Mean Time In Range Research Articles

Real-world glycaemic outcomes in children and young people on advanced hybrid closed-loop therapy: A population-based study in Western Australia.

To evaluate real-world glycaemic outcomes in children with type 1 diabetes (T1D) commencing advanced hybrid closed loop therapy (AHCL) and to explore these outcomes based on the cohort's clinical and socioeconomic characteristics. A single-centre, population-based retrospective study in children commencing AHCL (Smart Guard, Control IQ, CamAPS) with minimum 70% data from two-weeks CGM pre-AHCL was conducted between December 2021 and June 2023 in Western Australia. CGM metrics (time in range (TIR) 3.9-10 mmol/L, time below range (TBR) < 3.9 mmol/L, glucose management indicator (GMI)) were analysed at baseline, monthly and 6 months. HbA1c at baseline and 6 months were also collected. The proportion meeting glycaemic targets of TIR > 70%, TBR < 4% and GMI < 7.0% were determined. Change in TIR from baseline to 6 months was examined by the following characteristics: %TIR, age group and Index of Relative Socioeconomic Disadvantage (IRSD) of residential postcode. CGM data of 309 children, mean (SD) age 12.4 (3.2) years were analysed. Glycaemia improved from baseline to 6 months with (mean) TIR +8% (95% CI 7, 9; P ≤ 0.001), GMI -0.3% (95% CI -0.3, -0.2; P < 0.001) and (median) TBR -0.3% (95% CI -0.4, -0.1; P < 0.001). Proportion meeting glycaemic targets increased from 13.3% at baseline to 30.6% at 6 months. Improvement in TIR did not differ based on age group or IRSD Quintile. Greater increase in TIR was seen in those with lowest TIR at baseline (+20.9%, -0.2%; P < 0.001 for baseline TIR < 40%, >70%). There was a 0.27% reduction in HbA1c in 6 months (n = 116) (P < 0.001). AHCL improves glycaemia, irrespective of age and socioeconomic characteristics, with greatest changes seen in those with lowest baseline TIR.

Safety of a Novel Continuous Glucose Monitoring–Informed Insulin Bolus Calculator Mobile Application for People With Type 1 or Type 2 Diabetes

BACKGROUND Managing bolus insulin dosing can be a significant burden for people with diabetes, many of whom have limited numeracy skills. Insulin bolus calculators (IBCs) may improve glycemia as well as treatment satisfaction. OBJECTIVE The purpose of this study was to demonstrate the safety of a novel, continuous glucose monitoring (CGM)-informed IBC mobile device app that applies trend arrow adjustments to bolus insulin dose recommendations. RESEARCH DESIGN AND METHODS This clinical trial was an open-label, industry-sponsored single-arm study conducted at two sites. Fifty-four participants with type 1 or type 2 diabetes were enrolled and used the IBC app on their mobile device for 30 days. Study participants were adults who were already using CGM and dosing bolus insulin. The analysis examined both noninferiority and superiority of time in range (TIR) during the study period compared with baseline. Other important end points included hypoglycemia, glucose variability, nocturnal and diurnal TIR, and diabetes distress. The per-protocol (PP) group was defined as participants who used the IBC &amp;gt;30 times during the study. RESULTS Mean TIR improved by 3.8% (95% CI 0.7–6.9%) from 69.2 to 73.0% (P = 0.017) in the PP group. This TIR corresponds to a mean of 0.9 more hours per day spent in range, and the improvement was driven by those with type 2 diabetes. There was no increase in measures of hypoglycemia or diabetes distress. Exploratory analysis revealed a reduction in measures of glucose variability. In addition, individuals with type 1 diabetes had greater improvements in diurnal TIR than in nocturnal TIR. CONCLUSION A CGM-informed IBC app that applies trend arrow adjustments to bolus insulin dose recommendations improved TIR without increasing hypoglycemia or diabetes distress in individuals with type 1 or type 2 diabetes.

Comparison of Computational Statistical Packages for the Analysis of Continuous Glucose Monitoring Data with a Reference Software, "Ambulatory Glucose Profile," in Type 1 Diabetes.

