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OBJECTIVE While continuous glucose monitors (CGMs), insulin pumps, and hybrid closed-loop (HCL) systems each improve glycemic control in type 1 diabetes, it is unclear how the use of these technologies impacts real-world pediatric care. RESEARCH DESIGN AND METHODS We found 1,455 patients aged 3 months, and who had data from a single center in between both 2016–2017 (n = 2,827) and 2020–2021 (n = 2,731). Patients were grouped by multiple daily injections or insulin pump, with or without an HCL system, and using a blood glucose monitor or CGM. Glycemic control was compared using linear mixed-effects models adjusting for age, diabetes duration, and race/ethnicity. RESULTS CGM use increased from 32.9 to 75.3%, and HCL use increased from 0.3 to 27.9%. Overall A1C decreased from 8.9 to 8.6% (P < 0.0001). CONCLUSIONS Adoption of CGM and HCL was associated with decreased A1C, suggesting promotion of these technologies may yield glycemic benefits.

The incidence of type 1 diabetes (T1D) is rising in all age groups. T1D is associated with chronic microvascular and macrovascular complications but improving glycemic trends can delay the onset and slow the progression of these complications. Utilization of technological devices for diabetes management, such as continuous glucose monitors (CGM) and insulin pumps, is increasing, and these devices are associated with improvements in glycemic trends. Thus, device use may be associated with long-term prevention of T1D complications, yet few studies have investigated the direct impacts of devices on chronic complications in T1D. This review will describe common diabetes devices and combination systems, as well as review relationships between device use and cardiovascular outcomes in T1D.Findings from existing cohort and national registry studies suggest that pump use may aid in improving cardiovascular risk factors such as hypertension and dyslipidemia. Furthermore, pump users have been shown to have lower arterial stiffness and better measures of myocardial function. In registry and case-control longitudinal data, pump use has been associated with fewer cardiovascular events and reduction of cardiovascular disease (CVD) and all-cause mortality. CVD is the leading cause of morbidity and mortality in T1D. Consistent use of diabetes devices may protect against the development and progression of macrovascular complications such as CVD through improvement in glycemic trends. Existing literature is limited, but findings suggest that pump use may reduce acute cardiovascular risk factors as well as chronic cardiovascular complications and overall mortality in T1D.

Combining technologies including rapid insulin analogs, insulin pumps, continuous glucose monitors, and control algorithms has allowed for the creation of automated insulin delivery (AID) systems. These systems have proven to be the most effective technology for optimizing metabolic control and could hold the key to broadly achieving goal-level glycemic control for people with type 1 diabetes. The use of AID has exploded in the past several years with several options available in the United States and even more in Europe. In this article, we review the largest studies involving these AID systems, and then examine future directions for AID with an emphasis on usability.

Objective While continuous glucose monitors (CGM), insulin pumps, and hybrid-closed-loop (HCL) systems each improve glycemic control in type 1 diabetes, it is unclear how use of these technologies impact real-world pediatric care. Research Design and Methods Of patients 3 months at a single center in 2016-2017 (n=2827) and 2020-2021 (n=2731), 1455 had data in both time periods. Patients were grouped by multiple daily injections (MDI) or insulin pump with or without HCL and using a blood glucose monitor or CGM. Glycemic control was compared using linear mixed effects models adjusting for age, diabetes duration, and race/ethnicity. Results CGM use increased from 32.9% to 75.3%; HCL increased from 0.3% to 27.9%. Overall A1C decreased from 8.9% to 8.6% (p Conclusions Adoption of CGM and HCL was associated with decreased A1C, suggesting promotion of these technologies may yield glycemic benefits.

BACKGROUND: Technology for patients with type 1 diabetes (T1D), including continuous glucose monitoring (CGM), insulin pumps, and hybrid closed-loop (HCL) systems, is improving, being used more commonly in the pediatric population, and impacts glycemic control. MATERIALS AND METHODS: We evaluated the use of these technologies and their impact on glycemic control among patients with T1D who were seen at the Barbara Davis Center (n = 4003) between January 2018 and December 2020, 3 months. Data were analyzed by age group and technology-use group defined as multiple daily injection with blood glucose meter (MDI/BGM), pump with BGM (pump/BGM), MDI with CGM (MDI/CGM), and pump with CGM (pump/CGM). Glycemic control was compared using analysis of covariance (ANCOVA) and controlling for diabetes duration, race, and insurance. RESULTS: Among 4003 patients, 20% used MDI/BGM (mean hemoglobin A1c [HbA1c] = 10.0%); 14.4% used pump/BGM (mean HbA1c = 10.0%); 15.4% used MDI/CGM (mean HbA1c = 8.6%); and 49.8% used pump/CGM (mean HbA1c = 8.1%). Compared with MDI/BGM patients, MDI/CGM and pump/CGM users had a lower HbA1c and were more likely to reach an HbA1c

Automated insulin delivery (AID) systems, which connect an insulin pump, continuous glucose monitoring system, and software algorithm to automate insulin delivery based on real-time glycemic data, hold promise for improving outcomes and reducing therapeutic burden for people with diabetes. This article reviews the features of the Omnipod 5 Automated Insulin Delivery System and how it compares to other AID systems available on or currently under review for the U.S. market. It also provides practical guidance for clinicians on how to effectively train and onboard people with diabetes on the Omnipod 5 System, including how to personalize therapy and optimize glycemia. Many people with diabetes receive their diabetes care in primary care settings rather than in a diabetes specialty clinic. Therefore, it is important that primary care providers have access to resources to support the adoption of AID technologies such as the Omnipod 5 System.

Despite evidence of improved diabetes outcomes with diabetes technology such as continuous glucose monitoring (CGM) systems, insulin pumps, and hybrid closed-loop (HCL) insulin delivery systems, these devices are underutilized in clinical practice for the management of insulin-requiring diabetes. This low uptake may be the result of health care professionals’ (HCPs’) lack of confidence or time to prescribe and manage devices for people with diabetes. We administered a survey to HCPs in primary care, pediatric endocrinology, and adult endocrinology practices in the United States. Responding HCPs expressed a need for device-related insurance coverage tools and online data platforms with integration to electronic health record systems to improve diabetes technology uptake in these practice settings across the United States.

