Expert Panel Recommendations for a Standardized Ambulatory Glucose Profile Report for Connected Insulin Pens.

Background: Connected insulin pens capture data on insulin dosing/timing and can integrate with continuous glucose monitoring (CGM) devices with essential insulin and glucose metrics combined into a single platform. Standardization of connected insulin pen reports is desirable to enhance clinical utility with a single report. Methods: An international expert panel was convened to develop a standardized connected insulin pen report incorporating insulin and glucose metrics into a single report containing clinically useful information. An extensive literature review and identification of examples of current connected insulin pen reports were performed serving as the basis for creation of a draft of a standardized connected insulin pen report. The expert panel participated in three virtual standardization meetings and online surveys. Results: The Ambulatory Glucose Profile (AGP) Report: Connected Insulin Pen brings all clinically relevant CGM-derived glucose and connected insulin pen metrics into a single simplified two-page report. The first page contains the time in ranges bar, summary of key insulin and glucose metrics, the AGP curve, and detailed basal (long-acting) insulin assessment. The second page contains the bolus (mealtime and correction) insulin assessment periods with information on meal timing, insulin-to-carbohydrate ratio, average bolus insulin dose, and number of days with bolus doses recorded. The report's second page contains daily glucose profiles with an overlay of the timing and amount of basal and bolus insulin administered. Conclusion: The AGP Report: Connected Insulin Pen is a standardized clinically useful report that should be considered by companies developing connected pen technology as part of their system reporting/output.

Towards the standardisation of adult person-reported outcome domains in diabetes research: A Consensus Statement development panel.

Diabetes is unique among chronic diseases because clinical outcomes are intimately tied to how the person living with diabetes reacts to and implements treatment recommendations. It is further characterised by widespread social stigma, judgement and paternalism. This physical, social and psychological burden collectively influences self-management behaviours. It is widely recognised that the individual's perspective about the impact of trying to manage the disease and the burden that self-management confers must be addressed to achieve optimal health outcomes. Standardised, rigorous assessment of mental and behavioural health status, in interaction with physical health outcomes is crucial to aid understanding of person-reported outcomes (PROs). Whilst tempting to conceptualise PROs as an issue of perceived quality of life (QoL), in fact health-related QoL is multi-dimensional and covers indicators of physical or functional health status, psychological and social well-being. This complexity is illuminated by the large number of person reported outcome measures (PROMs) that have been developed across multiple psychosocial domains. Often measures are used inappropriately or because they have been used in the scientific literature rather than based on methodological or outcome assessment rigour. Given the broad nature of psychosocial functioning/mental health, it is important to broadly define PROs that are evaluated in the context of therapeutic interventions, real-life and observational studies. This report summarises the central themes and lessons derived in the assessment and use of PROMs amongst adults with diabetes. Effective assessment of PROMs routinely in clinical research is crucial to understanding the true impact of any intervention. Selecting appropriate measures, relevant to the specific factors of PROs important in the research study will provide valuable data alongside physical health data.

Continuous glucose monitoring and metrics for clinical trials: an international consensus statement.

