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Objectives: Background investigated whether Ramadan, a yearly religious fasting lasting for 1 month, could challenge the metabolic control obtained under a hybrid closed-loop (HCL) therapy in patients living with type 1 diabetes (T1D). Material and Method: This real-life prospective study involved 20 patients with T1D and moderate to high-risk score of adverse events at baseline. We compared continuous glucose monitoring (CGM) parameters under HCL therapy 1 month before and during the Ramadan fasting month. The main outcome was the evolution of the percentage of time-in-range (TIR, 70–180 mg/dL) between the two time points, and secondary outcomes were the evolution of other CGM parameters and frequency of acute metabolic events. Results: We observed no statistical difference regarding TIR (mean±SD) (63 ± 11% during fasting vs. 62 ± 12% before) as well as for other parameters including time spent under 70 mg/dL (1.1 ± 1.0% vs. 1.5 ± 1.3%) and percentage of HCL use (93 ± 5% vs. 94 ± 5%). No acute metabolic event was observed during fasting under HCL. Results were homogenous across baseline risk score groups. [ABSTRACT FROM AUTHOR]

Aims/Hypotheses: To investigate the frequency and characteristics of partial remission in Swedish children with type 1 diabetes and whether the insulin delivery method, that is, continuous subcutaneous insulin infusion (CSII) or multiple daily injections (MDIs), affects incidence and duration of this period, 2007–2011. Factors that increase the proportion of subjects who enter partial remission and extend this period can improve long-term metabolic control and reduce the risk of severe hypoglycemia, improve quality of life, and, in the long run, reduce late complications. Methods: Longitudinal data from 2007 to 2020 were extracted from the Swedish National Quality Register (SWEDIABKIDS) with all reported newly diagnosed children. Data on C-peptide from the participants in the Better Diabetes Diagnosis study from 2007 to 2010 were used. The definition of partial remission was insulin dose–adjusted HbA1c: HbA1c (%) + [4 × total daily insulin dose (U/kg/day)] ≤9. Results: Of the 3887 patients, 56% were boys. More boys than girls were in partial remission throughout the follow-up period until 24 months after diabetes onset. Fewer children 0–6 years old had partial remission at 3 and 12 months but not at 24 months compared with older age-groups. A larger proportion of patients using CSII at 12 and 24 months remained in partial remission compared with those with MDI (37% vs. 33%, P = 0.02 and 31% vs. 27%, P = 0.01, respectively). The level of C-peptide was higher in the group with partial remission and mean HbA1c was lower (both P < 0.001). Partial remission at 12 months after diabetes onset was associated with CSII (odds ratio [OR]: 1.39, confidence interval [CI]:1.13, 1.71), shorter diabetes duration (OR: 0.80, CI: 0.76, 0.84), and male sex (OR: 1.23, CI: 1.04, 1.46). Conclusions/Interpretation: Insulin through MDI, longer duration of diabetes, and female sex were associated with lower frequency of partial remission. Use of CSII seems to contribute to longer partial remission among Swedish children with type 1 diabetes. [ABSTRACT FROM AUTHOR]

Aim: To compare the safety in terms of hypoglycemic events and continuous glucose monitoring (CGM) metrics during aerobic exercise (AE) of using temporary target (TT) versus suspension of insulin infusion (SII) in adults with type 1 diabetes (T1D) using advanced hybrid closed-loop systems. Methods: This was a randomized crossover clinical trial. Two moderate-intensity AE sessions were performed, one with TT and one with SII. Hypoglycemic events and CGM metrics were analyzed during the immediate (baseline to 59 min), early (60 min to 6 h), and late (6 to 36 h) post-exercise phases. Results: In total, 33 patients were analyzed (44.6 ± 13.8 years), basal time in range (%TIR 70–180 mg/dL) was 79.4 ± 12%, and time below range (%TBR) <70 mg/dL was 1.8 ± 1.7% and %TBR <54 mg/dL was 0.5 ± 0.9%. No difference was found in the number of hypoglycemic events, %TBR <70 mg/dL and %TBR <54 mg/dL between TT and SII. Differences were found in the early phase, with better values when using TT for %TIR 70–180 mg/dL (83.0 vs. 65.3, P = 0.005), time in tight range (%TITR 70–140 mg/dL) (56.3 vs. 41.5, P = 0.04), and time above range (%TAR >180 mg/dL) (15.3 vs. 31.8, P = 0.01). In the diurnal period, again %TIR was better for TT use (82.1 vs. 73.1, P = 0.02) and %TAR (15.0 vs. 22.96, P = 0.04). No significant differences were found in the CGM metrics during the different phases of AE. Conclusion: Our data appear to show that the use of TT compared with SII is equally safe in all phases of AE. However, the use of TT allows for a better glycemic profile in the early phase of exercise. [ABSTRACT FROM AUTHOR]

Objective: To predict hypoglycemia and hyperglycemia risk during and after activity for adolescents with type 1 diabetes (T1D) using real-world data from the Type 1 Diabetes Exercise Initiative Pediatric (T1DEXIP) study. Methods: Adolescents with T1D (n = 225; [mean ± SD] age = 14 ± 2 years; HbA1c = 7.1 ± 1.3%; T1D duration = 5 ± 4 years; 56% using hybrid closed loop), wearing continuous glucose monitors (CGMs), logged 3738 total activities over 10 days. Repeated Measures Random Forest (RMRF) and Repeated Measures Logistic Regression (RMLR) models were used to predict a composite risk of hypoglycemia (<70 mg/dL) and hyperglycemia (>250 mg/dL) within 2 h after starting exercise. Results: RMRF achieved high precision predicting composite risk and was more accurate than RMLR Area under the receiver operating characteristic curve (AUROC 0.737 vs. 0.661; P < 0.001). Activities with minimal composite risk had a starting glucose between 132 and 160 mg/dL and a glucose rate of change at activity start between −0.4 and −1.9 mg/dL/min. Time <70 mg/dL and time >250 mg/dL during the prior 24 h, HbA1c level, and insulin on board at activity start were also predictive. Separate models explored factors at the end of activity; activities with glucose between 128 and 133 mg/dL and glucose rate of change between 0.4 and −0.6 mg/dL/min had minimal composite risk. Conclusions: Physically active adolescents with T1D should aim to start exercise with an interstitial glucose between 130 and 160 mg/dL with a flat or slightly decreasing CGM trend to minimize risk for developing dysglycemia. Incorporating factors such as historical glucose and insulin can improve prediction modeling for the acute glucose responses to exercise. [ABSTRACT FROM AUTHOR]

Objective: A subgroup analysis of the Hypoglycemia Awareness Restoration Programme for people with type 1 diabetes and problematic hypoglycemia persisting despite optimized care (HARPdoc) trial was conducted to explore the impact of Blood Glucose Awareness Training (BGAT, a hypoglycemia awareness training program) and the HARPdoc (a psychoeducation addressing unhelpful hypoglycemia beliefs) in reducing severe hypoglycemia (SH) in individuals using advanced diabetes technologies (ADTs). Methods: Data from trial participants who utilized ADTs, including continuous glucose monitors or automated insulin delivery systems, were extracted. Generalized linear mixed-effects models with Poisson distribution or linear mixed-effects models were used to evaluate SH incidence, and Gold questionnaire, Attitudes to Awareness of Hypoglycemia (A2A), Problem Areas in Diabetes (PAID), Hospital Anxiety and Depress Scale (HADS)-anxiety, and HADS-depression scores as measures of hypoglycemia awareness, unhelpful hypoglycemia beliefs, diabetes distress, and anxiety and depression symptoms, respectively. Results: In the 45 participants using ADTs, the BGAT and HARPdoc interventions both reduced SH incidence by more than 50% (P < 0.0001) and yielded improvements in hypoglycemia awareness (P < 0.05). HARPdoc outperformed BGAT in reducing SH at month 24 (P = 0.01). HARPdoc also mitigated unhelpful hypoglycemia beliefs (P < 0.0001), diabetes distress (P < 0.05), and anxiety symptoms (P < 0.05); BGAT demonstrated no significant impacts in these respects. Neither HARPdoc nor BGAT had significant effects on depression symptoms. Conclusion: Psychoeducation (BGAT and HARPdoc) was effective in reducing SH in people using ADTs. HARPdoc may also provide greater long-term SH reduction and improves psychological well-being in this patient group. [ABSTRACT FROM AUTHOR]

