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Background: Closed-loop systems that automate insulin delivery may improve glycemic outcomes in patients with type 1 diabetes.Methods: In this 6-month randomized, multicenter trial, patients with type 1 diabetes were assigned in a 2:1 ratio to receive treatment with a closed-loop system (closed-loop group) or a sensor-augmented pump (control group). The primary outcome was the percentage of time that the blood glucose level was within the target range of 70 to 180 mg per deciliter (3.9 to 10.0 mmol per liter), as measured by continuous glucose monitoring.Results: A total of 168 patients underwent randomization; 112 were assigned to the closed-loop group, and 56 were assigned to the control group. The age range of the patients was 14 to 71 years, and the glycated hemoglobin level ranged from 5.4 to 10.6%. All 168 patients completed the trial. The mean (±SD) percentage of time that the glucose level was within the target range increased in the closed-loop group from 61±17% at baseline to 71±12% during the 6 months and remained unchanged at 59±14% in the control group (mean adjusted difference, 11 percentage points; 95% confidence interval [CI], 9 to 14; P<0.001). The results with regard to the main secondary outcomes (percentage of time that the glucose level was >180 mg per deciliter, mean glucose level, glycated hemoglobin level, and percentage of time that the glucose level was <70 mg per deciliter or <54 mg per deciliter [3.0 mmol per liter]) all met the prespecified hierarchical criterion for significance, favoring the closed-loop system. The mean difference (closed loop minus control) in the percentage of time that the blood glucose level was lower than 70 mg per deciliter was -0.88 percentage points (95% CI, -1.19 to -0.57; P<0.001). The mean adjusted difference in glycated hemoglobin level after 6 months was -0.33 percentage points (95% CI, -0.53 to -0.13; P = 0.001). In the closed-loop group, the median percentage of time that the system was in closed-loop mode was 90% over 6 months. No serious hypoglycemic events occurred in either group; one episode of diabetic ketoacidosis occurred in the closed-loop group.Conclusions: In this 6-month trial involving patients with type 1 diabetes, the use of a closed-loop system was associated with a greater percentage of time spent in a target glycemic range than the use of a sensor-augmented insulin pump. (Funded by the National Institute of Diabetes and Digestive and Kidney Diseases; iDCL ClinicalTrials.gov number, NCT03563313.). [ABSTRACT FROM AUTHOR]

Introduction: Insulin pump therapy can be adversely affected by interruption of insulin flow, leading to a rise in blood glucose (BG) and subsequently of blood beta-hydroxybutyrate (BHB) ketone levels., Methods: We performed a PubMed search for English language reports (January 1982 to July 2024) estimating the rate of rise in BG and/or BHB after ≥ 60 minutes of interruption of continuous subcutaneous insulin infusion (CSII) in persons with type 1 diabetes (PwT1D). We also simulated the rise in BG in a virtual population of 100 adults with T1D following suspension of continuous subcutaneous insulin infusion., Results: We identified eight relevant studies where BG and BHB (seven of these eight studies) were measured following suspension of CSII as a model for occlusion. After 60 minutes post-suspension, the mean extracted rates of rise averaged 0.62 mg/dL/min (37 mg/dL/h) for BG and 0.0038 mmol/L/min (0.20 mmol/L/h) for BHB. Mean estimated time to moderately/severely elevated BG (300/400 mg/dL) or BHB (1.6/3.0 mmol/L) was, respectively, 5.8/8.5 and 8.0/14.2 hours. The simulation model predicted moderately/severely elevated BG (300/400 mg/dL) after 9.25/12, 6.75/8.75, and 4.75/5.75 hours in the virtual subjects post-interruption with small (5th percentile), medium (50th percentile), and large (95th percentile) hyperglycemic changes., Discussion: Clinical studies and a simulation model similarly predicted that, following CSII interruption, moderate/severe hyperglycemia can occur within 5-9/6-14 hours, and clinical studies predicted that moderate/severe ketonemia can occur within 7-12/13-21 hours. Patients and clinicians should be aware of this timing when considering the risks of developing metabolic complications after insulin pump occlusion., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: D.C.K. is a consultant for Afon, Embecta, GlucoTrack, Lifecare, Novo, Samsung, and Thirdwayv. C. N. H. has nothing to disclose. A.T.A. has nothing to disclose. C.F. reports receiving research support from Novo Nordisk A/S and Dexcom, Inc handled by the University of Virginia, and patent royalties from Novo Nordisk A/S and Dexcom, Inc handled by the University of Virginia’s Licensing and Ventures Group. M.F.V.-T. reports receiving patent royalties from Dexcom, Inc handled by the University of Virginia’s Licensing and Ventures Group. E.A. has nothing to disclose. E.C. has served on the scientific advisory board of Novo Nordisk, Eli Lilly, MannKind, Arecor, Portal Insulin, Provention Bio, Tandem, and Ypsomed. L.E. receives salary support from NIDDK; has received research support from JDRF, Medtronic, MannKind, and Abbot and has served on the advisory board of Diabetes Center Berne, Sequel, and Medtronic. She has received consulting fees from Jaeb, Tandem Diabetes Care, and Ypsomed and has received honorarium fees from Medtronic and Insulet. J.C.W. has received research support from Dexcom, Inc and Tandem Diabetes Care. L.H. is a shareholder of the Profil Institut für Stoffwechselforschung GmbH, Neuss, Germany, Science Consulting in Diabetes GmbH Düsseldorf, and diateam GmbH, Bad Mergentheim, and Düsseldorf. L.H. is a consultant for several companies that are developing novel diagnostic and therapeutic options for diabetes treatment. M.A.K. has nothing to disclose.

The quality of clinician-patient relationship is integral to patient health and well-being. This article is a narrative review of published literature on concordance between clinician and patient perspectives on barriers to diabetes technology use. The goals of this manuscript were to review published literature on concordance and to provide practical recommendations for clinicians and researchers. In this review, we discuss the qualitative and quantitative methods that can be applied to measure clinician and patient concordance. There is variability in how concordance is defined, with some studies using questionnaires related to working alliance, while others use a dichotomous variable. We also explore the impact of concordance and discordance on diabetes care, barriers to technology adoption, and disparities in technology use. Published literature has emphasized that physicians may not be aware of their patients' perspectives and values. Discordance between clinicians and patients can be a barrier to diabetes management and technology use. Future directions for research in diabetes technology including strategies for recruiting and retaining representative samples, are discussed. Recommendations are given for clinical care, including shared decision-making frameworks, establishing social support groups optimizing clinician-patient communication, and using patient-reported outcomes to measure patient perspectives on outcomes of interest., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: AA, KH, and YH do not have any relevant disclosures. LE receives salary support from NIDDK; has received research support from Breakthrough T1D, Medtronic, Abbot, and Mannkind; has served on the advisory board of Diabetes Center Berne and Medtronic. She has received consulting fees from Jaeb, Tandem Diabetes Care and Ypsomed, Sequel and has received honorarium fee from Medtronic and Insulet.

Objective: To evaluate the impact of missed or late meal boluses (MLBs) on glycemic outcomes in children and adolescents with type 1 diabetes using automated insulin delivery (AID) systems. Research Design and Methods: AID-treated (Tandem Control-IQ or Medtronic MiniMed 780G) children and adolescents (aged 6-21 years) from Stanford Medical Center and Steno Diabetes Center Copenhagen with ≥10 days of data were included in this two-center, binational, population-based, retrospective, 1-month cohort study. The primary outcome was the association between the number of algorithm-detected MLBs and time in target glucose range (TIR; 70-180 mg/dL). Results: The study included 189 children and adolescents (48% females with a mean ± standard deviation age of 13 ± 4 years). Overall, the mean number of MLBs per day in the cohort was 2.2 ± 0.9. For each additional MLB per day, TIR decreased by 9.7% points (95% confidence interval [CI] 11.3; 8.1), and compared with the quartile with fewest MLBs (Q 1 ), the quartile with most (Q 4 ) had 22.9% less TIR (95% CI: 27.2; 18.6). The age-, sex-, and treatment modality-adjusted probability of achieving a TIR of >70% in Q 4 was 1.4% compared with 74.8% in Q 1 ( P < 0.001). Conclusions: MLBs significantly impacted glycemic outcomes in AID-treated children and adolescents. The results emphasize the importance of maintaining a focus on bolus behavior to achieve a higher TIR and support the need for further research in technological or behavioral support tools to handle MLBs.

