Association Between Continuous Glucose Monitoring-Derived Time in Range, Other Core Metrics, and Albuminuria in Type 2 Diabetes

Closed-Loop Insulin Therapy for People With Type 2 Diabetes Treated With an Insulin Pump: A 12-Week Multicenter, Open-Label Randomized, Controlled, Crossover Trial

OBJECTIVE

Continuous glucose monitoring (CGM) combined with continuous subcutaneous insulin infusion (CSII) achieves better glycemic control than multi-injection therapy in people with type 2 diabetes. The effectiveness of closed-loop therapy needs to be further evaluated in this population.

RESEARCH DESIGN AND METHODS

The study objective was to measure the impact of a hybrid closed-loop device (DBLG1) compared with CSII + CGM on glycemic control in people with type 2 diabetes previously treated with CSII. The randomized, controlled, crossover, two-period, open-label, and multicenter study was conducted from August 2022 to July 2023 in 17 individuals (9 to receive 6 weeks of CSII + CGM first and 8 to receive 6 weeks of closed-loop therapy first). The primary end point was the percentage time in range (TIR: 70-180 mg/dL). Secondary outcomes were other CGM-glucose metrics, physical activity, and sleep objectively measured using 1-week actimetry.

RESULTS

Data were analyzed using a modified intention-to-treat approach. Mean age was 63 (SD 9) years and 35% were women. Mean HbA1c at inclusion was 7.9% (SD 0.9). TIR increased to 76.0% (interquartile range 69.0-84.0) during the closed-loop condition vs. 61.0% (interquartile range 55.0-70.0) during the CSII + CGM condition; mean difference was 15.0 percentage points (interquartile range 8.0-22.0; P < 0.001). Analyses of secondary end points showed a decrease in time above range, in glucose management indicator, in glucose variability, and an increase in daily insulin dose. Actimetric sleep analysis showed an improvement in sleep fragmentation during closed-loop treatment.

CONCLUSIONS

Closed-loop therapy improved glycemic control more than did CSII + CGM in people with type 2 diabetes.

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

INTRODUCTION

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

METHODS

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

RESULTS

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

CONCLUSION

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

Differences Between Glycated Hemoglobin and Glucose Management Indicator in Real-Time and Intermittent Scanning Continuous Glucose Monitoring in Adults With Type 1 Diabetes

BACKGROUND

This study demonstrates the difference between glucose management indicator (GMI) and glycated hemoglobin (HbA1c) according to sensor mean glucose and HbA1c status using 2 continuous glucose monitoring (CGM) sensors in people with type 1 diabetes.

METHODS

A total of 275 subjects (117 Dexcom G6 [G6] and 158 FreeStyle Libre 1 [FL]) with type 1 diabetes was included. The G6 and FL sensors were used, respectively, over 90 days to analyze 682 and 515 glycemic profiles that coincide with HbA1c.

RESULTS

The mean HbA1c was 6.6% in Dexcom G6 and 7.2% in FL profiles. In G6 profiles, GMI was significantly higher than HbA1c irrespective of mean glucose (all P < .001, mean difference: 0.58% ± 0.49%). The GMI was significantly higher than the given HbA1c when HbA1c was below 8.0% (all P < .001). The discordance was the highest at 0.9% for lower HbA1c values (5.0%-5.9%). The proportion of discordance >0.5% improved from 60.1% to 30.9% when using the revised GMI equation in G6 profiles. In FL profile, the overall mean difference between GMI and HbA1c was 0 (P = .966). The GMI was significantly lower by 0.9% than HbA1c of 9.0% to 9.9% and higher by 0.5% in HbA1c of 5.0% to 5.9% (all P < .001).

CONCLUSIONS

The GMI is overestimated in G6 users, particularly those with well-controlled diabetes, but the GMI and HbA1c discordance improved with a revised equation from the observed data. The FL profile showed greater discordance for lower HbA1c levels or higher HbA1c levels.

The Relationship Between Hemoglobin A1c, Time in Range, and Glycemic Management Indicator in Patients With Type 1 and Type 2 Diabetes in a Tertiary Care Hospital in Saudi Arabia

OBJECTIVES

This study aimed to assess the correlation between glycated hemoglobin A1 (HbA1c), time in range (TIR), and glycemic management indicator (GMI) in patients with both type 1 diabetes (T1D) and type 2 diabetes (T2D) who were using a flash glucose monitoring (FGM) device (FreeStyle Libre; Abbott Diabetic Care, Witney, UK).

METHODS

This was a retrospective study that looked at T1D and T2D FreeStyle Libre users' LibreView database in the period between January 2020 to June 2022. The study was conducted at the diabetes department at the King Fahad Medical City (KFMC) in Riyadh, Saudi Arabia, following Institutional Review Board (IRB) approval. Data were collected from the LibreView website, as well as from the electronic privacy information center (EPIC) hospital records.

RESULTS

Data were available for 327 patients, mean age of 33.08(±17.1) years old, and 55.7% were females. HbA1c had a statistically significant correlation with both TIR and GMI with coefficient of correlation (r) values of 0.78 (p<0.001) and 0.82 (p<0.001), respectively. A linear regression model between TIR and Hb1Ac was also developed and found to be statistically significant (p<0.001) with an acceptable R2 value (0.60).

CONCLUSION

Study findings revealed that the %TIR could be a reliable predictor of Hb1Ac. Thus, Freestyle Libre was able to determine Hb1Ac as close to the lab results as possible. Therefore, it is necessary to encourage diabetes patients to achieve at least 70% TIR in order to keep Hb1Ac within the desired range.

Continuous glucose monitoring for the routine care of type 2 diabetes mellitus

Although continuous glucose monitoring (CGM) devices are now considered the standard of care for people with type 1 diabetes mellitus, the uptake among people with type 2 diabetes mellitus (T2DM) has been slower and is focused on those receiving intensive insulin therapy. However, increasing evidence now supports the inclusion of CGM in the routine care of people with T2DM who are on basal insulin-only regimens or are managed with other medications. Expanding CGM to these groups could minimize hypoglycaemia while allowing efficient adaptation and escalation of therapies. Increasing evidence from randomized controlled trials and observational studies indicates that CGM is of clinical value in people with T2DM on non-intensive treatment regimens. If further studies confirm this finding, CGM could soon become a part of routine care for T2DM. In this Perspective we explore the potential benefits of widening the application of CGM in T2DM, along with the challenges that must be overcome for the evidence-based benefits of this technology to be delivered for all people with T2DM.

Long-Term Improvements in Glycemic Control with Dexcom CGM Use in Adults with Noninsulin-Treated Type 2 Diabetes

Aims: The objective of this real-world, observational study was to evaluate change in continuing glucose monitoring (CGM) metrics for 1 year after CGM initiation in adults with noninsulin-treated type 2 diabetes (T2D). Methods: Data were analyzed from Dexcom G6 and G7 users who self-reported: T2D, ≥18 years, gender, no insulin use, and had a baseline percent time in range (TIR) 70-180 mg/dL of ≤70%. Outcomes were change in CGM metrics from baseline to 6 and 12 months overall and for younger (<65 years) and older (≥65 years) cohorts. Additional analyses explored the relationship between use of the high alert feature and change in TIR and time in tight range (TITR) 70-140 mg/dL. Results: CGM users (n = 3,840) were mean (SD) 52.5 (11.2) years, 47.9% female, mean TIR was 41.7% (21.4%), and 12.4% of participants were ≥65 years. Significant improvement in all CGM metrics not meeting target values at baseline was observed at 6 months, with continued improvement at 12 months. Mean baseline TIR increased by 17.3% (32.1%) from 41.7% (21.4%) to 59.0% (28.9%), and mean glucose management indicator decreased by 0.5% (1.2%) from 8.1% (0.9%) to 7.6% (1.1%) (both P < 0.001). Participants who maintained or customized the high alert default setting of 250 mg/dL had a greater increase in TIR and TITR compared with participants who disabled the alert. Days of CGM use over 12 months were high in 84.7% (15.9%). Conclusion: In this large, real-world study of adults with suboptimally controlled T2D not using insulin, Dexcom CGM use was associated with meaningful improvements in glycemic control over 12 months. Use of the high alert system feature was positively associated with glycemic outcomes. High use of CGM over 12 months suggests benefits related to consistent CGM use in this population.