Introduction: This study examined associations between hypoglycemia awareness status and hypoglycemia symptoms reported in real-time using the novel Hypoglycaemia—MEasurement, ThResholds and ImpaCtS (Hypo-METRICS) smartphone application (app) among adults with insulin-treated type 1 (T1D) or type 2 diabetes (T2D). Methods: Adults who experienced at least one hypoglycemic episode in the previous 3 months were recruited to the Hypo-METRICS study. They prospectively reported hypoglycemia episodes using the app for 10 weeks. Any of eight hypoglycemia symptoms were considered present if intensity was rated between "A little bit" to "Very much" and absent if rated "Not at all." Associations between hypoglycemia awareness (as defined by Gold score) and hypoglycemia symptoms were modeled using mixed-effects binary logistic regression, adjusting for glucose monitoring method and diabetes duration. Results: Of 531 participants (48% T1D, 52% T2D), 45% were women, 91% white, and 59% used Flash or continuous glucose monitoring. Impaired awareness of hypoglycemia (IAH) was associated with lower odds of reporting autonomic symptoms than normal awareness of hypoglycemia (NAH) (T1D odds ratio [OR] 0.43 [95% confidence interval {CI} 0.25–0.73], P = 0.002); T2D OR 0.51 [95% CI 0.26–0.99], P = 0.048), with no differences in neuroglycopenic symptoms. In T1D, relative to NAH, IAH was associated with higher odds of reporting autonomic symptoms at a glucose concentration <54 than >70 mg/dL (OR 2.18 [95% CI 1.21–3.94], P = 0.010). Conclusion: The Hypo-METRICS app is sensitive to differences in hypoglycemia symptoms according to hypoglycemia awareness in both diabetes types. Given its high ecological validity and low recall bias, the app may be a useful tool in research and clinical settings. The clinical trial registration number is NCT04304963. [ABSTRACT FROM AUTHOR]

Introduction: This study aimed to compare efficacy and safety of ultra-rapid-acting insulin analogs (URAIs; faster aspart [FAsp], ultra-rapid lispro [URLi], and technosphere insulin [TI]) with rapid-acting insulin analogs (RAI) in individuals with type 1 (T1D) or type 2 diabetes (T2D). Methods: Searching for randomized control trial comparing the effects of URAI versus RAI that lasted at least 12 weeks, we initially selected 15 studies for analysis. Three studies involving TI were excluded due to a high degree of heterogeneity. The final meta-analysis included only 12 studies with either FAsp or URLi. Results: Mealtime URAI significantly reduced overall early 1 h postprandial glycemia in individuals with T1D (−20.230 mg/dL [95% confidence interval, 95% CI −24.040 to −16.421]; P < 0.001; I2 = 33.42%) and those with T2D (−9.138 mg/dL [95% CI −12.612 to −5.663]; P < 0.001; I2 = 0%). However, the significant reduction in 2 h postprandial glucose remained only in individuals with T1D (−17.620 mg/dL [95% CI −26.047 to −9.193]; P < 0.001; I2 = 65.88%). These benefits were lost when URAI was administered postmeal. At 24–26 weeks, there was no significant difference in HbA1c between groups, but at 52 weeks, a slight reduction in HbA1c with mealtime URAI was observed (−0.080% [95% CI −0.147 to −0.013]; P = 0.019; I2 = 0%). No difference in weight or the rate of severe or confirmed hypoglycemia was observed. Only individuals with T1D showed a small, but significant increase in early 1-h hypoglycemia with URAI (1.468 [95% CI 1.235 to 1.747]; P < 0.001; I2 = 0%). Conclusion: Mealtime URAI improves 1 and 2 h postprandial glycemic control compared to RAI without increasing hypoglycemia or weight gain. [ABSTRACT FROM AUTHOR]

Aim: The aim of this study was to develop and validate a prediction model based on continuous glucose monitoring (CGM) data to identify a week-to-week risk profile of excessive hypoglycemia. Methods: We analyzed, trained, and internally tested two prediction models using CGM data from 205 type 1 diabetes patients with long-term CGM monitoring. A binary classification approach (XGBoost) combined with feature engineering deployed on the CGM signals was utilized to predict excessive hypoglycemia risk defined by two targets (time below range [TBR] >4% and the upper TBR 90th percentile limit) of TBR the following week. The models were validated in two independent cohorts with a total of 253 additional patients. Results: A total of 61,470 weeks of CGM data were included in the analysis. The XGBoost models had an area under the receiver operating characteristic curve (ROC-AUC) of 0.83–0.87 (95% confidence interval; 0.83–0.88) in the test dataset. The external validation showed ROC-AUCs of 0.81–0.90. The most discriminative features included the low blood glucose index, the glycemic risk assessment diabetes equation (GRADE), hypoglycemia, the TBR, waveform length, the coefficient of variation and mean glucose during the previous week. This highlights that the pattern of hypoglycemia combined with glucose variability during the past week contains information on the risk of future hypoglycemia. Conclusion: Prediction models based on real-world CGM data can be used to predict the risk of hypoglycemia in the forthcoming week. The models showed good performance in both the internal and external validation cohorts. [ABSTRACT FROM AUTHOR]

Introduction: Nocturnal hypoglycemia is generally calculated between 00:00 and 06:00. However, those hours may not accurately reflect sleeping patterns and it is unknown whether this leads to bias. We therefore compared hypoglycemia rates while asleep with those of clock-based nocturnal hypoglycemia in adults with type 1 diabetes (T1D) or insulin-treated type 2 diabetes (T2D). Methods: Participants from the Hypo-METRICS study wore a blinded continuous glucose monitor and a Fitbit Charge 4 activity monitor for 10 weeks. They recorded details of episodes of hypoglycemia using a smartphone app. Sensor-detected hypoglycemia (SDH) and person-reported hypoglycemia (PRH) were categorized as nocturnal (00:00–06:00 h) versus diurnal and while asleep versus awake defined by Fitbit sleeping intervals. Paired-sample Wilcoxon tests were used to examine the differences in hypoglycemia rates. Results: A total of 574 participants [47% T1D, 45% women, 89% white, median (interquartile range) age 56 (45–66) years, and hemoglobin A1c 7.3% (6.8–8.0)] were included. Median sleep duration was 6.1 h (5.2–6.8), bedtime and waking time ∼23:30 and 07:30, respectively. There were higher median weekly rates of SDH and PRH while asleep than clock-based nocturnal SDH and PRH among people with T1D, especially for SDH <70 mg/dL (1.7 vs. 1.4, P < 0.001). Higher weekly rates of SDH while asleep than nocturnal SDH were found among people with T2D, especially for SDH <70 mg/dL (0.8 vs. 0.7, P < 0.001). Conclusion: Using 00:00 to 06:00 as a proxy for sleeping hours may underestimate hypoglycemia while asleep. Future hypoglycemia research should consider the use of sleep trackers to record sleep and reflect hypoglycemia while asleep more accurately. The trial registration number is NCT04304963. [ABSTRACT FROM AUTHOR]

