiority criteria. Three severe hypoglycaemia events occurred in two SWITCH participants during the continuation phase.

CONCLUSION

ADAPT study phase glycaemic improvements were reproduced and sustained in the continuation phase, supporting the early adoption of AID therapy in people with type 1 diabetes not meeting glucose targets on MDI therapy.

WaveFlex biosensor based on S-tapered and waist-expanded technique for detection of glycosylated hemoglobin

Glycosylated hemoglobin (HbA1c) is considered a new standard for the detection of diabetes mellitus because it is more accurate than regular blood sugar tests and there is no need to take blood on an empty stomach or at a specific time. In this work, we have developed a novel optical fiber biosensor, referred to as the "WaveFlex biosensor," which operates on the principles of localized surface plasmon resonance (LSPR) plasmonic wave. The sensor is fabricated using an innovative S-tapered and waist-expanded technique, enabling it to effectively detect HbA1c. Compared to the HbA1c sensors currently in use, HbA1c optical fiber sensors possess the characteristics of high sensitivity, low cost, and strong anti-interference ability. The gold nanoparticles (AuNPs), cerium oxide (CeO2) nanorods (NRs), and tungsten disulfide (WS2) nanosheets (NSs) are functionalized to improve the effectiveness of the fiber sensor on the probe surface. AuNPs are utilized to generate LSPR by the excitation of evanescent waves to amplify the sensing signal. The CeO2-NRs can have a strong metal-carrier interaction with AuNPs, enhancing the cascade of CeO2-NRs and AuNPs. The WS2-NSs with layered fold structure have a large specific surface area. Therefore, the combination of CeO2-NRs and WS2-NSs is conducive to the binding of antibodies and the addition of sites. The functionalized antibodies on the fiber make the sensor probe capable of specific selection. The developed probe is applied to test the HbA1c solution over concentrations of 0-1000 µg/mL, and the sensitivity and limits of detection of 1.195×10-5 a.u./(µg/mL) and 1.66 µg/mL are obtained, respectively. The sensor probe is also evaluated using assays for reproducibility, reusability, selectivity, and pH. According to the findings, a novel method for detecting blood glucose based on a plasmonic biosensor is proposed.

The effects of inspiratory muscle training on swimming performance: A study on the cohort of swimming specialization students

PURPOSE

Current evidence posits a strong correlation between respiratory muscle function and swimming performance. Despite this, few studies have explored the integration of inspiratory muscle training (IMT) into standard swimming training regimens, which remains an unexplored avenue for improving performance in swimmers. This study aims to evaluate the potential advantages of IMT for enhancing respiratory function and swimming performance and determine whether such training could induce beneficial physiological adaptations.

METHODS

We designed and conducted a randomized controlled trial involving 43 swimming specialization students aged 18-25 years. Participants were randomly allocated to two groups: a control group, which followed regular swimming training, and an experimental group, which complemented the standard training with IMT. The intervention lasted for six weeks. Key outcomes measured included swimming performance metrics (time of 50 m freestyle, number of breaths in 50 m freestyle, distance before first breath in freestyle, time of 100 m freestyle) and various inspiratory muscle function parameters such as vital capacity (VC), maximum inspiratory pressure (MIP), maximum inspiratory flow (MIF), and maximum inspiratory capacity (MIC). We also assessed certain biochemical parameters, including hemoglobin, creatine kinase (CK), blood urea nitrogen (BUN), testosterone, and cortisol concentrations.

RESULTS

Following the training period, the experimental group exhibited significant improvements in swimming performance and respiratory function parameters. We also noted an increase in hemoglobin levels and a reduction in testosterone concentrations in this group, suggesting beneficial physiological adaptations in response to the combined IMT and swimming training.

CONCLUSION

Our findings underline the potential of IMT as a supplementary training modality for enhancing respiratory function and improving swimming performance. The changes in biochemical parameters suggest physiological adaptations that might contribute to these observed improvements. This study opens the door for future research on the benefits of integrating IMT into training regimens for competitive swimmers. Further investigation is warranted to fully elucidate the mechanisms behind the observed benefits and to validate these findings in a larger cohort and other athlete populations.

Attachment in close relationships and glycemic outcomes in children with type 1 diabetes

BACKGROUND

Our aim was to determine whether child attachment to parents, parent attachment style, and morning cortisol levels were related to diabetes outcomes measured by average glycated hemoglobin (HbA1c), HbA1c variability over 4 years and time in range (TIR) in children with type 1 diabetes (T1D).