Background Hybrid Closed Loop (HCL) systems aid individuals with type 1 diabetes in improving glycemic control, however, sustained use over time has not been consistent for all users. This study developed and validated prognostic models for successful 12-month use of the first commercial HCL system based on baseline and 1-month or 3-month data. Methods and materials Data from participants at the Barbara Davis Center (N=85) who began use of the MiniMed 670G HCL were used to develop prognostic models using logistic regression and Lasso model selection. Candidate factors included sex, age, duration of diabetes, baseline HbA1c, race, ethnicity, insurance status, history of insulin pump and continuous glucose monitor use, 1-month or 3-month Auto Mode use, boluses per day, and time in range (70-180 mg/dL; TIR), and scores on behavioral questionnaires. Successful use of HCL was predefined as Auto Mode use ≥60%. The 3-month model was then externally validated against a sample from Stanford University (N=55). Results Factors in the final model included baseline HbA1c, sex, ethnicity, 1-month or 3-month Auto Mode use, Boluses per Day, and TIR. The 1-month and 3-month prognostic models had very good predictive ability with area under the curve values of 0.894 and 0.900, respectively. External validity was acceptable with an area under the curve of 0.717. Conclusions Our prognostic models use clinically accessible baseline and early device-use factors to identify risk for failure to succeed with 670G HCL technology. These models may be useful to develop targeted interventions to promote success with new technologies.

Background. Adolescents and young adults with type 1 diabetes have high HbA1c levels and often struggle with self-management behaviors and attention to diabetes care. Hybrid closed-loop systems (HCL) like the t:slim X2 with Control-IQ technology (Control-IQ) can help improve glycemic control. The purpose of this study is to assess adolescents’ situational awareness of their glucose control and engagement with the Control-IQ system to determine significant factors in daily glycemic control. Methods. Adolescents (15–25 years) using Control-IQ participated in a 2-week prospective study, gathering detailed information about Control-IQ system engagements (boluses, alerts, and so on) and asking the participants’ age and gender about their awareness of glucose levels 2-3 times/day without checking. Mixed models assessed which behaviors and awareness items correlated with time in range (TIR, 70–180 mg/dl, 3.9–10.0 mmol/L). Results. Eighteen adolescents/young adults (mean age 18 ± 1.86 years and 86% White non-Hispanic) completed the study. Situational awareness of glucose levels did not correlate with time since the last glucose check ( p = 0.8 ). In multivariable modeling, lower TIR was predicted on days when adolescents underestimated their glucose levels (r = −0.22), received more CGM alerts (r = −0.31), and had more pump engagements (r = −0.27). A higher TIR was predicted when adolescents responded to CGM alerts (r = 0.20) and entered carbohydrates into the bolus calculator (r = 0.49). Conclusion. Situational awareness is an independent predictor of TIR and may provide insight into patterns of attention and focus that could positively influence glycemic outcomes in adolescents. Proactive engagements predict better TIR, whereas reactive engagement predicted lower TIR. Future interventions could be designed to train users to develop awareness and expertise in effective diabetes self-management.

Highly variable insulin sensitivity, susceptibility to hypoglycemia and inability to effectively communicate hypoglycemic symptoms pose significant challenges for young children with type 1 diabetes (T1D). Herein, outcomes during clinical MiniMed™ 670G system use were evaluated in children aged 2-6 years with T1D.Participants (N = 46, aged 4.6 ± 1.4 years) at seven investigational centers used the MiniMed™ 670G system in Manual Mode during a two-week run-in period followed by Auto Mode during a three-month study phase. Safety events, mean A1C, sensor glucose (SG), and percentage of time spent in (TIR, 70-180 mg/dl), below (TBR,70 mg/dl) and above (TAR,180 mg/dl) range were assessed for the run-in and study phase and compared using a paired t-test or Wilcoxon signed-rank test.From run-in to end of study (median 87.1% time in auto mode), mean A1C and SG changed from 8.0 ± 0.9% to 7.5 ± 0.6% (p 0.001) and from 173 ± 24 to 161 ± 16 mg/dl (p 0.001), respectively. Overall TIR increased from 55.7 ± 13.4% to 63.8 ± 9.4% (p 0.001), while TBR and TAR decreased from 3.3 ± 2.5% to 3.2 ± 1.6% (p = 0.996) and 41.0 ± 14.7% to 33.0 ± 9.9% (p 0.001), respectively. Overnight TBR remained unchanged and TAR was further improved 12:00 am-6:00 am. Throughout the study phase, there were no episodes of severe hypoglycemia or diabetic ketoacidosis (DKA) and no serious adverse device-related events.At-home MiniMed™ 670G Auto Mode use by young children safely improved glycemic outcomes compared to two-week open-loop Manual Mode use. The improvements are similar to those observed in older children, adolescents and adults with T1D using the same system for the same duration of time.

Background: Cgmanalysis is open-source software based on the R programming language for data management and descriptive analysis of data from continuous glucose monitors (CGM). We sought to validat...

Objective: To describe real-world outcomes for youth using the Tandem t:slim X2 insulin pump with Control-IQ technology (“Control-IQ”) for 6 months at a large pediatric clinic. Methods: Youth with type 1 diabetes, who started Control-IQ for routine care, were prospectively followed. Data on system use and glycemic control were collected before Control-IQ start, and at 1, 3, and 6 months after start. Mixed models assessed change across time; interactions with baseline hemoglobin A1c (HbA1c) and age were tested. Results: In 191 youth (median age 14, 47% female, and median HbA1c 7.6%), percent time with glucose levels 70–180 mg/dL (time-in-range [TIR]) improved from 57% at baseline to 66% at 6 months (P 70%) doubled from 23.5% at baseline to 47.8% at 3 months, sustaining at 46.7% at 6 months (P

Numerous studies have demonstrated the clinical value and safety of insulin pump therapy in type 1 diabetes and type 2 diabetes populations. However, the eligibility criteria for insulin pump coverage required by the Centers for Medicare & Medicaid Services (CMS) discount conclusive evidence that supports insulin pump use in diabetes populations that are currently deemed ineligible. This article discusses the limitations and inconsistencies of the insulin pump eligibility criteria relative to current scientific evidence and proposes workable solutions to address this issue and improve the safety and care of all individuals with diabetes.