Randomised controlled trials and other prospective clinical studies for novel medical interventions in people with diabetes have traditionally reported HbA1c as the measure of average blood glucose levels for the 3 months preceding the HbA1c test date. The use of this measure highlights the long-established correlation between HbA1c and relative risk of diabetes complications; the change in the measure, before and after the therapeutic intervention, is used by regulators for the approval of medications for diabetes. However, with the increasing use of continuous glucose monitoring (CGM) in clinical practice, prospective clinical studies are also increasingly using CGM devices to collect data and evaluate glucose profiles among study participants, complementing HbA1c findings, and further assess the effects of therapeutic interventions on HbA1c. Data is collected by CGM devices at 1-5 min intervals, which obtains data on glycaemic excursions and periods of asymptomatic hypoglycaemia or hyperglycaemia (ie, details of glycaemic control that are not provided by HbA1c concentrations alone that are measured continuously and can be analysed in daily, weekly, or monthly timeframes). These CGM-derived metrics are the subject of standardised, internationally agreed reporting formats and should, therefore, be considered for use in all clinical studies in diabetes. The purpose of this consensus statement is to recommend the ways CGM data might be used in prospective clinical studies, either as a specified study endpoint or as supportive complementary glucose metrics, to provide clinical information that can be considered by investigators, regulators, companies, clinicians, and individuals with diabetes who are stakeholders in trial outcomes. In this consensus statement, we provide recommendations on how to optimise CGM-derived glucose data collection in clinical studies, including the specific glucose metrics and specific glucose metrics that should be evaluated. These recommendations have been endorsed by the American Association of Clinical Endocrinologists, the American Diabetes Association, the Association of Diabetes Care and Education Specialists, DiabetesIndia, the European Association for the Study of Diabetes, the International Society for Pediatric and Adolescent Diabetes, the Japanese Diabetes Society, and the Juvenile Diabetes Research Foundation. A standardised approach to CGM data collection and reporting in clinical trials will encourage the use of these metrics and enhance the interpretability of CGM data, which could provide useful information other than HbA1c for informing therapeutic and treatment decisions, particularly related to hypoglycaemia, postprandial hyperglycaemia, and glucose variability.

Consensus Recommendations for the Use of Automated Insulin Delivery Technologies in Clinical Practice.

The significant and growing global prevalence of diabetes continues to challenge people with diabetes (PwD), healthcare providers, and payers. While maintaining near-normal glucose levels has been shown to prevent or delay the progression of the long-term complications of diabetes, a significant proportion of PwD are not attaining their glycemic goals. During the past 6 years, we have seen tremendous advances in automated insulin delivery (AID) technologies. Numerous randomized controlled trials and real-world studies have shown that the use of AID systems is safe and effective in helping PwD achieve their long-term glycemic goals while reducing hypoglycemia risk. Thus, AID systems have recently become an integral part of diabetes management. However, recommendations for using AID systems in clinical settings have been lacking. Such guided recommendations are critical for AID success and acceptance. All clinicians working with PwD need to become familiar with the available systems in order to eliminate disparities in diabetes quality of care. This report provides much-needed guidance for clinicians who are interested in utilizing AIDs and presents a comprehensive listing of the evidence payers should consider when determining eligibility criteria for AID insurance coverage.

Impact of Temporary Glycemic Target Use in the Hybrid and Advanced Hybrid Closed-Loop Systems.

The Medtronic advanced hybrid closed-loop (AHCL) and MiniMed™ 670G hybrid closed-loop (HCL) systems provide the option to temporarily increase the glucose target to 150 mg/dL (8.3 mmol/L). This analysis investigated the efficacy of the AHCL compared with that of the HCL after the use of this setting. Data from 60 participants in the Fuzzy Logic Automated Insulin Regulation (FLAIR) study were used to compare the AHCL and HCL systems after the use of the temporary target (TT), and during analogous periods where this setting was not used. Differences in time in range 70-180 mg/dL between the systems were similar after the use of the TT setting and during analogous non-TT periods (interaction P = 0.87). Similar trends were observed for mean glucose, percentage time >180 mg/dL, and percentage time >250 mg/dL. Differences between AHCL and HCL systems were similar after the use of the TT setting compared with those of non-TT periods. ClinicalTrials.gov NCT03040414.

Symptoms and Glycemic Control in Young People With Type 1 Diabetes Following SARS-CoV-2 Infection: An Observational Study.