Objective: To assess the clinical impact of flash glucose monitoring (FGM) systems on fear of hypoglycemia (FoH) and quality of life in adults with type 1 diabetes mellitus (T1DM). Methods: Prospective quasi-experimental study with a 12-month follow-up. People with T1DM (18–80 years old) and self-monitoring by blood capillary glycemia controls were included. The FH15 questionnaire, a survey validated in Spanish in a comparable study population, was used to diagnose FoH with a cutoff point of 28 points. Results: A total of 181 participants were included, with a FoH prevalence of 69% (n = 123). A mean reduction in FH15 score of −4 points (95% confidence interval [−5.5 to −3]; P < 0.001) was observed, along with an improvement in quality of life (EsDQOL-test (Diabetes Quality of Life, Spanish version), −7 points [−10; −4], P < 0.001) and satisfaction with treatment (Diabetes Treatment Satisfaction questionnaire, self-reported version [DTSQ-s] test, +4.5 points [4; 5.5], P < 0.001). At the end of the follow-up, 64.2% of the participants saw an improved FoH intensity, compared to 35.8% who scored the same or higher. This improvement in FoH status was associated with a higher time-in-range at the end of the follow-up (P = 0.003), as well as a lower time spent in hyperglycemia (P = 0.005). In addition, it was linked to participants with a high baseline FoH levels (P < 0.001) and those who were university degree holders (P = 0.07). Conclusions: FGM is associated with an overall reduction of FoH in adults with T1DM and with an increase in their quality of life. Nevertheless, a significant percentage of patients may experience an increase of this phenomenon leading to clinical repercussions and a profound impact on quality of life. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: No published data are available on the use of the community-derived open-source Loop hybrid closed-loop controller ("Loop") by individuals with type 2 diabetes (T2D). Methods: Through social media postings, we invited individuals with T2D currently using the Loop system to join an observational study. Thirteen responded of whom seven were eligible for the study, were using the Loop algorithm, and provided data. Results: Mean (±standard deviation) age was 61 ± 13 years, and mean body mass index was 31 ± 5 kg/m2. All but one participant were using noninsulin glucose-lowering medications. Self-reported mean hemoglobin A1c decreased from 7.3% ± 1.1% before starting Loop to 6.0% ± 0.5% on Loop. Time in range 70–180 mg/dL increased from 84% to 93%. The amount of time in hypoglycemia was extremely low before and with Loop (time <54 mg/dL was 0.04% ± 0.06% vs. 0.09% ± 0.07%, respectively). No severe hypoglycemia or diabetic ketoacidosis events were reported while using Loop. Conclusion: These data, though limited, suggest that the Loop system is likely to be effective when used by individuals with T2D and should be evaluated in large-scale studies. Clinical Trial Registration numbers: NCT05951569. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Objective: Determine whether continuous glucose monitor (CGM) metrics can provide actionable advance warning of an emergency department (ED) visit or hospitalization for hypoglycemic or hyperglycemic (dysglycemic) events. Research Design and Methods: Two nested case–control studies were conducted among insulin-treated diabetes patients at Kaiser Permanente, who shared their CGM data with their providers. Cases included dysglycemic events identified from ED and hospital records (2016–2021). Controls were selected using incidence density sampling. Multiple CGM metrics were calculated among patients using CGM >70% of the time, using CGM data from two lookback periods (0–7 and 8–14 days) before each event. Generalized estimating equations were specified to estimate odds ratios and C-statistics. Results: Among 3626 CGM users, 108 patients had 154 hypoglycemic events and 165 patients had 335 hyperglycemic events. Approximately 25% of patients had no CGM data during either lookback; these patients had >2 × the odds of a hypoglycemic event and 3–4 × the odds of a hyperglycemic event. While several metrics were strongly associated with a dysglycemic event, none had good discrimination. Conclusion: Several CGM metrics were strongly associated with risk of dysglycemic events, and these can be used to identify higher risk patients. Also, patients who are not using their CGM device may be at elevated risk of adverse outcomes. However, no CGM metric or absence of CGM data had adequate discrimination to reliably provide actionable advance warning of an event and thus justify a rapid intervention. [ABSTRACT FROM AUTHOR]

Older adults with type 1 diabetes may face challenges driving safely. Glucose "above-5-to-drive" is often recommended for insulin-treated diabetes to minimize hypoglycemia while driving. However, the effectiveness of this recommendation among older adults has not been evaluated. Older drivers with type 1 diabetes were assessed while using sensor-augmented insulin pumps during a 2-week clinical trial run-in. Twenty-three drivers (median age 69 years [interquartile range; IQR 65–72]; diabetes duration 37 years [20–45]) undertook 618 trips (duration 10 min [5–21]). Most trips (n = 535; 87%) were <30 min duration; 9 trips (1.5%) exceeded 90 min and 3 trips (0.5%) exceeded 120 min. Pre-trip continuous glucose monitoring (CGM) was >5.0 mmol/L for 577 trips (93%) and none of these had CGM <3.9 mmol/L during driving (including 8 trips >90 min and 3 trips >120 min). During 41 trips with pre-trip CGM ≤5.0 mmol/L, 11 trips had CGM <3.9 mmol/L. Seventy-one CGM alerts occurred during 60 trips (10%), of which 54 of 71 alerts (76%) were unrelated to hypoglycemia. Our findings support a glucose "above-5-to-drive" recommendation to avoid CGM-detected hypoglycemia among older drivers, including for prolonged drives, and highlight the importance of active CGM low-glucose alerts to prevent hypoglycemia during driving. Driving-related CGM usability and alert functionality warrant investigation. Clinical trial ACTRN1261900515190 [ABSTRACT FROM AUTHOR]

Background: Few studies have evaluated the implications of the alarm thresholds of continuous glucose monitoring (CGM) systems for individuals with diabetes. The present study aimed to investigate the influence of hypoglycemia and hyperglycemia alarm thresholds on glycemic control in adults with type 1 diabetes (T1DM) and the characteristics of patients who use these alarms more frequently. Methods: This observational cross-sectional study included 873 users of the FreeStyle Libre 2 system (501 men, median age 48 years, range 18–90 years) with T1DM from a single center. We investigated the role of demographic and metabolic factors on the use of alarms and the impact of hypoglycemia and hyperglycemia alarms and their thresholds on glycemic control. Results: Alarm users were older than nonusers (median age 49 vs. 43 years, respectively; P < 0.001). The hypoglycemia alarms were set by 76.1% of women and by 69.1% of men (P = 0.022). The hypoglycemia alarms reduced hypoglycemia features and glucose variability, although at the expense of shorter time in range. The higher the hypoglycemia alarm threshold, the greater these effects. The hyperglycemia alarms were effective in reducing hyperglycemia and lowering the glucose management indicator, although at the expense of a greater tendency to hypoglycemia. The lower the hyperglycemia alarm threshold, the greater these effects. Conclusions: CGM alarms contribute to better glycemic control. However, hypoglycemia and hyperglycemia alarms have advantages and disadvantages. Adults with T1DM should explore, under medical supervision, which alarm thresholds will best help them achieve their individual glycemic goals. [ABSTRACT FROM AUTHOR]

Aim: To assess the real-world performance of MiniMed™ 780G for Australians with type 1 diabetes (T1D) following advanced hybrid closed loop (AHCL) activation and to evaluate the effect of changing from MiniMed 670/770G to 780G. Methods: We analyzed deidentified Carelink™ continuous glucose monitoring (CGM) data from Australian users from January 2020 to December 2022, including the proportion attaining three major consensus targets: Glucose management indicator (GMI <7.0%), time in range (TIR 70–180 mg/dL >70%), and time below range (TBR 70 mg/dL <4%). Results: Comparing 670/770G users (n = 5676) for mean ± standard deviation 364 ± 244 days with 780G users (n = 3566) for 146 ± 145 days, the latter achieved a higher TIR (72.6% ± 10.6% vs. 67.3% ± 11.4%; P < 0.001), lower time above range (TAR) (25.5% ± 10.9% vs. 30.6% ± 11.7%; P < 0.001), and lower GMI (6.9% ± 0.4% vs. 7.2% ± 0.4%; P < 0.001) without compromising TBR (1.9% ± 1.8% vs. 2.0% ± 1.8%; P = 0.0015). Of 1051 670/770G users transitioning to 780G, TIR increased (70.0% ± 10.7% to 74.0% ± 10.2%; P < 0.001), TAR decreased (28.1% ± 10.9% to 24.0% ± 10.7%; P < 0.001), and TBR was unchanged. The percentage of users attaining all three CGM targets was higher in 780G users (50.1% vs. 29.5%; P < 0.001). CGM metrics were stable at 12 months post-transition. Conclusion: Real-world data from Australia shows that a higher proportion of MiniMed 780G users meet clinical targets for CGM consensus metrics compared to MiniMed 670/770G users and glucose control was sustained over 12 months. [ABSTRACT FROM AUTHOR]

This document is a compilation of various studies and research related to the management of diabetes. The studies cover a range of topics, including the use of continuous glucose monitoring (CGM) systems, the impact of diabetes technology on glycemic control and quality of life, and the psychosocial needs of individuals with diabetes. The findings suggest that CGM can lead to improvements in glycemic control and quality of life, but more research is needed to fully understand the long-term effects and benefits. Additionally, barriers to the use of diabetes technology need to be addressed for widespread adoption. [Extracted from the article]

Background: Uptake of exercise in people with type 1 diabetes (T1D) is low despite significant health benefits. Fear of hypoglycemia is the main barrier to exercise. Continuous glucose monitoring (CGM) with predictive alarms warning of impending hypoglycemia may improve self-management of diabetes around exercise. Aim: To assess the impact of Dexcom G6 real-time CGM system with a predictive hypoglycemia alert function on the frequency, duration, and severity of hypoglycemia occurring during and after regular (≥150 min/week) physical activity in people with T1D. Methods: After 10 days of blinded run-in (Baseline), CGM was unblinded and participants randomized 1:1 to have the "urgent low soon" (ULS) alert switched "on" or "off" for 40 days. Participants then switched alerts "off" or "on," respectively, for a further 40 days. Physical activity, and carbohydrate and insulin doses were recorded. Results: Twenty-four participants (8 men, 16 women) were randomized. There was no difference in change from baseline of hypoglycemia <3.0 and <3.9 mmol/L with the ULS on or off during the 24 h after exercise. With ULS alert "on" time spent below 2.8 mmol/L compared with baseline was significantly (P = 0.04) lower than with ULS "off" in the 24 h after exercise. In mixed effects regression, timing of the exercise and baseline HbA1c independently affected risk of hypoglycemia during exercise; exercise timing also affected hypoglycemia risk after exercise. Conclusion: A CGM device with an ULS alert reduces exposure to hypoglycemia below 2.8 mmol/L overall and in the 24 h after exercise compared with a threshold alert. [ABSTRACT FROM AUTHOR]