Intra-pancreatic fat is associated with continuous glucose monitoring metrics

AIM

To investigate the relationship of fat in the pancreas with time spent in different glycaemic ranges.

METHODS

Abdominal magnetic resonance imaging at 3.0 Tesla was used to quantify fat in the pancreas as both continuous [i.e. intra-pancreatic fat deposition (IPFD)] and binary (i.e. fatty change of the pancreas vs. normal pancreas) variables. Dexcom G6 devices were used to collect continuous glucose monitoring data every 5 min over a continuous 7-day period. Time above range (TAR), time in range (TIR) and time below range were computed. Statistical models were built to adjust for age, sex, body composition, and other covariates in linear regression analysis and analysis of covariance.

RESULTS

In total, 38 individuals were studied. IPFD was significantly associated with TAR (p = .036) and TIR (p = .042) after adjustment for covariates. For every 1% increase in IPFD, there was a 0.3 unit increase in TAR and a decrease in TIR. Individuals with fatty change of the pancreas, when compared with those with normal pancreas, had significantly higher TAR (p = .034) and lower TIR (p = .047) after adjustment for covariates. Neither IPFD (p = .805) nor fatty change of the pancreas (p = .555) was associated with time below range after adjustment for covariates.

CONCLUSION

Increased fat in the pancreas is associated with excessive glycaemic variability. Fatty change of the pancreas may contribute to heightening the risk of cardiovascular diseases.

Correlation Between Blood Urea Nitrogen and Short- and Long-Term Glycemic Variability in Elderly Patients with Type 2 Diabetes Mellitus Who Were hospitalized:A Retrospective Study

Objective

Type 2 diabetes mellitus (T2DM) is a metabolic disease characterized by insulin resistance and progressively impaired insulin secretion resulting in dynamic fluctuations in glucose levels.High blood urea nitrogen (BUN) levels have been linked to decreased insulin sensitivity, suppressed insulin synthesis and increased risk of incident diabetes mellitus in humans as well as insulin use in patients with T2DM.This study characterize the association between BUN levels and short-term and long-term glycemic variability(GV) in the elderly patients with T2DM who were hospitalized.

Methods

A total of 927 elderly patients with T2DM were included in the study. The short-term GV was quantified using parameters such as standard deviation (SD), coefficient of variation (CV), time in range (TIR), and mean amplitude of glycemic excursions (MAGE), based on multi-point fingertip blood glucose monitoring. The long-term GV was quantified using parameters such as SD, CV, variation independent of the mean (VIM), and average successive variability (ARV), based on fasting blood glucose(FPG). The relationship between BUN levels and short-term and long-term GV in elderly T2DM who were hospitalized was explored using methods such as Spearman correlation coefficient, linear regression analysis, logistic regression analysis, and interaction tests.

Results

In elderly patients with T2DM were hospitalized, there is a significant correlation between BUN levels and both short-term and long-term GV. BUN is negatively correlated with the GV parameter TIR (r=-0.12, P=0.000), and positively correlated with SD (r=0.12, P=0.000), CV (r=0.07, P=0.026), MAGE (r=0.11, P=0.001), FPG-SD (r=0.08, P=0.013), and FPG-CV (r=0.08, P=0.014).Furthermore, the association remains consistent across different age, gender, BMI, and haemoglobin A1c (HbA1c) subgroups (P interaction > 0.05).

Conclusion

In elderly patients with T2DM were hospitalized, BUN levels were positively associated with GV.Therefore, monitoring BUN levels were beneficial in assessing the degree of GV.

Higher Derived Time in Range With IDegLira Versus Insulin Glargine U100 in People With Type 2 Diabetes

BACKGROUND

Derived time in range (dTIR), calculated from self-monitored blood glucose (SMBG-dTIR) profiles, has demonstrated correlation with risk of cardiovascular and microvascular complications. This post hoc analysis of the DUAL V and DUAL VIII trials aimed to compare dTIR with an insulin degludec/liraglutide fixed-ratio combination (IDegLira) versus insulin glargine 100 units/mL (glargine U100) in people with type 2 diabetes (T2D).

MATERIALS AND METHODS

Nine-point SMBG profiles were taken more than 24 hours at baseline and end of trial (EOT: 26 weeks [DUAL V] and 104 weeks [DUAL VIII]) and used to derive the percentage of readings within target range (70-180 mg/dL). Estimated treatment differences (ETDs, IDegLira-glargine U100) were analyzed using analysis of covariance, with treatment as fixed effects and baseline response as a covariate.

RESULTS

ETDs for change from baseline to EOT in dTIR were significantly greater with IDegLira versus glargine U100 in DUAL V (4.18%, P = .027) and DUAL VIII (5.17%, P = .001). The proportions of people achieving ≥70% dTIR at EOT with IDegLira and glargine U100, respectively, were 62% and 60% in DUAL V (P = .7541), and 50% and 26% in DUAL VIII (P < .0001). The proportion achieving a ≥5% increase in dTIR from baseline to EOT with IDegLira and glargine U100 was 63% in both groups in DUAL V (P = .9043), and 44% and 25%, respectively, in DUAL VIII (P < .0001).

CONCLUSIONS

IDegLira was associated with significantly greater increases in dTIR versus basal insulin alone in people with T2D.

TRIAL ID(S)

ClinicalTrials.gov, NCT01952145 (DUAL V); ClinicalTrials.gov, NCT02501161 (DUAL VIII).

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.

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.

Association between brain imaging biomarkers and continuous glucose monitoring-derived glycemic control indices in Japanese patients with type 2 diabetes mellitus

INTRODUCTION

Although type 2 diabetes mellitus (T2DM) is associated with alterations in brain structure, the relationship between glycemic control indices and brain imaging markers remains unclear. This study aimed to investigate the association between continuous glucose monitoring (CGM)-derived glycemic control indices and brain imaging biomarkers assessed by MRI.

RESEARCH DESIGN AND METHODS

This cross-sectional study included 150 patients with T2DM. The severity of cerebral white matter lesions (WMLs) was assessed using MRI for deep and subcortical white matter and periventricular hyperintensities. The degree of medial temporal lobe atrophy (MTA) was assessed using voxel-based morphometry. Each participant wore a retrospective CGM for 14 consecutive days, and glycemic control indices, such as time in range (TIR) and glycemia risk index (GRI), were calculated.

RESULTS

The proportion of patients with severe WMLs showed a decreasing trend with increasing TIR (P for trend=0.006). The proportion of patients with severe WMLs showed an increasing trend with worsening GRI (P for trend=0.011). In contrast, no significant association was observed between the degree of MTA and CGM-derived glycemic control indices, including TIR (P for trend=0.325) and GRI (P for trend=0.447).

CONCLUSIONS

The findings of this study indicate that the severity of WMLs is associated with TIR and GRI, which are indices of the quality of glycemic control.

TRIAL REGISTRATION NUMBER

UMIN000032143.

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.

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 Glycemic Variability on Regulatory T Cells in Patients with Type 2 Diabetes and Kidney Disease

Purpose

To investigate the pathogenesis of diabetic kidney disease (DKD) in type 2 diabetes mellitus (T2DM), we evaluated the effects of short-term glycemic variability (GV) on the profile of T cell subpopulations.

Methods

A total of 47 T2DM patients with normoalbuminuria, 47 microalbuminuria, and 49 macroalbuminuria were enrolled. The continuous glucose monitoring (CGM) determined the GV of enrolled patients. Flow cytometry was used to determine the proportion of T cell subpopulations.

Results

The frequency of T helper (Th) 17 and Th1 cells significantly increased while regulatory T cells (Tregs) significantly decreased in the macroalbuminuria group compared to normoalbuminuria and microalbuminuria groups (P < 0.01). The suppressive function of Tregs was significantly lower in the macroalbuminuria group than the normoalbuminuria group (P < 0.05). Compared with the normoalbuminuria group, the mean amplitude of glucose excursions (MAGE) of the macroalbuminuria group was significantly higher (P<0.05). Furthermore, there were negative associations between the proportion of Tregs and MAGE.