OBJECTIVE Advances in diabetes technology have transformed the treatment paradigm for type 1 diabetes, yet the burden of disease is significant. We report on a pivotal safety study of the first tubeless, on-body automated insulin delivery system with customizable glycemic targets. RESEARCH DESIGN AND METHODS This single-arm, multicenter, prospective study enrolled 112 children (age 6–13.9 years) and 129 adults (age 14–70 years). A 2-week standard therapy phase (usual insulin regimen) was followed by 3 months of automated insulin delivery. Primary safety outcomes were incidence of severe hypoglycemia and diabetic ketoacidosis. Primary effectiveness outcomes were change in HbA1c and percent time in sensor glucose range 70–180 mg/dL (“time in range”). RESULTS A total of 235 participants (98% of enrolled, including 111 children and 124 adults) completed the study. HbA1c was significantly reduced in children by 0.71% (7.8 mmol/mol) (mean ± SD: 7.67 ± 0.95% to 6.99 ± 0.63% [60 ± 10.4 mmol/mol to 53 ± 6.9 mmol/mol], P < 0.0001) and in adults by 0.38% (4.2 mmol/mol) (7.16 ± 0.86% to 6.78 ± 0.68% [55 ± 9.4 mmol/mol to 51 ± 7.4 mmol/mol], P < 0.0001). Time in range was improved from standard therapy by 15.6 ± 11.5% or 3.7 h/day in children and 9.3 ± 11.8% or 2.2 h/day in adults (both P < 0.0001). This was accomplished with a reduction in time in hypoglycemia CONCLUSIONS This tubeless automated insulin delivery system was safe and allowed participants to significantly improve HbA1c levels and time in target glucose range with a very low occurrence of hypoglycemia.

Background: The objective of this study was to assess the safety and effectiveness of the first commercial configuration of a tubeless automated insulin delivery system, Omnipod® 5, in children (6–13.9 years) and adults (14–70 years) with type 1 diabetes (T1D) in an outpatient setting. Materials and Methods: This was a single-arm, multicenter, prospective clinical study. Data were collected over a 14-day standard therapy (ST) phase followed by a 14-day hybrid closed-loop (HCL) phase, where participants (n = 36) spent 72 h at each of three prespecified glucose targets (130, 140, and 150 mg/dL, 9 days total) then 5 days with free choice of glucose targets (110–150 mg/dL) using the Omnipod 5. Remote safety monitoring alerts were enabled during the HCL phase. Primary endpoints were difference in time in range (TIR) (70–180 mg/dL) between ST and HCL phases and proportion of participants reporting serious device-related adverse events. Results: Mean TIR was significantly higher among children in the free-choice period overall (64.9% ± 12.2%, P

Background: Data are limited on the need for and benefits of pump setting optimization with automated insulin delivery. We examined clinical management of a closed-loop control (CLC) system and its relationship to glycemic outcomes. Materials and Methods: We analyzed personal parameter adjustments in 168 participants in a 6-month multicenter trial of CLC with Control-IQ versus sensor-augmented pump (SAP) therapy. Preset parameters (BR = basal rates, CF = correction factors, CR = carbohydrate ratios) were optimized at randomization, 2 and 13 weeks, for safety issues, participant concerns, or initiation by participants' usual diabetes care team. Time in range (TIR 70–180 mg/dL) was compared in the week before and after parameter changes. Results: In 607 encounters for parameter changes, there were fewer adjustments for CLC than SAP (3.4 vs. 4.1/participant). Adjustments involved BR (CLC 69%, SAP 80%), CR (CLC 68%, SAP 50%), CF (CLC 44%, SAP 41%), and overnight parameters (CLC 62%, SAP 75%). TIR before and after adjustments was 71.2% and 71.3% for CLC and 61.0% and 62.9% for SAP. The highest baseline HbA(1c) CLC subgroup had the largest TIR improvement (51.2% vs. 57.7%). When a CR was made more aggressive in the CLC group, postprandial time >180 mg/dL was 43.1% before the change and 36.0% after the change. The median postprandial time

The publisher of Diabetes TechnologiesTherapeutics officially withdraws the Just Accepted version of the article entitled, "Positive Impact of the Bionic Pancreas on Diabetes Control in Youth 6-17 Years Old with Type 1 Diabetes: A Multicenter Randomized Trial," by Laurel H Messer, et al. (epub 28 Jun 2022; DOI: 10.1089/dia.2022.0201) due to its erroneous release before being finalized. The correct version will be republished in due course. The publisher extends its sincerest apologies to the authors of the article and to the journal's readership for this regrettable mishap.

Objective: Very young children with type 1 diabetes often struggle to achieve glycemic targets, putting them at risk of long-term complications and creating an immense management burden for caregivers. We conducted the first evaluation of the Omnipod® 5 Automated Insulin Delivery (AID) System in this population. Research Design and Methods: Eighty children aged 2-5.9 years used the investigational system in a single-arm study for 13 weeks following 14 days of baseline data collection with their usual therapy. Results: There were no episodes of severe hypoglycemia (SH) or diabetic ketoacidosis (DKA). By study end, HbA1c decreased by 0.55% (6.0mmol/mol) (p Conclusions: Use of the AID system was safe, and participants experienced improved glycemic measures and reduced hypoglycemia during the study phase compared with baseline.

