Time In Range Research Articles

The aim of this work was to assess the effect of video consultations over 1 year compared with usual care for patients with type 1 diabetes treated with insulin pumps, with time in range (TiR) as the primary outcome measure. We carried out a 52 week, open label, randomised, controlled superiority trial including adult type 1 diabetes patients treated with insulin pumps. Participants were recruited from the Hospital of Southern Jutland and were adult patients, diagnosed with type 1 diabetes mellitus who had used an insulin pump for at least 6 months. Participants were randomised to video consultations (intervention) or physical consultations (control) using a computer-generated block randomisation sequence in a 1:1 allocation, stratified for sensor type (continuous glucose monitor and flash glucose monitor, respectively).Since this was an 'open-label' trial, neither the healthcare professionals providing the treatment nor the participants were blinded to allocation after randomisation. The primary outcome measure was the percentage of TiR (glucose levels 3.9-10.0 mmol/l) from week 51 to 52, measured by continuous glucose monitoring. Continuous endpoints were analysed using ANCOVA, with randomised treatment and stratification groups as fixed effects and the baseline value as a covariate. Missing data in the intention-to-treat (ITT) population were addressed using multiple imputation. Of the 76 randomised participants (ITT population, 38 per group, median age 49 years, 51% women), 32 participants in the intervention group and 31 in the control group completed the study. Least square means TiR at 1 year was 64.3% in the video group and 63.5% in the control group, with a clinically insignificant difference of 0.8 percentage points (95% CI -5.3, 6.9; p=0.25). For secondary outcomes, the video group was superior in terms of treatment satisfaction and reduction in HbA1c. However, the video group experienced an inferior impact on quality of life. Video consultations did not significantly improve the primary endpoint. However, compared with control, the intervention was associated with superior treatment satisfaction and a favourable effect on HbA1c, albeit with an inferior impact on quality of life. ClinicalTrials.gov NCT04612933 FUNDING: The study received funding from Knud and Edith Eriksens Mindefond. The Section for Biostatistics and Evidence-Based Research, the Parker Institute, Bispebjerg and Frederiksberg Hospital is supported by a core grant from the Oak Foundation.

A continuous glucose monitoring system (CGM) is a digital health technology (DHT) device that measures interstitial glucose. CGMs are used in the management of diabetes. The purpose of this study was to retrospectively assess the quality of CGM data in a clinical trial involving patients with type 1 diabetes. CGM data were collected from 461 patients with type 1 diabetes who participated in a 16-week, double-blind phase 3 trial designed to examine the efficacy of prandial (mealtime) insulins. CGM data were collected at three 2 week study time points. The patterns of missing CGM data (due to non-wear, user- and device-related causes) and the relationship between CGM metrics and hemoglobin A1C (HbA1c) were examined using data visualization approaches. Across the three observation periods, 4.7-6% of CGM observations were missing. Approximately 16% of daily values were missing on days when a new CGM sensor was inserted. For many patients, high glucose variability was associated with low time in range (TIR) and HbA1c >7%. Conversely, low glucose variability was associated with higher TIR. Our analysis identified the need for adequate documentation indicating the presence of patient- and device-related events (e.g., sensor changes, non-wear time) to address causes of missing CGM data. These causes need to be considered prior to the statistical assessment of such data for research and regulatory purposes. Accurate documentation of post-baseline events is important for the development of research and regulatory standards for the collection and analysis of data acquired from DHTs.

To evaluate the effect of the August´s 2023 heatwaves over glycemic control in adults with type 1 diabetes (T1D) treated with advance hybrid closed-loop systems (AHCL). Cross-sectional retrospective analysis of adult patients with T1D in Castilla-La Mancha (south-central Spanish region) using AHCL during the August´s 2023 heatwaves period. Primary outcome was change in time in range (TIR) 3.0-10 mmol/L (70-180mg/dL) of interstitial glucose after the end of the heatwaves period. A total of 193 T1D patients were analyzed. TIR remained constant after the end of the heatwaves period (0.5% [95% CI -0.3, 1.3; P = 0.236]). No differences were observed among the rest of glycometric index. The percentage of patients meeting all the recommendations of the International Consensus of Time in Range was similar during the heatwaves period than after it ended (44.6% vs. 45.6%, P = 1.000). Finally, the percentage of time in automatization and daily insulin dose also stayed stable (0.5% [95% CI -1.4, 2.4; P = 0.601] and 0.0 UI/day [95% CI -1.0, 1.0; P = 0.981], respectively). Adults with T1D treated with AHCL maintained glycemic control during August´s 2023 heatwaves. These data raise the possibility that AHCL systems could help protect T1D patients from the effects of heatwaves on glycemic control.