Conclusions

Increased GV could decrease the proportion of Tregs and may impair their function. This may lead to increases in Th1 and Th17 cells, and some inflammatory cytokines, which might contribute to the development and progression of DKD in T2DM.

Correlation Between Glycemic Variability and Diabetic Complications: A Narrative Review

Diabetes mellitus is a metabolic disorder with a complex etiology in which glycemic dynamics are disturbed and the body is unable to maintain the process of glucose homeostasis through the pancreas. Persistent symptoms of high blood glucose or low blood glucose may lead to diabetic complications, such as neuropathy, nephropathy, retinopathy, and cardiovascular diseases. Glycemic variability which can represent the presence of excessive glycemic excursions is an indicator for evaluating glucose homoeostasis. Limiting glycemic variability has gradually become an emerging therapeutic target in improve diabetes metabolism and prevent associated complications. This article reviews the progress of research on the various quantifiable parameters of glycemic variability and their relationships with vascular lesions and mechanisms.

Differential correlation between time in range and eGFR or albuminuria in type 2 diabetes

INTRODUCTION

As a CGM-derived indicator, 'time in range' (TIR) is emerging as a key indicator for accurate assessment of glycaemic control. However, there is few report focusing on the correlation of TIR with albumuria and renal fuction. The aim of this work was to investigate whether TIR, as well as nocturnal TIR and hypoglycaemic events is related to the presence and severity of albuminuria and decrease of eGFR in type 2 diabetes.

RESEARCH DESIGN AND METHODS

A total of 823 patients were enrolled in this study. All patients received continuous glucose monitoring, TIR indicating the percentage of time that blood glucose was in the range of 3.9-10.0 mmol/L. The Spearman analysis was applied to analyze the relationship between TIR (or nocturnal TIR) and ACR. Logistic regression was used to explore whether TIR (or nocturnal TIR) is an independent risk factor for albuminuria.

RESULTS

The prevalence of albuminuria decreased with increasing TIR quartiles. Binary logistic regression revealed that TIR as well as nocturnal TIR was obviously related to the presence of albuminuria. Multiple regression analysis found that only nocturnal TIR was obviously related to the severity of albuminuria. In our study, eGFR was significantly associated with the number of hypoglycemic events.

CONCLUSIONS

In T2DM patients, TIR and nocturnal TIR is associated with the presence of albuminuria independent of HbA1c and GV metrics. Nocturnal TIR shows better correlation than TIR. The role of TIR especially nocturnal TIR in the evaluation of diabetes kidney disease should be emphasized.

Glycemia according to the Use of Continuous Glucose Monitoring among Adults with Type 1 Diabetes Mellitus in Korea: A Real-World Study

BACKGROUND

We explored the association between continuous glucose monitoring (CGM) use and glycemia among adults with type 1 diabetes mellitus (T1DM) and determined the status of CGM metrics among adults with T1DM using CGM in the real-world.

METHODS

For this propensity-matched cross-sectional study, individuals with T1DM who visited the outpatient clinic of the Endocrinology Department of Samsung Medical Center between March 2018 and February 2020 were screened. Among them, 111 CGM users (for ≥9 months) were matched based on propensity score considering age, sex, and diabetes duration in a 1:2 ratio with 203 CGM never-users. The association between CGM use and glycemic measures was explored. In a subpopulation of CGM users who had been using official applications (not "do-it-yourself" software) such that Ambulatory Glucose Profile data for ≥1 month were available (n=87), standardized CGM metrics were summarized.

RESULTS

Linear regression analyses identified CGM use as a determining factor for log-transformed glycosylated hemoglobin. The fully-adjusted odds ratio (OR) and 95% confidence interval (CI) for uncontrolled glycosylated hemoglobin (>8%) were 0.365 (95% CI, 0.190 to 0.703) in CGM users compared to never-users. The fully-adjusted OR for controlled glycosylated hemoglobin (<7%) was 1.861 (95% CI, 1.119 to 3.096) in CGM users compared to never-users. Among individuals who had been using official applications for CGM, time in range (TIR) values within recent 30- and 90-day periods were 62.45%±16.63% and 63.08%±15.32%, respectively.

CONCLUSION

CGM use was associated with glycemic control status among Korean adults with T1DM in the real-world, although CGM metrics including TIR might require further improvement among CGM users.

Association between low-carbohydrate diets and continuous glucose monitoring-derived time in ranges

AIMS

Low-carbohydrate diets have become popular in the general community. The mutual relationship between the percentage of total energy intake from carbohydrates (CHO/E), glycemic control indices, and diabetes complications remains unclear.

MATERIALS AND METHODS

This cross-sectional study included 177 patients with type 2 diabetes mellitus who regularly visited outpatient clinics. In this study, dietary questionnaires were used to assess the intake ratio of the three macronutrients, and the low-carbohydrate-diet score was calculated. We investigated the association between the low-carbohydrate-diet score, continuous glucose monitoring (CGM)-derived short-term glycemic control indices, and diabetes complications in patients with type 2 diabetes mellitus.

RESULTS

The results are presented as medians (interquartile ranges) unless otherwise stated. Hemoglobin A1c was 7.1% (6.6-7.7%), CGM-derived time in range (TIR) was 75.3% (62.8-87.0%), body mass index (BMI) was 24.0 (22.1-26.3) kg/m2, and CHO/E was 49.8% (44.8-55.6%). BMI, triglycerides, and CGM-derived time above range decreased significantly with increasing low-carbohydrate-diet scores. However, no significant association was found between the low-carbohydrate-diet score and glycemic control indices, including TIR, mean amplitude of glycemic excursions, and vascular complications of type 2 diabetes mellitus.

CONCLUSION

Moderate-carbohydrate diets positively impact weight control and lipid metabolism but may have a limited effect on short-term glycemic variability in Japanese patients with type 2 diabetes mellitus.

Use of Continuous Glucose Monitors to Manage Type 1 Diabetes Mellitus: Progress, Challenges, and Recommendations

Type 1 diabetes (T1D) management has been revolutionized with the development and routine utilization of continuous glucose monitoring (CGM). CGM technology has allowed for the ability to track dynamic glycemic fluctuations and trends over time allowing for optimization of medical therapy and the prevention of dangerous hypoglycemic events. This review details currently-available real-time and intermittently-scanned CGM devices, clinical benefits, and challenges of CGM use, and current guidelines supporting its use in the clinical care of patients with T1D. We additionally describe future issues that will need to be addressed as CGM technology continues to evolve.

The Association of Time in Range and Diabetic Complications: The Evidence is Strong

N/A.

A Comparison of Continuous Glucose Monitoring Estimated Hemoglobin A1c in Adults with Type 1 or Type 2 Diabetes

Background: The relationship of mean glucose measured with continuous glucose monitoring (CGM) and hemoglobin A1c (HbA1c) shows considerable variability between individuals with diabetes and may be influenced by race-related factors. Whether the relationship of mean glucose with HbA1c varies according to type 1 diabetes (T1D) or type 2 diabetes (T2D) has not been well evaluated. Methods: Data from 343 participants in four clinical trials (191 with T1D and 152 with T2D) were analyzed. Least squares linear regression models were fit with HbA1c as the dependent variable and mean glucose as the independent variable. Results: Mean age was 57 ± 15 years in the T1D cohort and 58 ± 10 years in the T2D cohort. The T1D cohort was 89% White non-Hispanic, 5% African American, 3% Hispanic, and 3% other or mixed race compared with 52%, 16%, 22%, and 9%, respectively, in the T2D cohort. The relationship between CGM-measured mean glucose and laboratory-measured HbA1c significantly differed between T1D and T2D cohorts, with HbA1c on average being higher with T2D than T1D for the same mean glucose (P = 0.002). However, this difference was largely attributable to the difference in the proportion of African Americans between T1D and T2D; and after stratifying by race, the mean glucose-HbA1c relationship showed only a small difference between T1D non-African Americans and T2D non-African Americans. The mean glucose-HbA1c relationship appeared similar for White non-Hispanic and Hispanic individuals. Conclusion: HbA1c on average was higher in T2D than T1D for a given mean glucose, but after accounting for race, there was no meaningful difference in the mean glucose-HbA1c relationship comparing T1D and T2D. The mean glucose-HbA1c relationship differs in African American compared with White individuals, but does not appear to differ comparing White non-Hispanic to Hispanic individuals. The published glucose management indicator formula appears to be suitable for both T1D and T2D.