Objective: To compare the accuracy of commonly used continuous glucose monitoring (CGM) analysis programs with ambulatory glucose profile (AGP) and Dexcom Clarity (DC) in analyzing CGM metrics in patients with type 1 diabetes (T1D). Research Methods: CGM data up to 90 days from 152 adults using the same CGM and automated insulin delivery system with T1D were collected. Six of the 19 CGM analysis programs (CDGA, cgmanalysis, Glyculator, iglu, EasyGV, and GLU) were selected to compare with AGP and DC. Metrics were compared etween all tools with two one-sided t-tests equivalence testing. For the equivalence test, the acceptable range of deviation was set as ±2 mg/dL for mean glucose, ±2% for time in range (TIR), ±1% for time above range (TAR), time above range level 1 (TAR1), time above range level 2 (TAR2), and coefficient of variation (CV). Results: All packages were compared with each other for all CGM metrics, and most of them had statistically significant differences for at least some metrics. All tools were equivalent to AGP for mean glucose, TIR, TAR, TAR1, and TAR2 within ±2 mg/dL, ±2%, ±1%, ±1% and 1%, respectively. CDGA, Glyculator, cgmanalysis, and iglu were not equivalent to AGP for CV within ±1%. All tools were equivalent to DC for mean glucose, TIR, and TAR2 within ±2 mg/dL, ±2%, and ±1%, respectively. Glyculator was not equivalent for TAR1, TAR, and CV. CGDA, cgmanalysis, and iglu were not equivalent to DC for TAR1 and TAR. EasyGV and GLU were not equivalent for TAR within ±1%. Conclusions: CGM analysis programs reported CGM metrics statistically differently, but these differences may not be applicable in clinical practice. The equivalence test also confirmed that the differences are negligible for TIR and mean glucose, while they can be important for hyperglycemic ranges and CV. A standardization for CGM data handling and analysis is necessary for clinical studies reporting CGM-generated outcomes.

Automated insulin delivery systems in elderly patients with brittle type 2 diabetes

PurposeGeriatric diabetes is complicated by the frailty of this population, and hypoglycemia with insulin is not uncommon in these patients. Automated Insulin Delivery (AID) systems may provide better glycemic control in elderly patients with brittle type 2 diabetes. MethodsThirty-four patients (≥ 60 years) including cancer patients with brittle diabetes were switched to an AID system from multiple-dose insulin (MDI) treatment. HbA1c level, weight, total daily insulin requirement, and C-peptide, creatinine, and lipids were followed for at least six months. ResultsThere were 34 patients (14 male, 41.2 %) with a median age of 67 (IQR 63.0–75.5). Six patients (17.6 %) were on chemotherapy and/or steroids (Ch/S). The patients’ initial median HbA1c % was 9.3 (IQR 7.6–11.0), c-peptide level was 0.9 (IQR 0.5–2.2) ng/mL, and median total daily insulin dose was 41 IU (IQR 32–53).Six months after the patients were switched to an AID system their HbA1c % decreased to 7.1 (IQR 6.5–8.1), p < 0.001 and c-peptide increased to 1.21 (IQR 0.2–1.7) ng/mL, p = 0.878. Total insulin dose decreased with AID systems [32 IU (IQR 23.9–37.8)), p < 0.001].There was a decrease in median HbA1c % in patients on Ch/S [8.7 (IQR 7.0–11.5) to 6.9 (IQR 6.3–9.2)] however it didn’t reach statistical significance p = 0.225. Total insulin dose also decreased without statistical significance [33 IU (IQR 41–28) to 28 (IQR 23–35), p = 0.173].The mean time in range (TIR) percent of the patients with AID systems were as follows; <54 mg/dL was 0.5 %, 56–70 mg/dL was 1.3 %, 70–180 mg/dL was 64.8 %, >180 mg/dL was 26.7 % and > 250 mg/dL was 6.7 %. ConclusionAlthough AID systems are tested mostly in young type 1 patients our results show that elderly patients with brittle type 2 diabetes also benefit from an AID system. Even in very frail patients such as cancer patients, improvement can be seen.

Impact of Telemedicine Versus In-Person Pediatric Outpatient Type 1 Diabetes Visits on Immediate Glycemic Control: Retrospective Chart Review.