CONTEXT: Data is needed regarding the effect of SARS-CoV-19 infection on young people with established type 1 diabetes. Identifying the disease outcomes, short and long-term sequelae may help to establish an evidence-based prevention and education policy for sick days management and DKA prevention. OBJECTIVE: This work aims to describe clinical manifestations of SARS-CoV-2 infection in children, adolescents, and young adults with established type 1 diabetes (T1D) and explore the effects of COVID-19 on glycemic control and disease course. METHODS: An observational study was conducted at 3 pediatric diabetes clinics in Israel between mid-March 2020 and mid-March 2021. Included were young people with established T1D, age younger than 30 years, who tested positive for SARS-CoV-2 (quantitative real-time polymerase chain reaction). Data were collected from medical files, diabetes devices, and COVID-19 questionnaire. Outcome measures were analyzed by the presence/absence of clinical symptoms (symptomatic/asymptomatic) and by age group (pediatric, < 19 years/young adults, 19-30 years). RESULTS: Of 132 patients, mean age 16.9 ±â€…5.3years, with COVID-19-confirmed infection, 103 (78%) had related symptoms; the most common were headaches, fatigue, fever, and loss of sense of smell. All had a mild disease course, but 4 required hospitalization and 2 cases were directly related to COVID-19 infection (pleuropneumonia in a patient with immunodeficiency syndrome, 1 case of diabetic ketoacidosis). Logistic regression analysis showed that age (odds ratio [OR] = 1.11; 95% CI, 1.01-1.23; P = .033), elevated glucose levels (OR = 5.23; 95% CI, 1.12-24.41; P = .035), and comorbidities (OR = 8.21; 95% CI, 1.00-67.51; P = .050) were positively associated with symptomatic infection. Persistent symptoms occurred in 16.5% of the cohort over a median of 6.7 months; age (OR = 1.14; 95% CI, 1.01-1.29; P = .030) and elevated glucose levels (OR = 3.42; 95% CI, 1.12-10.40; P = .031) were positively associated with persistent symptoms. Usually, no change was reported in glucose levels (64%) except for a temporary deterioration in glycemic control during the short infection period. CONCLUSION: Young people with established T1D experience mild COVID-19 infection. Elevated glucose levels during COVID-19 infection and older age were associated with prolonged disease course.

A Comparison of Postprandial Glucose Control in the Medtronic Advanced Hybrid Closed-Loop System Versus 670G.

Background: We recently reported that use of an "advanced" hybrid closed-loop system reduced hyperglycemia without increasing hypoglycemia compared to a first-generation system. The aim of this analysis was to evaluate whether this improved performance was specifically related to better mealtime glycemic control. Methods: We conducted a secondary analysis of postprandial glycemic control in an open-label, multinational, randomized crossover trial of 112 participants with type 1 diabetes, aged 14-29, of the Medtronic MiniMed™ 670G hybrid closed-loop system (670G) versus the Medtronic advanced hybrid closed-loop (AHCL) system, for 12 weeks each. We compared glycemic and insulin delivery metrics over a 3 h horizon across all meals to assess system performance and outcomes. Results: Overall meal size and premeal insulin on board were similar during run-in and between 670G and AHCL arms. Compared with 670G arm, premeal, peak, and mean glucose levels were numerically lower in the AHCL arm (167 ± 23, 231 ± 23, and 177 ± 20 mg/dL vs. 175 ± 23, 235 ± 23, and 180 ± 19 mg/dL, respectively), with a trend to lower hyperglycemia level 2 in AHCL arm. Adjusting for premeal glucose level, all postmeal outcomes between 670G and AHCL were statistically similar. Prandial insulin delivery also was similar in both treatment arms (21 ± 9 vs. 23 ± 10 U), with a shift in basal/bolus ratio from 28%/71% in 670G arm to 20%/80% in AHCL arm. Conclusions: Reduced hyperglycemia with AHCL compared to 670G was not related to early postprandial glycemic excursions after adjusting for premeal glucose level (<3 h after meal), but likely to later (>3 h) postprandial or overnight improvements. Further refinements to mealtime bolus algorithms and strategies may more optimally control prandial glycemic excursions.

Comparison of Insulin Dose Adjustments Made by Artificial Intelligence-Based Decision Support Systems and by Physicians in People with Type 1 Diabetes Using Multiple Daily Injections Therapy.