Introduction Basal insulin with glucagon-like peptide-1 receptor agonist could be preferred over premixed insulin for intensification in type 2 diabetes due to better glycemic control, lower hypoglycemia risk, and favorable effects on body weight. Comparative data on premixed insulin and the combination of degludec and liraglutide (iDegLira) are limited. Methods We conducted a 24-week single-arm prospective study to evaluate the impact of iDegLira compared to premixed insulin on the regulation of diabetes and glucovariability using continuous glucose monitoring (CGM), HbA1c, and anthropometric measurements. A total of 37 participants with type 2 diabetes (20 male and 17 female, aged 70.2 ± 10.0 years with BMI 31.0 (28.0-34.0) kg/m 2 and duration of diabetes for 15.2 ± 7.7 years) were switched from premixed insulin treatment to iDegLira. The primary outcome was the change in HbA1c. Secondary outcomes included change in time in range (TIR) from baseline to 6 months, change in time below range (TBR), change in nocturnal hypoglycemia, glucovariability, insulin dose and body weight. Results We observed improved glycemic control on iDegLira with improvement of average fasting glucose (6.92 ± 1.64 vs . 8.25 ± 2.2 mmol/l; p<0.031), HbA1c (7.10 ± 0.7% vs . 7.39 ± 0.7% p=0.045) and TIR (71.2 ± 17.2% vs . 64.3 ± 18.0; p=0.027). These results were accompanied by a nearly halved total daily insulin dose (-21 units/day, p<0.001) and a modest reduction of body weight. Discussion iDegLira improved glycemic control, resulting in a lower HbA1c and higher TIR, alongside beneficial effects on body weight and total daily insulin doses. While numerical reductions in hypoglycemia did not reach statistical significance, treatment was not associated with an increased risk of hypoglycemia. iDegLira can be an efficient and safe treatment option, providing simplified treatment with improved glycemic control.

Purpose: It has been previously described that some women with type 1 diabetes (T1D) may experience changes in glucose levels in relation to their menstrual cycle. However, whether an advanced hybrid closed-loop system (AHCL) can mitigate these cycle-dependent changes is yet to be determined. Methods: This study is a prospective analysis of a cohort of premenopausal women with T1D with spontaneous menstrual cycles who are users of an AHCL system 780G Medtronic®. Three consecutive cycles were analyzed for each patient, and each cycle was divided into three phases (menstrual, luteal, and rest of cycle phase). Results: Fifteen subjects were included. Mean age was 38 ± 7.6 years, HbA1c was 7.12 ± 0.7%, and diabetes duration was 21 ± 13.7 years. Mean glucose was higher in the luteal phase compared to the menstrual period (p = 0.029 luteal vs. menstrual) and the rest of the cycle (p = 0.018 luteal vs. rest of cycle). The time in range (TIR) was lower in the luteal phase compared to the rest of cycle phase (p = 0.015 luteal vs. rest of cycle). The time below range (TBR) was significantly higher in the menstrual compared to the luteal phase (p = 0.007 luteal vs. menstrual). Daily insulin requirements were higher in luteal phase compared to rest of cycle (p = 0.017 luteal vs. rest of cycle). Conclusions: A higher mean glucose and lower TIR, despite a higher total insulin dose, was observed in the luteal phase. A higher TBR was observed in the menstrual phase. However, AHCL with 780G Medtronic® achieves a TIR of almost 70% in all cycle phases.