Objectives: To report the safety and side effects associated with taking verapamil for beta-cell preservation in children with newly-diagnosed T1D., Research Design and Methods: Eighty-eight participants aged 8.5 to 17.9 years weighing ≥ 30 kg were randomly assigned to verapamil (N = 47) or placebo (N = 41) within 31 days of T1D diagnosis and followed for 12 months from diagnosis, main CLVer study. Drug dosing was weight-based with incremental increases to full dosage. Side effect monitoring included serial measurements of pulse, blood pressure, liver enzymes, and electrocardiograms (ECGs). At study end, participants were enrolled in an observational extension study (CLVerEx), which is ongoing. No study drug is provided during the extension, but participants may use verapamil if prescribed by their diabetes care team., Results: Overall rates of adverse events were low and comparable between verapamil and placebo groups. There was no difference in the frequency of liver function abnormalities. Three CLVer participants reduced or discontinued medication due to asymptomatic ECG changes. One CLVerEx participant (18 years old), treated with placebo during CLVer, who had not had a monitoring ECG, experienced complete AV block with a severe hypotensive episode 6 weeks after reaching his maximum verapamil dose following an inadvertent double dose on the day of the event., Conclusions: The use of verapamil in youth newly-diagnosed with T1D appears generally safe and well tolerated with appropriate monitoring. We strongly recommend monitoring for potential side effects including an ECG at screening and an additional ECG once full dosage is reached.ClinicalTrials.gov number: NCT04233034., Competing Interests: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Dr. Ekhlaspour receives salary support from NIH and research support from JDRF. She reports receiving consulting fees from Medtronic, Tandem Diabetes Care and Ypsomed; receiving speaking fees from Insulet; and receiving research support from Medtronic, MannKind and Abbot through her institution. Her prior institution has received research support from Medtronic, Tandem Diabetes Care, Insulet, Dexcom and Beta Bionics. Dr. Buckingham reports receiving grants, personal fees, and/or nonfinancial support from Medtronic, Tandem Diabetes Care, Insulet, NovoNordisk, and Lilly and reports his institution has received research funding from Medtronic, Tandem Diabetes Care, Beta Bionics, and Insulet. Dr. Bauza reports no disclosures. Dr. Clements reports receiving personal fees from Glooko Inc and nonfinancial support from Dexcom and Abbott Diabetes Care. Dr. Forlenza reports serving as a consultant, speaker or advisory board member for Medtronic, Dexcom, Abbott, Tandem Diabetes Care, Insulet, Lilly, and Beta Bionics and reports his institution has received funding on his behalf for research grants from Medtronic, Dexcom, Abbott, Tandem Diabetes Care, Insulet, Lilly, and Beta Bionics. Dr. Neyman reports no disclosures. Dr. Norlander reports no disclosures. Dr. Schamberger reports no disclosures. Dr. Sherr reported receiving speaking honoraria from Lilly, Insulet, Medtronic, and Zealand Pharma; serving on advisory boards for Bigfoot Biomedical, Cecelia Health, Insulet, Medtronic Diabetes, JDRF (formally the Juvenile Diabetes Research Foundation) T1D Fund, StartUp Health T1D Moonshot, and Vertex Pharmaceuticals; receiving consultant fees from Insulet and Medtronic; and reported that her institution has received research grant support from Medtronic and Insulet. Mr. Bailey reports no disclosures. Dr. Beck reports his institution has received funding on his behalf as follows: grant funding and study supplies from Tandem Diabetes Care, Beta Bionics, and Dexcom; grant funding from Bigfoot Biomedical; study supplies from Medtronic, Ascencia, and Roche; consulting fees and study supplies from Lilly and NovoNordisk; and consulting fees from Insulet and Zucara Therapeutics. Dr. Kollman reports receiving grants from Dexcom and Tandem Diabetes Care. Ms. Beasley reports no disclosures. Dr. Cobry reports no disclosures. Dr. DiMeglio reports receiving consulting or advisory fees from Abata Therapeutics, MannKind, Provention Bio, and Zealand Pharma and study supplies from Dexcom. Dr. Paprocki reports no disclosures. Dr. Van Name reports receiving research support from ProventionBio. Dr. Moran reports serving on advisory boards from Dompé Farmaceutici SpA, ProventionBio, and Abata Therapeutics; serving on a data and safety monitoring board for NovoNordisk; and reported that her institution has received grant funding on her behalf from Abbott Diabetes, ProventionBio, Intrexon (now Precigen), and Caladrius Biosciences and study supplies from NovoNordisk, Medtronic, and Abbott Diabetes., (© 2024 The Authors.)

Objective: Modeling the effect of meal composition on glucose excursion would help in designing decision support systems (DSS) for type 1 diabetes (T1D) management. In fact, macronutrients differently affect post-prandial gastric retention (GR), rate of appearance (R[Formula: see text]), and insulin sensitivity (S[Formula: see text]). Such variables can be estimated, in inpatient settings, from plasma glucose (G) and insulin (I) data using the Oral glucose Minimal Model (OMM) coupled with a physiological model of glucose transit through the gastrointestinal tract (reference OMM, R-OMM). Here, we present a model able to estimate those quantities in daily-life conditions, using minimally-invasive (MI) technologies, and validate it against the R-OMM., Methods: Forty-seven individuals with T1D (weight =78±13 kg, age =42±10 yr) underwent three 23-hour visits, during which G and I were frequently sampled while wearing continuous glucose monitoring (CGM) and insulin pump (IP). Using a Bayesian Maximum A Posteriori estimator, R-OMM was identified from plasma G and I measurements, and MI-OMM was identified from CGM and IP data., Results: The MI-OMM fitted the CGM data well and provided precise parameter estimates. GR and R[Formula: see text] model parameters were not significantly different using the MI-OMM and R-OMM (p 0.05) and the correlation between the two S[Formula: see text] was satisfactory ( ρ =0.77)., Conclusion: The MI-OMM is usable to estimate GR, R[Formula: see text], and S[Formula: see text] from data collected in real-life conditions with minimally-invasive technologies., Significance: Applying MI-OMM to datasets where meal compositions are available will allow modeling the effect of each macronutrient on GR, R[Formula: see text], and S[Formula: see text]. DSS could finally exploit this information to improve diabetes management.