6. Glycemic Targets: 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.

The association between time in the glucose target range and abnormal ankle-brachial index: a cross-sectional analysis

BACKGROUND

Time in range (TIR), a novel proxy measure of glucose control, is found closely related to diabetic microangiopathy and some other chronic complications, but the correlation between TIR and lower limb angiopathy has not been studied yet. Our purpose is to explore the relationship between TIR and abnormal ankle-brachial index(ABI) in type 2 diabetes.

METHODS

We retrospectively collected patients' information from the database and performed cross-sectional analysis. A total of 405 type 2 diabetes patients were enrolled in this study. ABI was measured and patients were stratified into low, normal, and high groups according to ≤ 0.9, > 0.9 and < 1.3, ≥ 1.3 ABI values. All patients underwent continuous glucose monitoring(CGM), and TIR was defined as the percentage of time in which glucose was in the range of 3.9-10 mmol/L during a 24-h period. Correlations between TIR and abnormal ABI were analyzed using Spearman analysis. And logistic regression was used to explore whether TIR is an independent risk factor for abnormal ABI.

RESULTS

The overall prevalence of abnormal ABI was 20.2% (low 4.9% and high 15.3%). TIR was lower in patients with abnormal ABI values (P = 0.009). The prevalence of abnormal ABI decreased with increasing quartiles of TIR (P = 0.026). Abnormal ABI was negatively correlated with TIR and positively correlated with hypertension, age, diabetes duration, UREA, Scr, ACR, TAR, MBG, and M values (P < 0.05). The logistic regression revealed a significant association between TIR and abnormal ABI, while HbA1C and blood glucose variability measures had no explicit correlation with abnormal ABI. Additionally, there was a significant difference in LDL between the low and high ABI groups (P = 0.009), and in Scr between normal and low groups (P = 0.007). And there were significant differences in TIR (P = 0.003), age (P = 0.023), UREA (P = 0.006), ACR (P = 0.004), TAR (P = 0.015), and MBG (P = 0.014) between normal and high ABI groups, and in diabetes duration between both normal and low (P = 0.023) and normal and high (P = 0.006) groups.

CONCLUSIONS

In type 2 diabetes patients, abnormal ABI is associated with lower TIR, and the correlation is stronger than that with HbA1C. Therefore, the role of TIR should be emphasized in the evaluation of lower limb vascular diseases.

Comparison of glucose time in range and area under curve in range in relation to risk of diabetic retinopathy in type 2 diabetes patients

AIMS/INTRODUCTION

We proposed a novel continuous glucose monitoring (CGM)-based metric, area under the curve in range (AucIR), for integrating both the amplitude and duration of dysglycemia, and further compared AucIR with the emerging key CGM-derived metric, time in range (TIR).

MATERIALS AND METHODS

A total of 2,030 adult patients with type 2 diabetes were enrolled during May 2020 to October 2021. AucIR and TIR were measured with 7-day CGM data. Logistic regression analysis and the C-statistic was carried out to assess the association of AucIR and TIR with diabetic retinopathy (DR).

RESULTS

Both AucIR (r = -0.89) and TIR (r = -0.95) were strongly correlated with mean glucose levels. Compared with TIR, AucIR showed a tighter relationship with parameters of glycemic variability, including the coefficient of variation (r = -0.56), standard deviation (r = -0.89) and mean amplitude of glycemic excursions (r = -0.70). For each absolute 10% decrease in AucIR, the risk of DR was increased by 7% (95% confidence interval 1.02-1.13) after adjustment for confounders. With respect to TIR, each absolute 10% decrease was associated with an 8% (95% confidence interval 1.03-1.14) increased risk of DR. The model discrimination for DR, as measured by C-statistic, did not differ significantly between the two metrics (P > 0.05).

CONCLUSIONS

AucIR did not provide added benefit over TIR in the assessment of DR risk among patients with type 2 diabetes. The potential value of AucIR needs to be explored in future studies.

The Effects of Diabetes and Glycemic Control on Cancer Outcomes in Individuals With Metastatic Breast Cancer

BACKGROUND

It is unclear whether diabetes and glycemic control affects the outcomes of breast cancer, especially among those with metastatic disease. This study aims to determine the impact of diabetes and hyperglycemia on cancer progression and mortality in individuals with metastatic breast cancer (MBC).

METHODS

Patients with a diagnosis of MBC between 2010 and 2021 were identified using the MBC database at 2 academic institutions. We evaluated the effects of diabetes and glycemic control on overall survival (OS) and time to next treatment (TTNT).

RESULTS

We compared 244 patients with diabetes (median age 57.6 years) to 244 patients without diabetes (matched for age, sex, ethnicity, and receptor subtype). OS at 5 years [diabetes: 54% (95% CI 47-62%) vs controls: 56% (95% CI 49-63%), P = 0.65] and TTNT at 1 year [diabetes: 43% (95% CI 36-50%) vs controls: 44% (95% CI 36-51%), P = 0.33] were similar between groups. A subgroup analysis comparing those with good glycemic control and those with poor glycemic control among patients with specific receptor subtype profiles showed no differences in OS at 5 years or TTNT at 1 year. In an 8-year landmark subgroup analysis, there was worse OS among individuals with diabetes compared to controls, and OS was found to be better among those with good glycemic control compared to those with poor control.

CONCLUSIONS

Diabetes was not associated with increased mortality in individuals with MBC at 5 years. However, diabetes and hyperglycemia were associated with worse OS among a cohort of longer-term survivors. These findings suggest that individualized diabetes and glycemic goals should be considered in patients with MBC.

Association of time in range with lower extremity atherosclerotic disease in type 2 diabetes mellitus: a prospective cohort study

PURPOSE

Time in range (TIR) has surfaced as a key continuous glucose monitoring (CGM)-derived metric, which was linked to diabetes-related outcomes. We aimed to investigate the association of TIR with the risk of lower extremity atherosclerotic disease (LEAD) among patients with type 2 diabetes.

METHODS

A total of 1351 adult patients with type 2 diabetes were prospectively recruited from a single center in Shanghai, China. TIR was obtained from CGM data at baseline. LEAD was measured with color Doppler ultrasonography. Cox proportion hazard regression analysis was used to assess the association between TIR and the risk of incident/progressive LEAD.

RESULTS

During a median follow-up of 7.4 years, 450 participants developed incident/progressive LEAD. The multivariable-adjusted hazard ratios (HRs) for incident/progressive LEAD across different levels of TIR ( > 85%, 71~85%, 51~70%, and ≤50%) were 1.00, 1.15 (95% confidence interval [CI] 0.87-1.52), 1.37 (95% CI 1.04-1.80) and 1.46 (95% CI 1.10-1.94) (P for trend = 0.004), respectively. With each 10% decrease in TIR, the multivariable-adjusted risk of incident/progressive LEAD increased by 7% (95% CI 1.02-1.11). Similar results were found in the association between TIR and incident LEAD as the secondary outcome (P for trend < 0.001).

CONCLUSIONS

The current study found an inverse association of TIR with the risk of LEAD among patients with type 2 diabetes.

Complications of Diabetes and Metrics of Glycemic Management Derived From Continuous Glucose Monitoring

CONTEXT

Although glycated hemoglobin A1c is currently the best parameter used clinically to assess risk for the development of diabetes complications, it does not provide insight into short-term fluctuations in glucose levels. This review summarizes the relationship between continuous glucose monitoring (CGM)-derived metrics of glycemic variability and diabetes-related complications.