Children and adolescents with type 1 diabetes require frequent outpatient evaluation to assess glucose trends, modify insulin doses, and screen for comorbidities. Continuous glucose monitoring (CGM) provides a detailed glycemic control assessment. Telemedicine has been increasingly used since the COVID-19 pandemic. To investigate CGM profile parameter improvement immediately following pediatric outpatient diabetes visits and determine if visit modality impacted these metrics, completion of screening laboratory tests, or diabetic emergency occurrence. A dual-center retrospective review of medical records assessed the CGM metrics time in range and glucose management indicator for pediatric outpatient diabetes visits during 2021. Baseline values were compared with those at 2 and 4 weeks post visit. Rates of completion of screening laboratory tests and diabetic emergencies following visits were determined. A total of 269 outpatient visits (41.2% telemedicine) were included. Mean time in range increased by 1.63% and 1.35% at 2 and 4 weeks post visit (P=.003 and .01, respectively). Mean glucose management indicator decreased by 0.07% and 0.06% at 2 and 4 weeks post visit (P=.003 and .02, respectively). These improvements in time in range and glucose management indicator were seen across both telemedicine visits and in-person visits without a significant difference. However, patients seen in person were 2.69 times more likely to complete screening laboratory tests (P=.03). Diabetic emergencies occurred too infrequently to analyze. Our findings demonstrate an immediate improvement in CGM metrics following outpatient visits, regardless of modality. While statistically significant, the magnitude of these changes was small; hence, multiple visits over time would be required to achieve clinically relevant improvement. However, completion of screening laboratory tests was found to be more likely after visits occurring in person. Therefore, we suggest a hybrid approach that allows patient convenience with telemedicine but also incorporates periodic in-person assessment.

Performance of the MiniMed 780G system on mitigating menstrual cycle-dependent glycaemic variability.

To map the glycaemic variabilities and insulin requirements across different phases of the menstrual cycle and assess the efficacy and performance of the MiniMed 780G system on mitigating glycaemic variabilities during phases of the menstrual cycle. A pilot study recruiting 15 adolescent and young adult females with type 1 diabetes was conducted. Only females with regular spontaneous menstruation were enrolled in the current study. Phases of each menstrual cycle were determined as either follicular phase or luteal phase. The study analysed continuous glucose monitoring metrics during two study periods: the open loop period (OLP) and the advanced hybrid closed-loop (AHCL) period; each period lasted 3 consecutive months. During the OLP, the mean time in range (TIR) significantly decreased during the luteal phase compared with the follicular phase (65.13% ± 3.07% vs. 70.73% ± 2.05%) (P < .01). The mean time above range significantly increased from 21.07% ± 2.58% during the follicular phase to 24.87% ± 2.97% during the luteal phase (P < .01). After initiating the AHCL period, TIR was comparable during both phases of the menstrual cycle (P = .72), without increasing the time spent below 70 mg/dL (P > .05). Regarding insulin delivery during the AHCL period, the percentage of Auto basal and Auto correction delivered by the algorithm increased by 13.55% and 30.6%, respectively (P < .01), during the luteal phase. The fully automated adaptive algorithm of the MiniMed 780G system mitigated menstrual cycle-dependent glycaemic variability, successfully attaining the recommended glycaemic outcomes with a TIR greater than 70% throughout the entire menstrual cycle.

A new approach in insulin pump education improves glycemic outcomes: a randomized controlled trial.

To address the scarcity of continued education for insulin pump users, we developed and evaluated a new program (NP) for individuals transitioning to a different insulin pump. In a randomized, controlled 3-month study, adults with type 1 diabetes and suboptimal HbA1c received either NP or usual care program (UC). The NP was designed in collaboration with representatives of the target group and incorporated technical training, case-based learning, and peer experience sharing - encompassing two group sessions, and two follow-up telephone calls. The UC included a single training session led by the pump company with hotline assistance (clinic) but no structured follow-up. The primary endpoint was the difference in time in range (TIR) (70-180mg/dL (3.9-10.0 mmol/L)), measured by continuous glucose monitoring from baseline to 3 months post-course. Psychosocial self-efficacy was measured by the Diabetes Empowerment Scale (DES-SF). Thirty-nine participants (median age 43, 74% female) were included. Mean TIR increased significantly in the NP group and remained unchanged in the UC group (between-group difference in change was 13.5% [95% CI: 4.0 to 22.9], p = 0.0064). Psychosocial self-efficacy improved and HbA1c decreased only significantly in the NP group. Applying a novel education program at pump transition significantly improved glycemic outcomes and self-efficacy.