Objective: Examine patient-reported outcomes (PROs) after the use of t:slim X2 insulin pump with Control-IQ technology (CIQ) in young children with type 1 diabetes., Methods: Children with type 1 diabetes, ages 2 to < 6 years (n = 102), were randomly assigned 2:1 to either CIQ or standard care (SC) with pump or multiple daily injections (MDI) plus continuous glucose monitoring (CGM) for 13 weeks. Both groups were offered to use CIQ for an additional 13 weeks after the randomized control trial's (RCT) completion. Guardians completed PRO questionnaires at baseline, 13-, and 26-weeks examining hypoglycemia concerns, quality of life, parenting stress, and sleep. At 26 weeks, 28 families participated in user-experience interviews. Repeated measures analyses compared PRO scores between systems used., Result: Comparing CIQ vs SC, responses on all 5 PRO surveys favored the CIQ group, showing that CIQ was superior to SC at 26 weeks (p values < 0.05). User-experience interviews indicated significant benefits in optimized glycemic control overall and nighttime control (28 of 28 families endorsed). All but 2/28 families noted substantial reduction in management burden resulting in less mental burden and all but 4 stated that they wanted their children to continue using CIQ., Conclusions: Families utilizing CIQ experienced glycemic benefits coupled with substantial benefits in PROs, documented in surveys and interviews. Families utilizing CIQ had reduced hypoglycemia concerns and parenting stress, and improved quality of life and sleep. These findings demonstrate the benefit of CIQ in young children with type 1 diabetes that goes beyond documented glycemic benefit., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Type 1 diabetes (T1D) is the most frequent form of diabetes in pediatric age, affecting more than 1.5 million people younger than age 20 years worldwide. Early and intensive control of diabetes provides continued protection against both microvascular and macrovascular complications, enhances growth, and ensures normal pubertal development. In the absence of definitive reversal therapy for this disease, achieving and maintaining the recommended glycemic targets is crucial. In the last 30 years, enormous progress has been made using technology to better treat T1D. In spite of this progress, the majority of children, adolescents and young adults do not reach the recommended targets for glycemic control and assume a considerable burden each day. The development of promising new therapeutic advances, such as more physiologic insulin analogues, pioneering diabetes technology including continuous glucose monitoring and closed loop systems as well as new adjuvant drugs, anticipate a new paradigm in T1D management over the next few years. This review presents insights into current management of T1D in youths., Competing Interests: Declaration of Competing Interest CM and MM declared no conflict of interest., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

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.

Importance: Near normalization of glucose levels instituted immediately after diagnosis of type 1 diabetes has been postulated to preserve pancreatic beta cell function by reducing glucotoxicity. Previous studies have been hampered by an inability to achieve tight glycemic goals., Objective: To determine the effectiveness of intensive diabetes management to achieve near normalization of glucose levels on preservation of pancreatic beta cell function in youth with newly diagnosed type 1 diabetes., Design, Setting, and Participants: This randomized, double-blind, clinical trial was conducted at 6 centers in the US (randomizations from July 20, 2020, to October 13, 2021; follow-up completed September 15, 2022) and included youths with newly diagnosed type 1 diabetes aged 7 to 17 years., Interventions: Random assignment to intensive diabetes management, which included use of an automated insulin delivery system (n = 61), or standard care, which included use of a continuous glucose monitor (n = 52), as part of a factorial design in which participants weighing 30 kg or more also were assigned to receive either oral verapamil or placebo., Main Outcomes and Measures: The primary outcome was mixed-meal tolerance test-stimulated C-peptide area under the curve (a measure of pancreatic beta cell function) 52 weeks from diagnosis., Results: Among 113 participants (mean [SD] age, 11.8 [2.8] years; 49 females [43%]; mean [SD] time from diagnosis to randomization, 24 [5] days), 108 (96%) completed the trial. The mean C-peptide area under the curve decreased from 0.57 pmol/mL at baseline to 0.45 pmol/mL at 52 weeks in the intensive management group, and from 0.60 to 0.50 pmol/mL in the standard care group (treatment group difference, -0.01 [95% CI, -0.11 to 0.10]; P = .89). The mean time in the target range of 70 to 180 mg/dL, measured with continuous glucose monitoring, at 52 weeks was 78% in the intensive management group vs 64% in the standard care group (adjusted difference, 16% [95% CI, 10% to 22%]). One severe hypoglycemia event and 1 diabetic ketoacidosis event occurred in each group., Conclusions and Relevance: In youths with newly diagnosed type 1 diabetes, intensive diabetes management, which included automated insulin delivery, achieved excellent glucose control but did not affect the decline in pancreatic C-peptide secretion at 52 weeks., Trial Registration: ClinicalTrials.gov Identifier: NCT04233034.

Importance: In preclinical studies, thioredoxin-interacting protein overexpression induces pancreatic beta cell apoptosis and is involved in glucotoxicity-induced beta cell death. Calcium channel blockers reduce these effects and may be beneficial to beta cell preservation in type 1 diabetes., Objective: To determine the effect of verapamil on pancreatic beta cell function in children and adolescents with newly diagnosed type 1 diabetes., Design, Setting, and Participants: This double-blind, randomized clinical trial including children and adolescents aged 7 to 17 years with newly diagnosed type 1 diabetes who weighed 30 kg or greater was conducted at 6 centers in the US (randomized participants between July 20, 2020, and October 13, 2021) and follow-up was completed on September 15, 2022., Interventions: Participants were randomly assigned 1:1 to once-daily oral verapamil (n = 47) or placebo (n = 41) as part of a factorial design in which participants also were assigned to receive either intensive diabetes management or standard diabetes care., Main Outcomes and Measures: The primary outcome was area under the curve values for C-peptide level (a measure of pancreatic beta cell function) stimulated by a mixed-meal tolerance test at 52 weeks from diagnosis of type 1 diabetes., Results: Among 88 participants (mean age, 12.7 [SD, 2.4] years; 36 were female [41%]; and the mean time from diagnosis to randomization was 24 [SD, 4] days), 83 (94%) completed the trial. In the verapamil group, the mean C-peptide area under the curve was 0.66 pmol/mL at baseline and 0.65 pmol/mL at 52 weeks compared with 0.60 pmol/mL at baseline and 0.44 pmol/mL at 52 weeks in the placebo group (adjusted between-group difference, 0.14 pmol/mL [95% CI, 0.01 to 0.27 pmol/mL]; P = .04). This equates to a 30% higher C-peptide level at 52 weeks with verapamil. The percentage of participants with a 52-week peak C-peptide level of 0.2 pmol/mL or greater was 95% (41 of 43 participants) in the verapamil group vs 71% (27 of 38 participants) in the placebo group. At 52 weeks, hemoglobin A1c was 6.6% in the verapamil group vs 6.9% in the placebo group (adjusted between-group difference, -0.3% [95% CI, -1.0% to 0.4%]). Eight participants (17%) in the verapamil group and 8 participants (20%) in the placebo group had a nonserious adverse event considered to be related to treatment., Conclusions and Relevance: In children and adolescents with newly diagnosed type 1 diabetes, verapamil partially preserved stimulated C-peptide secretion at 52 weeks from diagnosis compared with placebo. Further studies are needed to determine the longitudinal durability of C-peptide improvement and the optimal length of therapy., Trial Registration: ClinicalTrials.gov Identifier: NCT04233034.

Background: Closed-loop control systems of insulin delivery may improve glycemic outcomes in young children with type 1 diabetes. The efficacy and safety of initiating a closed-loop system virtually are unclear., Methods: In this 13-week, multicenter trial, we randomly assigned, in a 2:1 ratio, children who were at least 2 years of age but younger than 6 years of age who had type 1 diabetes to receive treatment with a closed-loop system of insulin delivery or standard care that included either an insulin pump or multiple daily injections of insulin plus a continuous glucose monitor. The primary outcome was the percentage of time that the glucose level was in the target range of 70 to 180 mg per deciliter, as measured by continuous glucose monitoring. Secondary outcomes included the percentage of time that the glucose level was above 250 mg per deciliter or below 70 mg per deciliter, the mean glucose level, the glycated hemoglobin level, and safety outcomes., Results: A total of 102 children underwent randomization (68 to the closed-loop group and 34 to the standard-care group); the glycated hemoglobin levels at baseline ranged from 5.2 to 11.5%. Initiation of the closed-loop system was virtual in 55 patients (81%). The mean (±SD) percentage of time that the glucose level was within the target range increased from 56.7±18.0% at baseline to 69.3±11.1% during the 13-week follow-up period in the closed-loop group and from 54.9±14.7% to 55.9±12.6% in the standard-care group (mean adjusted difference, 12.4 percentage points [equivalent to approximately 3 hours per day]; 95% confidence interval, 9.5 to 15.3; P<0.001). We observed similar treatment effects (favoring the closed-loop system) on the percentage of time that the glucose level was above 250 mg per deciliter, on the mean glucose level, and on the glycated hemoglobin level, with no significant between-group difference in the percentage of time that the glucose level was below 70 mg per deciliter. There were two cases of severe hypoglycemia in the closed-loop group and one case in the standard-care group. One case of diabetic ketoacidosis occurred in the closed-loop group., Conclusions: In this trial involving young children with type 1 diabetes, the glucose level was in the target range for a greater percentage of time with a closed-loop system than with standard care. (Funded by the National Institute of Diabetes and Digestive and Kidney Diseases; PEDAP ClinicalTrials.gov number, NCT04796779.)., (Copyright © 2023 Massachusetts Medical Society.)