Objective: Artificial intelligence-based decision support systems (DSS) need to provide decisions that are not inferior to those given by experts in the field. Recommended insulin dose adjustments on the same individual data set were compared among multinational physicians, and with recommendations made by automated Endo.Digital DSS (ED-DSS). Research Design and Methods: This was a noninterventional study surveying 20 physicians from multinational academic centers. The survey included 17 data cases of individuals with type 1 diabetes who are treated with multiple daily insulin injections. Participating physicians were asked to recommend insulin dose adjustments based on glucose and insulin data. Insulin dose adjustments recommendations were compared among physicians and with the automated ED-DSS. The primary endpoints were the percentage of comparison points for which there was agreement on the trend of insulin dose adjustments. Results: The proportion of agreement and disagreement in the direction of insulin dose adjustment among physicians was statistically noninferior to the proportion of agreement and disagreement observed between ED-DSS and physicians for basal rate, carbohydrate-to insulin ratio, and correction factor (P < 0.001 and P ≤ 0.004 for all three parameters for agreement and disagreement, respectively). The ED-DSS magnitude of insulin dose change was consistently lower than that proposed by the physicians. Conclusions: Recommendations for insulin dose adjustments made by automatization did not differ significantly from recommendations given by expert physicians regarding the direction of change. These results highlight the potential utilization of ED-DSS as a useful clinical tool to manage insulin titration and dose adjustments.

Adjustment of Insulin Pump Settings in Type 1 Diabetes Management: Advisor Pro Device Compared to Physicians' Recommendations.

AIMS: To compare insulin dose adjustments made by physicians to those made by an artificial intelligence-based decision support system, the Advisor Pro, in people with type 1 diabetes (T1D) using an insulin pump and self-monitoring blood glucose (SMBG). METHODS: This was a multinational, non-interventional study surveying 17 physicians from 11 countries. Each physician was asked to provide insulin dose adjustments for the settings of the pump including basal rate, carbohydrate-to-insulin ratios (CRs), and correction factors (CFs) for 15 data sets of pumps and SMBG of people with T1D (mean age 18.4 ± 4.8 years; eight females; mean glycated hemoglobin 8.2% ± 1.4% [66 ± 11mmol/mol]). The recommendations were compared among the physicians and between the physicians and the Advisor Pro. The study endpoint was the percentage of comparison points for which there was an agreement on the direction of insulin dose adjustments. RESULTS: The percentage (mean ± SD) of agreement among the physicians on the direction of insulin pump dose adjustments was 51.8% ± 9.2%, 54.2% ± 6.4%, and 49.8% ± 11.6% for the basal, CR, and CF, respectively. The automated recommendations of the Advisor Pro on the direction of insulin dose adjustments were comparable )49.5% ± 6.4%, 55.3% ± 8.7%, and 47.6% ± 14.4% for the basal rate, CR, and CF, respectively( and noninferior to those provided by physicians. The mean absolute difference in magnitude of change between physicians was 17.1% ± 13.1%, 14.6% ± 8.4%, and 23.9% ± 18.6% for the basal, CR, and CF, respectively, and comparable to the Advisor Pro 11.7% ± 9.7%, 10.1% ± 4.5%, and 25.5% ± 19.5%, respectively, significant for basal and CR. CONCLUSIONS: Considerable differences in the recommendations for changes in insulin dosing were observed among physicians. Since automated recommendations by the Advisor Pro were similar to those given by physicians, it could be considered a useful tool to manage T1D.

User and Healthcare Professional Perspectives on Do-It-Yourself Artificial Pancreas Systems: A Need for Guidelines.

A growing number of individuals with type 1 diabetes are choosing to use "do-it-yourself" artificial pancreas systems (DIY APS) to support their diabetes self-management. Observational and self-report data of glycemic benefits of DIY APS are promising; however, without rigorous clinical trials or regulation from governing bodies, liability and user safety continue to be central concerns for stakeholders. Despite DIY APS having been used for several years now, there are no guidelines to assist users and healthcare professionals in addressing DIY APS use in routine clinical care. This commentary reports key stakeholders' perspectives presented at the annual Advanced Technologies and Treatments in Diabetes conference in February 2020. Important considerations to inform the development of clinical care guidelines are also presented to generate further debate.

Diabetes ketoacidosis recovery in youth with newly diagnosed and established type 1 diabetes.