Purpose: To understand the relative importance of support tools for HCPs to increase engagement with diabetes devices Methods: Primary care, pediatric and adult endocrinology HCPs completed an online survey assessing their comfort with continuous glucose monitors, connected insulin pens, insulin pumps, hybrid closed-loop systems, and their perceived needs for support tools. Hypothetical tools were described and Visual Analog Scales (VAS) (0 to 100) were used to "indicate how useful each tool would be in clinical practice." Results: 113 primary care HCPs (mean 16.3±10.1 yrs in practice) , 84 adult endocrinology HCPs (10.7±9.2 yrs in practice) , and 34 pediatric endocrinology HCPs (13.6±12.2 yrs in practice) completed the survey. A tool that assists in determining patients' insurance coverage for devices was ranked with the highest median score for all HCP types (VAS score: 90, 99, 95/100 respectively) , followed by an Online Data Platform to access device information (85, 88, 91.5/100) [Figure]. HCPs additionally indicated the importance of device data integration into an electronic health record (EHR) (83, 87.5, 82/100) , support tool accessibility from the EHR (79.5, 71, 75/100) , and device information communication to patients via EHR (78, 73.5, 75/100) . Conclusion: HCPs from 3 disciplines highlighted the need for clinical tools to work with diabetes devices in clinical practice, with particular interest in insurance aid and data platform. Disclosure L. H. Messer: Consultant; Capillary Biomedical, Inc., Dexcom, Inc., Tandem Diabetes Care, Inc., Research Support; Beta Bionics, Inc., Dexcom, Inc., Insulet Corporation, Medtronic. L. Pyle: None. V. Shah: Advisory Panel; Medscape, Sanofi, Consultant; Dexcom, Inc., Research Support; Dexcom, Inc., Eli Lilly and Company, Insulet Corporation, Novo Nordisk. R. Wadwa: Advisory Panel; Dompé, Consultant; Beta Bionics, Inc., Other Relationship; Tandem Diabetes Care, Inc., Research Support; Dexcom, Inc., Eli Lilly and Company, Tandem Diabetes Care, Inc. T. Oser: Advisory Panel; Cecelia Health, Dexcom, Inc. T. B. Vigers: None. H. K. Akturk: Research Support; Dexcom, Inc., Eli Lilly and Company, REMD Biotherapeutics. G. P. Forlenza: Advisory Panel; Lilly, Medtronic, Consultant; Dexcom, Inc., Insulet Corporation, Tandem Diabetes Care, Inc., Research Support; Dexcom, Inc., Insulet Corporation, Medtronic, Tandem Diabetes Care, Inc. K. B. Huss: None. A. J. Karami: None. E. Malecha: None. S. Oser: Advisory Panel; Cecelia Health, Children with Diabetes, Inc., Dexcom, Inc., Consultant; American Diabetes Association, Association of Diabetes Care & Education Specialists, Jaeb Center for Health Research, Research Support; American Academy of Family Physicians, Leona M. and Harry B. Helmsley Charitable Trust. S. Polsky: Advisory Panel; Medtronic, Other Relationship; diaTribe, Research Support; Dexcom, Inc., Eli Lilly and Company, Leona M. and Harry B. Helmsley Charitable Trust, Medtronic, National Institute of Diabetes and Digestive and Kidney Diseases, Sanofi-Aventis U. S. Funding The Leona M. and Harry B. Helmsley Charitable Trust (G-2206-05306)

Background: We investigated the potential benefits of automated insulin delivery (AID) among individuals with type 1 diabetes (T1D) in sub-populations of baseline device use determined by continuous glucose monitor (CGM) use status and insulin delivery via multiple daily injections (MDI) or insulin pump. Materials and Methods: In a six-month randomized, multicenter trial, 168 individuals were assigned to closed-loop control (CLC, Control-IQ, Tandem Diabetes Care), or sensor-augmented pump (SAP) therapy. The trial included a two- to eight-week run-in phase to train participants on study devices. The participants were stratified into four subgroups: insulin pump and CGM (pump+CGM), pump-only, MDI and CGM (MDI+CGM), and MDI users without CGM (MDI-only) users. We compared glycemic outcomes among four subgroups. Results: At baseline, 61% were pump+CGM users, 18% pump-only users, 10% MDI+CGM users, and 11% MDI-only users. Mean time in range 70-180 mg/dL (TIR) improved from baseline in the four subgroups using CLC: pump+CGM, 62% to 73%; pump-only, 61% to 70%; MDI+CGM, 54% to 68%; and MDI-only, 61% to 69%. The reduction in time below 70 mg/dL from baseline was comparable among the four subgroups. No interaction effect was detected with baseline device use for TIR ( P = .67) or time below ( P = .77). On the System Usability Questionnaire, scores were high at 26 weeks for all subgroups: pump+CGM: 87.2 ± 12.1, pump-only: 89.4 ± 8.2, MDI+CGM 87.2 ± 9.3, MDI: 78.1 ± 15. Conclusions: There was a consistent benefit in patients with T1D when using CLC, regardless of baseline insulin delivery modality or CGM use. These data suggest that this CLC system can be considered across a wide range of patients.

Background: Pediatric patients undergoing hematopoietic stem cell transplantation (HSCT) may be at risk for malglycemia and adverse outcomes, including infection, prolonged hospital stays, organ dysfunction, graft-versus-host-disease, delayed hematopoietic recovery, and increased mortality. Continuous glucose monitoring (CGM) may aid in describing and treating malglycemia in this population. However, no studies have demonstrated safety, tolerability, or accuracy of CGM in this uniquely immunocompromised population. Materials and Methods: A prospective observational study was conducted, using the Abbott Freestyle Libre Pro, in patients aged 2–30 undergoing HSCT at Children's Hospital Colorado to evaluate continuous glycemia in this population. CGM occurred up to 7 days before and 60 days after HSCT, during hospitalization only. In a secondary analysis of this data, blood glucoses collected during routine HSCT care were compared with CGM values to evaluate accuracy. Adverse events and patient refusal to wear CGM device were monitored to assess safety and tolerability. Results: Participants (n = 29; median age 13.1 years, [interquartile range] [4.7, 16.6] years) wore 84 sensors for an average of 25 [21.5, 30.0] days per participant. Paired serum-sensor values (n = 893) demonstrated a mean absolute relative difference of 20% ± 14% with Clarke Error Grid analysis showing 99% of pairs in the clinically acceptable Zones (A+B). There were four episodes of self-limited bleeding (4.8% of sensors); no other adverse events occurred. Six patients (20.7%) refused subsequent CGM placements. Conclusions: CGM use appears safe and feasible although with suboptimal accuracy in the hospitalized pediatric HSCT population. Few adverse events occurred, all of which were low grade.