RESEARCH DESIGN AND METHODS

101 children with T1D and one of their parents were assessed at baseline for child attachment (Child Attachment Interview; CAI) and parent attachment (Relationship Structures Questionnaire; ECR-RS). Serum samples were collected for cortisol measurements before the interviews. HbA1c levels were measured during a 4-year follow-up period at regular 3-monthly visits, and data for TIR were exported from blood glucose measuring devices. Multivariate linear regression models were constructed to identify independent predictors of glycemic outcomes.

RESULTS

More girls than boys exhibited secure attachment to their mothers. The results of the regression models showed that securely attached girls (CAI) had higher average HbA1c than did insecurely attached girls (B = -0.64, p = 0.03). In boys, the more insecure the parent's attachment style, the worse the child's glycemic outcome: the higher the average Hb1Ac (B = 0.51, p = 0.005), the higher the HbA1c variability (B = 0.017, p = 0.011), and the lower the TIR (B = -8.543, p = 0.002).

CONCLUSIONS

Attachment in close relationships is associated with glycemic outcomes in children with T1D, and we observed significant differences between sexes. A sex- and attachment-specific approach is recommended when treating children with less favorable glycemic outcomes. Special attention and tailored support should be offered to securely attached girls in transferring responsibility for diabetes care and at least to male children of insecurely attached parents to prevent suboptimal glycemic control. Further studies in larger samples and more daily cortisol measurements may help us better understand the links between stress response, attachment and T1D.

Safety Event Outcomes and Glycemic Control with a Hybrid Closed-Loop System Used by Chinese Adolescents and Adults with Type 1 Diabetes Mellitus

Background: While evidence supports glycemic control benefits for individuals with type 1 diabetes mellitus (T1DM) using hybrid closed-loop (HCL) systems, HCL automated insulin delivery therapy in China has not been assessed. This study evaluated safety events and effectiveness during HCL system use by Chinese adolescents and adults with T1DM. Methods: Sixty-two participants (n = 12 adolescents with a mean ± standard deviation [SD] of 15.5 ± 1.1 years and n = 50 adults [mean ± SD of 37.6 ± 11.1 years]) with T1DM and baseline A1C of 7.1% ± 1.0% underwent a run-in period (∼2 weeks) using open-loop Manual Mode (sensor-augmented pump) insulin delivery with the MiniMed™ 770G system with the Guardian™ Sensor (3) glucose sensor, followed by a study period (4 weeks) with HCL Auto Mode enabled. Analyses compared continuous glucose monitoring data and insulin delivered during the run-in versus study period (Wilcoxon signed-rank test or t-test). Safety events included rates of severe hypoglycemia and diabetic ketoacidosis (DKA). Results: Compared to baseline run-in, overall Auto Mode use increased time in range (TIR, 70-180 mg/dL) from 75.3% to 80.9% (P < 0.001) and reduced time below range (TBR, <70 mg/dL) from 4.7% to 2.2% (P < 0.001). Subgroup analysis demonstrated that participants (n = 29) with baseline A1C <7.0% had TBR that reduced from 5.6% to 2.0%, while participants (n = 21) with baseline A1C ≥7.5% had time above range (TAR, >180 mg/dL) that reduced from 31.6% to 20.8%. Auto Mode use also increased the percentage achieving combined recommendations for time at sensor glucose ranges (i.e., TIR of >70%, TBR of <4% and TAR of <25%) from 24.2% at baseline to 77.4% at study end. Total daily insulin dose reduced from 42.8 ± 19.8 to 40.7 ± 18.9 U (P = 0.013). There were no severe hypoglycemic, DKA, or serious adverse events. Conclusions: Chinese adolescents and adults, some of whom met target A1C at baseline, safely achieved significantly improved glycemia with 1 month of MiniMed 770G system use when compared to open-loop insulin delivery. ClinicalTrials.gov ID: NCT04663295.

Association Between Continuous Glucose Monitoring-Derived Glycemia Risk Index and Albuminuria in Type 2 Diabetes