Background: Few data are available in children with type 1 diabetes using automated insulin delivery systems during physical activity (PA). We evaluated the time in range (TIR) during 2-h of outdoor PA in children using t:slim X2 with Control-IQ® technology. Materials and Methods: Caucasian children and adolescents, aged 9–18 years using t:slim X2 with Control-IQ technology were recruited during a local sporting event. Participants were divided into two groups: Group A practiced endurance activities for 60 min (1000-meter run, a jump circuit) and then power activities for 60 min (80-meter run, long jump); Group B practiced power activities for 60 min and then followed by endurance activities for 60 min. Ninety minutes before the PA, participants had lunch and self-administered a low-dose insulin, reduced by 50% compared to their regularly calculated meal dose per pump calculator. DexcomG6® data were downloaded. Results: Twenty-six children were recruited, 2 refused PA. Participants were divided as follows: 13 in Group A (7 males, median age 14.6 years) and 11 in Group B (8 males, median age 13.5 year). The mean glucose level when PA started was similar between groups (P = 0.06). Subjects in Group B showed a higher TIR than those in Group A ([50.4%, 95% confidence interval, CI: 33.8–75] vs. 39.6% [95% CI: 26.9–58.3], respectively [P = 0.39]). A significantly better TIR in Group B (53.8%, 95% CI: 30.2–96.1) compared to Group A (17.4%, 95% CI: 7.3–41.7, P = 0.02) was recorded during the first session. During the second session, TIR increased in both groups. There were no episodes of serious or severe hypoglycemia. Conclusions: No serious or severe hypoglycemic episodes were recorded during PA performed 90 min after lunch. Future studies using t:slim X2 with Control-IQ technology are necessary. [ABSTRACT FROM AUTHOR]

Objective: Severe hypoglycemia (SH) and diabetic ketoacidosis (DKA) remain significant risks with intensive insulin therapy. While these adverse event (AE) rates are generally very low in advanced hybrid closed-loop (AHCL) clinical studies, prospectively collected real-world AE rates are lacking. Research Design and Methods: The Control-IQ Observational (CLIO) study was a single-arm, prospective, longitudinal, postmarket surveillance study of individuals with type 1 diabetes (T1D) age 6 years and older who began the use of t:slim X2 insulin pump with Control-IQ technology in the real-world outpatient setting. AEs were reported monthly over 12 months and were compared to historical data from the T1D Exchange. Patient-reported outcomes were assessed quarterly. All study visits were virtual. Results: Three thousand one hundred fifty-seven participants enrolled from August 2020 through March 2022. Two thousand nine hundred ninety-eight participants completed through 12 months. SH rates were significantly lower than historic rates for children (9.31 vs. 19.31 events/100 patient years, d = 0.29, P < 0.01) and adults (9.77 vs. 29.49 events/100 patient years, d = 0.53, P < 0.01). DKA rates were also significantly lower in both groups. Lower observed rates of AEs occurred independent of baseline hemoglobin A1c or prior insulin delivery method. Time in range 70–180 mg/dL was 70.1% (61.0–78.8) for adults, 61.2% (52.4–70.5) for age 6–13, 60.9% (50.1–71.8) for age 14–17, and 67.3% (57.4–76.9) overall. Reduction in diabetes burden was consistently reported. Conclusions: SH and DKA rates were lower for users of t:slim X2 with Control-IQ technology compared to historical data for both adults and children. Real-world use of this AHCL system proved safe and effective in this virtual study design. The study was registered at clinicaltrials.gov (NCT04503174) [ABSTRACT FROM AUTHOR]

Objectives: Reaching optimal postprandial glucose dynamics is a daily challenge for people with type 1 diabetes (T1D). This study aimed to analyze the postprandial hyperglycemic excursion (PHEs) and late postprandial hypoglycemia (LPH) risk according to prandial insulin time and type. Research Design and Methods: Real-world, retrospective study in T1D using multiple daily injections (MDI) analyzing 5 h of paired continuous glucose monitoring and insulin injections data collected from the connected cap Insulclock®. Meal events were identified using the rate of change detection methodology. Postprandial glucometrics and LPH (glucose <70 mg/dL 2–5 h after a meal) were evaluated according to insulin injection time and rapid (RI) or ultrarapid analog, Fiasp® (URI), use. Results: Meal glycemic excursions (n = 2488), RI: 1211, 48.7%; UR: 1277, 51.3%, in 82 people were analyzed according to injection time around the PHE: −45 to −15 min; −15 to 0 min; and 0 to +45 min. In 63% of the meals, insulin was injected after the PHE started. Lower PHE was observed with URI versus RI (glucose peak-baseline; mg/dL; mean ± standard deviation): 106.7 ± 35.2 versus 111.2 ± 40.3 (P = 0.003), particularly in 0/+45 injections: 111.6 ± 40.2 versus 118.1 ± 43.3; (P = 0.002). One third (29.1%) of participants added a second (correction) injection. The use of URI and avoiding a second injection were independently associated with less LPH risk, even in delayed injections (0/+45), (−36%, odds ratio [OR] 0.641; confidence interval [CI]: 0.462–0.909; P = 0.012) and −56% (OR 0.641; CI: 0.462–0.909 P = 0.038), respectively. Conclusions: URI analog use as prandial insulin reduces postprandial hyper- and hypoglycemia, even in delayed injections. [ABSTRACT FROM AUTHOR]

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

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

Continuous glucose monitoring (CGM)-based metrics such as time in range and time below range (TBR) and their clinical targets are recommended along with glycated hemoglobin (A1c) to optimize diabetes care. CGM metrics are easy to understand by people with diabetes and have been widely accepted among health care providers. TBR, that is, time spent below a certain glucose level (e.g., <70 mg/dL and <54 mg/dL), is expressed as a percentage. This brief report draws attention to some limitations of TBR when expressed as an integer percentage and highlights problems introduced by rounding-off of numerical values for TBR on ambulatory glucose profile and other reports from CGM and automated insulin delivery systems that may be misleading or incorrectly interpreted. The goal of this article is to generate more discussion around reporting of TBR in ways that can be clinically impactful for people living with diabetes, health care providers, regulatory agencies, and payers to stratify and predict severe hypoglycemic events. [ABSTRACT FROM AUTHOR]

Aims: Ease of use and acceptability of nasal versus injectable glucagon (IG) among pediatric responders have been little investigated. This study compared the performance of administering nasal and IG in parents of youth with type 1 diabetes (T1D) and in school workers. Enablers and barriers associated with each glucagon and preferred glucagon administration learning modality were also evaluated. Methods: Three months after watching short pedagogical videos, 30 parents and 30 school workers performed simulated scenarios where they administered both glucagon. Completion time and successful execution of critical steps were collected. Interviews assessed preferred learning modalities, barriers, and enablers associated with each glucagon. Results: Both groups administered nasal glucagon faster than IG (median [interquartile range]: parents 19 [12–29] vs. 97 [71–117] s, P < 0.001; school workers 24 [16–33] vs. 129 [105–165] s, P < 0.001). A lower proportion of participants successfully executed all critical steps for injectable versus nasal glucagon (significant difference for school workers [53% vs. 90%; P = 0.007] but not for parents [68% vs. 83%; P = 0.227]). Nasal glucagon was preferred for ease of use and acceptability. Preferred learning modalities were a combination of videos and workshops, but videos alone could suffice for nasal glucagon. Conclusions: Nasal glucagon is faster to use, more likely to be successfully administered, and more acceptable than IG for parents of children with T1D and school workers. Nasal glucagon training with videos could improve school workers' involvement in severe hypoglycemia management. Clinical Trial number, URL to the registration: NCT05395000, https://clinicaltrials.gov/ct2/show/NCT05395000 [ABSTRACT FROM AUTHOR]