Use of Financial Incentives to Promote Adolescent Type 1 Diabetes Self-management: A Pilot Randomized Controlled Trial.

To evaluate whether financial incentives lead to improvement in self-management behaviors and glycemia in adolescents with type 1 diabetes (T1D). Adolescents (12- to 18-year-olds) with T1D selected incentivized self-management behavior and clinical outcome goals in a 3-treatment (gain frame, loss frame, no incentives) crossover randomized controlled trial. Participants could earn up to $180 in each 12-week incentive treatment arm. Compared with a mean 41% behavioral goal attainment within the nonfinancial incentives arm, mean behavioral goal attainment under gain and loss frames was 50% (P < 0.01) and 45% (P < 0.01), respectively. Mean time in range (TIR) in gain frame and loss frame arms was higher 43% (P < 0.01) and 42% (P < 0.01), respectively, compared with when not receiving financial incentives (38%). There was no difference in A1C among the three arms. Financial incentives can improve diabetes self-management behaviors and TIR in adolescents with T1D in the short-term.

Seasonal fluctuations of CGM metrics in individuals with type 1 diabetes using an intermittently scanned CGM device or sensor augmented pump.

To elucidate the fluctuations in glucose levels measured using CGM-metrics during the four distinct seasons of the year in individuals with type 1 diabetes mellitus (T1DM) using an intermittently scanned CGM (isCGM) device or sensor augmented pump (SAP). This retrospective, single-center study enrolled 93 individuals with T1DM who were equipped with an isCGM device or SAP at Kobe University Hospital. The subjects had a median age of 47.0 years [interquartile range, 37.0-62.0 years], 25 individuals (26.9%) were male, median body mass index was 22.0 kg/m2 [20.8-23.8 kg/m2], and median hemoglobin A1c level was 7.4% [6.9-8.0%]. CGM data were reviewed from January to December 2019, and the mean sensor glucose (SG) value, time above range (TAR), time in range (TIR), time below range (TBR), and standard deviation (SD) of SG were calculated for each season (spring, March-May; summer, June-August; autumn, September-November; winter, December-February). Seasonal fluctuations were detected for mean SG, TAR, TIR, and SD, with TIR being lower and mean SG, TAR, and SD being higher in cold seasons (spring or winter) than in warm seasons (summer or autumn). Seasonal fluctuations in CGM metrics should be taken into account in future studies performed to evaluate the favorable impact of CGM on glycemic management in individuals with T1DM.

Continuous glucose monitoring with FreeStyle Libre PRO sensor in patients with type 2 diabetes and end-stage renal failure on haemoDIALysis (FSLPRO-DIAL pilot study).

For end-stage renal disease (ESRD) patients with diabetes on haemodialysis, diabetes control is difficult to achieve. Hypoglycaemia is a major problem in these frailty subjects. Continuous glucose monitoring (CGM) devices appear therefore to be a good tool to help patients monitor their glycaemic control and to help practitioners optimize treatment. We aimed to compare the laboratory value of Hba1c with the sensor-estimated value of Hba1c (= glucose management indicator, GMI) in ESRD patients with type 2 diabetes (T2D) (with or without insulin treatment) on haemodialysis. Secondly, we aimed to identify CGM-derived monitoring parameters [time in range, time in hypo/hyperglycaemia, glycaemic variability (coefficient of variation, CV)] to identify patients at risk of frequent hypo- or hyperglycaemia. The FSLPRO-DIAL pilot study (NCT04641650) was a prospective monocentric cohort study including 29 subjects with T2D who achieve the protocol. Inclusion criteria were: age ≥ 18years, haemodialysis duration for at least 3months, type 2 diabetes with no change in treatment for at least 3months. Demographic data and blood sample were collected at the day of inclusion. Freestyle Libre pro IQ sensor (blinded CGM) was inserted for 14days. After this period, all CGMs data were collected and analysed. Data were available for 27 patients. Mean age was 73 ± 10, mean BMI 27.2kg/m2, mean duration of diabetes 16.9years and mean dialysis duration 2.9years. Twenty-four subjects were treated with insulin. Mean HbA1c was 6.6% (SD 1.2), and mean GMI was 6.7% (SD 0.9) (no significant difference, p = 0.3). Twelve subjects (44.4%) had a discordance between HbA1c and GMI of < 0.5%, 11 (40.8%) had a discordance between 0.5 and 1%, and only 4 (14.8%) had a discordance of > 1%. Mean time in range (70-180mg/dl) was 71.9%, mean time below range (< 70mg/dl) was 5.6%, and mean time above range (> 180mg/dl) was 22.1%. Mean CV was 31.8%. For 13 out of 27 patients, we reduced antidiabetic treatment by stopping treatments or reducing insulin doses. In this pilot study, there was no global significant difference between HbA1c and GMI in this particular cohort with very well-controlled diabetes. However, the use of the sensor enabled us to identify an excessive time in hypoglycemia in this fragile population and to adapt their treatment.