BACKGROUND: The objective of this study was to describe the differences in metabolic parameters and in time to recovery from diabetes ketoacidosis (DKA), between children and adolescents with newly diagnosed diabetes compared with established type 1 diabetes (T1DM). METHODS: This was a single-center, retrospective study. The cohort consists of 356 children and adolescents with T1DM who had DKA during 2008-2018. Data were obtained from the patients' medical files. Recovery of DKA was defined as the resolution of acidosis (pH >7.3 and bicarbonate >15 meq/L). RESULTS: The mean time to recovery from DKA was significantly longer in patients with newly diagnosed diabetes than in those with established diabetes (13± versus 8.5± h) (p < 0.001). This difference was maintained in an analysis according to DKA severity: mild, moderate, and severe. pH at presentation did not differ between the groups, but bicarbonate at presentation was significantly lower in patients with newly diagnosed diabetes than in those with established diabetes, 9.9± versus 12± mmol/L (p < 0.001). Potassium and phosphorus levels were lower, and sodium and chloride levels were higher in patients with newly diagnosed diabetes than in those with established diabetes (p < 0.001). CONCLUSIONS: DKA is associated with a shorter recovery time in patients with established diabetes compared to newly diagnosed diabetes. This may have implications on the treatment of people with established diabetes. IMPACT: DKA is associated with a shorter recovery time in patients with established diabetes compared with newly diagnosed diabetes. Shorter recovery time in a patient with established diabetes compared with newly diagnosed diabetes was observed in any DKA severity. The time to recovery from DKA did not differ significantly between patients treated with an insulin pump and those treated with multiple daily injections. Triggers for DKA among patients with established diabetes were poor compliance with treatment, infection, pump dysfunction, and dehydration.

Clinical characteristics, growth patterns, and long-term diabetes complications of 24 patients with neonatal diabetes mellitus: A single center experience.

OBJECTIVES: Neonatal diabetes mellitus (NDM) is a rare form of monogenic diabetes, diagnosed before age 6 months. We aimed to describe the clinical characteristics, molecular genetics, and long-term follow-up of NDM patients from a single pediatric endocrine center in Israel. METHODS: Retrospective study (1975-2020) of all patients diagnosed with diabetes before 6 months of age, who tested negative for pancreatic autoantibodies. Medical records were reviewed for demographic, familial and medical history, and clinical and biochemical features; a genetic analysis was performed. RESULTS: Of 24 patients, nine had transient neonatal diabetes (TNDM) and 15 permanent neonatal diabetes (PNDM), of whom five had rare syndromic causes. Genetic etiology was revealed in 87.5% of the NDM cohort, and the most common causes were ABCC8 mutations in TNDM and KCNJ11 and insulin gene mutations in PNDM. The switch from insulin to off-label sulfonylurea therapy was successful for 5/9 (56%) of the qualifying candidates. Severe hypoglycemia and diabetic ketoacidosis developed in 2 (8%) patients, and chronic diabetes complications in 5 (21%) patients with more than 10 years NDM. At last follow-up, weight and height of all but two syndromic PNDM patients were normal. The median height-SDS of the TNDM subgroup was significantly taller and the mean weight-SDS significantly heavier than those of the PNDM subgroup (-0.52 (-0.67, -0.09) vs. -0.9 (-1.42, -0.3) (p = 0.035) and 0.22 ± 0.69 vs. -0.89 ± 1.21 (p = 0.02), respectively). PNDM patients showed no incremental change in mean weight SDS over the time. CONCLUSION: The Israeli NDM cohort has clinical and genetic characteristics comparable with other populations. Patients with TNDM were taller and heavier than those diagnosed with PNDM, although both show rapid catch-up growth and reached normal growth parameters. Chronic diabetes complications developed in patients with long-standing NDM.

Lived Experience of Advanced Hybrid Closed-Loop Versus Hybrid Closed-Loop: Patient-Reported Outcomes and Perspectives.

