Continuous Glucose Monitoring Metrics Research Articles

Enhancing equity in access to automated insulin delivery systems in an ethnically and socioeconomically diverse group of children with type 1 diabetes

IntroductionManufacturer-supported didactic teaching programmes offer effective automated insulin delivery (AID) systems onboarding in children and young people (CYP) with type 1 diabetes (T1D). However, this approach has limited flexibility to...

The relationship between continuous glucose monitoring metrics, circadian rhythms, and the presence of albuminuria in insulin-using patients with type 2 diabetes

The relationship between continuous glucose monitoring metrics, circadian rhythms, and the presence of albuminuria in insulin-using patients with type 2 diabetes

Glucose Color Index: Development and Validation of a Novel Measure of the Shape of Glycemic Variability.

Standard continuous glucose monitoring (CGM) metrics: mean glucose, standard deviation, coefficient of variation, and time in range, fail to capture the shape of variability in the CGM time series. This information could facilitate improved diabetes management. We analyzed CGM data from 141 adults with type 2 diabetes in the Hyperglycemic Profiles in Obstructive Sleep Apnea (HYPNOS) trial. Participants in HYPNOS wore CGM sensors for up to two weeks at two time points, three months apart. We calculated the log-periodogram for each time period, summarizing using disjoint linear models. These summaries were combined into a single value, termed the Glucose Color Index (GCI), using canonical correlation analysis. We compared the between-wear correlation of GCI with those of standard CGM metrics and assessed associations between GCI and diabetes comorbidities in 398 older adults with type 2 diabetes from the Atherosclerosis Risk in Communities (ARIC) study. The GCI achieved a test-retest correlation of R = .75. Adjusting for standard CGM metrics, the GCI test-retest correlation was R = .55. Glucose Color Index was significantly associated (p < .05) with impaired physical functioning, frailty/pre-frailty, cardiovascular disease, chronic kidney disease, and dementia/mild cognitive impairment after adjustment for confounders. We developed and validated the GCI, a novel CGM metric that captures the shape of glucose variability using the periodogram signal decomposition. Glucose Color Index was reliable within participants over a three-month period and associated with diabetes comorbidities. The GCI suggests a promising avenue toward the development of CGM metrics which more fully incorporate time series information.

Continuous Glucose Monitoring Metrics for Pregnancies Complicated by Diabetes: Critical Appraisal of Current Evidence.

Ascertaining the utility of continuous glucose monitoring (CGM) in pregnancy complicated by diabetes is a rapidly evolving area, as the prevalence of type 1 diabetes (T1D), type 2 diabetes (T2D), and gestational diabetes mellitus (GDM) escalates. The seminal randomized controlled trial (RCT) evaluating CGM use added to standard care in pregnancy in T1D demonstrated significant improvements in maternal glycemia and neonatal health outcomes. Current clinical guidance recommends targets for percentage time in range (TIR), time above range (TAR), and time below range (TBR) during pregnancy complicated by T1D that are widely used in clinical practice. However, the superiority of CGM over blood glucose monitoring (BGM) is still questioned in both T2D and GDM, and whether glucose targets should be different than in T1D is unknown. Questions requiring additional research include which CGM metrics are superior in predicting clinical outcomes, how should pregnancy-specific CGM targets be defined, whether CGM targets should differ according to gestational age, and if CGM metrics during pregnancy should be similar across all types of diabetes. Limiting the potential for CGM to improve pregnancy outcomes may be our inability to maintain TIR > 70% throughout gestation, a goal achieved in the minority of patients studied. Adverse pregnancy outcomes remain high in women with T1D and T2D in pregnancy despite CGM technology, and this review explores the potential reasons and questions yet to be investigated.

Switching from Intermittently Scanned Continuous Glucose Monitoring to Real-Time Continuous Glucose Monitoring with a Predictive Urgent Low Soon Alert Reduces Exposure to Hypoglycemia.