EVIDENCE ACQUISITION

PubMed and Embase databases were searched from January 1, 2010 to August 22, 2020, using the terms type 1 diabetes, type 2 diabetes, diabetes-related microvascular and macrovascular complications, and measures of glycaemic variability. Exclusion criteria were studies that did not use CGM and studies involving participants who were not diabetic, acutely unwell (post stroke, post surgery), pregnant, or using insulin pumps.

EVIDENCE SYNTHESIS

A total of 1636 records were identified, and 1602 were excluded, leaving 34 publications in the final review. Of the 20 852 total participants, 663 had type 1 diabetes (T1D) and 19 909 had type 2 diabetes (T2D). Glycemic variability and low time in range (TIR) showed associations with all studied microvascular and macrovascular complications of diabetes. Notably, higher TIR was associated with reduced risk of albuminuria, retinopathy, cardiovascular disease mortality, all-cause mortality, and abnormal carotid intima-media thickness. Peripheral neuropathy was predominantly associated with standard deviation of blood glucose levels (SD) and mean amplitude of glycemic excursions (MAGE).

CONCLUSION

The evidence supports the association between diabetes complications and CGM-derived measures of intraday glycemic variability. TIR emerged as the most consistent measure, supporting its emerging role in clinical practice. More longitudinal studies and trials are required to confirm these associations, particularly for T1D, for which there are limited data.

Virtual Endocrinology Care Emphasizing Data-Driven Insights and Continuous Engagement and Its Impact on Glycemic Outcomes in Patients With Uncontrolled Diabetes: A Real-world Retrospective Case Series

Background

Steady Health’s novel virtual care model incorporates continuous glucose monitoring (CGM) and a multidisciplinary approach to timely person-centered diabetes care.

Objective

This real-world retrospective case series explores the early glycemic outcomes of its patients with uncontrolled diabetes.

Methods

All patients of Steady Health who had an initial time in range (TIR) below 70% from their first 4 weeks of available CGM data and who had completed onboarding by February 2021 were included in this analysis. We compared the change in TIR, time below range, and average blood glucose from their first 4 weeks with their latest 4 weeks of available CGM data. Hemoglobin A_1c (HbA_1c) values at baseline and at the end of the study were also compared. Patients completed a questionnaire assessing their satisfaction with Steady Health’s intervention.

Results

A total of 53 patients (n=35, 66% with type 1 diabetes; n=44, 83% treated with insulin) were included in this analysis. This cohort had a median baseline TIR of 53.0% (IQR 40.9%, 61.7%) and saw a median change in TIR of +16.6% (IQR +6.0%, +27.9%; P<.001) over a median duration of care of 11 months, amounting to nearly 4 more hours spent between 70 to 180 mg/dL a day. Of the 27 patients who had both baseline and follow-up HbA_1c results, their median baseline HbA_1c was 8.6% (IQR 7.5%, 11.4%; 70 mmol/mol), while their median change in HbA_1c was –1.2% (IQR –2.6%, –0.2%; P=.001). Importantly, these glycemic improvements were achieved with a median decrease in the time below range by –0.3% (IQR –1.1%, 0.0%; P<.001), regardless of whether patients were started on an automated insulin delivery system. A total of 40 (75.5%) patients improved TIR by ≥5%, and 27 (50.9%) achieved TIR≥70% by the end of the study. Glycemic improvements were greatest among patients with the lowest baseline TIR and those who collaborated most intensively with Steady Health’s clinicians. A total of 25 of these patients responded to a questionnaire assessing levels of satisfaction with their care, and all of them agreed that Steady Health had a positive impact on their diabetes management.

Conclusions

Our findings suggest that patients with uncontrolled diabetes can achieve significant glycemic improvements by working with a virtual multidisciplinary care team that uses CGM to provide continuous clinical feedback and support.

Comparisons of efficacy and safety in insulin glargine and lixisenatide plus glulisine combination therapy with multiple daily injection therapy in Japanese patients with type 2 diabetes

AIMS/INTRODUCTION

Multiple daily injection therapy for early glycemic control in patients with type 2 diabetes mellitus is associated with hypoglycemia and weight gain. This study aimed to compare the efficacy (time in range of glucose level 70-180 mg/dL), safety (time below range level 1 of glucose <70 mg/dL), glycemic variability changes, therapeutic indices, body mass index and titration periods between multiple daily injection and insulin glargine U100 and lixisenatide (iGlarLixi) combination (iGlarLixi + insulin glulisine; injected once daily [evenings]) therapies using intermittent continuous glucose monitoring.

MATERIALS AND METHODS

A total of 40 hospitalized patients with type 2 diabetes were randomly assigned to the iGlarLixi + insulin glulisine group or the multiple daily injection group. An intermittent continuous glucose monitoring system was attached, and each injection was adjusted to achieve the target glucose level according to the respective titration algorithm. Times in and below the range were analyzed using data collected on days 11-13 of the intermittent continuous glucose monitoring.

RESULTS

The time in range did not significantly differ between the groups. However, the time below range level 1 was lower in the iGlarLixi + insulin glulisine group (P = 0.047). The changes in glycemic variability, therapeutic indices and body mass index were not significantly different between the groups, although the titration period was significantly shorter in the iGlarLixi + insulin glulisine group (P = 0.033).

CONCLUSIONS

iGlarLixi + insulin glulisine combination therapy is safe and equally efficacious as multiple daily injection therapy for glycemic control, while avoiding hypoglycemia risk and reducing the number of injections are required.

Continuous glucose monitoring in primary care - are we there?

PURPOSE OF REVIEW

In this review, we examine the expanding role of continuous glucose monitoring in glycaemic management in primary care.

RECENT FINDINGS

Improving technology and decreasing cost have increased the uptake of use of continuous glucose monitoring (CGM) for glycaemic management in primary care, wherein most diabetes is managed. Optimized use of this technology, however, will require a convergence of several factors. Availability of devices for people with diabetes, availability of data at the time of clinical interactions, and expertise in interpretation of CGM and ambulatory glucose profile (AGP) data, as well as optimization of therapies, will be required. Significant progress has been made in all three areas in recent years, yet creating systems of support for widespread use of CGM in primary care remains an area of active investigation.

SUMMARY

There has been significant uptake in the use of CGM in the management of diabetes in primary care. Optimized use, however, requires both access to CGM data and the expertise to use the data. Although promising strategies have emerged, the task of generalizing these strategies to the broad population of primary care in America is ongoing. CGM technology holds significant potential for improving glycaemic management in primary care, yet important work remains to leverage the full potential of this promising technology.

Significance of Glycemic Variability in Diabetes Mellitus

The goal of diabetes treatment is to maintain good glycemic control, prevent the development and progression of diabetic complications, and ensure the same quality of life and life expectancy as healthy people. Hemoglobin A1c (HbA1c) is used as an index of glycemic control, but strict glycemic control using HbA1c as an index may lead to severe hypoglycemia and cardiovascular death. Glycemic variability (GV), such as excessive hyperglycemia and hypoglycemia, is associated with diabetic vascular complications and has been recognized as an important index of glycemic control. Here, we reviewed the definition and evaluated the clinical usefulness of GV, and its relationship with diabetic complications and therapeutic strategies to reduce GV.

Relationship Between Time in Range, Glycemic Variability, HbA1c, and Complications in Adults With Type 1 Diabetes Mellitus

PURPOSE

Real-time continuous glucose monitoring (RT-CGM) provides information on glycemic variability (GV), time in range (TIR), and guidance to avoid hypoglycemia, thereby complimenting HbA1c for diabetes management. We investigated whether GV and TIR were independently associated with chronic and acute diabetes complications.

METHODS

Between September 2014 and January 2017, 515 subjects with type 1 diabetes using sensor-augmented pump therapy were followed for 24 months. The link between baseline HbA1c and CGM-derived glucometrics (TIR [70-180 mg/dL], coefficient of variation [CV], and SD) obtained from the first 2 weeks of RT-CGM use and the presence of complications was investigated. Complications were defined as: composite microvascular complications (presence of neuropathy, retinopathy, or nephropathy), macrovascular complications, and hospitalization for hypoglycemia and/or ketoacidosis.