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., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Endocrine Society.)

Background: Currently available semiautomated insulin-delivery systems require individualized insulin regimens for the initialization of therapy and meal doses based on carbohydrate counting for routine operation. In contrast, the bionic pancreas is initialized only on the basis of body weight, makes all dose decisions and delivers insulin autonomously, and uses meal announcements without carbohydrate counting., Methods: In this 13-week, multicenter, randomized trial, we randomly assigned in a 2:1 ratio persons at least 6 years of age with type 1 diabetes either to receive bionic pancreas treatment with insulin aspart or insulin lispro or to receive standard care (defined as any insulin-delivery method with unblinded, real-time continuous glucose monitoring). The primary outcome was the glycated hemoglobin level at 13 weeks. The key secondary outcome was the percentage of time that the glucose level as assessed by continuous glucose monitoring was below 54 mg per deciliter; the prespecified noninferiority limit for this outcome was 1 percentage point. Safety was also assessed., Results: A total of 219 participants 6 to 79 years of age were assigned to the bionic-pancreas group, and 107 to the standard-care group. The glycated hemoglobin level decreased from 7.9% to 7.3% in the bionic-pancreas group and did not change (was at 7.7% at both time points) in the standard-care group (mean adjusted difference at 13 weeks, -0.5 percentage points; 95% confidence interval [CI], -0.6 to -0.3; P<0.001). The percentage of time that the glucose level as assessed by continuous glucose monitoring was below 54 mg per deciliter did not differ significantly between the two groups (13-week adjusted difference, 0.0 percentage points; 95% CI, -0.1 to 0.04; P<0.001 for noninferiority). The rate of severe hypoglycemia was 17.7 events per 100 participant-years in the bionic-pancreas group and 10.8 events per 100 participant-years in the standard-care group (P = 0.39). No episodes of diabetic ketoacidosis occurred in either group., Conclusions: In this 13-week, randomized trial involving adults and children with type 1 diabetes, use of a bionic pancreas was associated with a greater reduction than standard care in the glycated hemoglobin level. (Funded by the National Institute of Diabetes and Digestive and Kidney Diseases and others; ClinicalTrials.gov number, NCT04200313.)., (Copyright © 2022 Massachusetts Medical Society.)

Background: Automated insulin delivery (AID) systems have proven effective in increasing time-in-range during both clinical trials and real-world use. Further improvements in outcomes for single-hormone (insulin only) AID may be limited by suboptimal insulin delivery settings. Methods: Adults (≥18 years of age) with type 1 diabetes were randomized to either sensor-augmented pump (SAP) (inclusive of predictive low-glucose suspend) or adaptive zone model predictive control AID for 13 weeks, then crossed over to the other arm. Each week, the AID insulin delivery settings were sequentially and automatically updated by an adaptation system running on the study phone. Primary outcome was sensor glucose time-in-range 70-180 mg/dL, with noninferiority in percent time below 54 mg/dL as a hierarchical outcome. Results: Thirty-five participants completed the trial (mean age 39 ± 16 years, HbA1c at enrollment 6.9% ± 1.0%). Mean time-in-range 70-180 mg/dL was 66% with SAP versus 69% with AID (mean adjusted difference +2% [95% confidence interval: -1% to +6%], P  = 0.22). Median time <70 mg/dL improved from 3.0% with SAP to 1.6% with AID (-1.5% [-2.4% to -0.5%], P  = 0.002). The adaptation system decreased initial basal rates by a median of 4% (-8%, 16%) and increased initial carbohydrate ratios by a median of 45% (32%, 59%) after 13 weeks. Conclusions: Automated adaptation of insulin delivery settings with AID use did not significantly improve time-in-range in this very well-controlled population. Additional study and further refinement of the adaptation system are needed, especially in populations with differing degrees of baseline glycemic control, who may show larger benefits from adaptation.

Objective: Very young children with type 1 diabetes often struggle to achieve glycemic targets, putting them at risk for long-term complications and creating an immense management burden for caregivers. We conducted the first evaluation of the Omnipod 5 Automated Insulin Delivery System in this population., Research Design and Methods: A total of 80 children aged 2.0-5.9 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 or diabetic ketoacidosis. By study end, HbA1c decreased by 0.55% (6.0 mmol/mol) (P < 0.0001). Time with sensor glucose levels in target range 70-180 mg/dL increased by 10.9%, or 2.6 h/day (P < 0.0001), while time with levels <70 mg/dL declined by median 0.27% (P = 0.0204)., Conclusions: Use of the automated insulin delivery system was safe, and participants experienced improved glycemic measures and reduced hypoglycemia during the study phase compared with baseline., (© 2022 by the American Diabetes Association.)

Using a closed-loop system significantly improves time in range (TIR) 70-180 mg/dL in patients with type 1 diabetes (T1D). In a 6-month RCT, 112 subjects were randomly assigned to closed-loop control (Tandem Control-IQ) after obtaining 2 weeks of baseline Continuous glucose monitoring (CGM) data from sensor-augmented pump therapy. We compared glycemic outcomes from baseline to end of study among subgroups classified by baseline HbA1c levels. All HbA1c subgroups showed an improvement in TIR due to reduction of both hyperglycemia and hypoglycemia. Those with HbA1c <6.5% improved mostly by reducing nocturnal hypoglycemia due to the automated basal insulin adjustments. Those with HbA1c ≥8.5% improved mostly by reducing daytime and nocturnal hyperglycemia due to both automated basal insulin adjustments and correction boluses during the day. There does not appear to be any reason to exclude individuals with T1D from automated insulin delivery based on their HbA1c. Clinical Trial Identifier: NCT03563313.

Background: 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., Methods: 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., Results: 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., Conclusions: 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., (© 2022 The Authors. Pediatric Diabetes published by John Wiley & Sons Ltd.)

Objective: Achieving optimal glycemic control for many individuals with type 1 diabetes (T1D) remains challenging, even with the advent of newer management tools, including continuous glucose monitoring (CGM). Modern management of T1D generates a wealth of data; however, use of these data to optimize glycemic control remains limited. We evaluated the impact of a CGM-based decision support system (DSS) in patients with T1D using multiple daily injections (MDI)., Research Design and Methods: The studied DSS included real-time dosing advice and retrospective therapy optimization. Adults and adolescents (age >15 years) with T1D using MDI were enrolled at three sites in a 14-week randomized controlled trial of MDI + CGM + DSS versus MDI + CGM. All participants (N = 80) used degludec basal insulin and Dexcom G5 CGM. CGM-based and patient-reported outcomes were analyzed. Within the DSS group, ad hoc analysis further contrasted active versus nonactive DSS users., Results: No significant differences were detected between experimental and control groups (e.g., time in range [TIR] +3.3% with CGM vs. +4.4% with DSS). Participants in both groups reported lower HbA1c (-0.3%; P = 0.001) with respect to baseline. While TIR may have improved in both groups, it was statistically significant only for DSS; the same was apparent for time spent <60 mg/dL. Active versus nonactive DSS users showed lower risk of and exposure to hypoglycemia with system use., Conclusions: Our DSS seems to be a feasible option for individuals using MDI, although the glycemic benefits associated with use need to be further investigated. System design, therapy requirements, and target population should be further refined prior to use in clinical care., (© 2021 by the American Diabetes Association.)