Differences in the effectiveness of real-time continuous glucose monitoring (rtCGM) and intermittently scanned continuous glucose monitoring (isCGM) in type 1 diabetes (T1D) are reported. The impact on percent time in range of switching from an isCGM with glucose threshold-based optional alerts only (FreeStyle Libre 2 [FSL2]) to an rtCGM (Dexcom G7) with an urgent low soon predictive alert was assessed, alongside other secondary outcomes including hemoglobin A1c (HbA1c) and other continuous glucose monitoring metrics. Adults with T1D using FSL2 were switched to Dexcom G7 for 12 weeks. HbA1c and continuous glucose data during FSL2 and Dexcom G7 use were compared. Data from 29 participants (aged 44.8 ± 16.5 years, 12 male and 17 female) were analyzed. After switching to rtCGM, participants spent less time in hypoglycemia below 3.9 mmol/L (70 mg/dL) (3.0% [1.0%, 5.0%] vs. 2.0% [1.0%, 3.0%], P = 0.006) and had higher percentage achievement of time below 3.9 mmol/L (70 mg/dL) of <4% (55.2% vs. 82.8%, P = 0.005). Coefficient of variation was lower (39.3 ± 6.6% vs. 37.2 ± 5.6%, P = 0.008). In conclusion, adults with T1D who switched from isCGM to rtCGM may benefit from reduced exposure to hypoglycemia and glycemic variability.

Comparing Equil patch versus traditional catheter insulin pump in type 2 diabetes using continuous glucose monitoring metrics and profiles.

It is not clear whether there are differences in glycemic control between the Equil patch and the MMT-712 insulin pump. Our objective was to compare two types of insulin pumps in the treatment of type 2 diabetes mellitus (T2DM), using continuous glucose monitoring (CGM) metrics and profiles. This was a randomized case-crossover clinical trial. Participants were hospitalized and randomly allocated to two groups and underwent two types of insulin pump treatments (group A: Equil patch-Medtronic MMT-712 insulin pump; group B: Medtronic MMT-712-Equil patch insulin pump) separated by a 1-day washout period. Glycemic control was achieved after 7-8 days of insulin pump therapy. Each patient received CGM for 5 consecutive days (from day 1 to day 5). On day 3 of CGM performance, the Equil patch insulin pump treatment was switched to Medtronic MMT-712 insulin pump treatment at the same basal and bolus insulin doses or vice versa. CGM metrics and profiles including glycemic variability (GV), time in range (TIR, 3.9-10.0 mmol/L), time below range (TBR, <3.9 mmol/L), time above range (TAR, >10.0 mmol/L), and postprandial glucose excursions, as well as incidence of hypoglycemia. Forty-six T2DM patients completed the study. There was no significant difference in parameters of daily GV and postprandial glucose excursions between the Equil patch insulin pump treatment and the Medtronic insulin pump treatment. Similarly, there was no between-treatment difference in TIR, TBR, and TAR, as well as the incidence of hypoglycemia. The Equil patch insulin pump was similar to the traditional MMT-712 insulin pump in terms of glycemic control. Equil patch insulin pump is a reliable tool for glycemic management of diabetes mellitus.

Intra-pancreatic fat is associated with continuous glucose monitoring metrics.

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

Continuous glucose monitoring metrics in pregnancy with type 1 diabetes mellitus.

Managing diabetes during pregnancy is challenging, given the significant risk it poses for both maternal and foetal health outcomes. While traditional methods involve capillary self-monitoring of blood glucose level monitoring and periodic HbA1c tests, the advent of continuous glucose monitoring (CGM) systems has revolutionized the approach. These devices offer a safe and reliable means of tracking glucose levels in real-time, benefiting both women with diabetes during pregnancy and the healthcare providers. Moreover, CGM systems have shown a low rate of side effects and high feasibility when used in pregnancies complicated by diabetes, especially when paired with continuous subcutaneous insulin infusion pump as hybrid closed loop device. Such a combined approach has been demonstrated to improve overall blood sugar control, lessen the occurrence of preeclampsia and neonatal hypoglycaemia, and minimize the duration of neonatal intensive care unit stays. This paper aims to offer a comprehensive evaluation of CGM metrics specifically tailored for pregnancies impacted by type 1 diabetes mellitus.

Associations between daily step count classifications and continuous glucose monitoring metrics in adults with type 1 diabetes: analysis of the Type 1 Diabetes Exercise Initiative (T1DEXI) cohort.