RESULTS

Individuals with microvascular complications were older (P < 0.001), had a longer diabetes duration (P < 0.001), a higher HbA1c (7.8 ± 0.9 vs 7.5 ± 0.9%, P < 0.001), and spent less time in range (60.4 ± 12.2 vs 63.9 ± 13.8%, P = 0.022) compared with those without microvascular complication. Diabetes duration (odds ratio [OR] = 1.12 [1.09-1.15], P < 0.001) and TIR (OR = 0.97 [0.95-0.99], P = 0.005) were independent risk factors for composite microvascular complications, whereas SD and CV were not. Age (OR = 1.08 [1.03-1.14], P = 0.003) and HbA1c (OR = 1.80 [1.02-3.14], P = 0.044) were risk factors for macrovascular complications. TIR (OR = 0.97 [0.95-0.99], P = 0.021) was the only independent risk factor for hospitalizations for hypoglycemia or ketoacidosis.

CONCLUSIONS

Lower TIR was associated with the presence of composite microvascular complications and with hospitalization for hypoglycemia or ketoacidosis. TIR, SD, and CV were not associated with macrovascular complications.

Factors leading to alpelisib discontinuation in patients with hormone receptor positive, human epidermal growth factor receptor-2 negative breast cancer

PURPOSE

Alpelisib is a phosphoinositide-3-kinase inhibitor approved for hormone-receptor-positive, PIK3CA-mutated metastatic breast cancer. However, length of drug exposure, maximum-tolerated dose, and therefore clinical response can vary significantly outside of the trial setting. This study evaluates our center's "real world" experience with alpelisib and focuses on duration of therapy and factors associated with cancer progression.

METHODS

Patients receiving alpelisib at our center between 2019 and 2021 were identified. We evaluated duration of alpelisib therapy and the causative reasons for drug discontinuation. The association of drug duration and dose with subsequent cancer progression were assessed, along with the association between hyperglycemia during alpelisib therapy and cancer progression.

RESULTS

Sixty-two women prescribed alpelisib were included (mean age 61 years). Disease progression was the most common reason for drug discontinuation, while discontinuation within 30 days was primarily attributed to adverse events (AEs). Among those who progressed, median time to progression was longer in those on alpelisib for > 90 days compared with those on alpelisib for ≤ 90 days (187 vs. 77 days, p < 0.001). At 200 days, freedom from progression was greater for those on alpelisib for > 90 days compared to those receiving therapy for ≤ 90 days (59% vs. 19%, p = 0.001). Median blood glucose as a continuous variable was associated with disease progression (HR 1.01, 95% CI 1.00-1.02, p = 0.02).

CONCLUSION

While progression of disease is the largest contributor to alpelisib discontinuation, AEs are the leading cause for early drug cessation. Shorter alpelisib exposure is associated with greater cancer progression. Further studies are needed to determine the impact of sustained hyperglycemia on cancer progression.

Can Faster Aspart Be Used to Optimize Glycemic Control With Insulin Pump Therapy? From Expectations to Lessons Learned After a Year of Use in the United States

Fast-acting insulin aspart (faster aspart) is an ultra-rapid-acting formulation of insulin aspart developed to more closely match the prandial endogenous insulin profile, and its accelerated absorption kinetics are expected to provide clinical benefits for patients using insulin pump therapy. A head-to-head trial versus the original insulin aspart formulation in pump therapy did not demonstrate superiority of faster aspart in terms of A1C reduction, but pump settings were not optimized for the pharmacokinetic/pharmacodynamic profile of faster aspart. Nevertheless, meal test and continuous glucose monitoring data suggest that faster aspart is beneficial for postprandial glucose control, and a case study is presented illustrating excellent results using this insulin in pump therapy. Frequent blood glucose monitoring and appropriate patient education are vital for success.

6. Glycemic Targets: 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.

Effects of Teneligliptin on HbA1c levels, Continuous Glucose Monitoring-Derived Time in Range and Glycemic Variability in Elderly Patients with T2DM (TEDDY Study)

BACKGROUND

To evaluate the effects of teneligliptin on glycosylated hemoglobin (HbA1c) levels, continuous glucose monitoring (CGM)-derived time in range, and glycemic variability in elderly type 2 diabetes mellitus patients.

METHODS

This randomized, double-blinded, placebo-controlled study was conducted in eight centers in Korea (clinical trial registration number: NCT03508323). Sixty-five participants aged ≥65 years, who were treatment-naïve or had been treated with stable doses of metformin, were randomized at a 1:1 ratio to receive 20 mg of teneligliptin (n=35) or placebo (n=30) for 12 weeks. The main endpoints were the changes in HbA1c levels from baseline to week 12, CGM metrics-derived time in range, and glycemic variability.

RESULTS

After 12 weeks, a significant reduction (by 0.84%) in HbA1c levels was observed in the teneligliptin group compared to that in the placebo group (by 0.08%), with a between-group least squares mean difference of -0.76% (95% confidence interval [CI], -1.08 to -0.44). The coefficient of variation, standard deviation, and mean amplitude of glycemic excursion significantly decreased in participants treated with teneligliptin as compared to those in the placebo group. Teneligliptin treatment significantly decreased the time spent above 180 or 250 mg/dL, respectively, without increasing the time spent below 70 mg/dL. The mean percentage of time for which glucose levels remained in the 70 to 180 mg/dL time in range (TIR70-180) at week 12 was 82.0%±16.0% in the teneligliptin group, and placebo-adjusted change in TIR70-180 from baseline was 13.3% (95% CI, 6.0 to 20.6).

CONCLUSION

Teneligliptin effectively reduced HbA1c levels, time spent above the target range, and glycemic variability, without increasing hypoglycemia in our study population.

Association of continuous glucose monitoring-derived time in range with major amputation risk in diabetic foot osteomyelitis patients undergoing amputation

OBJECTIVE

The metrics generated from continuous glucose monitoring (CGM), such as time in range (TIR), are strongly correlated with diabetes complications. This study explored the association of perioperative CGM-derived metrics with major amputation risk in patients with diabetic foot osteomyelitis (DFO).

METHODS

This study recruited 55 DFO patients with grade 3-4 wounds according to the Wagner Diabetic Foot Ulcer Classification System, all of whom underwent CGM for 5 days during the perioperative period. The CGM-derived metrics were defined in accordance with the most recent international consensus recommendations.

RESULTS

Patients with major amputation had significantly less TIR and higher time below range (TBR) (all p < 0.05). In binary logistic regression analyses, a lower TIR was associated with the risk of major amputation (odds ratio: 0.83 (95% confidence interval: 0.71-0.99), p = 0.039). This association remained statistically significant after adjustments for age, sex, body mass index, type of diabetes, smoking, drinking, durations of diabetes and DFU, ankle-brachial index, albumin, estimated-glomerular filtration rate, Society for Vascular Surgery wound, ischemia, and foot infection (WIfi) stage, multidrug-resistant organisms, and hemoglobin A1c. Further adjustment for the mean amplitude of glycemic excursion (MAGE) reduced this association. TBR was also independently associated with the risk of major amputation (odds ratio: 1.60 (95% confidence interval: 1.17-2.18), p = 0.003); this association persisted after adjustment for MAGE.

CONCLUSION

Perioperative TIR (3.9-10.0 mmol/L) and TBR (<3.9 mmol/L) were significantly associated with major amputation in hospitalized patients with DFO.