Purpose: Continuous glucose monitoring (CGM) technology offers real-time glucose feedback and has shown potential to improve glycemic control. This retrospective study evaluated the effect of CGM on glycemic outcomes in Korean children and adolescents with type 1 diabetes mellitus (T1DM) in a real-world setting.Methods: We included 66 participants divided into a CGM group (n=22) and a self-monitoring blood glucose (SMBG) group (n=44). We compared changes in hemoglobin A1c (HbA1c) of the 2 groups over 1 year and observed changes in CGM activation time, mean glucose, glucose management indicator (GMI), coefficient of variation (CV), time in range (TIR), and hypoglycemia.Results: The CGM group had a mean age of 16.63 years and time from diagnosis to the initiation of study of 4.19 years, while those of the SMBG group were 17.85 years and 5.19 years, respectively. In the CGM group, mean HbA1c decreased from 8.68% at baseline to 7.92% at 12 months (P=0.011), whereas HbA1c increased from 8.46% to 8.93% in the SMBG group (P<0.001). The changes in HbA1c at 1 year between the CGM and SMBG groups were significantly different (-0.76%±1.39% vs. 0.47%±1.38%, P=0.001). CGM activation time decreased slightly (89.09% to 79.24%, P=0.093), and there were no significant changes in TIR, mean glucose, GMI, CV, or hypoglycemia over time.Conclusion: CGM use in Korean children and adolescents with T1DM significantly improves HbA1c levels over 12 months compared to SMBG. The implementation of CGM may provide valuable benefits in glycemic control and potentially reduce the risk of diabetes-related complications.

Most European countries experienced three COVID-19 waves in 2020–2021. In Poland, Wave 1 (March-July 2020) was associated with a severe lockdown prohibiting external social activities beyond every-day necessities. During Waves 2 and 3 some restrictions were reimplemented, however, impacted everyday life less. The study aimed to analyze the individual as well as long-term impacts of COVID-19 pandemic lockdowns on glycemic control in different age groups of people with diabetes using intermittently scanned continuous glucose monitoring (isCGM), in Poland. We analyzed retrospective data from isCGM users during the COVID-19 pandemic (from January 2020 to September 2021), describing glucometrics according to the International Consensus on time in range (TIR). Longitudinal data were analyzed from 680 Polish patients with diabetes, comprising 470 adults aged 18–64, 66 adults aged 65+, and 144 children and adolescents. The most evident improvement in glycemic indices was observed during the first, most severe lockdown, especially in adults (TIR 68.2 vs. 65.6%). For seniors, most indices were stable during the pandemic, with only small improvement in time below range (TBR) (TBR70 1.9 vs. 2.6%). The comparison of the pre-pandemic and post-lockdown periods showed that most glycemic indices returned to similar levels, however, in children and adolescents, some deterioration was seen. Changes in glycemic indices during the COVID-19 pandemic in 2020–2021 in patients using isCGM differed between the 3 lockdown events and between age groups. Results demonstrate an age dependency in users’ response to the COVID-19 lockdowns in Poland and suggest that behavior changes brought on by dramatic lifestyle changes associated with COVID lockdowns were not sustained following the pandemic. Supplementary InformationThe online version contains supplementary material available at 10.1038/s41598-025-20323-z.

Disclosure: D. Raptis: None. S. Chiotis: None. M. Shah: None. E. Bekiari: None. N. Bloomgarden: None. A. Tsapas: None. T. Karagiannis: None.Introduction: Insulin therapy plays an important role in the management of type 2 diabetes mellitus (T2DM) as the disease progresses. To improve patient adherence and convenience, once-weekly basal insulin analogs such as insulin icodec and insulin Fc have been developed. This systematic review and meta-analysis assessed the efficacy and safety of once-weekly basal insulin compared to daily basal insulin in people with T2DM. Methods: We searched PubMed and Cochrane Library up to December 4th, 2024. We did random-effects meta-analyses and calculated mean differences (MDs) for change in HbA1c, body weight, fasting plasma glucose (FPG) and time in range (TIR), as well as odds ratios (ORs) for achieving an Hba1c <7.0%, and for incidence of hypoglycemia. Results: The search identified 4,859 records, with 11 randomized controlled trials (5,976 participants) deemed eligible for inclusion. Seven studies recruited insulin-naive patients. Once-weekly basal insulin reduced HbA1c 0.12% (95% CI, -0.20 to -0.05) more compared to daily basal insulin, independent of insulin naivety status. Similarly, patients treated with once-weekly basal insulin achieved higher mean TIR change (MD 3.722; 95% CI, 2.36 to 5.09) and HbA1c<7.0% (OR 4.15; 95% CI, 2.77; 6.23) compared to people treated with daily basal insulin, yet with higher odds for any hypoglycemia (OR 1.72; 95% CI, 1.10; 2.71). Mean changes in body weight and in FPG were similar between the two groups. Conclusion: This meta-analysis demonstrates significant improvements in HbA1c and TIR with once-weekly basal insulin in T2DM at the cost of more hypoglycemic events. There was no difference in the benefit of weekly insulin on HbA1c reduction, in regards to insulin naivety status.Presentation: Monday, July 14, 2025