Objective: Exercise is known to increase the risk for hypoglycemia in type 1 diabetes (T1D) but predicting when it may occur remains a major challenge. The objective of this study was to develop a hypoglycemia prediction model based on a large real-world study of exercise in T1D. Research Design and Methods: Structured study-specified exercise (aerobic, interval, and resistance training videos) and free-living exercise sessions from the T1D Exercise Initiative study were used to build a model for predicting hypoglycemia, a continuous glucose monitoring value <70 mg/dL, during exercise. Repeated measures random forest (RMRF) and repeated measures logistic regression (RMLR) models were constructed to predict hypoglycemia using predictors at the start of exercise and baseline characteristics. Models were evaluated with area under the receiver operating characteristic curve (AUC) and balanced accuracy. Results: RMRF and RMLR had similar AUC (0.833 vs. 0.825, respectively) and both models had a balanced accuracy of 77%. The probability of hypoglycemia was higher for exercise sessions with lower pre-exercise glucose levels, negative pre-exercise glucose rates of change, greater percent time <70 mg/dL in the 24 h before exercise, and greater pre-exercise bolus insulin-on-board (IOB). Free-living aerobic exercises, walking/hiking, and physical labor had the highest probability of hypoglycemia, while structured exercises had the lowest probability of hypoglycemia. Conclusions: RMRF and RMLR accurately predict hypoglycemia during exercise and identify factors that increase the risk of hypoglycemia. Lower glucose, decreasing levels of glucose before exercise, and greater pre-exercise IOB largely predict hypoglycemia risk in adults with T1D. [ABSTRACT FROM AUTHOR]

Aims: To investigate the effect of empagliflozin on glucose dynamics in individuals suffering from postbariatric hypoglycemia (PBH) after Roux-en-Y gastric bypass (RYGB). Methods: Twenty-two adults with PBH after RYGB were randomized to empagliflozin 25 mg or placebo once daily over 20 days in a randomized, double-blind, placebo-controlled, crossover trial. The primary efficacy outcome was the amplitude of plasma glucose excursion (peak to nadir) during a mixed-meal tolerance test (MMTT). Outcomes of the outpatient period were assessed using continuous glucose monitoring (CGM) and an event-tracking app. Results: The amplitude of glucose excursion during the MMTT was 8.1 ± 2.4 mmol/L with empagliflozin versus 8.1 ± 2.6 mmol/L with placebo (mean ± standard deviation, P = 0.807). CGM-based mean amplitude of glucose excursion during the 20-day period was lower with empagliflozin than placebo (4.8 ± 1.3 vs. 5.2 ± 1.6. P = 0.028). Empagliflozin reduced the time spent with CGM values >10.0 mmol/L (3.8 ± 3.5% vs. 4.7 ± 3.8%, P = 0.009), but not the time spent with CGM values <3.0 mmol/L (1.7 ± 1.6% vs. 1.5 ± 1.5%, P = 0.457). No significant difference was observed in the quantity and quality of recorded symptoms. Eleven adverse events occurred with empagliflozin (three drug-related) and six with placebo. Conclusions: Empagliflozin 25 mg reduces glucose excursions but not hypoglycemia in individuals with PBH. Clinical Trial Registration: Clinicaltrials.gov: NCT05057819 [ABSTRACT FROM AUTHOR]

Objective: We aimed to assess whether percentage of time spent in hypoglycemia during closed-loop insulin delivery differs by age group and time of day. Methods: We retrospectively analyzed data from hybrid closed-loop studies involving young children (2–7 years), children and adolescents (8–18 years), adults (19–59 years), and older adults (≥60 years) with type 1 diabetes. Main outcome was time spent in hypoglycemia <3.9 mmol/L (<70 mg/dL). Eight weeks of data for 88 participants were analyzed. Results: Median time spent in hypoglycemia over the 24-h period was highest in children and adolescents (4.4% [interquartile range 2.4–5.0]) and very young children (4.0% [3.4–5.2]), followed by adults (2.7% [1.7–4.0]), and older adults (1.8% [1.2–2.2]); P < 0.001 for difference between age groups. Time spent in hypoglycemia during nighttime (midnight–05:59) was lower than during daytime (06:00–23:59) across all age groups. Conclusion: Time in hypoglycemia was highest in the pediatric age group during closed-loop insulin delivery. Hypoglycemia burden was lowest overnight across all age groups. [ABSTRACT FROM AUTHOR]

This study examined correlations between continuous glucose monitoring (CGM)-based composite metrics and standard glucose metrics within CGM data sets from individuals with recent-onset and long-duration type 1 diabetes. First, a literature review and critique of published CGM-based composite metrics was undertaken. Second, composite metric results were calculated for the two CGM data sets and correlations with six standard glucose metrics were examined. Fourteen composite metrics met selection criteria; these metrics focused on overall glycemia (n = 8), glycemic variability (n = 4), and hypoglycemia (n = 2), respectively. Results for the two diabetes cohorts were similar. All eight metrics focusing on overall glycemia strongly correlated with glucose time in range; none strongly correlated with time below range. The eight overall glycemia-focused and two hypoglycemia-focused composite metrics were all sensitive to automated insulin delivery therapeutic intervention. Until a composite metric can adequately capture both achieved target glycemia and hypoglycemia burden, the current two-dimensional CGM assessment approach may offer greatest clinical utility. [ABSTRACT FROM AUTHOR]

More than one third of U.S. adults age ≥65 years have diabetes. According to early studies, 61% of all diabetes-related costs in the United States were for individuals age ≥65 years, and more than half of these costs attributable to treating diabetes-related complications. Numerous studies have shown that use of continuous glucose monitoring (CGM) has been shown to improve glycemic control and reduce the incidence and severity of hypoglycemia in younger adults with type 1 diabetes and insulin-treated type 2 diabetes (T2D), and there is growing evidence demonstrating the same benefits in older T2D populations. However, because older adults with diabetes are a heterogeneous group with variable clinical, functional, and psychosocial milieu, clinicians must consider whether each patient can use CGM and, if so, the type of CGM device best addresses each patient's needs and capabilities. This article reviews the evidence supporting CGM in the older population, discusses the barriers and benefits of CGM use in older adults with diabetes, and provides recommendations for how different types of CGM systems can be used strategically to improve glycemic control, reduce hypoglycemia, decrease the burden of diabetes, and improve quality of life. [ABSTRACT FROM AUTHOR]

We evaluated the use of hybrid closed-loop (HCL) insulin delivery with faster insulin aspart (Fiasp) in very young children with type 1 diabetes (T1D). In a double-blind, multicenter, randomized, crossover study, children aged 2–6 years with T1D underwent two 8-week periods of HCL using CamAPS FX with Fiasp and standard insulin aspart (IAsp), in random order. Primary endpoint was between-treatment difference in time in target range 3.9–10.0 mmol/L. We randomized 25 participants: mean (±standard deviation) age 5.1 ± 1.3 years, baseline HbA1c 55 ± 9 mmol/mol. Time in range was not significantly different between interventions (64% ± 9% vs. 65% ± 9% for HCL with Fiasp vs. IAsp; mean difference −0.33% [95% confidence interval: −2.13 to 1.47; P = 0.71]). There was no significant difference in time with glucose <3.9 mmol/L. No post-randomization severe hypoglycemia or diabetic ketoacidosis events occurred. Use of Fiasp with CamAPS FX HCL demonstrated no significant difference in glycemic outcomes compared with IAsp in very young children with T1D. Clinical trials registration: NCT04759144. [ABSTRACT FROM AUTHOR]

Time spent in glycemic target range (time in range [TIR]; plasma glucose 70–180 mg/dL [3.9–10.0 mmol/L]) as a surrogate endpoint for long-term diabetes-related outcomes requires validation. This post hoc analysis investigated the association between TIR, derived from 8-point glucose profiles (derived TIR [dTIR]) at 12 months, and time to cardiovascular or severe hypoglycemic episodes in people with type 2 diabetes in the DEVOTE trial. At 12 months, dTIR was significantly negatively associated with time to first major adverse cardiovascular event (P = 0.0087), severe hypoglycemic episode (P < 0.0001), or microvascular event (P = 0.024). A nonsignificant trend was seen toward association between 12-month hemoglobin A1c (HbA1c) and these outcomes, but this was no longer seen after addition of dTIR to the model. The results support targeting TIR >70% and suggest dTIR could be used in addition to, or in some instances in place of, HbA1c as a clinical biomarker. Trial registration details: ClinicalTrials.gov, NCT01959529 [ABSTRACT FROM AUTHOR]