Time in range, as measured by continuous glucose monitor, as a predictor of microvascular complications in type 2 diabetes: a systematic review

Continuous glucose monitoring (CGM)-derived time in range (TIR) correlates with hemoglobin A1c (A1c) among patients with type 2 diabetes mellitus (T2DM); however, there is a paucity of data evaluating its association with microvascular complications. We conducted this systematic review to examine the association between TIR and microvascular complications of diabetic retinopathy (DR), diabetic nephropathy (DN), and diabetic peripheral neuropathy (DPN). We conducted a comprehensive literature search on PubMed, Scopus, and Web of Science online databases following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Full-text original articles that evaluated the association between CGM-derived TIR and risk of microvascular complications and were published between 2010 and June 2021 were included in our systematic review. The quality of the included studies was evaluated using the National Heart, Lung, and Blood Institute Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies. Data were analyzed using qualitative synthesis. Eleven studies on a total of 13 987 patients were included in the systematic review. The median sample size, baseline A1c, and diabetes duration were 466 patients (range: 105-5901), 8.2% (SD 0.5%), and 11.3 years (1.0), respectively. Majority of the studies were conducted in Asia (10 out of 11). Four studies evaluated the relationship between CGM-derived TIR and DR and CGM-derived TIR and DN, while seven studies evaluated the relationship between CGM-derived TIR and DPN. A 10% increase in TIR was associated with a reduction in albuminuria, severity of DR, and prevalence of DPN and cardiac autonomic neuropathy. In addition, an association was observed between urinary albumin to creatinine ratio but not with estimated glomerular filtration rate. This review summarizes recent evidence supporting an association between CGM-derived TIR and microvascular complications among patients with T2DM. A larger-scale multicenter investigation that includes more diverse participants is warranted to further validate the utility of TIR as a predictor of diabetic microvascular complications.

The Effect of Discontinuing Continuous Glucose Monitoring in Adults With Type 2 Diabetes Treated With Basal Insulin

OBJECTIVE

To explore the effect of discontinuing continuous glucose monitoring (CGM) after 8 months of CGM use in adults with type 2 diabetes treated with basal without bolus insulin.

RESEARCH DESIGN AND METHODS

This multicenter trial had an initial randomization to either real-time CGM or blood glucose monitoring (BGM) for 8 months followed by 6 months in which the BGM group continued to use BGM (n = 57) and the CGM group was randomly reassigned either to continue CGM (n = 53) or discontinue CGM with resumption of BGM for glucose monitoring (n = 53).

RESULTS

In the group that discontinued CGM, mean time in range (TIR) 70-180 mg/dL, which improved from 38% before initiating CGM to 62% after 8 months of CGM, decreased after discontinuing CGM to 50% at 14 months (mean change from 8 to 14 months -12% [95% CI -21% to -3%], P = 0.01). In the group that continued CGM use, little change was found in TIR from 8 to 14 months (baseline 44%, 8 months 56%, 14 months 57%, mean change from 8 to 14 months 1% [95% CI -11% to 12%], P = 0.89). Comparing the two groups at 14 months, the adjusted treatment group difference in mean TIR was -6% (95% CI -16% to 4%, P = 0.20).

CONCLUSIONS

In adults with type 2 diabetes treated with basal insulin who had been using real-time CGM for 8 months, discontinuing CGM resulted in a loss of about one-half of the initial gain in TIR that had been achieved during CGM use.

A personalized blood glucose level prediction model with a fine-tuning strategy: A proof-of-concept study

BACKGROUND

The accurate prediction of blood glucose (BG) level is still a challenge for diabetes management. This is due to various factors such as diet, personal physiological characteristics, stress, and activities influence changes in BG level. To develop an accurate BG level predictive model, we propose a personalized model based on a convolutional neural network (CNN) with a fine-tuning strategy.

METHODS

We utilized continuous glucose monitoring (CGM) datasets from 1052 professional CGM sessions and split them into three groups according to type 1, type 2, and gestational diabetes mellitus (T1DM, T2DM, and GDM, respectively). During the preprocessing, only CGM data points were utilized, and future BG levels of four different prediction horizons (PHs, 15, 30, 45, and 60 min) were used as output. In training, we trained a general CNN and a multi-output random forest regressor using a hold-out method for each group. Next, we developed two personalized models: (1) by fine-tuning the general CNN on partial sample points of each CGM dataset, and (2) by learning a CNN from scratch on the points.

RESULTS

For all groups, the fine-tuned CNN showed the lowest average root mean squared error, average mean absolute percentage error, highest average time gain (PH = 15 and 60 min in T1DM) and highest percentage in region A of Clarke error grid analysis at all PHs. In the performance comparison between the fine-tuned CNN and other models, we found that the fine-tuned CNN improved the performance of the general CNN in most cases and outperformed the scratch CNN at all PHs in all groups, making the fine-tuning strategy was useful for accurate BG level prediction. We analyzed all cases of four predictive patterns in each group, and found that the input BG level trend and the BG level at the time of prediction were related to the future BG level trend.

CONCLUSIONS

We demonstrated the efficacy of the fine-tuning method in a large number of CGM datasets and analyzed the four predictive patterns. Therefore, we believe that the proposed method will significantly contribute to the development of an accurate personalized model and the analysis for its predictions.

Metformin improves glycemic variability in adults with type 1 diabetes mellitus: an open-label randomized control trial

INTRODUCTION

Metformin has been demonstrated to enhance cardioprotective benefits in type 1 diabetes (T1DM). Although glycemic variability (GV) is associated with increased risk of CVD in diabetes, there is a scarcity of research evaluating the effect of metformin on GV in T1DM.

OBJECTIVES

In the present study, the effects of adjuvant metformin therapy on GV and metabolic control in T1DM were explored.

PATIENTS AND METHODS

A total of 65 adults with T1DM were enrolled and subjected to physical examination, fasting laboratory tests, and continuous glucose monitoring, and subsequently randomized 1:1 to 3 months of 1000-2000 mg metformin daily add-on insulin (MET group, n = 34) or insulin (non-MET group, n = 31). After, baseline measurements were repeated.

RESULTS

The mean amplitude of glycemic excursions was substantially reduced in MET group, compared with non-MET group (-1.58 (-3.35, 0.31) mmol/L vs 1.36 (-1.12, 2.24) mmol/L, P = 0.004). In parallel, the largest amplitude of glycemic excursions (-2.83 (-5.47, -0.06) mmol/L vs 0.45 (-1.29, 4.48) mmol/L, P = 0.004), the s.d. of blood glucose (-0.85 (-1.51, 0.01) mmol/L vs -0.14 (-0.68, 1.21) mmol/L, P = 0.015), and the coefficient of variation (-6.66 (-15.00, 1.50)% vs -1.60 (-6.28, 11.71)%, P = 0.012) all demonstrated improvement in the MET group, compared with the non-MET group. Significant reduction in insulin dose, BMI, and body weight was observed in patients in MET, not those in non-MET group.

CONCLUSION

Additional metformin therapy improved GV in adults with T1DM, as well as improving body composition and reducing insulin requirement. Hence, metformin as an adjunctive therapy has potential prospects in reducing the CVD risk in patients with T1DM in the long term.

Evaluation of the Long-Term Cost-Effectiveness of the Dexcom G6 Continuous Glucose Monitor versus Self-Monitoring of Blood Glucose in People with Type 1 Diabetes in Canada

BACKGROUND

The Dexcom G6 real-time continuous glucose monitoring (RT-CGM) system is one of the most sophisticated RT-CGM systems developed to date and became available in Canada in 2019. A health economic analysis was performed to determine the long-term cost-effectiveness of the Dexcom G6 RT-CGM system versus SMBG in adults with type 1 diabetes (T1D) in Canada.

METHODS

The analysis was performed using the IQVIA Core Diabetes Model. Based on clinical trial data, patients with mean baseline HbA1c of 8.6% were assumed to have a HbA1c reduction of 1.0% with RT-CGM versus 0.4% reduction with SMBG. RT-CGM was also associated with a quality of life (QoL) benefit owing to reduced incidence of hypoglycemia, reduced fear of hypoglycemia (FoH) and elimination of fingerstick testing. Direct medical costs were sourced from published literature, and inflated to 2019 Canadian dollars (CAD).