Background: The purpose of this study was to develop and test a new Clinic Tool to assist health care professionals with clinical care of persons with diabetes using the Control-IQ system. Methods: A Clinic Tool was iteratively developed with input from diabetes clinicians, which outlined a systematic process for assessing data, reviewing insulin settings, providing education, and documenting the encounter. Diabetes clinicians were recruited to trial the Clinical Tool in up to five clinical encounters (in-person, telehealth, or telephone). Quantitative surveys and free-text responses, including a knowledge quiz and the System Usability Scale (SUS), were administered to determine clinician satisfaction, confidence, knowledge, and implications for practice. Results: Twenty-nine clinicians (43% endocrinologists, mean 10.7 years in practice) enrolled in the study and completed 89 encounters using the Control-IQ Clinic Tool. Participants spent an average of 10 minutes using the Tool and reported excellent SUS scores within the 90%-95% percentile for usability. Knowledge quiz scores increased in 42% of participants. Both familiarity with Control-IQ and confidence providing clinical care to Control-IQ users significantly improved ( P = .009 and P < .001 respectively). Ninety percent of participants agreed that the Tool will change their clinical care going forward. Conclusion: The Control-IQ Clinical Tool is highly usable and impacted clinical care delivery to Control-IQ users. Tools that serve to improve clinician confidence in delivery of care to diabetes device users should be expanded, leveraged, and studied to assess the impact on adherence and glycemic control for persons with diabetes.

To evaluate psychosocial outcomes for adults with type 1 diabetes (T1D) using the tubeless Omnipod® 5 Automated Insulin Delivery (AID) System.A single-arm, multicenter (across the United States), prospective safety and efficacy study of the tubeless AID system included 115 adults with T1D. Participants aged 18-70 years completed questionnaires assessing psychosocial outcomes - diabetes distress (T1-DDS), hypoglycemic confidence (HCS), well-being (WHO-5), sleep quality (PSQI), insulin delivery satisfaction (IDSS), diabetes treatment satisfaction (DTSQ), and system usability (SUS) - before and after 3 months of AID use. Associations among participant characteristics, psychosocial measures and glycemic outcomes were evaluated using linear regression analyses.Adults using the tubeless AID system demonstrated improvements in diabetes-specific psychosocial measures, including diabetes distress, hypoglycemic confidence, insulin delivery satisfaction, diabetes treatment satisfaction, and system usability after 3 months (all P 0.001). No changes in general well-being or sleep quality were observed. The psychosocial outcomes assessed were not consistently associated with baseline participant characteristics (i.e., age, sex, diabetes duration, glycemic outcomes including percent time in range 70-180 mg/dL, percent time below range 70 mg/dL, hemoglobin A1c, or insulin regimen).Use of the Omnipod 5 AID system was associated with significant improvements in diabetes-related psychosocial outcomes for adults with T1D.NCT04196140.

Insulin pumps are commonly used for intensive insulin therapy to treat type 1 diabetes in adults and youth. Insulin pump technologies have advanced dramatically in the last several years to integrate with continuous glucose monitors (CGM) and incorporate control algorithms. These control algorithms automate some insulin delivery in response to the glucose information received from the CGM to reduce the occurrence of hypoglycemia and hyperglycemia and improve overall glycemic control. The t:slim X2 insulin pump system became commercially available in 2016. It is an innovative insulin pump technology that can be updated remotely by the user to install new software onto the pump device as new technologies become available. Currently, the t:slim X2 pairs with the Dexcom G6 CGM and there are two advanced software options available: Basal-IQ, which is a predictive low glucose suspend (PLGS) technology, and Control-IQ, which is a Hybrid Closed Loop (HCL) technology. This paper will describe the different types of advanced insulin pump technologies, review how the t:slim X2 insulin pump works, and summarize the clinical studies leading to FDA approval and commercialization of the Basal-IQ and Control-IQ technologies.

Background: We determined the uptake rate of continuous glucose monitors (CGMs) and examined associations of clinical and demographic characteristics with CGM use among patients with type 1 diabetes covered by Colorado Medicaid during the first two years of CGM coverage with no out-of-pocket cost. Method: We retrospectively reviewed data from 892 patients with type 1 diabetes insured by Colorado Medicaid (Colorado Health Program [CHP] and CHP+, Colorado Medicaid expansion). Demographics, insulin pump usage, CGM usage, and hemoglobin A1c (A1c) were extracted from the medical record. Data downloaded into CGM software at clinic appointments were reviewed to determine 30-day use prior to appointments. Subjects with some exposure to CGM were compared to subjects never exposed to CGM, and we examined the effect of CGM use on glycemic control. Results: Twenty percent of subjects had some exposure to CGM with a median of 22 [interquartile range 8, 29] days wear. Sixty one percent of CGM users had >85% sensor wear. Subjects using CGM were more likely to be younger ( P < .001), have shorter diabetes duration ( P < .001), and be non-Hispanic White ( P < .001) than nonusers. After adjusting for age and diabetes duration, combined pump and CGM users had a lower A1c than those using neither technology ( P = .006). Lower A1c was associated with greater CGM use ( P = .002) and increased percent time in range ( P < .001). Conclusion: Pediatric Medicaid patients successfully utilized CGM. Expansion of Medicaid coverage for CGM may help improve glycemic control and lessen disparities in clinical outcomes within this population.

Background: The objective of this study was to assess the safety and performance of the Omnipod® personalized model predictive control (MPC) algorithm in adults, adolescents, and children aged ≥6 years with type 1 diabetes (T1D) under free-living conditions using an investigational device. Materials and Methods: A 96-h hybrid closed-loop (HCL) study was conducted in a supervised hotel/rental home setting following a 7-day outpatient standard therapy (ST) phase. Eligible participants were aged 6–65 years with A1C

Objective To describe glycemic and psychosocial outcomes in youth with type 1 diabetes using a hybrid closed loop (HCL) system. Subjects Youth with type 1 diabetes (2-25 years) starting the 670G HCL system for their diabetes care were enrolled in an observational study. Methods Prospective data collection occurred during routine clinical care and included glycemic variables (sensor time in range [70-180 mg/dL], HbA1c), and psychosocial variables (Hypoglycemia Fear Survey [HFS]; Problem Areas in Diabetes [PAID]). Mixed models were used to analyze change across time. Results Ninety-two youth (mean age 15.7 ± 3.6 years, 50% female, HbA1c 8.8% ± 1.8%) started HCL for their diabetes care. Youth used Auto Mode 65.5% ± 3.0% of the time at month 1, which decreased to 51.2% ± 3.4% at month 6 (P = .001). Sensor time in range increased from 50.7% ± 1.8% at baseline to 56.9% ± 2.1% at 6 months (P = .007). HbA1c decreased from 8.7% ± 0.2% at baseline to 8.4% ± 0.2% after 6 months of use (P ≤ .0001), with the greatest HbA1c decline in participants with high baseline HbA1c. Increased percent time in auto mode was associated with lower HbA1c (P = .02). Thirty percent of youth discontinued HCL in the first 6 months of use. There were no changes in the HFS or PAID scores across time. Conclusions HCL use is associated with improved glycemic control and no change in psychosocial outcomes in this clinical sample. The decline in HCL use across time suggests that youth experience barriers in sustaining use of HCL. Further research is needed to understand reasons for HCL discontinuation and determine intervention strategies.