Closed-loop insulin delivery systems are fast becoming the standard of care in the management of type 1 diabetes and have led to significant improvements in diabetes management. Nevertheless, there is still room for improvement for the closed-loop systems to optimize treatment and meet target glycemic control. Adjunct treatments have been introduced as an alternative method to insulin-only treatment methods to overcome diabetes treatment challenges and improve clinical and patient reported outcomes during closed-loop treatment. The adjunct treatment agents mostly consist of medications that are already approved for type 2 diabetes treatment and aim to complete the missing physiologic factors, such as the entero-endocrine system, that regulate glycemia in addition to insulin. This paper will review many of these adjunct therapies, including the basic mechanisms of action, potential benefits, side effects, and the evidence supporting their use during closed-loop treatment.

Background: Closed-loop control (CLC) has been shown to improve glucose time in range and other glucose metrics; however, randomized trials >3 months comparing CLC with sensor-augmented pump (SAP) therapy are limited. We recently reported glucose control outcomes from the 6-month international Diabetes Closed-Loop (iDCL) trial; we now report patient-reported outcomes (PROs) in this iDCL trial. Methods: Participants were randomized 2:1 to CLC ( N  = 112) versus SAP ( N  = 56) and completed questionnaires, including Hypoglycemia Fear Survey, Diabetes Distress Scale (DDS), Hypoglycemia Awareness, Hypoglycemia Confidence, Hyperglycemia Avoidance, and Positive Expectancies of CLC (INSPIRE) at baseline, 3, and 6 months. CLC participants also completed Diabetes Technology Expectations and Acceptance and System Usability Scale (SUS). Results: The Hypoglycemia Fear Survey Behavior subscale improved significantly after 6 months of CLC compared with SAP. DDS did not differ except for powerless subscale scores, which worsened at 3 months in SAP. Whereas Hypoglycemia Awareness and Hyperglycemia Avoidance did not differ between groups, CLC participants showed a tendency toward improved confidence in managing hypoglycemia. The INSPIRE questionnaire showed favorable scores in the CLC group for teens and parents, with a similar trend for adults. At baseline and 6 months, CLC participants had high positive expectations for the device with Diabetes Technology Acceptance and SUS showing high benefit and low burden scores. Conclusion: CLC improved some PROs compared with SAP. Participants reported high benefit and low burden with CLC. Clinical Trial Identifier: NCT03563313.

Background: Studies of closed-loop control (CLC) in patients with type 1 diabetes (T1D) consistently demonstrate improvements in glycemic control as measured by increased time-in-range (TIR) 70-180 mg/dL. However, clinical predictors of TIR in users of CLC systems are needed. Materials and Methods: We analyzed data from 100 children aged 6-13 years with T1D using the Tandem Control-IQ CLC system during a randomized trial or subsequent extension phase. Continuous glucose monitor data were collected at baseline and during 12-16 weeks of CLC use. Participants were stratified into quartiles of TIR on CLC to compare clinical characteristics. Results: TIR for those in the first, second, third, and fourth quartiles was 54%, 65%, 71%, and 78%, respectively. Lower baseline TIR was associated with lower TIR on CLC ( r  = 0.69, P  < 0.001). However, lower baseline TIR was also associated with greater improvement in TIR on CLC ( r  = -0.81, P  < 0.001). During CLC, participants in the highest versus lowest TIR-quartile administered more user-initiated boluses daily (8.5 ± 2.8 vs. 5.8 ± 2.6, P  < 0.001) and received fewer automated boluses (3.5 ± 1.0 vs. 6.0 ± 1.6, P  < 0.001). Participants in the lowest (vs. the highest) TIR-quartile received more insulin per body weight (1.13 ± 0.27 vs. 0.87 ± 0.20 U/kg/d, P  = 0.008). However, in a multivariate model adjusting for baseline TIR, user-initiated boluses and insulin-per-body-weight were no longer significant. Conclusions: Higher baseline TIR is the strongest predictor of TIR on CLC in children with T1D. However, lower baseline TIR is associated with the greatest improvement in TIR. As with open-loop systems, user engagement is important for optimal glycemic control.

Introduction: Hybrid closed-loop systems increase time-in-range (TIR) and reduce glycemic variability. Person-reported outcomes (PROs) are essential to assess the utility of new devices and their impact on quality of life. This article focuses on the PROs for pediatric participants (ages 6-13 years) with type 1 diabetes (T1D) and their parents during a trial using the Tandem Control-IQ system, which was shown to increase TIR and improve other glycemic metrics. Research Design and Methods: One hundred and one children 6 to 13 years old with T1D were randomly assigned to closed-loop control (CLC) or sensor-augmented pump (SAP) in a 16-week randomized clinical trial with extension to 28 weeks during which the SAP group crossed over to CLC. Health-related quality of life and treatment satisfaction measures were obtained from children and their parents at baseline, 16 weeks, and 28 weeks. Results: Neither the children in the CLC group nor their parents had statistically significant changes in PRO outcomes compared with the SAP group at the end of the 16-week randomized controlled trial and the 28-week extension. Parents in the CLC group reported nonsignificant improvements in some PRO scores when compared with the SAP group at 16 weeks, which were sustained at 28 weeks. Sleep scores for parents improved from "poor sleep quality" to "adequate sleep quality" between baseline and 16 weeks, however, the change in scores was not statistically different between groups. Conclusions: Children with T1D who used the Control-IQ system did not experience increased burden compared with those using SAP based on person-reported outcomes from the children and their parents. Clinical Trials Registration: NCT03844789.

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  < 0.01) and when using a 110 mg/dL target (71.2% ± 10.2%, P  < 0.01), a 130 mg/dL target (61.5% ± 7.7%, P  < 0.01), and a 140 mg/dL target (64.8% ± 11.6%, P  < 0.01), and among adults using a 130 mg/dL target (75.1% ± 11.6%, P  < 0.05), compared to the ST phase (children: 51.0% ± 13.3% and adults: 65.6% ± 15.7%). There were no serious device-related adverse events reported during the HCL phase, nor were there episodes of severe hypoglycemia or diabetic ketoacidosis. Conclusion: The Omnipod 5 System was safe and effective when used at glucose targets from 110 to 150 mg/dL for 14 days at home in children and adults with T1D.

Background: Glycemic control is particularly challenging for toddlers and preschoolers with type 1 diabetes (T1D), and data on the use of closed-loop systems in this age range are limited. Materials and Methods: We studied use of a modified investigational version of the Tandem t:slim X2 Control-IQ system in children aged 2 to 5 years during 48 h in an outpatient supervised hotel (SH) setting followed by 3 days of home use to examine the safety of this system in young children. Meals and snacks were not restricted and boluses were estimated per parents' usual routine. At least 30 min of daily exercise was required during the SH phase. All participants were remotely monitored by study staff while on closed-loop in addition to monitoring by at least one parent throughout the study. Results: Twelve participants diagnosed with T1D for at least 3 months with mean age 4.7 ± 1.0 years (range 2.0-5.8 years) and hemoglobin A1c of 7.3% ± 0.8% were enrolled at three sites. With use of Control-IQ, the percentage of participants meeting our prespecified goals of less than 6% time below 70 mg/dL and less than 40% time above 180 mg/dL increased from 33% to 83%. Control-IQ use significantly improved percent time in range (70-180 mg/dL) compared to baseline (71.3 ± 12.5 vs. 63.7 ± 15.1, P  = 0.016). All participants completed the study with no adverse events. Conclusions: In this brief pilot study, use of the modified Control-IQ system was safe in 2-5-year-old children with T1D and improved glycemic control.