Disclosure: S. Sim: None. B. Suh: None. M. Ahn: None.Background: With growing awareness of metabolic diseases, non-nutritive sweeteners (NNS) have gained popularity as sugar alternatives. While NNS-containing beverages are widely promoted as safe option for blood sugar control, their effects on glycemic variability and overall glucose homeostasis remain uncertain, particularly in pediatric and young adult diabetic patients. Limited studies have utilized continuous glucose monitoring (CGM) to assess the real-time impact of NNS intake in this population. This study aimed to investigate the short-term glycemic effects of NNS-containing beverages in pediatric and young adult patients with diabetes using CGM devices. Method: A prospective crossover study was conducted with 27 diabetic patients aged 10 to 29 years, including individuals with type 1 and type 2 diabetes. Each participant underwent two 10-day CGM monitoring periods: one with daily consumption of an NNS-containing beverage (Coca-Cola Zero Sugar, 250mL/day) for five days, followed by a five-day of control period without NNS intake. After three-month washout period, a second crossover period was conducted, reversing the order of NNS consumption and control periods. CGM metrics, including postprandial glucose levels, glycemic variability, Time in Range (TIR), Time above Range (TAR), Time below Range (TBR) and average level were analyzed. Additionally, and glycemic parameters such as fasting blood glucose, HbA1c, insulin and HOMA-IR were measured at each trial. Results: No statistically significant differences were observed in CGM parameters between NNS consumption and control conditions. TIR, TAR, TBR, average glucose, glucose management indicator (GMI), and glycemic variability (GV) did not significantly differ between interventions. The mean CGM value before consumption was 156.88±59.79 mg/dL (mean ± standard deviations), with a post-prandial value (2 hours) was 153.62±1.51 mg/dL. The peak CGM glucose concentration value was 175.42±65.75 mg/dL. Postprandial glucose response within 2 hours after NNS consumption showed no significant difference between NNS consumption and control conditions (p=0.524). Additionally, glycemic parameters such as fasting blood glucose, HbA1c, C-peptide, insulin, and HOMA-IR showed no significant differences between trials. Conclusion: These findings suggests that NNS consumption may have minimal direct effects on postprandial glucose levels in pediatric and young adult diabetes patients. Therefore, NNS-containing beverages may serve as a potential alternative to high glucose containing sugar-sweetened beverages in this population when reducing glucose intake is necessary.Presentation: Monday, July 14, 2025