Numerous studies have demonstrated the clinical value of continuous glucose monitoring (CGM) in type 1 diabetes (T1D) and type 2 diabetes (T2D) populations. However, the eligibility criteria for CGM coverage required by the Centers for Medicare & Medicaid Services (CMS) ignore the conclusive evidence that supports CGM use in various diabetes populations that are currently deemed ineligible. In an earlier article, we discussed the limitations and inconsistencies of the agency’s CGM eligibility criteria relative to current scientific evidence and proposed practice solutions to address this issue and improve the safety and care of Medicare beneficiaries with diabetes. Although Medicaid is administered through CMS, there is no consistent Medicaid policy for CGM coverage in the United States. This article presents a rationale for modifying and standardizing Medicaid CGM coverage eligibility across the United States.

The Omnipod 5 System is a novel hybrid closed-loop (HCL) system with full on-body operation. A tubeless insulin pump containing a personalized MPC algorithm communicates directly with a Dexcom G6 CGM to automate insulin delivery. Following demonstration of positive safety and efficacy in older children (≥6y) and adults, we evaluated the system in very young children (2-5.9y) with T1D. Preschoolers with T1D often have erratic eating behaviors and may dislike being tethered to devices, and parental concern may lead to permissive hyperglycemia. This HCL system may be ideal for young children, given its customizable glucose targets from 110-150mg/dL, wireless system interaction through a mobile application, and bolus calculator that incorporates CGM trend information. Also, the system has no minimum weight or total daily dose (TDD) requirement. Participants with T1D and A1C180mg/dL was 39.4±16.5%, and ≥250mg/dL was 14.7±12.0%. The same efficacy analysis is planned for the 3-month HCL phase upon its completion in January 2021. This multi-center pivotal study has, to date, demonstrated safety of the Omnipod 5 System in very young children with T1D. At completion, this will be the largest study of HCL in this age group reported to date. Disclosure J. Sherr: Advisory Panel; Self; Cecelia Health, Insulet Corporation, Medtronic, Consultant; Self; Insulet Corporation, Lexicon Pharmaceuticals, Inc., Lilly Diabetes, Medtronic, Research Support; Self; Dexcom, Inc., Insulet Corporation, Medtronic, Speaker’s Bureau; Self; Lilly Diabetes. D. W. Hansen: None. T. T. Ly: Employee; Self; Insulet Corporation. Omnipod 5 in preschoolers study group: n/a. B. W. Bode: Advisory Panel; Self; Eli Lilly and Company, Consultant; Self; Bigfoot Biomedical, Inc., Companion Medical, Lexicon Pharmaceuticals, Inc., Medtronic, Novo Nordisk Inc., Zealand Pharma A/S, Research Support; Self; Abvance Therapeutics, Dexcom, Inc., Diasome Pharmaceuticals, Inc., Dompe, Eli Lilly and Company, Eyenuk, Inc., Insulet Corporation, Jaeb Center for Health Research, Medtronic, Nova Biomedical, Novo Nordisk, Provention Bio, Inc., REMD Biotherapeutics, Sanofi, Senseonics, Viacyte, Inc., vTv Therapeutics, Xeris Pharmaceuticals, Inc., Speaker’s Bureau; Self; AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Eli Lilly and Company, MannKind Corporation, Medtronic, Novo Nordisk, Sanofi, Stock/Shareholder; Self; AgaMatrix, Aseko, Inc., Glytec, LLC. G. P. Forlenza: Advisory Panel; Self; Medtronic, Consultant; Self; Beta Bionics, Inc., Dexcom, Inc., Insulet Corporation, Tandem Diabetes Care, Research Support; Self; Abbott Diabetes, Dexcom, Inc., Insulet Corporation, Medtronic, Tandem Diabetes Care. L. M. Laffel: Consultant; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Dexcom, Inc., Dompe, Insulogic LLC, Janssen Pharmaceuticals, Inc., Laxmi Therapeutic Devices, LifeScan, Lilly Diabetes, Medtronic, Provention Bio, Inc. S. A. Brown: Research Support; Self; Dexcom, Inc., Insulet Corporation, Roche Diabetes Care, Tandem Diabetes Care, Tolerion, Inc. B. A. Buckingham: Advisory Panel; Self; Medtronic, Tolerion, Inc., Research Support; Self; Beta Bionics, Inc., Insulet Corporation, Medtronic, Tandem Diabetes Care. A. B. Criego: Consultant; Self; Bigfoot Biomedical, Inc., Other Relationship; Self; Sanofi, Research Support; Self; Abbott Diabetes, Eli Lilly and Company, Insulet Corporation, Medtronic. D. Desalvo: Consultant; Self; Insulet Corporation, Research Support; Self; Insulet Corporation, Speaker’s Bureau; Self; Dexcom, Inc. S. A. Macleish: Advisory Panel; Self; Insulet Corporation. Funding Insulet Corporation