RESULTS

Dexcom G6 RT-CGM was projected to improve mean quality-adjusted life expectancy by 2.09 quality-adjusted life years (QALYs) relative to SMBG (15.52 versus 13.43 QALYs) but mean total lifetime cots were CAD 35,353 higher with RT-CGM (CAD 227,357 versus CAD 192,004) resulting in an incremental cost-effectiveness ratio (ICER) of CAD 16,931 per QALY gained. Sensitivity analyses revealed that assumptions relating to the QoL benefit associated with reduced FoH and the elimination of fingerstick testing with RT-CGM as well as SMBG usage and change in HbA1c were the key drivers of cost-effectiveness.

CONCLUSION

For adults with T1D in Canada, RT-CGM is associated with improved glycemic control and QoL benefits owing to a reduced FoH and elimination of the requirement for fingerstick testing and over a lifetime time horizon is cost-effective relative to SMBG.

Daytime Glycemic Variability and Frailty in Older Patients with Diabetes: a Pilot Study Using Continuous Glucose Monitoring

We investigated the relationship between glucose variability and frailty. Forty-eight type 2 diabetic patients aged ≥ 65 years were enrolled. The FRAIL scale was used for frailty assessment, and participants were classified into 'healthy & pre-frail' (n = 24) and 'frail' (n = 24) groups. A continuous glucose monitoring (CGM) system was used for a mean of 6.9 days and standardized CGM metrics were analyzed: mean glucose, glucose management indicator (GMI), coefficient of variation, and time in range, time above range (TAR), and time below range. The demographics did not differ between groups. However, among the CGM metrics, mean glucose, GMI, and TAR in the postprandial periods were higher in the frail group (all P < 0.05). After multivariate adjustments, the post-lunch TAR (OR = 1.12, P = 0.019) affected the prevalence of frailty. Higher glucose variability with marked daytime postprandial hyperglycemia is significantly associated with frailty in older patients with diabetes.

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

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

Association of time in range with hemoglobin A1c, glycated albumin and 1,5-anhydro-d-glucitol

AIMS/INTRODUCTION

Hemoglobin A1c (HbA1c), glycated albumin (GA) and 1,5-anhydro-d-glucitol (1,5-AG) are used as indicators of glycemic control, whereas continuous glucose monitoring (CGM) is used to assess daily glucose profiles. The aim of this study was to investigate the relationships between CGM metrics, such as time in range (TIR), and glycemic control indicators.

MATERIALS AND METHODS

We carried out retrospective CGM and blood tests on 189 outpatients with impaired glucose tolerance (n = 22), type 1 diabetes mellitus (n = 67) or type 2 diabetes mellitus (n = 100).

RESULTS

In type 1 diabetes mellitus and type 2 diabetes mellitus patients, HbA1c and GA were negatively correlated with TIR, whereas 1,5-AG was positively correlated with TIR. In type 1 diabetes mellitus patients, a TIR of 70% corresponded to HbA1c, GA and 1,5-AG of 6.9% (95% confidence interval [CI] 6.5-7.2%), 20.3% (95% CI 19.0-21.7%) and 6.0 µg/mL (95% CI 5.1-6.9 µg/mL), respectively. In type 2 diabetes mellitus patients, a TIR of 70% corresponded to HbA1c, GA and 1,5-AG of 7.1% (95% CI 7.0-7.3%), 19.3% (95% CI 18.7-19.9%) and 10.0 µg/mL (95% CI 9.0-11.0 µg/mL), respectively. TIR values corresponding to HbA1c levels of 7.0% were 56.1% (95% CI 52.3-59.8%) and 74.2% (95% CI 71.3-77.2%) in type 1 diabetes mellitus and type 2 diabetes mellitus patients, respectively.

CONCLUSIONS

The results of this study showed that the estimated HbA1c corresponding to a TIR of 70% was approximately 7.0% for both type 1 diabetes mellitus and type 2 diabetes mellitus patients, and that the estimated 1,5-AG calculated from the TIR of 70% might be different between type 1 diabetes mellitus and type 2 diabetes mellitus patients.

American Association of Clinical Endocrinology Clinical Practice Guideline: The Use of Advanced Technology in the Management of Persons With Diabetes Mellitus

OBJECTIVE

To provide evidence-based recommendations regarding the use of advanced technology in the management of persons with diabetes mellitus to clinicians, diabetes-care teams, health care professionals, and other stakeholders.

METHODS

The American Association of Clinical Endocrinology (AACE) conducted literature searches for relevant articles published from 2012 to 2021. A task force of medical experts developed evidence-based guideline recommendations based on a review of clinical evidence, expertise, and informal consensus, according to established AACE protocol for guideline development.

MAIN OUTCOME MEASURES

Primary outcomes of interest included hemoglobin A1C, rates and severity of hypoglycemia, time in range, time above range, and time below range.

RESULTS

This guideline includes 37 evidence-based clinical practice recommendations for advanced diabetes technology and contains 357 citations that inform the evidence base.

RECOMMENDATIONS

Evidence-based recommendations were developed regarding the efficacy and safety of devices for the management of persons with diabetes mellitus, metrics used to aide with the assessment of advanced diabetes technology, and standards for the implementation of this technology.

CONCLUSIONS

Advanced diabetes technology can assist persons with diabetes to safely and effectively achieve glycemic targets, improve quality of life, add greater convenience, potentially reduce burden of care, and offer a personalized approach to self-management. Furthermore, diabetes technology can improve the efficiency and effectiveness of clinical decision-making. Successful integration of these technologies into care requires knowledge about the functionality of devices in this rapidly changing field. This information will allow health care professionals to provide necessary education and training to persons accessing these treatments and have the required expertise to interpret data and make appropriate treatment adjustments.

The Association Between Continuous Glucose Monitoring-Derived Metrics and Cardiovascular Autonomic Neuropathy in Outpatients with Type 2 Diabetes

Background: Continuous glucose monitoring (CGM)-derived metrics, including time in range (TIR), are attracting attention as new indicators, beyond hemoglobin A1c, of glycemic control and diabetes complications. This study investigated the associations between CGM-derived TIR, hyperglycemia, and hypoglycemia metrics and cardiovascular autonomic neuropathy (CAN) in patients with type 2 diabetes. Methods: A total of 284 patients with type 2 diabetes who underwent CGM using GOLD™ (Medtronic MiniMed) for 3 days or iPro™2 (Medtronic MiniMed) for 6 days and autonomic function tests within 3 months based on outpatient data were recruited. The definition of CGM-derived metrics was subject to the most recent international consensus. CAN was defined as an abnormal result in two or more parasympathetic test, and the severity of CAN was estimated as the sum of the scores of the five cardiovascular autonomic function tests. Results: A total of 84 patients (29.6%) were diagnosed with CAN, and the mean TIR was 57.0% ± 7.0%. A multiple logistic regression analysis revealed that the odds ratio (OR) of presence of CAN was 0.876 [95% confidence interval (CI): 0.79-0.98] per 10% increase in the TIR 70-180 mg/dL, after adjusting for age, sex, diabetes duration, any medications, and glycemic variability. A 10% increase in the TIR was significantly inversely associated with the severity of CAN (OR: 0.89, 95% CI: 0.81-0.98). Among the metrics of hyperglycemia, each 10% increase in a time above range (TAR) >180 mg/dL was also independently correlated with the presence of CAN (OR: 1.141, 97.5% CI: 1.01-1.29) and the severity of CAN (OR: 1.13, 97.5% CI: 1.01-1.26). Conclusion: A TIR 70-180 mg/dL and a TAR >180 mg/dL were significantly associated with CAN in outpatients with type 2 diabetes.

Clinical Application of Time in Range and Other Metrics

Time in range (TIR) and other continuous glucose monitoring (CGM)-derived metrics have been standardized in international consensus conferences. TIR correlates closely with A1C; a TIR of 70% correlates to an A1C of 6.7-7%. Evidence is emerging on the association of TIR with long-term diabetes complications, and each 10% increase in TIR shows a substantial decrease in risk for long-term complications. Application of TIR to clinical practice can be easily done with a stepped approach to the analysis and interpretation of CGM-derived metrics and the ambulatory glucose profile report. Clinician education and partnership with patients are crucial for successful implementation of TIR and all CGM-derived metrics in clinical practice.