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

To investigate the relationship between continuous glucose monitoring (CGM)-derived glucometrics and metabolic dysfunction-associated steatotic liver disease (MASLD) in type 1 diabetes (T1D). A cross-sectional study collecting data on anthropometrics, glucometrics and MASLD in adults with T1D using a CGM device was conducted. MASLD was assessed by abdominal ultrasound and the presence of at least one cardiometabolic criterion. Backward multivariable logistic regression models were applied to define variables independently associated with MASLD. A total of 302 consecutive participants were included (median age 49 [34-61] years, male sex 58%, median diabetes duration 29 [17-38] years, mean time in range [TIR] 55% ± 16%). MASLD was present in 17% of cases, and 32% had metabolic syndrome (MetS). MetS was significantly more prevalent in the MASLD group (65% vs. 25%, P < .0001). TIR (P = .038) and time below range (TBR) (P = .032) were lower and time above range (TAR) was higher (P = .006), whereas HbA1c did not reach significance (P = .068). No differences were found for the glycaemia risk index. TIR (P = .028), TAR (P = .007), TBR (P = .036), waist circumference (P < .001) and systolic blood pressure (P = .029) were independently associated with MASLD, while sex, age, aspartate aminotransferase/alanine aminotransferase ratio, gamma-glutamyl transferase, high-density lipoprotein cholesterol and triglycerides were not. TIR, TAR, TBR, waist circumference and systolic blood pressure were independently associated with MASLD.

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.

Time In Tight Range in children and adolescents with type 1 diabetes: A cross-sectional observational single centre study evaluating efficacy of new advanced technologies.

Early and tight glycaemic control is crucial to prevent long-term complications of Type 1 Diabetes (T1D). The aim of our study was to compare glucose metrics, including Time In Tight Range (TITR), in a real-world setting. We performed a single-centre cross-sectional study in 534 children and adolescents with T1D. Participants were divided into four groups (multiple daily injections+real-time Continuous glucose monitoring (CGM), multiple daily injections+intermittently scanned CGM, sensor augmented pump (SAP), and Advanced Hybrid Closed-Loop (AHCL). Demographical and clinical data were collected and analysed. The group with AHCL showed significantly higher Time In Range (TIR) (71.31%±10.88) than SAP (57.82%±14.98; p<0.001), MDI+rtCGM (54.56%±17.04; p<0.001) and MDI+isCGM (52.17%±19.36; p<0.001) groups with a lower Time Above Range (p<0.001). The group with AHCL also showed lower Time Below Range than MDI+isCGM and SAP groups (p<0.01). The overall TITR was 37%±14 with 19% of participants who reached a TITR ≥50% with a mean TIR of 81%. AHCL had significantly higher TITR (45.46%±11.77) than SAP (36.25%±13.53; p<0.001), MDI+rtCGM (34.03%±13.89; p<0.001) and MDI+isCGM (33.37%±15.84; p<0.001) groups with a lower Coefficient of Variation (p<0.001). Our study indicates that AHCL ensures a better glycaemic control with an improvement in both TIR and TITR, along with a reduction in CV. Implementation of automated insulin delivery systems should be considered in the treatment of children and adolescents with T1D.

Assessment of Patient-reported Satisfaction and Metabolic Outcomes Following Initiation of the Second Generation of Flash Glucose Monitoring in Patients with Type 1 Diabetes.