Safe and effective use of the Omnipod 5 System was demonstrated in adults and children with type 1 diabetes (T1D) during a 3-month pivotal study. Longer studies are needed to evaluate durability of glycemic benefit. Those completing the pivotal study were invited to continue system use for an additional 12 months, with 95% enrolling in the extension. We present results from the first 3-month follow-up. Participants aged 6-70y with T1D≥6 months and A1C Disclosure A. L. Carlson: Board Member; Self; JDRF, Other Relationship; Self; Medtronic, Research Support; Self; Abbott Diabetes, Dexcom, Inc., Eli Lilly and Company, Novo Nordisk, Omnipod, Sanofi, UnitedHealth Group. J. Sherr: Advisory Panel; Self; Cecelia Health, Insulet Corporation, Medtronic, Consultant; Self; Insulet Corporation, Lexicon Pharmaceuticals, Inc., Lilly Diabetes, Medtronic, Research Support; Self; Dexcom, Inc., Insulet Corporation, Medtronic, Speaker’s Bureau; Self; Lilly Diabetes. S. N. Mehta: None. L. M. Laffel: Consultant; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Dexcom, Inc., Dompe, Insulogic LLC, Janssen Pharmaceuticals, Inc., Laxmi Therapeutic Devices, LifeScan, Lilly Diabetes, Medtronic, Provention Bio, Inc. V. Shah: Advisory Panel; Self; Medscape, Sanofi, Research Support; Self; Dexcom, Inc., Eli Lilly and Company, Insulet Corporation, Novo Nordisk, Sanofi, vTv Therapeutics. A. Bhargava: Research Support; Self; Abbott, AbbVie Inc., Amgen Inc., Boehringer Ingelheim Pharmaceuticals, Inc., Boston Therapeutics, Inc., Covance Inc., Dexcom, Inc., Eli Lilly and Company, Gan & Lee Pharmaceuticals, Insulet Corporation, Janssen Research & Development, LLC, Kowa Pharmaceuticals America, Inc., Madrigal Pharmaceuticals, Inc., Medtronic, Merck & Co., Inc., Mylan N. V., Novo Nordisk, Poxel SA, Quintiles, Sanofi, Senseonics, Tolerion, Inc., Viking Therapeutics. R. S. Weinstock: Research Support; Self; Boehringer Ingelheim International GmbH, Diasome Pharmaceuticals, Inc., Eli Lilly and Company, Insulet Corporation, Kowa Research Institute, Inc., Medtronic, Tolerion, Inc. S. A. Macleish: Advisory Panel; Self; Insulet Corporation. D. Desalvo: Consultant; Self; Insulet Corporation, Research Support; Self; Insulet Corporation, Speaker’s Bureau; Self; Dexcom, Inc. T. C. Jones: None. G. Aleppo: Consultant; Self; Dexcom, Inc., Insulet Corporation, Research Support; Self; Dexcom, Inc., Eli Lilly and Company, Insulet Corporation, Novo Nordisk. A. B. Criego: Consultant; Self; Bigfoot Biomedical, Inc., Other Relationship; Self; Sanofi, Research Support; Self; Abbott Diabetes, Eli Lilly and Company, Insulet Corporation, Medtronic. B. A. Buckingham: Advisory Panel; Self; Medtronic, Tolerion, Inc., Research Support; Self; Beta Bionics, Inc., Insulet Corporation, Medtronic, Tandem Diabetes Care. T. T. Ly: Employee; Self; Insulet Corporation. Omnipod 5 research group: n/a. G. P. Forlenza: Advisory Panel; Self; Medtronic, Consultant; Self; Beta Bionics, Inc., Dexcom, Inc., Insulet Corporation, Tandem Diabetes Care, Research Support; Self; Abbott Diabetes, Dexcom, Inc., Insulet Corporation, Medtronic, Tandem Diabetes Care. B. W. Bode: Advisory Panel; Self; Eli Lilly and Company, Consultant; Self; Bigfoot Biomedical, Inc., Companion Medical, Lexicon Pharmaceuticals, Inc., Medtronic, Novo Nordisk Inc., Zealand Pharma A/S, Research Support; Self; Abvance Therapeutics, Dexcom, Inc., Diasome Pharmaceuticals, Inc., Dompe, Eli Lilly and Company, Eyenuk, Inc., Insulet Corporation, Jaeb Center for Health Research, Medtro Funding Insulet Corporation

Many of those with T1D in the US use MDI as their insulin delivery method. Hybrid closed-loop (HCL) systems such as the Omnipod 5 System may improve glycemic outcomes and reduce treatment burden, however, these systems must be accessible to current MDI users. We performed a subgroup analysis of participants transitioning directly from MDI in the pivotal study of the Omnipod 5 System. Children (6-13.9 y) and adults (14-70 y) with T1D≥6 months and A1C Disclosure V. Shah: Advisory Panel; Self; Medscape, Sanofi, Research Support; Self; Dexcom, Inc., Eli Lilly and Company, Insulet Corporation, Novo Nordisk, Sanofi, vTv Therapeutics. L. M. Laffel: Consultant; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Dexcom, Inc., Dompe, Insulogic LLC, Janssen Pharmaceuticals, Inc., Laxmi Therapeutic Devices, LifeScan, Lilly Diabetes, Medtronic, Provention Bio, Inc. G. Aleppo: Consultant; Self; Dexcom, Inc., Insulet Corporation, Research Support; Self; Dexcom, Inc., Eli Lilly and Company, Insulet Corporation, Novo Nordisk. B. A. Buckingham: Advisory Panel; Self; Medtronic, Tolerion, Inc., Research Support; Self; Beta Bionics, Inc., Insulet Corporation, Medtronic, Tandem Diabetes Care. D. Desalvo: Consultant; Self; Insulet Corporation, Research Support; Self; Insulet Corporation, Speaker’s Bureau; Self; Dexcom, Inc. I. B. Hirsch: Consultant; Self; Abbott Diabetes, Bigfoot Biomedical, Inc., Research Support; Self; Insulet Corporation, Leona M. and Harry B. Helmsley Charitable Trust, Medtronic. S. A. Macleish: Advisory Panel; Self; Insulet Corporation. J. E. Pinsker: Advisory Panel; Self; Medtronic, Consultant; Self; Eli Lilly and Company, Tandem Diabetes Care, Research Support; Self; Dexcom, Inc., Insulet Corporation, Medtronic, Tandem Diabetes Care. T. T. Ly: Employee; Self; Insulet Corporation. A. B. Criego: Consultant; Self; Bigfoot Biomedical, Inc., Other Relationship; Self; Sanofi, Research Support; Self; Abbott Diabetes, Eli Lilly and Company, Insulet Corporation, Medtronic. A. L. Carlson: Board Member; Self; JDRF, Other Relationship; Self; Medtronic, Research Support; Self; Abbott Diabetes, Dexcom, Inc., Eli Lilly and Company, Novo Nordisk, Omnipod, Sanofi, UnitedHealth Group. A. Bhargava: Research Support; Self; Abbott, AbbVie Inc., Amgen Inc., Boehringer Ingelheim Pharmaceuticals, Inc., Covance Inc., Dexcom, Inc., Eli Lilly and Company, Gan & Lee Pharmaceuticals, Gan & Lee Pharmaceuticals, Insulet Corporation, Janssen Research & Development, LLC, Madrigal Pharmaceuticals, Inc., Medtronic, Merck & Co., Inc., Mylan N. V., Novo Nordisk, Quintiles, Sanofi, Senseonics, Senseonics, Tolerion, Inc., viking. B. W. Bode: Advisory Panel; Self; Eli Lilly and Company, Consultant; Self; Bigfoot Biomedical, Inc., Companion Medical, Lexicon Pharmaceuticals, Inc., Medtronic, Novo Nordisk Inc., Zealand Pharma A/S, Research Support; Self; Abvance Therapeutics, Dexcom, Inc., Diasome Pharmaceuticals, Inc., Dompe, Eli Lilly and Company, Eyenuk, Inc., Insulet Corporation, Jaeb Center for Health Research, Medtronic, Nova Biomedical, Novo Nordisk, Provention Bio, Inc., REMD Biotherapeutics, Sanofi, Senseonics, Viacyte, Inc., vTv Therapeutics, Xeris Pharmaceuticals, Inc., Speaker’s Bureau; Self; AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Eli Lilly and Company, MannKind Corporation, Medtronic, Novo Nordisk, Sanofi, Stock/Shareholder; Self; AgaMatrix, Aseko, Inc., Glytec, LLC. S. A. Brown: Research Support; Self; Dexcom, Inc., Insulet Corporation, Roche Diabetes Care, Tandem Diabetes Care, Tolerion, Inc. Funding Insulet Corporation