Adults with type 1 diabetes should perform daily physical activity to help maintain health and fitness, but the influence of daily step counts on continuous glucose monitoring (CGM) metrics are unclear. This analysis used the Type 1 Diabetes Exercise Initiative (T1DEXI) dataset to investigate the effect of daily step count on CGM-based metrics. In a 4 week free-living observational study of adults with type 1 diabetes, with available CGM and step count data, we categorised participants into three groups-below (<7000), meeting (7000-10,000) or exceeding (>10,000) the daily step count goal-to determine if step count category influenced CGM metrics, including per cent time in range (TIR: 3.9-10.0 mmol/l), time below range (TBR: <3.9 mmol/l) and time above range (TAR: >10.0 mmol/l). A total of 464 adults with type 1 diabetes (mean±SD age 37±14 years; HbA1c 48.8±8.1 mmol/mol [6.6±0.7%]; 73% female; 45% hybrid closed-loop system, 38% standard insulin pump, 17% multiple daily insulin injections) were included in the study. Between-participant analyses showed that individuals who exceeded the mean daily step count goal over the 4 week period had a similar TIR (75±14%) to those meeting (74±14%) or below (75±16%) the step count goal (p>0.05). In the within-participant comparisons, TIR was higher on days when the step count goal was exceeded or met (both 75±15%) than on days below the step count goal (73±16%; both p<0.001). The TBR was also higher when individuals exceeded the step count goals (3.1%±3.2%) than on days when they met or were below step count goals (difference in means -0.3% [p=0.006] and -0.4% [p=0.001], respectively). The total daily insulin dose was lower on days when step count goals were exceeded (0.52±0.18 U/kg; p<0.001) or were met (0.53±0.18 U/kg; p<0.001) than on days when step counts were below the current recommendation (0.55±0.18 U/kg). Step count had a larger effect on CGM-based metrics in participants with a baseline HbA1c ≥53 mmol/mol (≥7.0%). Our results suggest that, compared with days with low step counts, days with higher step counts are associated with slight increases in both TIR and TBR, along with small reductions in total daily insulin requirements, in adults living with type 1 diabetes. The data that support the findings reported here are available on the Vivli Platform (ID: T1-DEXI; https://doi.org/10.25934/PR00008428 ).

Metabolic health tracking using Ultrahuman M1 continuous glucose monitoring platform in non- and pre-diabetic Indians: a multi-armed observational study

Continuous glucose monitoring (CGM) device adoption in non- and pre-diabetics for preventive healthcare has uncovered a paucity of benchmarking data on glycemic control and insulin resistance for the high-risk Indian/South Asian demographic. Furthermore, the correlational efficacy between digital applications-derived health scores and glycemic indices lacks clear supportive evidence. In this study, we acquired glycemic variability (GV) using the Ultrahuman (UH) M1 CGM, and activity metrics via the Fitbit wearable for Indians/South Asians with normal glucose control (non-diabetics) and those with pre-diabetes (N = 53 non-diabetics, 52 pre-diabetics) for 14 days. We examined whether CGM metrics could differentiate between the two groups, assessed the relationship of the UH metabolic score (MetSc) with clinical biomarkers of dysglycemia (OGTT, HbA1c) and insulin resistance (HOMA-IR); and tested which GV metrics maximally correlated with inflammation (Hs-CRP), stress (cortisol), sleep, step count and heart rate. We found significant inter-group differences for mean glucose levels, restricted time in range (70–110 mg/dL), and GV-by-SD, all of which improved across days. Inflammation was strongly linked with specific GV metrics in pre-diabetics, while sleep and activity correlated modestly in non-diabetics. Finally, MetSc displayed strong inverse relationships with insulin resistance and dysglycemia markers. These findings present initial guidance GV data of non- and pre-diabetic Indians and indicate that digitally-derived metabolic scores can positively influence glucose management.

Associations between continuous glucose monitoring (CGM) metrics and psycholinguistic measures: a correlational study.