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  < 0.001), which largely reflected a reduction in time >180 mg/dL (adjusted difference -12% [-2.9 h/day], P  < 0.001). Time <70 mg/dL decreased by 1.6% with CLC versus 0.3% with SAP (adjusted difference -0.7% [-10 min/day], 95% CI -1.0% to -0.2%, P  = 0.002). CLC use averaged 89% of the time for 6 months. The mean adjusted difference in HbA1c after 6 months was 0.30% in CLC versus SAP (95% CI -0.67 to +0.08, P  = 0.13). There was one diabetic ketoacidosis episode in the CLC group. Conclusions: CLC use for 6 months was substantial and associated with improved TIR and reduced hypoglycemia in adolescents and young adults with type 1 diabetes. Thus, CLC has the potential to improve glycemic outcomes in this challenging age group. The clinical trial was registered with ClinicalTrials.gov (NCT03563313).

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 <70 mg/dL before making CR less aggressive was 1.8%, and after the change was 0.7%. Conclusions: No difference in TIR was detected with parameter changes overall, but they may have an effect in higher HbA 1c subgroups or following user-directed boluses, suggesting that changes may matter more in suboptimal control or during discrete periods of the day. Clinical Trials Registration number: NCT03563313.

Objective: To further evaluate the safety and efficacy of the Control-IQ closed-loop control (CLC) system in children with type 1 diabetes., Research Design and Methods: After a 16-week randomized clinical trial (RCT) comparing CLC with sensor-augmented pump (SAP) therapy in 101 children 6-13 years old with type 1 diabetes, 22 participants in the SAP group initiated use of the CLC system (referred to as SAP-CLC cohort), and 78 participants in the CLC group continued use of CLC (CLC-CLC cohort) for 12 weeks., Results: In the SAP-CLC cohort, mean percentage of time in range 70-180 mg/dL (TIR) increased from 55 ± 13% using SAP during the RCT to 65 ± 10% using CLC ( P < 0.001), with 36% of the cohort achieving TIR >70% plus time <54 mg/dL <1% compared with 14% when using SAP ( P = 0.03). Substantial improvement in TIR was seen after the 1st day of CLC. Time <70 mg/dL decreased from 1.80% to 1.34% ( P < 0.001). In the CLC-CLC cohort, mean TIR increased from 53 ± 17% prerandomization to 67 ± 10% during the RCT and remained reasonably stable at 66 ± 10% through the 12 weeks post-RCT. No episodes of diabetic ketoacidosis or severe hypoglycemia occurred in either cohort., Conclusions: This further evaluation of the Control-IQ CLC system supports the findings of the preceding RCT that use of a closed-loop system can safely improve glycemic control in children 6-13 years old with type 1 diabetes from the 1st day of use and demonstrates that these improvements can be sustained through 28 weeks of use., (© 2020 by the American Diabetes Association.)

Background: This study assessed the efficacy and safety of ultrarapid insulin Fiasp ® in the hybrid closed-loop MiniMed™ 670G system. Methods: This was a pilot randomized double-blinded crossover study among established MiniMed™ 670G users comparing percentage time in range (TIR) and hypoglycemia for Novolog ® and Fiasp. After 2 weeks optimization with their home insulin, participants were randomized to receive Novolog or Fiasp for 2 weeks, followed by the other insulin for the next 2 weeks. Data from the second week of blinded insulin use were analyzed to allow 1 week for 670G adaptation. During the second week, individuals were asked to eat the same breakfast for 3 days to assess differences in meal pharmacodynamics. Results: Nineteen adults were recruited with mean age of 40 ± 18 years, diabetes duration of 27 ± 12 years, and median hemoglobin A1c of 7.1% (6.9, 7.5), using 0.72 (0.4, 1.2) units/(kg·day). For Novolog and Fiasp, respectively, the %TIR (70-180 mg/dL) was 75.3 ± 9.5 and 78.4 ± 9.3; %time <70 mg/dL was 3.1 ± 2.1 and 2.3 ± 2.0; %time >180 mg/dL was 21.6 ± 9.0 and 19.3 ± 8.9; mean glucose was 147 ± 12 and 146 ± 12 mg/dL; coefficient of variation was 28.6% ± 4.5% and 26.8% ± 4.4%; %time in auto mode 86.4 ± 9.2 and 84.4 ± 9.2. All comparisons were nonsignificant for insulin type. Total daily dose (Novolog 48.8 ± 28.4 vs. Fiasp 52.4 ± 31.7 units; P  = 0.01) and daily basal (Novolog 17.6 [15.5, 33.8] vs. Fiasp 19.1 [15.3, 38.5] units; P  = 0.07) correlated with TIR and %time >180 mg/dL. For insulin delivery in auto mode there was no statistical difference in total daily dose or daily basal between arms. Paired analysis for matched breakfast meals revealed no significant differences in time to maximum glucose, peak glucose, or glucose excursion. Conclusions: In this pilot study, the use of either Novolog or Fiasp in a commercially available MiniMed 670G system operating in auto mode resulted in clinically similar glycemic outcomes, with a slight increase in daily insulin requirements using Fiasp.

Background: A closed-loop system of insulin delivery (also called an artificial pancreas) may improve glycemic outcomes in children with type 1 diabetes., Methods: In a 16-week, multicenter, randomized, open-label, parallel-group trial, we assigned, in a 3:1 ratio, children 6 to 13 years of age who had type 1 diabetes to receive treatment with the use of either a closed-loop system of insulin delivery (closed-loop group) or a sensor-augmented insulin pump (control group). The primary outcome was the percentage of time that the glucose level was in the target range of 70 to 180 mg per deciliter, as measured by continuous glucose monitoring., Results: A total of 101 children underwent randomization (78 to the closed-loop group and 23 to the control group); the glycated hemoglobin levels at baseline ranged from 5.7 to 10.1%. The mean (±SD) percentage of time that the glucose level was in the target range of 70 to 180 mg per deciliter increased from 53±17% at baseline to 67±10% (the mean over 16 weeks of treatment) in the closed-loop group and from 51±16% to 55±13% in the control group (mean adjusted difference, 11 percentage points [equivalent to 2.6 hours per day]; 95% confidence interval, 7 to 14; P<0.001). In both groups, the median percentage of time that the glucose level was below 70 mg per deciliter was low (1.6% in the closed-loop group and 1.8% in the control group). In the closed-loop group, the median percentage of time that the system was in the closed-loop mode was 93% (interquartile range, 91 to 95). No episodes of diabetic ketoacidosis or severe hypoglycemia occurred in either group., Conclusions: In this 16-week trial involving children with type 1 diabetes, the glucose level was in the target range for a greater percentage of time with the use of a closed-loop system than with the use of a sensor-augmented insulin pump. (Funded by Tandem Diabetes Care and the National Institute of Diabetes and Digestive and Kidney Diseases; ClinicalTrials.gov number, NCT03844789.)., (Copyright © 2020 Massachusetts Medical Society.)