Objective: Automated insulin delivery (AID) may benefit individuals with long-standing type 1 diabetes where frequent exposure to hypoglycemia impairs counterregulatory responses. This study assessed the effect of 18 months AID on hypoglycemia avoidance and glucose counterregulatory responses to insulin-induced hypoglycemia in long-standing type 1 diabetes complicated by impaired awareness of hypoglycemia. Methods: Ten participants mean ± standard deviation age 49 ± 16 and diabetes duration 34 ± 16 years were initiated on AID. Continuous glucose monitoring was paired with actigraphy to assess awake- and sleep-associated hypoglycemia exposure every 3 months. Hyperinsulinemic hypoglycemic clamp experiments were performed at baseline, 6, and 18 months postintervention. Hypoglycemia exposure was reduced by 3 months, especially during sleep, with effects sustained through 18 months (P ≤ 0.001) together with reduced glucose variability (P < 0.01). Results: Hypoglycemia awareness and severity scores improved (P < 0.01) with severe hypoglycemia events reduced from median (interquartile range) 3 (3–10) at baseline to 0 (0–1) events/person·year postintervention (P = 0.005). During the hypoglycemic clamp experiments, no change was seen in the endogenous glucose production (EGP) response, however, peripheral glucose utilization during hypoglycemia was reduced following intervention [pre: 4.6 ± 0.4, 6 months: 3.8 ± 0.5, 18 months: 3.4 ± 0.3 mg/(kg·min), P < 0.05]. There were increases over time in pancreatic polypeptide (Pre:62 ± 29, 6 months:127 ± 44, 18 months:176 ± 58 pmol/L, P < 0.01), epinephrine (Pre: 199 ± 53, 6 months: 332 ± 91, 18 months: 386 ± 95 pg/mL, P = 0.001), and autonomic symptom (Pre: 6 ± 2, 6 months: 6 ± 2, 18 months: 10 ± 2, P < 0.05) responses. Conclusions: AID led to a sustained reduction of hypoglycemia exposure. EGP in response to insulin-induced hypoglycemia remained defective, however, partial recovery of glucose counterregulation was evidenced by a reduction in peripheral glucose utilization likely mediated by increased epinephrine secretion and, together with improved autonomic symptoms, may contribute to the observed clinical reduction in hypoglycemia. [ABSTRACT FROM AUTHOR]

Background: Ultrarapid-acting insulin analogs that could improve or even prevent postprandial hyperglycemia are now available for both research and clinical care. However, clear glycemic benefits remain elusive, especially when combined with automated insulin delivery (AID) systems. In this work, we study two insulin formulations in silico and highlight adjustments of both open-loop and closed-loop insulin delivery therapies as a critical step to achieve clinically meaningful improvements. Methods: Subcutaneous insulin transport models for two faster analogs, Fiasp (Novo Nordisk, Bagsværd, Denmark) and AT247 (Arecor, Saffron Walden, United Kingdom), were identified using data collected from prior clamp experiments, and integrated into the UVA/Padova type 1 diabetes simulator (adult cohort, N = 100). Pump therapy parameters and the aggressiveness of our full closed-loop algorithm were adapted to the new insulin pharmacokinetic and pharmacodynamic profiles through a sequence of in silico studies. Finally, we assessed these analogs' glycemic impact with and without modified therapy parameters in simulated conditions designed to match clinical trial data. Results: Simply switching to faster insulin analogs shows limited improvements in glycemic outcomes. However, when insulin acceleration is accompanied by therapy adaptation, clinical significance is found comparing time-in-range (70–180 mg/dL) with Aspart versus AT247 in open-loop (+5.1%); and Aspart versus Fiasp (+5.4%) or AT247 (+10.6%) in full closed-loop with no clinically significant differences in the exposure to hypoglycemia. Conclusion: In silico results suggest that properly adjusting intensive insulin therapy profiles, or AID tuning, to faster insulin analogs is necessary to obtain clinically significant improvements in glucose control. [ABSTRACT FROM AUTHOR]

Objective: Nationwide reimbursement of intermittently scanned continuous glucose monitoring (isCGM) was introduced in Belgium (2016). This real-world observational study investigates the impact of isCGM over 24 months on adults with type 1 diabetes with impaired or normal awareness of hypoglycemia (IAH or NAH). Methods: We included 1905 people who started first-generation 14-day FreeStyle Libre (without alerts). Sixteen percent had IAH. Primary endpoint was evolution of quality of life (QOL); secondary endpoints were evolution of severe hypoglycemia, work absenteeism, glycated hemoglobin (HbA1c), and sensor-measured outcomes. Results: At baseline, people with IAH (n = 308) had significantly worse QOL than people with NAH (n = 1594). Only people with IAH improved on the hypoglycemia fear survey-worry subscale after 24 months (22.8 [95% confidence interval: 21.4–24.2] at baseline; 20.6 [19.0–22.1] at 24 months, P = 0.002). For both groups, Diabetes Treatment Satisfaction Scale improved over 24 months (IAH: +3.1 [2.1–4.1], P < 0.001; NAH: +2.3 [1.9–2.7], P < 0.001), whereas general QOL, diabetes distress, and HbA1c remained stable. People with IAH showed the strongest decline in work absenteeism and severe hypoglycemia (36.4% having an event 6 months before isCGM initiation; 16.0% having an event during last 6 months of follow-up, P < 0.001), with similar observations for hypoglycemia hospitalization and hypoglycemia coma. Over 24 months, people with IAH spent more time in hypoglycemia, but less time in hyperglycemia than people with NAH. Conclusion: These data show sustained improvement of severe hypoglycemia, work absenteeism, and hypoglycemia fear after isCGM reimbursement, mostly driven by people with IAH. Together with improved treatment satisfaction, irrespective of hypoglycemia awareness level, isCGM without alerts is a valuable tool under long-term real-world conditions. Clinical Trial Registration number: NCT02898714. [ABSTRACT FROM AUTHOR]

Real-time continuous glucose monitoring (CGM) in hospital holds promise; however, further evidence is required on its use to guide adjustment of variable rate intravenous insulin infusion (VRIII). We retrospectively analyzed data from 20 women with type 1 diabetes during the peripartum period who were commenced on VRIII. Data were analyzed for CGM accuracy (Dexcom G6) using point-of-care glucose–CGM matched pairs. The study was entirely observational, with no deviation from standard clinical care. Twenty women were included; median age 30 (26–35) years with first glycated hemoglobin in pregnancy of 57 (49–60) mmol/mol. Overall median absolute relative difference was 6.1 (1.6–17.3)%. The total simulated CGM-adjusted VRIII was 2.5 U per hour, compared with 2.4 U per hour with capillary blood glucose-adjusted VRIII. In this retrospective analysis of CGM adjustment of maternal VRIII, we demonstrate early feasibility and considerable accuracy. Further prospective studies are required to confirm the safety and potential efficacy of CGM-based insulin titration. [ABSTRACT FROM AUTHOR]

Objective: While it is recognized that there is a strong relationship between the amount of time glucose levels are <70 mg/dL (T<70) and the amount of time <54 mg/dL (T<54), the association has not been well quantified. Methods: Datasets with Dexcom continuous glucose monitoring (CGM) data from nine type 1 diabetes randomized trials were pooled to evaluate the relationship between CGM-measured T<70 and T<54. Penalized B-spline regression lines were fitted to assess the relationship between T<70 and T<54 for blinded CGM use, unblinded CGM use without an automated insulin delivery (AID) system, and unblinded CGM use with an AID system. Results: For blinded data, the T<54 : T<70 ratio varied from 19% when the amount of T<70 was <1% to 44% when the amount of T<70 was ≥7% whereas for unblinded data the ratio varied from 15% to 42%, respectively. When T<70 was 4%, the predicted T<54 was 1.18%, 0.94%, and 0.91% for the blinded, unblinded, and AID data, respectively (P<0.001 comparing blinded versus unblinded and AID). Conclusions: The T<54 : T<70 ratio increases with greater T<70, and the ratio generally is higher with blinded than unblinded CGM data, with the latter appearing to be similar to AID system data. The finding of greater T<54 for a given T<70 with blinded CGM data is presumed to be due to an action being taken by the unblinded CGM user and/or by the AID system to minimize hypoglycemia which will have the effect of reducing the amount of T<54. [ABSTRACT FROM AUTHOR]

Background: Hypoglycemia rates usually increase when insulin treatment is intensified to improve glycemic control. We evaluated (post hoc) hypoglycemic rates in adult patients with type 1 diabetes (T1D) on sotagliflozin (a dual sodium-glucose cotransporter [SGLT] 1 and 2 inhibitor) in two phase 3, 52-week clinical trials (inTandem 1 and 2; NCT02384941 and NCT02421510). Materials and Methods: We analyzed rates of documented hypoglycemia (level 1, blood glucose ≥54 to