Background: The glycemia risk index (GRI) is a new composite metric derived from continuous glucose monitoring (CGM) data to assess the quality of glycemia. This study investigates the association between the GRI and albuminuria. Methods: Professional CGM and urinary albumin-to-creatinine ratio (UACR) data from 866 individuals with type 2 diabetes were retrospectively reviewed. Albuminuria and macroalbuminuria were defined as one or more UACR measurements ≥30 and ≥300 mg/g, respectively. Results: The overall prevalence of albuminuria and macroalbuminuria was 36.6% and 13.9%, respectively. Participants with a higher UACR had a significantly higher hyperglycemia component and GRI score than those with a lower UACR (all P < 0.001), although the hypoglycemia component did not differ among the groups. Multiple logistic regression analyses that adjusted for various factors affecting albuminuria revealed that the odds ratio (OR) of albuminuria was 1.13 (95% confidence interval [CI]: 1.02-1.27, P = 0.039) per increase in the GRI zone. The results were similar for the risk of macroalbuminuria (OR: 1.42 [95% CI: 1.20-1.69], P < 0.001), and that association remained after adjusting for glycated hemoglobin (OR: 1.31 [95% CI: 1.10-1.58], P = 0.004). Conclusions: GRI is strongly associated with albuminuria, especially macroalbuminuria, in type 2 diabetes.

Glucose control and psychosocial outcomes with use of automated insulin delivery for 12 to 96 weeks in type 1 diabetes: a meta-analysis of randomised controlled trials

BACKGROUND

Glycaemic control of Type 1 Diabetes Mellitus (T1DM) remains a challenge due to hypoglycaemic episodes and the burden of insulin self-management. Advancements have been made with the development of automated insulin delivery (AID) devices, yet, previous reviews have only assessed the use of AID over days or weeks, and potential benefits with longer time of AID use in this population remain unclear.

METHODS

 We performed a systematic review and meta-analysis of randomised controlled trials comparing AID (hybrid and fully closed-loop systems) to usual care (sensor augmented pumps, multiple daily insulin injections, continuous glucose monitoring and predictive low-glucose suspend) for adults and children with T1DM with a minimum duration of 3 months. We searched PubMed, Embase, Cochrane Central, and Clinicaltrials.gov for studies published up until April 4, 2023. Main outcomes included time in range 70-180 mg/dL as the primary outcome, and change in HbA1c (%, mmol/mol), glucose variability, and psychosocial impact (diabetes distress, treatment satisfaction and fear of hypoglycaemia) as secondary outcomes. Adverse events included diabetic ketoacidosis (DKA) and severe hypoglycaemia. Statistical analyses were conducted using mean differences and odds ratios. Sensitivity analyses were performed according to age, study duration and type of AID device. The protocol was registered in PROSPERO, CRD42022366710.

RESULTS

We identified 25 comparisons from 22 studies (six crossover and 16 parallel designs) including a total of 2376 participants (721 in adult studies, 621 in paediatric studies, and 1034 in combined studies) which were eligible for analysis. Use of AID devices ranged from 12 to 96 weeks. Patients using AID had 10.87% higher time in range [95% CI 9.38 to 12.37; p < 0.0001, I2 = 87%) and 0.37% (4.77 mmol/mol) lower HbA1c (95% CI - 0.49% (- 6.39 mmol/mol) to - 0.26 (- 3.14 mmol/mol); p < 0·0001, I2 = 77%]. AID systems decreased night hypoglycaemia, time in hypoglycaemia and hyperglycaemia and improved patient distress, with no increase in the risk of DKA or severe hypoglycaemia. No difference was found regarding treatment satisfaction or fear of hypoglycaemia. Among children, there was no difference in glucose variability or time spent in hypoglycaemia between the use of AID systems or usual care. In sensitivity analyses, results remained consistent with the overall analysis favouring AID.

CONCLUSION

The use of AID systems over 12 weeks, regardless of technical or clinical differences, improved glycaemic outcomes and diabetes distress without increasing the risk of adverse events in adults and children with T1DM.

A systematic bibliometric analysis on the clinical practice of CGM in diabetes mellitus from 2012 to 2022

Background

Continuous glucose monitoring (CGM) has revolutionized diabetes management, but a comprehensive analysis of its clinical implementation is lacking. This study aims to explore CGM in diabetes practice over the past decade using bibliometric analysis. It will identify trends, research focal points, and provide a framework for future investigations.

Materials and methods

The Web of Science Core Collection (WOSCC) was utilized to acquire literature pertaining to the employment of continuous glucose monitoring (CGM) in diabetes that was published between the years 2012 and 2022, and to conduct a comprehensive analysis of the associated citation data. To achieve bibliometric visualization and analysis of the collated data, the bibliography package in the Rstudio(v.4.2.2), Citespace 6.2.R4, and VOS viewer were employed.