Objective: Limited information is available about glycemic outcomes with a closed-loop control (CLC) system compared with a predictive low-glucose suspend (PLGS) system., Research Design and Methods: After 6 months of use of a CLC system in a randomized trial, 109 participants with type 1 diabetes (age range, 14-72 years; mean HbA 1c , 7.1% [54 mmol/mol]) were randomly assigned to CLC ( N = 54, Control-IQ) or PLGS ( N = 55, Basal-IQ) groups for 3 months. The primary outcome was continuous glucose monitor (CGM)-measured time in range (TIR) for 70-180 mg/dL. Baseline CGM metrics were computed from the last 3 months of the preceding study., Results: All 109 participants completed the study. Mean ± SD TIR was 71.1 ± 11.2% at baseline and 67.6 ± 12.6% using intention-to-treat analysis (69.1 ± 12.2% using per-protocol analysis excluding periods of study-wide suspension of device use) over 13 weeks on CLC vs. 70.0 ± 13.6% and 60.4 ± 17.1% on PLGS (difference = 5.9%; 95% CI 3.6%, 8.3%; P < 0.001). Time >180 mg/dL was lower in the CLC group than PLGS group (difference = -6.0%; 95% CI -8.4%, -3.7%; P < 0.001) while time <54 mg/dL was similar (0.04%; 95% CI -0.05%, 0.13%; P = 0.41). HbA 1c after 13 weeks was lower on CLC than PLGS (7.2% [55 mmol/mol] vs. 7.5% [56 mmol/mol], difference -0.34% [-3.7 mmol/mol]; 95% CI -0.57% [-6.2 mmol/mol], -0.11% [1.2 mmol/mol]; P = 0.0035)., Conclusions: Following 6 months of CLC, switching to PLGS reduced TIR and increased HbA 1c toward their pre-CLC values, while hypoglycemia remained similarly reduced with both CLC and PLGS., (© 2020 by the American Diabetes Association.)

Objective: Assess the efficacy of inControl AP, a mobile closed-loop control (CLC) system., Research Design and Methods: This protocol, NCT02985866, is a 3-month parallel-group, multicenter, randomized unblinded trial designed to compare mobile CLC with sensor-augmented pump (SAP) therapy. Eligibility criteria were type 1 diabetes for at least 1 year, use of insulin pumps for at least 6 months, age ≥14 years, and baseline HbA 1c <10.5% (91 mmol/mol). The study was designed to assess two coprimary outcomes: superiority of CLC over SAP in continuous glucose monitor (CGM)-measured time below 3.9 mmol/L and noninferiority in CGM-measured time above 10 mmol/L., Results: Between November 2017 and May 2018, 127 participants were randomly assigned 1:1 to CLC ( n = 65) versus SAP ( n = 62); 125 participants completed the study. CGM time below 3.9 mmol/L was 5.0% at baseline and 2.4% during follow-up in the CLC group vs. 4.7% and 4.0%, respectively, in the SAP group (mean difference -1.7% [95% CI -2.4, -1.0]; P < 0.0001 for superiority). CGM time above 10 mmol/L was 40% at baseline and 34% during follow-up in the CLC group vs. 43% and 39%, respectively, in the SAP group (mean difference -3.0% [95% CI -6.1, 0.1]; P < 0.0001 for noninferiority). One severe hypoglycemic event occurred in the CLC group, which was unrelated to the study device., Conclusions: In meeting its coprimary end points, superiority of CLC over SAP in CGM-measured time below 3.9 mmol/L and noninferiority in CGM-measured time above 10 mmol/L, the study has demonstrated that mobile CLC is feasible and could offer certain usability advantages over embedded systems, provided the connectivity between system components is stable., (© 2020 by the American Diabetes Association.)

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 <10.0% using insulin pump therapy or multiple daily injections. Meals during HCL were unrestricted, with boluses administered per usual routine. There was daily physical activity. The primary endpoints were percentage of time with sensor glucose <70 and ≥250 mg/dL. Results: Participants were 11 adults, 10 adolescents, and 15 children aged (mean ± standard deviation) 28.8 ± 7.9, 14.3 ± 1.3, and 9.9 ± 1.0 years, respectively. Percentage time ≥250 mg/dL during HCL was 4.5% ± 4.2%, 3.5% ± 5.0%, and 8.6% ± 8.8% per respective age group, a 1.6-, 3.4-, and 2.0-fold reduction compared to ST ( P  = 0.1, P  = 0.02, and P  = 0.03). Percentage time <70 mg/dL during HCL was 1.9% ± 1.3%, 2.5% ± 2.0%, and 2.2% ± 1.9%, a statistically significant decrease in adults when compared to ST ( P  = 0.005, P  = 0.3, and P  = 0.3). Percentage time 70-180 mg/dL increased during HCL compared to ST, reaching significance for adolescents and children: HCL 73.7% ± 7.5% vs. ST 68.0% ± 15.6% for adults ( P  = 0.08), HCL 79.0% ± 12.6% vs. ST 60.6% ± 13.4% for adolescents ( P  = 0.01), and HCL 69.2% ± 13.5% vs. ST 54.9% ± 12.9% for children ( P  = 0.003). Conclusions: The Omnipod personalized MPC algorithm was safe and performed well over 5 days and 4 nights of use by a cohort of participants ranging from youth aged ≥6 years to adults with T1D under supervised free-living conditions with challenges, including daily physical activity and unrestricted meals.

Recent, rapid changes in the treatment of type 1 diabetes have allowed for commercialization of an "artificial pancreas" that is better described as a closed-loop controller of insulin delivery. This review presents the current state of closed-loop control systems and expected future developments with a discussion of the human factor issues in allowing automation of glucose control. The goal of these systems is to minimize or prevent both short-term and long-term complications from diabetes and to decrease the daily burden of managing diabetes. The closed-loop systems are generally very effective and safe at night, have allowed for improved sleep, and have decreased the burden of diabetes management overnight. However, there are still significant barriers to achieving excellent daytime glucose control while simultaneously decreasing the burden of daytime diabetes management. These systems use a subcutaneous continuous glucose sensor, an algorithm that accounts for the current glucose and rate of change of the glucose, and the amount of insulin that has already been delivered to safely deliver insulin to control hyperglycemia, while minimizing the risk of hypoglycemia. The future challenge will be to allow for full closed-loop control with minimal burden on the patient during the day, alleviating meal announcements, carbohydrate counting, alerts, and maintenance. The human factors involved with interfacing with a closed-loop system and allowing the system to take control of diabetes management are significant. It is important to find a balance between enthusiasm and realistic expectations and experiences with the closed-loop system., (Copyright © 2019 Endocrine Society.)

Background: We tested the safety and performance of the "insulin-only" configuration of the bionic pancreas (BP) closed-loop blood-glucose control system in a home-use setting to assess glycemic outcomes using different static and dynamic glucose set-points., Method: This is an open-label non-randomized study with three consecutive intervention periods. Participants had consecutive weeks of usual care followed by the insulin-only BP with (1) an individualized static set-point of 115 or 130 mg/dL and (2) a dynamic set-point that automatically varied within 110 to 130 mg/dL, depending on hypoglycemic risk. Human factors (HF) testing was conducted using validated surveys. The last five days of each study arm were used for data analysis., Results: Thirteen participants were enrolled with a mean age of 28 years, mean A1c of 7.2%, and mean daily insulin dose of 0.6 U/kg (0.4-1.0 U/kg). The usual care arm had an average glucose of 145 ± 20 mg/dL, which increased in the static set-point arm (159 ± 8 mg/dL, P = .004) but not in the dynamic set-point arm (154 ± 10 mg/dL, P = ns). There was no significant difference in time spent in range (70-180 mg/dL) among the three study arms. There was less time <70 mg/dL with both the static (1.8% ± 1.4%, P = .009) and dynamic set-point (2.7±1.5, P = .051) arms compared to the usual-care arm (5.5% ± 4.2%). HF testing demonstrated preliminary user satisfaction and no increased risk of diabetes burden or distress., Conclusions: The insulin-only configuration of the BP using either static or dynamic set-points and initialized only with body weight performed similarly to other published insulin-only systems.