This study aims to assess patient-reported satisfaction and metabolic outcomes following the initiation of the second generation of the Freestyle Libre 2 (FSL2) system in patients with type 1 diabetes (T1D). This non-randomized single-arm observation study was conducted on 86 patients with T1D living in Saudi Arabia, who were asked to wear the FSL2 for 12 weeks. The demographic data were collected at baseline, while the continuous glucose monitoring (CGM) metrics were gathered, i.e., Glucose Variability (GV) (%), mean Time in Range (TIR), Time Above Range (TAR), Time Below Range (TBR), and average duration of hypoglycemic events were collected at baseline, 6th week and 12 weeks. Further, the Continuous Glucose Monitoring Satisfaction (CGM-SAT) was collected at the end of the follow-up. Compared to the 6th week, significant differences were observed in the low glucose events (p = 0.037), % TIR (p = 0.045), and % below 70 mg/dL (p = 0.047) at 12 weeks. Improvement was seen in the other glucometric variables, but no significant changes were evident (p > 0.05). On completion of the study period, the ambulatory glucose profile (AGP) metrics showed a 74.3 ± 5.01 (mg/dL) FSL2 hypoglycemia alarm threshold and a 213 ± 38.1 (mg/dL) hyperglycemia alarm threshold. A majority of the patients stated that CGM-SAT had benefits (mean score > 3.58), although they felt FSL2 had 'additional benefits. With regard to the problems with the use of FSL2 majority of the patients stated that FSL2 has minimal discomfort. Using second-generation FSL2 in patients with T1D is positively associated with patient- reported satisfaction and metabolic outcomes.

Basal Hyperglycemia Contributes More Than Fifty Percent to Time in Range in Pregnant Women with Type 1 Diabetes.

To evaluate the relative contribution of basal hyperglycemia (BHG) and postprandial hyperglycemia (PHG) to the time in range (TIR) categories and adverse pregnancy outcomes in pregnant women with type 1 diabetes mellitus (T1DM). This observational study included 112 pregnancies with T1DM from the CARNATION study who wore continuous glucose monitoring (CGM) devices during pregnancy. The data from CGM were analyzed for TIR (range, 3.5-7.8 mmol/L), areas under the curve (AUC) of PHG, AUC of BHG, basal and postprandial hyperglycemia contribution rates. The contribution rates of BHG and PHG to the different levels of TIR(＜60%, 60-78%, ≥78%) and adverse pregnancy outcomes were analyzed. The participants' average age was 28.8±3.9 years with a diabetes duration of 8.4±6.2 years. All women experienced a mean TIR of 75.6±19.0% and a mean HbA1c of 6.2±1.1% during pregnancy. The BHG contribution accounted for 74.9(36.8, 100)%, 69.2(13.4, 100)%, and 66.5(10.0, 100)% (P＜0.001) and PHG accounted for 25.1(0, 63.2)% and 30.8(0, 86.6)% and 33.5(0, 90.0)% (P＜0.001) when participants experienced the TIR＜60%, 60-78%, ≥78%, respectively. Participants with higher BHG contribution rates tended to have more adverse pregnancy outcomes. Basal hyperglycemia was the major contributor to TIR during pregnancy. Along with controlling the postprandial hyperglycemia, pregnant women with T1DM who did not reach the target of TIR may benefit more from the optimization of insulin regimens focusing on reducing basal glucose.

Real-World Continuous Glucose Monitoring Data from a Population with Type 1 Diabetes in South Korea: Nationwide Single-System Analysis.

Background: We used continuous glucose monitoring (CGM) data to investigate glycemic outcomes in a real-world population with type 1 diabetes (T1D) from South Korea, where the widespread use of CGM and the nationwide education program began almost simultaneously. Methods: Data from Dexcom G6 users with T1D in South Korea were collected between January 2019 and January 2023. Users were included if they provided at least 90 days of glucose data and used CGM at least 70% of the days in the investigational period. The relationship between CGM utilization and glycemic metrics, including the percentage of time in range (TIR), time below range (TBR), and time above range (TAR), was assessed. The study was approved by the Institutional Review Board of Samsung Medical Center (SMC 2023-05-030). Results: A total of 2288 users were included. Mean age was 41.5 years (57% female), with average uploads of 428 days. Mean TIR was 62.4% ± 18.5%, mean TBR <70 mg/dL was 2.6% ± 2.8%, mean TAR >180 mg/dL was 35.0% ± 19.3%, mean glucose was 168.1 ± 35.8 mg/dL, mean glucose management indicator was 7.2% ± 0.9%, and mean coefficient of variation was 36.7% ± 6.0%. Users with higher CGM utilization had higher TIR (67.8% vs. 52.7%), and lower TBR <70 mg/dL (2.3% vs. 4.7%) and TAR >180 mg/dL (30.0% vs. 42.6%) than those with low CGM utilization (P < 0.001 for all). Users whose data were shared with others had higher TIR than those who did not (63.3% vs. 60.8%, P = 0.001). Conclusions: In this South Korean population, higher CGM utilization was associated with a favorably higher mean TIR, which was close to the internationally recommended target. Using its remote data-sharing feature showed beneficial impact on TIR.