Results

A total of 3024 eligible publications were extracted from 91 countries, with the United States being the leading country in terms of the number of issued articles. Furthermore, the annual publication rate has shown a gradual increase during the past decade. Among the various journals in this field, DIABETES TECHNOLOGY & THERAPEUTICS was identified as the most highly cited one. Keyword clustering analysis of the extracted publications indicates that the research hotspots in the past decade have primarily focused on "continuous glucose monitoring", "glycemic variability", "type 1 diabetes", "hypoglycemia", and "glycemic control". Moreover, the analysis of keyword emergence reveals that "Time In Range" and "Young Adult" represent the current research frontiers for the years 2012-2022.

Conclusion

The concept of Time in Range (TIR) has garnered considerable attention as a significant area of inquiry and an emerging research trend in the clinical practice of Continuous Glucose Monitoring (CGM) for Diabetes Mellitus. Moreover, recent investigations have demonstrated a growing focus on young adults with type 1 diabetes as the research population of interest. In the foreseeable future, research endeavors will persist in the pursuit of improving glycemic management among young adults through the utilization of continuous glucose monitoring (CGM) technology, while also delving into the examination of the Time in Range metric via supplementary clinical investigations.

Determination of Glucose-Independent Racial Disparity in HbA1c for Youth With Type 1 Diabetes in the Era of Continuous Glucose Monitoring

BACKGROUND

The magnitude and importance of higher HbA1c levels not due to mean blood glucose (MBG) in non-Hispanic black (B) versus non-Hispanic white (W) individuals is controversial. We sought to clarify the relationship of HbA1c with glucose data from continuous glucose monitoring (CGM) in a young biracial population.

METHODS

Glycemic data of 33 B and 85 W, healthy youth with type 1 diabetes (age 14.7 ± 4.8 years, M/F = 51/67, duration of diabetes 5.4 ± 4.7 years) from a factory-calibrated CGM was compared with HbA1c. Hemoglobin glycation index (HGI) = assayed HbA1c - glucose management index (GMI).

RESULTS

B patients had higher unadjusted levels of HbA1c, MBG, MBGSD, GMI, and HGI than W patients. Percent glucose time in range (TIR) and percent sensor use (PSU) were lower for B patients. Average HbA1c in B patients 8.3% was higher than 7.7% for W (P < .0001) after statistical adjustment for MBG, age, gender, insulin delivery method, and accounting for a race by PSU interaction effect. Higher HbA1c persisted in B patients when TIR was substituted for MBG. Predicted MBG was higher in B patients at any level of PSU. The 95th percentile for HGI was 0.47 in W patients, and 52% of B patients had HGI ≥ 0.5. Time below range was similar for both.

CONCLUSIONS

Young B patients have clinically relevant higher average HbA1c at any given level of MBG or TIR than W patients, which may pose an additional risk for diabetes complications development. HGI ≥ 0.5 may be an easy way to identify high-risk patients.

Correlation Between Blood Glucose Indexes Generated by the Flash Glucose Monitoring System and Diabetic Vascular Complications

Objective

To discuss the relationship between time in range (TIR) which is deprived of the FGMS and the risk of diabetic vascular complications and to provide a theoretical foundation for the clinical application of TIR and other FGMS-deprived indexes.

Methods

Patients with T2DM who wore the FGMS sensor continuously were enrolled. Relevant indexes such as TIR, time below range (TBR), time above range (TAR), a standard deviation of blood glucose (SDBG), coefficient of variation of blood glucose (CV), and mean amplitude of glycemic excursion (MAGE) generated by the FGMS were recorded, and the risk of diabetic vascular complications were followed up for one year. The TIR was measured by continuous glucose monitoring at baseline, and patients were grouped according to TIR every 20%. Finally, the Cox proportional hazards regression model was used to estimate the association of different levels of TIR with different rates of diabetic vascular complications.

Results

TIR was negatively correlated with HbA1C, CV, SDBG, and amplitude of glycemic excursion (MV), wherein, the lower the TIR, the higher the HbA1C, CV, SDBG, and MV. TIR in the diabetic microvascular complication was significantly lower than that in the non-microvascular complication group, and the difference was statistically significant. TIR <40% was identified as a risk factor for DN, DPN, and DR according to the risk assessment. The mean TAR in the DN group was significantly higher than that in the non-DN group. TAR, CV, SD, MAGE, and HbA1C in the DR group were significantly higher than those in the non-DR group. TAR, ABG, CV, SD, MAGE, and HbA1C in the DPN group were significantly higher than those in the non-DPN group.

Conclusion

The relationships between the TIR and the prevalence and risk of diabetic vascular complications and the HbA1C may be negative. Other CGM-deprived indexes such as CV and MV should be integrated into glycemic control and diabetes complication prediction.