Disclosure: L. Ramirez Garcia: None. A. Thatte: None. C. Gomez: None. L.A. Wright: Genentech, Inc., Patient Advisory Board.Background: Continuous Glucose Monitoring (CGM) has emerged as a powerful tool in managing Type 2 Diabetes (T2D), offering real-time insights into glucose fluctuations and allowing patients and their providers to better understand the effects of lifestyle changes and medication on their glycemic control. The impact of CGM on A1c and BMI has not been extensively studied in Latinx populations. We aimed to evaluate whether CGM utilization in Latinx patients with T2D results in improved A1c levels and reduced BMI, as surrogates of lifestyle modifications plus the effect on provider-driven therapeutic modifications such as the addition of hypoglycemic agents (HA). Methods: One-year observational retrospective study of Latinx patients with T2D. We obtained Age, gender, CGM use and metrics: average glucose, time in range (TIR), time below range (TBR), time above range (TAR), BMI, A1c, and HA at baseline and at 12-months. Paired-t-test and independent t-test, SPSS were used for statistical analysis. Results: Twenty-nine CGM users: age 54.3±13.2, 67% female, BMI 34.1±6.5 baseline, 34.7±8.2 at 12-months, p=0.2. Baseline A1c 8.9%±1.6, 8.1±1.6 at 12-months, p=0.02. Mean glucose was 202.2±58.3 mg/dl at baseline and 173.1±34.5 mg/dl at 12 months, p= 0.001. TIR went from 46.9%±26.5% to 60.3%±20.8%, p= 0.003, TAR went from 52.4%±26.8% to 39.0%±21.3%, p = 0.002, TBR went from 0.8%±1.6% to 0.9%±1.7%, p=0.556 and CV went from 29.3%±6.4% to 31.3%±6.5%, p=0.053. Glucagon-Like-peptide-1 Receptor agonist (GLP-1RA) use increased by 27.5%, p=0.003; Sodium-Glucose-Cotransporter2-inhibitors (SGLT2-Inh) by 13.8%, p=0.04 at 12-months. Total daily units of insulin (TDUI) baseline 99.7±66.5, 97.6±65.5 at 12-months, p=0.7. Twenty-eight Non-CGM users: Age 52.9±12.1, 44% female, BMI 35.3±9.4 baseline, 36±9.3 at 12-months, p=0.2. Baseline A1c 8.8%±1.6, 8.5±1.6 at 12-months, p=0.06. GLP-1RA use increased 17.9%, p=0.02; SGLT2-Inh 7.2%, p=0.16. TDUI baseline 78.6±69.5, 65.6±47.5 at 12-months, p=0.07.There was no change in BMI between groups; A1c decreased in both, significant only in CGM-users. There was a statistically significant increase within groups of GLP-1 RA and SGLT-2 inh use, but no difference when comparing CGM users vs Non-CGM users: p=0.08 for GLP-1RA, p=0.9 for SGLT2-inh. There was a reduction in TDUI in both groups, but more so in Non-CGM-users, p=0.04. Conclusion: In Latinx patients with T2D, CGM users had a reduction in A1c and higher total daily use of insulin when compared to non-CGM users, without an increased risk of hypoglycemia (TBR) or weight gain. Our results underscore the utility of CGM to optimize glycemic control. Longer CGM use may be needed for a beneficial effect in BMI. Offering and supporting use of CGM in the Latinx population is one tool to improve diabetes care and reduce health inequities.Presentation: Monday, July 14, 2025

Disclosure: A. Hanan: None. J.L. Snitzer: None.Introduction: Automated insulin delivery (AID) systems, such as Tandem Control-IQ, Medtronic 780G SmartGuard, and Omnipod Automated mode, have revolutionized diabetes management by providing real-time insulin adjustments based on continuous glucose monitoring (CGM) data. This report presents two distinct clinical cases that highlight the critical role of AID systems in managing diabetes mellitus (DM). Clinical Cases: The first case involves a 74-year-old male with Type 1 DM diagnosed in 1978, with complications including coronary artery disease, peripheral neuropathy, erectile dysfunction, and renal insufficiency. He maintained good glycemic control using a Tandem insulin pump and Dexcom CGM in Control-IQ mode despite not bolusing for food. However, after receiving a replacement pump, he failed to activate the Control-IQ feature, leading to significant deterioration of his glycemic metrics over two months. In September, with Control-IQ active 97% of the time, his average glucose was 187 mg/dL, time in range (TIR) 54%, standard deviation 88 mg/dL, glucose management indicator (GMI) 7.8%, and average daily insulin dose 37.56 units. By December, with Control-IQ inactive, his average glucose rose to 303 mg/dL, TIR dropped to 16%, standard deviation increased to 98 mg/dL, GMI rose to 10.6%, and his average daily insulin dose decreased to 25.16 units. The second case describes a 45-year-old male with Type 1 DM diagnosed in 1994, who had good diabetes control using a Medtronic 780G pump and Guardian 4 CGM. He inadvertently set his basal rate to zero but had the SmartGuard feature activated. Despite initial hyperglycemia with glucose levels in the 200-300 mg/dL range, the system was able to compensate, and after two weeks, it restored his glucose levels to his prior good control.Conclusion: These cases underscore the importance of AID systems in modern diabetes care. They demonstrate the importance of automation; the absence of Control-IQ in Case 1 revealed possible deficiencies in manual settings and lack of bolusing for food, leading to poor glycemic control. In Case 2, the Medtronic 780G SmartGuard worked well but if the patient went into manual mode, his BG’s would likely have been very high due to no basal rates. AID systems act as vital safety nets by reducing reliance on manual insulin adjustments and mitigating the impact of incorrect settings. Lastly, they highlight the critical need for patient education. Ensuring that patients understand how to turn on their AID function is essential, particularly when a pump is replaced. Overall, these findings emphasize the critical role of AID systems in enhancing glycemic control, mitigating human error, and improving the safety of diabetes management. They also highlight the need for comprehensive patient education, and periodic review with reassessment of pump settings to ensure optimal performance of these advanced technologies.Presentation: Monday, July 14, 2025