Recently, the relationship between diabetes and mental health has been widely studied. With the advent of continuous glucose monitoring (CGM), some researchers have been interested in exploring the association between glucose-related metrics and psychological aspects. These studies have primarily relied on self-report questionnaires which present some limitations. Therefore, the present multicenter study aims at testing potential associations between CGM metrics and affective processes derived from narratives about using a CGM sensor. An exploratory correlational design was used. Fifty-eight adults with type 1 diabetes using CGM were enrolled and invited to complete an online survey, where they replied to an open-ended question regarding their personal experience with the CGM sensor. Texts derived from the answers were analyzed through Linguistic Inquiry andWord Count, a widely used text analysis tool that can automatically identify and quantify linguistic patterns related to various psychological dimensions. Psycholinguistic measures were correlated with CGM metrics. Higher levels of sadness/depression correlated with lower %TIR (r = - 339; p < .01) and higher %TAR (r = .342; p < .01). The study highlights the relationship between CGM metrics and psychological variables derived from patients' narratives. In particular, it is possible to hypothesize a positive role of %TIR in reducing depressive feelings in individuals with diabetes, as well as a negative role of depressive feelings in achieving desirable CGM outcomes. Additionally, there is a potential role of glycemic variability, particularly hyperglycemia, in the expression of depressive and sad feelings, which has been less studied compared to the effects of hypoglycemia.

Clinical Outcomes with MiniMedTM 780G Advanced Hybrid Closed-Loop Therapy in 2- to 6-Year-Old Children with Type 1 Diabetes.

Advanced hybrid closed-loop (AHCL) therapy with the Medtronic MiniMed™ 780G system improves glycemia; however, the clinical outcomes in younger children remain less established. This pilot study aimed to explore the continuous glucose monitoring (CGM) metrics in very young children on AHCL. Children between 2 and 7 years of age and on insulin pump therapy were recruited. A 2-week phase in manual mode was followed by a 6-week AHCL phase. CGM metrics were analyzed to review glycemic outcomes. Out of 11 participants enrolled [mean (standard deviation [SD]) age 5.3 (0.8) years], 10 completed the study. Time in closed loop was 96.7 (3.9)%. In AHCL, participants had a mean (SD) time in range of 72.6 (7.4)% and spent 3.0 (1.74)% and 0.63 (0.46)% in time <70 and <54 mg/dL, respectively. AHCL is a feasible option for management of young children with type 1 diabetes.

Discrete glucose profiles identified using continuous glucose monitoring data and their association with adverse pregnancy outcomes

Continuous glucose monitoring (CGM) has facilitated the evaluation of dynamic changes in glucose throughout the day and their effect on fetal growth abnormalities in pregnancy. However, studies of multiple CGM metrics combined and their association with other adverse pregnancy outcomes are limited. Our goals were to 1) use machine-learning techniques to identify discrete glucose profiles based on weekly CGM metrics in pregnant individuals with pregestational diabetes and, 2) investigate their association with adverse pregnancy outcomes. We analyzed data from a retrospective cohort study of pregnant patients with type 1 or type 2 diabetes who used Dexcom G6 CGM and delivered a non-anomalous, singleton gestation at a tertiary center between 2019 and 2023. CGM data were collapsed into 39 weekly glycemic measures related to centrality, spread, excursions, and circadian cycle patterns. Principal component analysis and k-means clustering were used to identify 4 discrete groups, and patients were assigned to the group that best represented their CGM patterns during pregnancy. Finally, the association between glucose profile groups and outcomes (preterm birth, cesarean delivery, preeclampsia, large-for-gestational-age (LGA) neonate, neonatal hypoglycemia, and neonatal intensive care unit (NICU) admission) was estimated using multivariate logistic regression adjusted for diabetes type, maternal age, insurance, CGM use before pregnancy, and parity. Of 177 included patients, 90 (50.8%) had type 1 diabetes and 85 (48.3%) had type 2 diabetes. We identified 4 glucose profiles: 1) well-controlled, 2) suboptimally controlled with high variability, fasting hypoglycemia and daytime hyperglycemia, 3) suboptimally controlled with minimal circadian variation, and 4) poorly controlled with peak hyperglycemia overnight. Compared to the well-controlled profile, the suboptimally controlled with high variability had higher odds of LGA neonate (aOR 3.34, 95% CI 1.15-9.89). The suboptimally controlled with minimal circadian variation profile had higher odds of preterm birth (aOR 2.59, 95% CI 1.10-6.24), cesarean delivery (aOR 2.76, 95% CI 1.09-7.46), and NICU admission (aOR 4.08, 95% CI 1.58-11.4). The poorly controlled with peak hyperglycemia overnight profile had higher odds of preeclampsia (aOR 2.54, 95% CI 1.02-6.52), LGA neonate (aOR 3.72, 95% CI 1.37-10.4), neonatal hypoglycemia (aOR 3.53, 95% CI 1.37-9.71), and NICU admission (aOR 3.15, 95% CI 1.20, 9.09). Discrete glucose profiles of pregnant individuals with pregestational diabetes were identified through joint consideration of multiple CGM metrics. Prolonged exposure to maternal hyperglycemia may be associated with higher risk of adverse pregnancy outcomes compared to suboptimal glycemic control characterized by high glucose variability and intermittent hyperglycemia.