Glycemic Outcomes of Children 2-6 Years of Age with Type 1 Diabetes During the Pediatric Mini... I Forlenza GP SP 1 sp , Ekhlaspour L SP 2 sp , DiMeglio LA SP 3 sp , Fox LA SP 4 sp , Rodriguez H SP 5 sp , Shulman DI SP 5 sp , Kaiserman KB SP 6 sp , Liljenquist DR SP 7 sp , Shin J SP 8 sp , Lee SW SP 8 sp , Buckingham BA SP 2 sp i I SP 1 sp Division of Pediatric Endocrinology, Barbara Davis Center, Aurora, CO; SP 2 sp Division of Pediatric Endocrinology, Stanford University, Stanford, CA; SP 3 sp Division of Pediatric Endocrinology and Diabetology, Wells Center for Pediatric Research, Indiana University, Indianapolis, IN; SP 4 sp Division of Endocrinology, Diabetes and Metabolism, Nemours Children's Health System, Jacksonville, FL; SP 5 sp Division of Pediatric Endocrinology, University of South Florida, Tampa, FL; SP 6 sp SoCal Diabetes, Torrance, CA; SP 7 sp Rocky Mountain Diabetes Center, Idaho Falls, ID; SP 8 sp Medtronic Diabetes, Northridge, CA i I Pediatr Diabetes 2022; i B I 23 i b I : 324-329 i Background Management of diabetes in young children (2-6 years) is challenging because of highly variable insulin sensitivity, susceptibility to hypoglycemia, and inability to communicate symptoms of hypoglycemia. To select these 22 articles focused on diabetes technology and therapeutics in the pediatric age group, we conducted a Medline search for articles dealing with the following topics: diabetes technology, insulin pump therapy (continuous subcutaneous insulin infusion [CSII]), continuous glucose monitoring (CGM), closed-loop systems, and new therapies in type 1 (T1D) and type 2 diabetes (T2D) relating to the pediatric age group (0-18 years). [Extracted from the article]

Sanofi - Insulin Aspart SAR341402 Sanofi has two biosimilar insulins of rapid-acting insulin analogues (insulin lispro, Admelog; insulin aspart; SAR341402) on the market. A total of 149 patients were randomized 1:1 to basal-bolus therapy with insulin degludec and insulin aspart or insulin glargine U100 and insulin aspart. Comments Although most biosimilar insulin are "copies" of insulin analogues, human insulin formulations are still widely used, especially in countries in which the insulin price matters to the PwD directly. A biosimilar insulin may not be substituted for the reference insulin at the pharmacy counter unless the biosimilar insulin undergoes additional switch trials to earn the designation as an interchangeable biosimilar insulin. THIRD-GENERATION BASAL INSULIN ANALOGUES Molecular and Pharmacological Characterization of Insulin Icodec: A New Basal Insulin Analog... I Nishimura E SP 1 sp , Pridal L SP 1 sp , Glendorf T SP 1 sp , Hansen BF SP 1 sp , Hubálek F SP 1 sp , Thomas Kjeldsen T SP 1 sp , Kristensen NR SP 2 sp , Lützen A SP 1 sp , Lyby K SP 2 sp , Madsen P SP 1 sp , Pedersen TÅ SP 1 sp , Ribel-Madsen R SP 2 sp , Stidsen CE SP 1 sp , Haahr H SP 2 sp i I SP 1 sp Research & Early Development, Novo Nordisk A/S, Måløv, Denmark; SP 2 sp Development, Novo Nordisk A/S, Søborg, Denmark i I BMJ Open Diabetes Res Care 2021; i B I 9 i b I : e002301 i Background A new, long-acting insulin analogue, insulin iodec, has been developed to handle basal insulin needs; it is administered subcutaneously once a week. [Extracted from the article]

AIM To assess relationships between continuous glucose monitoring (CGM) time in 70-180mg/dL range (TIR), time below range (TBR), <70mg/dL, time above range (TAR), >180mg/dL and glucose coefficient of variation (CV) in relation to currently recommended clinical CGM targets for older people, which recommend reduced TIR and TBR targets relative to the general type 1 diabetes population. METHODS We conducted a post-hoc analysis using the JDRF Australia Adult Hybrid Closed Loop trial database examining correlations in 120 adults with type 1 diabetes of 3-weeks masked CGM (Guardian Sensor 3; Medtronic) metrics (n=61 on multiple daily injections, 59 on non-CGM augmented pumps) using manual insulin dosing at baseline and at 26-weeks, with 50% randomized to automated insulin dosing (AID). RESULTS Correlations between baseline TIR and TAR were strong (r= -0.966; p<0.0001), weak for TBR (r=0.363; p<0.0001) and glucose CV (r=0.037; p=0.687) while moderate between CV and TBR (r=0.726; p<0.0001). Associations were similar for participants aged >60 years (n=15) vs. younger subjects. Correlations of changes in (∆) TIR with ∆TAR over 26-weeks were strong (r=-0.945; p<0.001) and for ∆TBR were weak (r=0.025; p=0.802). ∆CV did not significantly correlate with ∆TAR (r=-0.064; p=0.526) but did with ∆TBR (r=0.770; p=<0.001) CONCLUSIONS Changes in TIR are not associated with changes in TBR. We therefore suggest that, particularly with AID, while TBR targets in older adults may be prioritized to ensure safety that they should not be linked to TIR but addressed independently. [ABSTRACT FROM AUTHOR]

Aims: To assess the safety and efficacy of two exercise sessions performed 60- and 120-min postmeal with a combination of meal bolus reduction and increased glucose target to the automated insulin delivery (AID) system. Methods: A randomized crossover trial in 13 adult participants (6 females) living with type 1 diabetes using AID (A1c = 7.9% ± 0.6%, age = 53.5 ± 15.5 years, T1D duration = 29.0 ± 16.0 years) was conducted. Just before breakfast, at the time of meal bolus, the AID glucose target was increased from 6 to 9 mmol/L, and a meal bolus reduction of 33% was applied. Two 60-min exercise sessions (60% of VO2 peak) were undertaken either 60 min (60EX) or 120 min (120EX) after a standardized breakfast, followed by a 90-min recovery period. Results: The mean reduction in plasma glucose (PG) levels from prebreakfast to postexercise (-0.8 ± 2.4 mmol/L vs. +0.3 ± 2.3 mmol/L, P = 0.082) were similar between 60EX and 120EX. From prebreakfast to postexercise, PG times in range (3.9-10.0 mmol/L; 63.4% ± 43.1% 60EX vs. 51.9% ± 29.7% 120EX, P = 0.219) and time above range (>10.0 mmol/L; 36.3% ± 43.3% 60EX vs. 48.1% ± 29.7% 120EX, P = 0.211) did not differ between interventions. The 60EX attenuated the glucose rise between premeal to pre-exercise (+1.8 ± 2.1 mmol/L 60EX vs. +3.9 ± 2.1 mmol/L 120EX, P = 0.001). No hypoglycemic events (<3.9 mmol/L) occurred during the study. Conclusion: Premeal announcement combining meal bolus reduction and increased glucose target was effective and safe during 60 min of moderate-intensity aerobic exercise, whether exercise onset was 60 or 120 min following a meal. Clinical Trial Registration No.: NCT04031599. [ABSTRACT FROM AUTHOR]

Objective: Stepped-care has been suggested in the management of patients with problematic hypoglycemia and impaired awareness of hypoglycemia (IAH), initially with psychoeducational programs based on blood glucose awareness training, progressing to diabetes technology in those with persisting need. We examined the clinical effectiveness of stepped-care starting with HypoAware and adding continuous glucose monitoring (CGM) as needed, versus immediate CGM in type 1 diabetes patients with problematic hypoglycemia despite previous structured education in insulin adjustment. Research Design and Methods: A randomized controlled trial (N = 52, mean age 53, 56% females). The stepped-care group attended HypoAware. If a severe hypoglycemic event (SHE) had occurred or IAH was still present after 6 months, CGM was initiated. The control group started immediate CGM. Primary endpoint was the number of participants with self-reported SHE. Secondary outcomes, evaluated at 6 and 12 months, were glycated hemoglobin (HbA1c), the number of participants with IAH time below range (TBR; <54 mg/dL), and patient-reported outcomes (PROs). Results: At 6 months, the number of patients reporting SHE had decreased significantly more in the CGM group: -39% (P < 0.05). HbA1c decreased more in the CGM group (-0.47 percentage-points, P < 0.05). IAH was restored in 31% of patients in both groups. TBR (<54 mg/dL) was lower in the CGM group (-2.4 percentage-points, P < 0.05). In the stepped-care group, 93% started CGM/intermittently scanned CGM. At 12 months, the number of patients reporting SHE was still higher in the stepped-care group. No differences were found in PROs. Conclusions: Immediate start of CGM is more effective than a hypoglycemia-focused reeducation program in reducing SHE risk and attaining glycemic targets in individuals with problematic hypoglycemia and IAH despite previous education in insulin dose adjustment. Trial registration: Netherlands Trial Register, NL64474.029.18. [ABSTRACT FROM AUTHOR]