Comparison between a tubeless, on-body automated insulin delivery system and a tubeless, on-body sensor-augmented pump in type 1 diabetes: a multicentre randomised controlled trial.

This study compares the efficacy and safety of a tubeless, on-body automated insulin delivery (AID) system with that of a tubeless, on-body sensor-augmented pump (SAP). This multicentre, parallel-group, RCT was conducted at 13 tertiary medical centres in South Korea. Adults aged 19-69 years with type 1 diabetes who had HbA1c levels of <85.8 mmol/mol (<10.0%) were eligible. The participants were assigned at a 1:1 ratio to receive a tubeless, on-body AID system (intervention group) or a tubeless, on-body SAP (control group) for 12 weeks. Stratified block randomisation was conducted by an independent statistician. Blinding was not possible due to the nature of the intervention. The primary outcome was the percentage of time in range (TIR), blood glucose between 3.9 and 10.0 mmol/l, as measured by continuous glucose monitoring. ANCOVAs were conducted with baseline values and study centres as covariates. A total of 104 participants underwent randomisation, with 53 in the intervention group and 51 in the control group. The mean (±SD) age of the participants was 40±11 years. The mean (±SD) TIR increased from 62.1±17.1% at baseline to 71.5±10.7% over the 12 week trial period in the intervention group and from 64.7±17.0% to 66.9±15.0% in the control group (difference between the adjusted means: 6.5% [95% CI 3.6%, 9.4%], p<0.001). Time below range, time above range, CV and mean glucose levels were also significantly better in the intervention group compared with the control group. HbA1c decreased from 50.9±9.9 mmol/mol (6.8±0.9%) at baseline to 45.9±7.4 mmol/mol (6.4±0.7%) after 12 weeks in the intervention group and from 48.7±9.1 mmol/mol (6.6±0.8%) to 45.7±7.5 mmol/mol (6.3±0.7%) in the control group (difference between the adjusted means: -0.7 mmol/mol [95% CI -2.0, 0.8 mmol/mol] (-0.1% [95% CI -0.2%, 0.1%]), p=0.366). No diabetic ketoacidosis or severe hypoglycaemia events occurred in either group. The use of a tubeless, on-body AID system was safe and associated with superior glycaemic profiles, including TIR, time below range, time above range and CV, than the use of a tubeless, on-body SAP. Clinical Research Information Service (CRIS) KCT0008398 FUNDING: The study was funded by a grant from the Korea Medical Device Development Fund supported by the Ministry of Science and ICT; the Ministry of Trade, Industry and Energy; the Ministry of Health and Welfare; and the Ministry of Food and Drug Safety (grant number: RS-2020-KD000056).

Abstract P269: Glycemic Dysregulation Detected by Continuous Glucose Monitoring in Children With Metabolic Dysfunction-Associated Steatotic Liver Disease