This article reports on the lived experience of Medtronic advanced hybrid closed-loop (AHCL) in comparison to first generation hybrid closed-loop (HCL) in a randomized, open-label, two-period crossover trial. Patient-reported outcome (PROs) measures were administered before randomization and at the end of each study period in 113 adolescents and young adults with type 1 diabetes. Glucose monitoring satisfaction subscales for emotional burden and behavioral burden improved significantly (P < 0.01) over time with use of AHCL versus HCL and co-occurred with glycemic improvements (reduced percent time above 180 mg/dL during the day and no change in % time less than 54 mg/dL across 24 h) and greater time in Auto Mode. PROs, including distress, technology attitudes, and hypoglycemia confidence, were not different. AHCL use was associated with improved glucose monitoring satisfaction. Satisfaction was greater in those participants who had more appreciable glycemic benefit and stayed in Auto Mode more often. Clinical Trial Registration number: NCT03040414.

A comparison of two hybrid closed-loop systems in adolescents and young adults with type 1 diabetes (FLAIR): a multicentre, randomised, crossover trial.

BACKGROUND: Management of type 1 diabetes is challenging. We compared outcomes using a commercially available hybrid closed-loop system versus a new investigational system with features potentially useful for adolescents and young adults with type 1 diabetes. METHODS: In this multinational, randomised, crossover trial (Fuzzy Logic Automated Insulin Regulation [FLAIR]), individuals aged 14-29 years old, with a clinical diagnosis of type 1 diabetes with a duration of at least 1 year, using either an insulin pump or multiple daily insulin injections, and glycated haemoglobin (HbA1c) levels of 7·0-11·0% (53-97 mmol/mol) were recruited from seven academic-based endocrinology practices, four in the USA, and one each in Germany, Israel, and Slovenia. After a run-in period to teach participants how to use the study pump and continuous glucose monitor, participants were randomly assigned (1:1) using a computer-generated sequence, with a permuted block design (block sizes of two and four), stratified by baseline HbA1c and use of a personal MiniMed 670G system (Medtronic) at enrolment, to either use of a MiniMed 670G hybrid closed-loop system (670G) or the investigational advanced hybrid closed-loop system (Medtronic) for the first 12-week period, and then participants were crossed over with no washout period, to the other group for use for another 12 weeks. Masking was not possible due to the nature of the systems used. The coprimary outcomes, measured with continuous glucose monitoring, were proportion of time that glucose levels were above 180 mg/dL (>10·0 mmol/L) during 0600 h to 2359 h (ie, daytime), tested for superiority, and proportion of time that glucose levels were below 54 mg/dL (<3·0 mmol/L) calculated over a full 24-h period, tested for non-inferiority (non-inferiority margin 2%). Analysis was by intention to treat. Safety was assessed in all participants randomly assigned to treatment. This trial is registered with ClinicalTrials.gov, NCT03040414, and is now complete. FINDINGS: Between June 3 and Aug 22, 2019, 113 individuals were enrolled into the trial. Mean age was 19 years (SD 4) and 70 (62%) of 113 participants were female. Mean proportion of time with daytime glucose levels above 180 mg/dL (>10·0 mmol/L) was 42% (SD 13) at baseline, 37% (9) during use of the 670G system, and 34% (9) during use of the advanced hybrid closed-loop system (mean difference [advanced hybrid closed-loop system minus 670G system] -3·00% [95% CI -3·97 to -2·04]; p<0·0001). Mean 24-h proportion of time with glucose levels below 54 mg/dL (<3·0 mmol/L) was 0·46% (SD 0·42) at baseline, 0·50% (0·35) during use of the 670G system, and 0·46% (0·33) during use of the advanced hybrid closed-loop system (mean difference [advanced hybrid closed-loop system minus 670G system] -0·06% [95% CI -0·11 to -0·02]; p<0·0001 for non-inferiority). One severe hypoglycaemic event occurred in the advanced hybrid closed-loop system group, determined to be unrelated to study treatment, and none occurred in the 670G group. INTERPRETATION: Hyperglycaemia was reduced without increasing hypoglycaemia in adolescents and young adults with type 1 diabetes using the investigational advanced hybrid closed-loop system compared with the commercially available MiniMed 670G system. Testing an advanced hybrid closed-loop system in populations that are underserved due to socioeconomic factors and testing during pregnancy and in individuals with impaired awareness of hypoglycaemia would advance the effective use of this technology FUNDING: National Institute of Diabetes and Digestive and Kidney Diseases.