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.

Hybrid Closed-Loop Versus Manual Insulin Delivery in Adults With Type 1 Diabetes: A Post Hoc Analysis Using the Glycemia Risk Index.

Glycemia risk index (GRI) is a novel composite metric assessing overall glycemic risk, accounting for both hypoglycemia and hyperglycemia and weighted toward extremes. Data assessing GRI as an outcome measure in closed-loop studies and its relation with conventional key continuous glucose monitoring (CGM) metrics are limited. A post hoc analysis was performed to evaluate the sensitivity of GRI in assessing glycemic quality in adults with type 1 diabetes randomized to 26 weeks hybrid closed-loop (HCL) or manual insulin delivery (control). The primary outcome was GRI comparing HCL with control. Comparisons were made with changes in other CGM metrics including time in range (TIR), time above range (TAR), time below range (TBR), and glycemic variability (standard deviation [SD] and coefficient of variation [CV]). GRI with HCL (N = 61) compared with control (N = 59) was significantly lower (mean [SD] 33.5 [11.7] vs 56.1 [14.4], respectively; mean difference -22.8 [-27.2, -18.3], P = .001). The mean increase in TIR was +14.8 (11.0, 18.5)%. GRI negatively correlated with TIR for combined arms (r = -.954; P = .001), and positively with TAR >250 mg/dL (r = .901; P = .001), TBR < 54 mg/dL (r = .416; P = .001), and glycemic variability (SD [r = .916] and CV [r = .732]; P = .001 for both). Twenty-six weeks of HCL improved GRI, in addition to other CGM metrics, compared with standard insulin therapy. The improvement in GRI was proportionally greater than the change in TIR, and GRI correlated with all CGM metrics. We suggest that GRI may be an appropriate primary outcome for closed-loop trials.

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.

Time in Range Is Associated with Incident Diabetic Retinopathy in Adults with Type 1 Diabetes: A Longitudinal Study.

Abstract Objective: To evaluate the association between continuous glucose monitoring (CGM)-based time in various ranges and the subsequent development of diabetic retinopathy (incident DR) in adults with type 1 diabetes. Methods: Between June 2018 and March 2022, adults with type 1 diabetes with incident DR or no retinopathy (control) were identified. CGM data were collected retrospectively for up to 7 years before the date of eye examination defining incident DR or control. Associations between incident DR and CGM metrics were evaluated using logistic regression models. Results: This analysis included 71 adults with incident DR (mean age 27 years, 52% females, and mean diabetes duration 15 years) and 92 adults without DR (mean age 38 years, 48% females, and mean diabetes duration 20 years). Adjusting for age, diabetes duration, and CGM type, each 0.5% increase in glycated hemoglobin (HbA1c), 10 mg/dL increase in mean glucose, 5% decrease in time in target range 70-180 mg/dL (TIR), 5% decrease in time in tight target range 70-140 mg/dL (TITR), and 5% increase in time above 180 mg/dL (TAR) were associated with 24%, 22%, 18%, 28%, and 20% increase in odds of incident DR, respectively. Spearman correlations of TIR, TITR, TAR, and mean glucose with each other were all ≥0.97. Conclusion: Similar to HbA1c, TIR, TITR, TAR, and mean glucose were associated with increased risk for incident DR in adults with type 1 diabetes. These CGM metrics are highly correlated indicating that they provide similar information on glycemic control and diabetic retinopathy risk.

Discordance between Glucose Management Indicator and Glycated Hemoglobin in a Pediatric Cohort with Type 1 Diabetes: A Real-World Study.