Disclosure: A. Ramachandran: None. S.K. Azad: None. V. Perugu: None. S. Agarwal: None.We present a 69-year-old male with Type 2 Diabetes with Gastroparesis on a T:Slim X2 insulin pump with U-200 insulin for two years. He has occasional nausea and vomiting managed by diet modification. Continuous Glucose Monitoring (CGM) showed a Time in range (TIR) (70-180) of 61%, high(>180) of 36.5%, low(<70) of 2.4. Interpretation revealed variable blood sugars with post prandial hyperglycemia followed by hypoglycemia. He was administering meal bolus 2 hours after the meal and entered extra carbohydrates to manage hyperglycemia. However, due to variable absorption he receives auto-boluses from the pump prior to meal bolus causing insulin stacking. We used ‘sleep mode’ to turn off auto-bolus with the advice to bolus 30 minutes in an extended bolus form, post prandially. Discussion: Patients with gastroparesis often have inadequate glycemic control (GC). Management is challenging as delayed absorption complicates timing and dosing of insulin which exacerbates glycemic variability. Although no clear guidelines have been established for management of glycemia in diabetic gastroparesis, ADA recommends automated insulin delivery (AID) as it can dynamically adjust insulin delivery based on real-time CGM which improves TIR and reduces HbA1c without increasing hypoglycemia. Our case highlights that insulin stacking could occur with background auto-bolus use with AID in such cases and the importance of tailoring management.Presentation: Monday, July 14, 2025

After total pancreatectomy (TP), patients are at high risk of hypoglycaemia regardless of insulin treatment modality. Information on treatment targets and modalities of insulin treatment following TP is sparse. This descriptive study presented experiences with a standardised insulin protocol and examined how the addition of intermittently scanned continuous glucose monitoring (isCGM) influenced the treatment of diabetes following TP. Results from two retrospective cohorts of patients who had undergone total pancreatectomy were collected, 30 patients not using isCGM served as references (operated in 2018-2019, mean age 65.4 years) for 40 patients using isCGM (operated in 2020-2021, mean age 63.3 years). An identical insulin treatment protocol was used for both cohorts. HbA1c, insulin doses, weight and episodes with severe hypoglycaemia were recorded at three, six, nine and 12 months after TP. Percentage of time below range (TBR), time in range (TIR) and time above range (TAR) were collected for isCGM users. HbA1c and insulin doses were similar in the two groups during the first year following TP. In isCGM users, TBR was 0%, TIR 43-48% and TAR 52-57%. Episodes of severe hypoglycaemia were numerically but not significantly lower in isCGM users (zero versus four, p = 0.21). The same applied to days of readmittance 4.0 ± 7.7 days versus 15.5 ± 40 (p = 0.13) per patient/year. In the first year following TP, the use of isCGM was not associated with better glycaemic control. A non-significant trend towards less severe cases of hypoglycaemia and a nonsignificant numerical reduction in days of hospitalisation were observed in isCGM users. None. Not relevant.

The objective of this systematic review and meta-analysis was to synthesize evidence from randomized controlled trials (RCTs) evaluating the use of continuous glucose monitoring (CGM) to guide lifestyle choices, particularly nutrition, in the management of T2D. PubMed and Cochrane CENTRAL were searched from inception to June 6, 2025. Randomized controlled trials were included if their intervention involved the use of a CGM device and education or feedback intended to modify nutrition choices, either as part of a nutrition intervention or a multicomponent lifestyle intervention. Random-effects meta-analyses were performed, and certainty of evidence was rated in alignment with the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. A total of 21 RCTs involving 2734 adults in groups of interest were included, with 20 RCTs eligible for meta-analysis. Results from meta-analysis showed statistically significant improvements in HbA1c (MD: -0.46%, 95% CI: -0.71, -0.22), time in range (TIR) 70-180 mg/dL (MD: 7.18%, 95% CI: 2.77, 11.58), time above range (TAR) >180 mg/dL (MD: -7.32%, 95% CI: -12.98, -1.66), fasting glucose (MD: -7.86 mg/dL, 95% CI: -15.06, -0.65), body weight (MD: -2.06 kg, 95% CI: -3.74, -0.38), with moderate certainty of evidence, and for mean CGM glucose (MD: -11.57 mg/dL, 95% CI: -22.58, -0.56), and standard deviation (SD) glucose (MD: -4.06 mg/dL, 95% CI: -6.54, -1.58), with low certainty of evidence. No statistically significant differences were found for other outcomes, typically with low certainty of evidence. Findings from this systematic review and meta-analysis support the use of CGM as a tool to guide lifestyle choices with a focus on nutrition in the management of T2D, with significant benefits related to glycemia and body weight.