The Artificial Pancreas and Type 1 Diabetes

Diabetes technologies represent a paradigm shift in type 1 diabetes care. Continuous subcutaneous insulin infusion (CSII) pumps and continuous glucose monitors (CGM) improve glycated hemoglobin (HbA1c) levels, enhance time in optimal glycemic range, limit severe hypoglycemia, and reduce diabetes distress. The artificial pancreas or closed-loop system connects these devices via a control algorithm programmed to maintain target glucose, partially relieving the person living with diabetes of this constant responsibility. Automating insulin delivery reduces the input required from those wearing the device, leading to better physiological and psychosocial outcomes. Hybrid closed-loop therapy systems, requiring user-initiated prandial insulin doses, are the most advanced closed-loop systems commercially available. Fully closed-loop systems, requiring no user-initiated insulin boluses, and dual hormone systems have been shown to be safe and efficacious in the research setting. Clinical adoption of closed-loop therapy remains in early stages despite recent technological advances. People living with diabetes, health care professionals, and regulatory agencies continue to navigate the complex path to equitable access. We review the available devices, evidence, clinical implications, and barriers regarding these innovatory technologies.

Time in Range Estimation in Patients with Type 2 Diabetes is Improved by Incorporating Fasting and Postprandial Glucose Levels

INTRODUCTION

Time in range (TIR) as assessed by continuous glucose monitoring (CGM) measures an individual's glucose fluctuations within set limits in a time period and is increasingly used together with HbA1c in patients with diabetes. HbA1c indicates the average glucose concentration but provides no information on glucose fluctuation. However, before CGM becomes available for patients with type 2 diabetes (T2D) worldwide, especially in developing nations, fasting plasma glucose (FPG) and postprandial plasma glucose (PPG) are still the common biomarkers used for monitoring diabetes conditions. We investigated the importance of FPG and PPG to glucose fluctuation in patients with T2D. We used machine learning to provide a new estimate of TIR based on the HbA1c, together with FPG and PPG.

METHODS

This study included 399 patients with T2D. (1) Univariate and (2) multivariate linear regression models and (3) random forest regression models were developed to predict the TIR. Subgroup analysis was performed in the newly diagnosed T2D population to explore and optimize the prediction model for patients with different disease history.

RESULTS

Regression analysis suggests that FPG was strongly linked to minimum glucose, while PPG was strongly correlated with maximum glucose. After FPG and PPG were incorporated into the multivariate linear regression model, the prediction performance of TIR was improved compared with the univariate correlation between HbA1c and TIR, and the correlation coefficient (95% CI) increased from 0.62 (0.59, 0.65) to 0.73 (0.72, 0.75) (p < 0.001). The random forest model significantly outperformed the linear model (p < 0.001) in predicting TIR through FPG, PPG and HbA1c, with a stronger correlation coefficient 0.79 (0.79, 0.80).

CONCLUSIONS

The results offered a comprehensive understanding of glucose fluctuations through FPG and PPG compared to HbA1c alone. Our novel TIR prediction model based on random forest regression with FPG, PPG, and HbA1c provides a better prediction performance than the univariate model with solely HbA1c. The results indicate a nonlinear relationship between TIR and glycaemic parameters. Our results suggest that machine learning may have the potential to be used in developing better models for understanding patients' disease status and providing necessary interventions for glycaemic control.

Dementia in Diabetes: The Role of Hypoglycemia

Hypoglycemia, a common consequence of diabetes treatment, is associated with severe morbidity and mortality and has become a major barrier to intensifying antidiabetic therapy. Severe hypoglycemia, defined as abnormally low blood glucose requiring the assistance of another person, is associated with seizures and comas, but even mild hypoglycemia can cause troubling symptoms such as anxiety, palpitations, and confusion. Dementia generally refers to the loss of memory, language, problem-solving, and other cognitive functions, which can interfere with daily life, and there is growing evidence that diabetes is associated with an increased risk of both vascular and non-vascular dementia. Neuroglycopenia resulting from a hypoglycemic episode in diabetic patients can lead to the degeneration of brain cells, with a resultant cognitive decline, leading to dementia. In light of new evidence, a deeper understating of the relationship between hypoglycemia and dementia can help to inform and guide preventative strategies. In this review, we discuss the epidemiology of dementia among patients with diabetes, and the emerging mechanisms thought to underlie the association between hypoglycemia and dementia. Furthermore, we discuss the risks of various pharmacological therapies, emerging therapies to combat hypoglycemia-induced dementia, as well as risk minimization strategies.