Add-on therapy with dapagliflozin under full closed loop control improves time in range in adolescents and young adults with type 1 diabetes: The DAPADream study.

AIM: To investigate the effect of the sodium-glucose co-transporter-2 inhibitor dapagliflozin on glucose levels overnight and during the following day after two unannounced meals under full closed loop (FCL) conditions. MATERIALS AND METHODS: For this single-centre, double-blind, randomized, placebo-controlled, cross-over trial, non-obese persons with type 1 diabetes (T1D) were studied twice (10 mg dapagliflozin bid vs. placebo) for 24 hours with two unannounced mixed meal tests 6 hours apart under FCL conditions. Primary outcome was sensor glucose time in range (TIR; 3.9-10 mmol/L). For safety evaluation, ß-hydroxybutyrate (BHB), glucagon, insulin and gastric inhibitory polypeptide were measured. RESULTS: Fifteen adolescents (aged 15.4 ± 1.6 years, diabetes duration 10.0 ± 3.4 years, HbA1c 8.4% ± 0.9% [67.7 ± 10.1 mmol/mol]) and 15 young adults (aged 18.7 ± 0.8 years; diabetes duration 12.5 ± 3.6 years; HbA1c 8.3% ± 0.9% [68.5 ± 11.2 mmol/mol]) completed the trial. TIR was significantly higher in the intervention group compared with placebo (68% ± 6% vs. 50% ± 13%; P < .001); nocturnal glucose was significantly lower with dapagliflozin (6.2 ± 0.7 vs. 7.3 ± 1.7 mmol/L; P = .003) without an increase in time at less than 3.9 mmol/L (3.3% ± 6.0% vs 3.1% ± 5.2%; P = .75). Urinary glucose excretion was increased 3-fold using dapagliflozin (149 ± 42 vs. 49 ± 23 g/24 hours) with a total insulin reduction of 22% (39.7 ± 12.7 vs. 30.6 ± 10.4 U; P = .004). No abnormal elevated BHB values were observed. CONCLUSIONS: In adolescents and adults with T1D, dapagliflozin significantly increased TIR on average by 259 minutes/day while reducing glycaemic variability during FCL control without any signs of hypoglycaemia or ketosis.

Feasibility Study of a Hybrid Closed-Loop System with Automated Insulin Correction Boluses.

Background: The Medtronic MiniMed™ 670G system adjusts basal insulin delivery in response to continuous glucose monitoring levels and is already in use in clinical practice. We tested the home-based feasibility of the new MiniMed advanced hybrid closed-loop (AHCL) system, which includes several algorithm enhancements and an optional autocorrection bolus mode. Methods: Twelve adolescents and young adults (eight females) with type 1 diabetes [median (interquartile range)] aged 16.6 (15.9, 18.2) years and diabetes duration of 7.1 (4.7, 8.8) years] participated in this single-arm study. The first stage was a 6-day open-loop run-in period, with the predictive low-glucose suspend feature on. This was followed by 6 days/5 nights in a supervised hotel setting, using the AHCL system, including closed-loop challenges (missed meal bolus, late meal bolus, and physical activity); and finally, 3 weeks with unrestricted home use. Glycemic parameters were compared between the open-loop and closed-loop periods. Results: Participants spent 93.3% (4.7) of the time in SmartGuard™ Auto Mode. Hemoglobin A1C levels decreased from median (interquartile range) 7.1% (6.7, 7.9) at baseline to 6.8% (6.6, 7.4) at study end, after 4 weeks (P = 0.0027). Time in range (TIR) (70-180 mg/dL) was 68.4% (10.6) and time below 70 mg/dL was 4% (3.5) during open-loop; and 74% (6.1) and 2.6% (1.9), respectively, during the closed-loop at home phase (P = 0.06, P = 0.27). TIR increased during the nighttime, from 64.6% (17.4) to 80.7% (7.8), P = 0.007, without change in time below 70 mg/dL (P = 0.15). No serious adverse events occurred. Conclusions: The new AHCL system demonstrated safety and effectiveness in controlling day and night glucose levels.