The study analysed real-world data of people with type 1 diabetes (PWT1D) using the Smart Multiple Daily Insulin (MDI) system with the aim of assessing associations between user interaction behaviours and parameters of glycaemic control to provide educational insights for optimal system use. A retrospective cohort analysis was conducted using data from 1852 PWT1D users of the Smart MDI system across 21 countries. The system comprises the InPen™ insulin injector, Simplera™ CGM, and the InPen™ phone application. Users were included if they had at least 10 days of InPen and CGM data. Glycaemic outcomes were correlated with user interaction, focusing on responses to missed dose alerts (MDA) and correct high glucose alerts (CHGA). The mean time in range (TIR) was 55.7%, with users responding with a bolus dose to 49.3% of MDA and 46.6% of CHGA. However, those users who responded within 1 h to over 75% of alerts with a bolus dose achieved higher TIRs of 67.2% (MDA) and 71.5% (CHGA). Prompt responses (within 10 min) showed greater TIR. The study highlighted significant associations between alert responsiveness and better glycaemic outcomes without increased hypoglycaemia risk. User engagement with the Smart MDI system is crucial for optimal glycaemic outcomes. The study underscores the need for structured education on system use and alert responses. While causality cannot be confirmed, the findings suggest that proactive user interactions contribute to meeting glycaemic targets. Further research is needed to explore these relationships and enhance educational strategies.

Consistent efficacy and safety of automated insulin delivery in children aged 2-6 years: results from the LENNY trial continuation phase.

Introduction: After total pancreatectomy, patients inevitably develop pancreatogenic diabetes with marked glycemic variability and high risk of malnutrition due to both endocrine and exocrine insufficiency. Weight loss and malnutrition can occur even in those with adequate dietary intake and plausible pancreatic enzyme replacement. We hypothesized that glycemic variability is associated with nutritional decline. Methods: We retrospectively analyzed 14 patients who underwent continuous glucose monitoring (CGM) after total pancreatectomy. Nutritional status was assessed using the Geriatric Nutritional Risk Index (GNRI), and patients were classified into malnutrition-risk progression or nutrition-maintaining groups. Then, we evaluated glycemic indices, dietary intake, anthropometry, and pancreatic enzyme replacement therapy (PERT). Results: Insulin use, PERT dose, and dietary intake were approximately comparable between groups. In contrast, the malnutrition-risk progression group showed significantly higher mean glucose and time above range, and lower time in range (TIR). Importantly, TIR consistently showed an inverse association with malnutrition-risk progression across models adjusted for clinical covariates, including time since pancreatectomy, primary diagnosis, insulin regimen, and pancrelipase dose. These findings indicate that the observed relationship between lower TIR and worsening GNRI was independent of dietary intake and adequacy of enzyme replacement therapy, underscoring TIR as a clinically meaningful indicator of nutritional decline in this population. Conclusions: Hyperglycemia and reduced TIR were significantly associated with worsening GNRI after total pancreatectomy, independent of dietary intake or PERT. CGM-based glycemic metrics may help identify patients at risk of malnutrition and guide postoperative management.

Automated insulin delivery (AID) is part of the standard of care for type 1 diabetes (T1D), but real-world evidence (RWE) comparing AID systems remains limited. A systematic review and meta-analysis was conducted for outcomes across commercially available AID systems in real-world settings. PubMed and Embase were searched to March 2025 for RWE studies of commercial AID systems in ambulatory people with T1D. Eligible studies had n ≥ 250 with ≥10 days of continuous glucose monitoring data. Main outcomes were time in range (TIR) and glycated haemoglobin (HbA1c). Random-effects meta-analyses with AID system as moderator were performed, including scenario analyses by age and optimal device settings. Thirty-six records covering 34 studies with 635 463 users were included. Studies evaluated MiniMed™ 780G (n = 16), Control-IQ™ (n = 9), MiniMed™ 670G (n = 6), and other systems (≤3 studies each). Meta-analysis demonstrated frequently statistically significant between-system differences in TIR, ranging from 60.1% (95% confidence interval [CI] 54.0 to 65.9) for Omnipod® 5 to 73.9% (95% CI 72.3 to 75.5) for MiniMed 780G. For HbA1c, estimates ranged from 6.5% (95% CI 5.4 to 7.7) for Loop to 7.0% (95% CI 6.7 to 7.4) for MiniMed 780G, although differences were not significant. Significant residual heterogeneity was observed. Age was an important effect modifier, with younger users experiencing less favourable outcomes. Optimal device settings improved glycaemic outcomes. RWE demonstrated differences in glycaemic outcomes, including TIR, between commercially available AID systems. User age influenced outcomes for all systems. Results must be interpreted cautiously given challenges and potential biases with RWE.