AIM To describe real-world hybrid closed loop (HCL) use and glycaemic outcomes across the lifespan and identify a clinical threshold for HCL use associated with meeting the internationally recommended target of 70% sensor glucose time in range (TIR; 70-180 mg/dL). MATERIALS AND METHODS Mixed models examined MiniMed 670G HCL use and glycaemic outcomes in 276 people with type 1 diabetes from four age groups: youth (aged

Objective: To assess the efficacy and safety of closed-loop control (CLC) insulin delivery system in adolescents and young adults with type 1 diabetes. Research Design and Methods: Prespecified subanalysis of outcomes in adolescents and young adults aged 14–24 years old with type 1 diabetes in a previously published 6-month multicenter randomized trial. Participants were randomly assigned 2:1 to CLC (Tandem Control-IQ) or sensor augmented pump (SAP, various pumps+Dexcom G6 CGM) and followed for 6 months. Results: Mean age of the 63 participants was 17 years, median type 1 diabetes duration was 7 years, and mean baseline HbA1c was 8.1%. All 63 completed the trial. Time in range (TIR) increased by 13% with CLC versus decreasing by 1% with SAP (adjusted treatment group difference = +13% [+3.1 h/day]; 95% confidence interval [CI] 9–16, P 180 mg/dL (adjusted difference −12% [−2.9 h/day], P

Background: The objective of this study was to assess the safety and performance of the Omnipod® personalized model predictive control (MPC) algorithm with variable glucose setpoints and moderate intensity exercise using an investigational device in adults with type 1 diabetes (T1D). Materials and Methods: A supervised 54-h hybrid closed-loop (HCL) study was conducted in a hotel setting after a 7-day outpatient standard treatment phase. Adults aged 18–65 years with T1D and HbA1c between 6.0% and 10.0% were eligible. Subjects completed two moderate intensity exercise sessions of >30 min duration on consecutive days: the first with the glucose set point increased from 130 to 150 mg/dL and the second with a temporary basal rate of 50%, both started 90 min pre-exercise. Primary endpoints were percentage time in hypoglycemia

Objective: Hybrid closed-loop (HCL) artificial pancreas (AP) systems are now moving from research settings to widespread clinical use. In this study, the inControl algorithm developed by TypeZero Technologies was embedded to a commercial Tandem t:slim X2 insulin pump, now called Control-IQ, paired with a Dexcom G6 continuous glucose monitor and tested for superiority against sensor augmented pump (SAP) therapy. Both groups were physician-monitored throughout the clinical trial. Research Design and Methods: In a randomized controlled trial, 24 school-aged children (6–12 years) with type 1 diabetes (T1D) participated in a 3-day home-use trial at two sites: Stanford University and the Barbara Davis Center (50% girls, 9.6 ± 1.9 years of age, 4.5 ± 1.9 years of T1D, baseline hemoglobin A1c 7.35% ± 0.68%). Study subjects were randomized 1:1 at each site to either HCL AP therapy with the Control-IQ system or SAP therapy with remote monitoring. Results: The primary outcome, time in target range 70–180 mg/dL, using Control-IQ significantly improved (71.0% ± 6.6% vs. 52.8% ± 13.5%; P = 0.001) and mean sensor glucose (153.6 ± 13.5 vs. 180.2 ± 23.1 mg/dL; P = 0.003) without increasing hypoglycemia time

Continuous glucose monitors (CGM) display real-time glucose values enabling greater glycemic awareness with reduced management burden. Factory-calibrated CGM systems allow for glycemic assessment without the pain and inconvenience of fingerstick glucose testing. Advances in sensor chemistry and CGM algorithms have enabled factory-calibrated systems to have greater accuracy than previous generations of CGM technology. Despite these advances many patients and providers are hesitant about the idea of removing fingerstick testing from their diabetes care. In this commentary, we aim to review the clinical trials on factory-calibrated CGM systems, present the algorithms which facilitate factory-calibrated CGMs to improve accuracy, discuss clinical use of factory-calibrated CGMs, and finally present two cases demonstrating the dangers of utilizing exploits in commercial systems to prolong sensor life.