The introduction of continuous glucose monitoring (CGM) systems in clinical practice has allowed a more detailed picture of the intra- and interdaily glycemic fluctuations of individuals with type 1 diabetes (T1D). However, CGM-measured glucose control indicators may be occasionally inaccurate. This study aims to assess the discrepancy between the glucose management indicator (GMI) and glycated hemoglobin (HbA1c) (ΔGMI-HbA1c) within a cohort of children and adolescents with T1D, exploring its correlation with other CGM metrics and blood count parameters. In this single-center, cross-sectional study, we gathered demographic and clinical data, including blood count parameters, HbA1c values, and CGM metrics, from 128 pediatric subjects with T1D (43% female; mean age, 13.4 ± 3.6 years). Our findings revealed higher levels of the coefficient of variation (CV) (p < 0.001) and time above range > 250 mg/dL (p = 0.033) among subjects with ΔGMI-HbA1c > 0.3%. No association was observed between blood count parameters and ΔGMI-HbA1c. In conclusion, despite the advancements and the widespread adoption of CGM systems, HbA1c remains an essential parameter for the assessment of glycemic control, especially in individuals with suboptimal metabolic control and extreme glycemic variability.

Efficacy and Safety of Tirzepatide in Adults With Type 1 Diabetes: A Proof of Concept Observational Study.

Tirzepatide is approved by the United States Food and Drug Administration (FDA) for the management of type 2 diabetes. The efficacy and safety of this drug have not been studied in people with type 1 diabetes (T1D). In this single-center, retrospective, observational study, hemoglobin A1C (HbA1c), weight, body mass index (BMI), and continuous glucose monitoring (CGM) data were collected from electronic health records of adults with T1D at initiation of tirzepatide and at subsequent clinic visits over 8 months. Primary outcomes were reduction in HbA1c and percent change in body weight and secondary outcomes were change in CGM metrics and BMI over 8 months from baseline. The mean (±SD) age of the 26 adults (54% female) with T1D was 42 ± 8 years with a mean BMI of 36.7 ± 5.3 kg/m2. There was significant reduction in HbA1c by 0.45% at 3 months and 0.59% at 8 months, and a significant reduction in body weight by 3.4%, 10.5%, and 10.1% at 3, 6, and 8 months after starting tirzepatide. Time in target range (TIR = 70-180 mg/dL) and time in tight target range (TITR = 70-140 mg/dL) increased (+12.6%, P = .002; +10.7%, P = .0016, respectively) and time above range (TAR >180 mg/dL) decreased (-12.6%, P = .002) at 3 months, and these changes were sustained over 8 months. The drug was relatively safe and well tolerated with only 2 patients discontinuing the medication. Tirzepatide significantly reduced HbA1c and body weight in adults with T1D. A randomized controlled trial is needed to establish efficacy and safety of this drug in T1D.

Muscle-to-fat ratio in children and adolescents with type 1 diabetes in predicting glycaemic control and partial clinical remission.

Advances in treatment could mitigate the expected adverse changes in the body composition of children and adolescents with type 1 diabetes (T1D). To examine the evolution of weight status and body composition and their association with glycaemic control and partial clinical remission in youth with T1D. Ninety-nine participants with T1D (median age 9.5 years [interquartile range 7.3, 12.9], 59.6% boys) were longitudinally followed for 3years since diagnosis. Data at seven pre-determined time points were extracted from medical files. Outcome measures included body mass index (BMI) z-scores, muscle-to-fat ratio (MFR) z-scores, haemoglobin A1c (HbA1c) levels, continuous glucose monitoring metrics, and insulin dose-adjusted HbA1c (IDAA1c) levels. The BMI z-scores increased significantly (p<0.001) for both sexes, with no significant change in MFR z-scores over time. The girls had higher BMI z-scores (p<0.001) and lower MFR z-scores than the boys (p=0.016). The mean HbA1c levels decreased during the first month and at 3months since diagnosis (p<0.001), then plateaued and achieved a median overall HbA1c of 7.1% for the entire cohort. At 12months, 37 participants (37.6%) were in partial clinical remission, as evidenced by IDAA1c≤9. The odds of partial clinical remission at 2years increased by 2.1-fold for each standard deviation increase in the MFR z-score (p<0.001). Higher MFR z-scores were associated with better metabolic control. Integration of body composition assessments could mitigate adverse body changes in paediatric patients with T1D.