Recommended pregnancy specific Time in Range (TIR) 63-140mg/dl is a quite wide range and, even if the goal of > 70% is achieved, the specific targets for fasting and mean glycaemia, which are much lower than 140mg/dl, could not be complied. This case series aimed to explore the performance of an Advanced Hybrid closed Loop (AHCL) in pregnancy on a stricter glycaemic range. We collected retrospective data about recommended glucose metrics and an hypothetic TITR 63-95mg/dl, more suitable for fasting periods, from 11 type 1 diabetes patients, using Medtronic MiniMed™ 780G, with glucose target 100mg/dl and Active Insulin Time 2h, from preconceptional phase until delivery. TIR 63-140mg/dl quickly improved throughout pregnancy, with progressively improving HbA1c and no significant changes in Time Below Range (TBR). TITR 63-95mg/dl was 26% in the 1st trimester, 20% in the 2nd and 30% in the 3rd, corresponding to 6, 5 and 7h per day, less than the hypothetic 8/24 hours of fasting. TAR > 140 reduced more compared to TAR > 95, reflecting a greater improve in postprandial values than in fasting. Although the AHCL Medtronic MiniMed™ 780G helped improving glycaemic control during pregnancy, our patients spent very few hours in the range 63-95mg/dl, probably because they did not reach fasting glucose goals. A stricter TIR may be hypothesized for pregnant women too, as an additional goal along with TIR 63-140mg/dl, but studies are needed to explore the consequences on maternal and fetal outcomes.

The primary goal of managing type1 diabetes mellitus (T1D) is to achieve glycemic control and prevent both acute and chronic complications. In recent years, automated insulin delivery (AID) systems, such as the 780G AID system, have significantly improved glycemic control and patient safety. Despite being the most advanced treatment option, AID initiation is often delayed until the honeymoon stage (partial remission phase). This study evaluated the impact of initiating MiniMed™ 780G at diagnosis on metabolic control and glycemic metrics in children newly diagnosed with T1D. It compares early AID initiation with continuous glucose monitoring (CGM) and multiple daily injection (MDI) therapy over a 1-year follow-up period. This retrospective study included children and adolescents (age range 0.87-17.72years) newly diagnosed with T1D between January 2023 and August 2024. Ten patients who were initiated on AID therapy at diagnosis were included, with eight patients completing a 1-year follow-up. Data from these eight patients and seven patients on CGM + MDI therapy were analyzed at baseline and at 3, 6, and 12months. The mean age at diagnosis was 6.98 ± 3.22years (0.87-9.82) for the AID group and 9.77 ± 4.89years (3.70-17.72) for the CGM + MDI group (p = 0.14). The AID system was initiated at an average of 3.33 ± 7.73days (2-23) after diagnosis, while sensor use in the CGM + MDI group began an average of 17.37 ± 8.86days (1-29) after diagnosis. At 12months, mean hemoglobin A1c (HbA1c) was 6.10% (43 mmol/mol) in the AID group compared with 7.73% (61 mmol/mol) in the CGM + MDI group. Time in range (TIR) was 79.0% vs. 50.7%, and time above range (TAR) was 13.4% vs. 30.7%, based on 2-week CGM data prior to the 12-month visit (p = 0.02, p = 0.009, p = 0.02). No case of diabetic ketoacidosis or severe hypoglycemia was reported during the follow-up period. This study highlights the potential benefits of initiating AID therapy at the time of diagnosis, offering novel insights into its safety and efficacy in the early management of T1D. These findings suggest that early initiation of AID therapy at the time of diagnosis is feasible and may improve glycemic outcomes.