Aim: To compare evening and overnight hypoglycemia risk after late afternoon exercise with a nonexercise control day in adults with type 1 diabetes using automated insulin delivery (AID). Methods: Thirty adults with type 1 diabetes using AID (Minimed 670G) performed in random order 40 min high intensity interval aerobic exercise (HIE), resistance (RE), and moderate intensity aerobic exercise (MIE) exercise each separated by >1 week. The closed-loop set-point was temporarily increased 2 h pre-exercise and a snack eaten if plasma glucose was ≤126 mg/dL pre-exercise. Exercise commenced at ∼16:00. A standardized meal was eaten at ∼20:40. Hypoglycemic events were defined as a continuous glucose monitor (CGM) reading <70 mg/dL for ≥15 min. Four-hour postevening meal and overnight (00:00-06:00) CGM metrics for exercise were compared with the prior nonexercise day. Results: There was no severe hypoglycemia. Between 00:00 and 06:00, the proportion of nights with hypoglycemia did not differ postexercise versus control for HIE (18% vs. 11%; P = 0.688), RE (4% vs. 14%; P = 0.375), and MIE (7% vs. 14%; P = 0.625). Time in range (TIR) (70-180 mg/dL), >75% for all nights, did not differ between exercise conditions and control. Hypoglycemia episodes postmeal after exercise versus control did not differ for HIE (22% vs. 7%; P = 0.219) and MIE (10% vs. 14%; P > 0.999), but were greater post-RE (39% vs. 10%; P = 0.012). Conclusions: Overnight TIR was excellent with AID without increased hypoglycemia postexercise between 00:00 and 06:00 compared with nonexercise days. In contrast, hypoglycemia risk was increased after the first meal post-RE, suggesting the importance of greater vigilance and specific guidelines for meal-time dosing, particularly with vigorous RE. ACTRN12618000905268. [ABSTRACT FROM AUTHOR]

Introduction: DailyDose is a decision support system designed to provide real-time dosing advice and weekly insulin dose adjustments for adults living with type 1 diabetes using multiple daily insulin injections. Materials and Methods: Twenty-five adults were enrolled in this single-arm study. All participants used Dexcom G6 for continuous glucose monitoring, InPen for short-acting insulin doses, and Clipsulin to track long-acting insulin doses. Participants used DailyDose on an iPhone for 8 weeks. The primary endpoint was % time in range (TIR) comparing the 2-week baseline to the final 2-week period of DailyDose use. Results: There were no significant differences between TIR or other glycemic metrics between the baseline period compared to final 2-week period of DailyDose use. TIR significantly improved by 6.3% when more than half of recommendations were accepted and followed compared with 50% or fewer recommendations (95% CI 2.5%-10.1%, P = 0.001). Conclusions: Use of DailyDose did not improve glycemic outcomes compared to the baseline period. In a post hoc analysis, accepting and following recommendations from DailyDose was associated with improved TIR. Clinical Trial Registration Number: NCT04428645. [ABSTRACT FROM AUTHOR]

Background: The aim was to compare the efficacy of real-time continuous glucose monitoring (rtCGM) and intermittently scanned continuous glucose monitoring (isCGM) focusing on glycated hemoglobin (HbA1c) as the primary endpoint. Methods: The CORRIDA LIFE was a 12-month, real-world, nonrandomized study that is part of the CORRIDA clinical trials program. The study compared rtCGM (Dexcom G5 or G6) and isCGM (FreeStyle Libre 14-Day; Abbott) in adults with type 1 diabetes (T1D). Only patients on multiple daily insulin injections or continuous subcutaneous insulin infusion with no automatic functions were included in this study. Primary outcome was the difference in HbA1c between study groups at 12 months. Results: One hundred ninety-one adults with T1D (mean age 40 ± 13 years, HbA1c 8.1% ± 3.4% [65 ± 14 mmol/mol]) participated in this study; 81 patients initiated rtCGM and 110 initiated isCGM. After 12-months, HbA1c was significantly lower with rtCGM versus isCGM (7.1% ± 3.1% [54.1 ± 10.1 mmol/mol] vs. 7.7% ± 3.3% [61.2 ± 12.2 mmol/mol]), P = 0.0001. The percentage of time in hypoglycemia (<70 mg/dL [<3.9 mmol/L]) was lower among rtCGM vs. isCGM participants [4.3% ± 2.8% vs. 6.4% ± 5.3%], P = 0.003). Patients with rtCGM spent less time in clinically significant hypoglycemia (<54 mg/dL [<3.0 mmol/L]) (0.9% ± 1.0% vs. 2.3% ± 2.5%, P < 0.0001) and more time in target range (70-180 mg/dL [3.9-10 mmol/L]) than isCGM users (67.5% ± 14.8% vs. 57.8% ± 17.0%), P = 0.0002. Conclusions: rtCGM was superior to isCGM in HbA1c, hypoglycemia, and other glycemic outcomes. Our findings provide guidance to clinicians when discussing monitoring options with their patients. The study was registered at www.clinicaltrials.gov (NCT04759495). [ABSTRACT FROM AUTHOR]

However, patient self-management and glycemic outcomes can be improved with diabetes education.[1] Health care providers are often overstretched, and their workload does not enable to allocate the sufficient time required for patient education. I Dear Editor: i Managing diabetes can be a challenging task for millions of people worldwide. Yet, AI technology such as ChatGPT still cannot replace the critical role of health care professionals in managing diabetes. [Extracted from the article]

Background: The aim of this prospective open-label single-arm single-center follow-up study was to analyze glycemic control in children and adolescents with type 1 diabetes treated with the advanced hybrid closed loop (AHCL) system in relation to a sensor-augmented pump with low-glucose suspend (SAP-LGS) or predictive low-glucose suspend (SAP-PLGS). Materials and Methods: The data for 50 children and adolescents (age 5.5-19.6 years) with type 1 diabetes, receiving insulin through an AHCL system after being switched from SAP-LGS/PLGS systems, were included in the analysis. The SAP-LGS/PLGS records from 2 weeks preceding the AHCL connection were compared with the records from the first 4 weeks of AHCL use, represented as two separate 2-week intervals. Results: Significant improvements in most of the parameters, namely time spent in the range of 70-140 mg/dL (from 53.80% ± 12.35% to 61.70% ± 8.42%, P < 0.001) and 70-180 mg/dL (from 76.17% ± 10.28% to 81.32% ± 7.71%, P < 0.001), average sensor glucose (from 138.61 ± 16.66 to 130.02 ± 10.91 mg/dL, P < 0.001), and glucose management indicator (from 6.54% ± 0.45% to 6.27% ± 0.29%, P = 0.001), were observed within 2 weeks of switching to the AHCL. More evident improvements were observed for the parameters monitored at night than during the day. The potential limitations of this study were the short observation time, lack of glycated hemoglobin measurements, and no control arm. Conclusion: The AHCL system can significantly improve glycemic control even in well-controlled children and adolescents with type 1 diabetes by increasing the proportion of time spent in the narrower range of 70-140 mg/dL and decreasing the mean glucose concentration, especially during the night. [ABSTRACT FROM AUTHOR]

Repeated hypoglycemia exposure leads to impaired awareness of hypoglycemia (IAH) and the development of defective counterregulatory responses. To date, only pancreas or islet transplantation has demonstrated normalization of hypoglycemia awareness and the endogenous glucose production (EGP) response to defend against insulin-induced hypoglycemia in long-standing type 1 diabetes (T1D). This study aims to validate clinical metrics of IAH (Clarke score), hypoglycemia severity (HYPO score), glycemic lability (lability index), and continuous glucose monitoring (CGM) as predictors of absent autonomic symptom (AS) recognition and defective glucose counterregulation during insulin-induced hypoglycemia, thus enabling early identification of individuals with compromised physiologic defense against clinically significant hypoglycemia. Forty-three subjects with mean ± standard deviation age 43 ± 13 years and T1D duration 28 ± 13 years, including 32 with IAH and 11 with hypoglycemia awareness (Aware), and 12 nondiabetic control subjects, underwent single-blinded randomized-paired hyperinsulinemic–euglycemic and hypoglycemic clamp experiments. Receiver operating characteristic (ROC) curves and sensitivity analyses were performed to assess metric prediction of absent AS recognition and defective EGP responses to hypoglycemia. Clarke score and CGM measures of hypoglycemia exposure demonstrated good ability to predict absent AS recognition (area under the curve ≥0.80). A composite threshold of IAH–Clarke ≥4 with ROC curve-derived thresholds for CGM measures of hypoglycemia exposure showed high specificity and predictive value in identifying an absent AS response during the hypoglycemic clamp. Metrics demonstrated poor ability to predict defective glucose counterregulation by the EGP response, which was impaired even in the Aware group. Screening for IAH alongside assessment of CGM data can increase the specificity for identifying individuals with absent hypoglycemia symptom recognition who may benefit from further intervention. [ABSTRACT FROM AUTHOR]