MASLD, also known as NAFLD, is the leading cause of chronic liver disease in youth, especially among children who are obese and Hispanic/Latino. Insulin resistance and dysglycemia are strongly linked with MASLD. Current methods for evaluating dysglycemia, including fasting glucose, HbA1c, and oral glucose tolerance tests, have limitations. We utilized continuous glucose monitors (CGMs), wearable devices that detect 24 hour, real-time glucose alterations, to test our hypothesis that children with MASLD exhibit greater glycemic dysregulation compared to non-MASLD controls. This study included 19 Hispanic children (63% (12/19) male; mean age 7.8 years ± 0.9; mean BMI percentile 92% ± 17; 5% (10/19)) with MASLD who were otherwise healthy. Hepatic steatosis was measured by magnetic resonance spectroscopy (MRS). MASLD was defined as hepatic steatosis ≥5%, with at least one of five cardiometabolic risk factors. All participants underwent clinical evaluation and wore a blinded Dexcom G6 Pro CGM for 10 days or until the device became detached. Data was analyzed using RStudio v. 4.2.3. In children with MASLD, the mean time in range (TIR, 70-140 mg/dL) of 84% was lower than the mean TIR of 90% observed in non-MASLD controls ( p =0.02). The mean high TIR (140-250 mg/dL) of 16 % in MASLD subjects was significantly higher than the 9% observed in non-MASLD controls (p= 0.01). Mean average glucose and the coefficient of variation (CV) were also higher in children with MASLD, although differences were non-significant ( p &gt;0.05). Fasting insulin and ALT levels were significantly elevated in children with MASLD compared to controls (p&lt; 0.05).Findings demonstrate greater glycemic dysregulation in pre-pubertal children with MASLD compared to non-MASLD controls, as detected by CGM. Importantly, the 24 hour monitoring detected glycemic variability not apparent by fasting glucose or HbA1c. This study suggests early onset MASLD is associated with early glucose dysregulation, and treatments will need to address both conditions.

Carbohydrate counting knowledge and ambulatory glucose profile in persons living with type 1 diabetes

Context.The amount of consumed carbohydrates is the strongest factor influencing glucose levels during the four hours following a meal.Our aim was to evaluate the association between carbohydrate counting knowledge and continuous glucose monitoring (CGM) parameters in patients with type 1 diabetes (T1D) using different insulin regimens. MethodIn this multicenter prospective study, the GluciQuizz questionnaire was used to evaluate carbohydrate knowledge. CGM data for the 14 days preceding completion of the questionnaire were analyzed.The primary endpoint was evaluation of the correlation between the GluciQuizz total score and time in range (TIR) in the study population. ResultsThe mean age of the 170 participants was 40.7 ± 14.8 years and duration of T1D 18.8 ± 12.1 years. The mean GluciQuizz total score for all participants was 66 ± 13 %. Mean TIR was 58.6 ± 18.7 %. GluciQuizz total score positively correlated with TIR (r = 0.3001; p < 0.0001). This correlation was observed in CSII users (r = 0.2526; p < 0.05) but not in MDI (r = 0.2510; p = 0.1134) and HCL users (r = -0.1065; p = 0.4914). TIR was also negatively correlated with the mean carb count error in all study participants (r = -0.2317; p < 0.01). ConclusionIn conclusion, as the Gluciquizz score was associated with metabolic control, this easy-to-use self-administered questionnaire could be used widely on a routine basis to assess the carbohydrate knowledge of T1D patients and to offer them targeted education tailored to their needs.

Celebrating the Data from 100,000 Real-World Users of the MiniMed™ 780G System in Europe, Middle East, and Africa Collected Over 3 Years: From Data to Clinical Evidence.

Introduction: The present report celebrates the benchmarking of 100,000 MiniMed™ 780G system users in Europe, Middle East, and Africa (EMEA) and summarizes the major insights into the usability and outcomes of this system. Methods: Carelink Personal data (August 2020-August 2023) of users living in EMEA were analyzed. Continuous glucose monitoring-based endpoints were aggregated for (1) the full cohort and (2) a 12-month longitudinal cohort. Subanalyses were done for users on optimal settings (those spending ≥95% of time with glucose target of 100 mg/dL, and ≥95% of time with active insulin time of 2 h), for self-reported age groups (≤15 and ≥56 years) and for various countries/regions. Results: Data from 101,629 users (34 countries) were analyzed. Mean time in range (TIR) was 72.3%, glucose management indicator (GMI) was 7%, time below 70 mg/dL (TBR70) was 2.0% and time below 54 mg/dL (TBR54) was 0.4%. In terms of international targets, 59.6% of users achieved a GMI <7%, 62.5% a TIR >70%, 88.4% a TBR70 < 4%, and 90.0% a TBR54 < 1%. Data improved impressively in optimal setting users (TIR = 78.8%, and users reaching TIR >70% = 86.3%) while safety remained (TBR70 = 2.2% and TBR54 = 0.4%). Data showed consistency across self-reported age groups and geographies. In the longitudinal cohort, TIR reached 75.5% in the first month and remained 73.3% or higher over the 12-month period. Conclusion: Over 100,000 users of the MiniMed™ 780G system have demonstrated consistency in achieving target control of glycemia.