Objective: Artificial pancreas (AP) systems have been shown to improve glycemic control throughout the day and night in adults, adolescents, and children. However, AP testing remains limited during intense and prolonged exercise in adolescents and children. We present the performance of the Tandem Control-IQ AP system in adolescents and children during a winter ski camp study, where high altitude, low temperature, prolonged intense activity, and stress challenged glycemic control., Methods: In a randomized controlled trial, 24 adolescents (ages 13-18 years) and 24 school-aged children (6-12 years) with Type 1 diabetes (T1D) participated in a 48 hours ski camp (∼5 hours skiing/day) at three sites: Wintergreen, VA; Kirkwood, and Breckenridge, CO. Study participants were randomized 1:1 at each site. The control group used remote monitored sensor-augmented pump (RM-SAP), and the experimental group used the t: slim X2 with Control-IQ Technology AP system. All subjects were remotely monitored 24 hours per day by study staff., Results: The Control-IQ system improved percent time within range (70-180 mg/dL) over the entire camp duration: 66.4 ± 16.4 vs 53.9 ± 24.8%; P = .01 in both children and adolescents. The AP system was associated with a significantly lower average glucose based on continuous glucose monitor data: 161 ± 29.9 vs 176.8 ± 36.5 mg/dL; P = .023. There were no differences between groups for hypoglycemia exposure or carbohydrate interventions. There were no adverse events., Conclusions: The use of the Control-IQ AP improved glycemic control and safely reduced exposure to hyperglycemia relative to RM-SAP in pediatric patients with T1D during prolonged intensive winter sport activities., (© 2019 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Using a continuous glucose monitor (CGM) improves glycemic control in patients with type 1 diabetes. The ambulatory glucose profile (AGP) has been recommended as a standard method for reporting CGM data. However, in recently developed automated insulin delivery (AID) systems, a standard format for reporting data has not yet been developed. Instead, reports are specific to each system being used. Currently, the only FDA approved AID system is a hybrid closed-loop insulin pump. In these systems, the patient is still required to announce a meal, respond to alerts, and keep the system in automated insulin delivery. The integrated pump and sensor information provides insights into how the system is performing, and how to make changes to tunable parameters, such as carbohydrate to insulin ratios. The reports also offer a window into human behavior related to performing diabetes tasks, responding to alarms, reasons for exiting HCL, and how glycemic goals are being met. This article reviews the pump and CGM data provided by several of the current closed-loop systems with a focus on systems that are currently approved in the United States (MiniMed™ 670G, Tandem Basal:IQ) and those used by patients using do-it-yourself systems. A step-wise approach to reviewing the nuances of these systems is provided. The comparison may reinforce the importance of the continued need for streamlining a standard report for providers to be able to interpret the CGM data of these systems.

Background: There is growing evidence to suggest that the brain is an important target for insulin action, and that states of insulin resistance may extend to the CNS with detrimental effects on cognitive functioning. Although the effect of systemic insulin resistance on peripheral organs is well-studied, the degree to which insulin impacts brain function in vivo remains unclear., Methods: This randomized, single-blinded, 2-way-crossover, sham-controlled, pilot study determined the effects of hyperinsulinemia on fMRI brain activation during a 2-back working memory task in 9 healthy older adults (aged 57-79 years). Each participant underwent two clamp procedures (an insulin infusion and a saline placebo infusion, with normoglycemia maintained during both conditions), to examine the effects of hyperinsulinemia on task performance and associated blood-oxygen-level dependent (BOLD) signal using fMRI., Results: Hyperinsulinemia (compared to saline control) was associated with an increase in both the spatial extent and relative strength of task-related BOLD signal during the 2-back task. Further, the degree of increased task-related activation in select brain regions correlated with greater systemic insulin sensitivity, as well as decreased reaction times and performance accuracy between experimental conditions., Conclusion: Together, these findings provide evidence of insulin action in the CNS among older adults during periods of sustained cognitive demand, with the greatest effects noted for individuals with highest systemic insulin sensitivity., Funding: This work was funded by the National Institutes of Health (5R21AG051958, 2016).

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 <70 mg/dL (1.7% [1.3%-2.1%] vs. 0.9% [0.3%-2.7%]; not significant). The HCL system was active for 94.4% of the study period. Subjects reported that use of the system was associated with less time thinking about diabetes, decreased worry about blood sugars, and decreased burden in managing diabetes., Conclusions: The use of the Tandem t:slim X2 with Control-IQ HCL AP system significantly improved time in range and mean glycemic control without increasing hypoglycemia in school-aged children with T1D during remote monitored home use.

Objective: This study evaluated a new insulin delivery system designed to reduce insulin delivery when trends in continuous glucose monitoring (CGM) glucose concentrations predict future hypoglycemia., Research Design and Methods: Individuals with type 1 diabetes ( n = 103, age 6-72 years, mean HbA 1c 7.3% [56 mmol/mol]) participated in a 6-week randomized crossover trial to evaluate the efficacy and safety of a Tandem Diabetes Care t:slim X2 pump with Basal-IQ integrated with a Dexcom G5 sensor and a predictive low-glucose suspend algorithm (PLGS) compared with sensor-augmented pump (SAP) therapy. The primary outcome was CGM-measured time <70 mg/dL., Results: Both study periods were completed by 99% of participants; median CGM usage exceeded 90% in both arms. Median time <70 mg/dL was reduced from 3.6% at baseline to 2.6% during the 3-week period in the PLGS arm compared with 3.2% in the SAP arm (difference [PLGS - SAP] = -0.8%, 95% CI -1.1 to -0.5, P < 0.001). The corresponding mean values were 4.4%, 3.1%, and 4.5%, respectively, represent-ing a 31% reduction in the time <70 mg/dL with PLGS. There was no increase in mean glucose concentration (159 vs. 159 mg/dL, P = 0.40) or percentage of time spent >180 mg/dL (32% vs. 33%, P = 0.12). One severe hypoglycemic event occurred in the SAP arm and none in the PLGS arm. Mean pump suspension time was 104 min/day., Conclusions: The Tandem Diabetes Care Basal-IQ PLGS system significantly reduced hypoglycemia without rebound hyperglycemia, indicating that the system can benefit adults and youth with type 1 diabetes in improving glycemic control., (© 2018 by the American Diabetes Association.)

Objective: The primary objective of this trial was to evaluate the feasibility, safety, and efficacy of a predictive hyperglycemia and hypoglycemia minimization (PHHM) system vs predictive low glucose suspension (PLGS) alone in optimizing overnight glucose control in children 6 to 14 years old., Research Design and Methods: Twenty-eight participants 6 to 14 years old with T1D duration ≥1 year with daily insulin therapy ≥12 months and on insulin pump therapy for ≥6 months were randomized per night into PHHM mode or PLGS-only mode for 42 nights. The primary outcome was percentage of time in sensor-measured range 70 to 180 mg/dL in the overnight period., Results: The addition of automated insulin delivery with PHHM increased time in target range (70-180 mg/dL) from 66 ± 11% during PLGS nights to 76 ± 9% during PHHM nights (P<.001), without increasing hypoglycemia as measured by time below various thresholds. Average morning blood glucose improved from 176 ± 28 mg/dL following PLGS nights to 154 ± 19 mg/dL following PHHM nights (P<.001)., Conclusions: The PHHM system was effective in optimizing overnight glycemic control, significantly increasing time in range, lowering mean glucose, and decreasing glycemic variability compared to PLGS alone in children 6 to 14 years old., (© 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Background: The accuracy of point-of-care blood glucose (BG) meters is important for the detection of dysglycemia, calculation of insulin doses, and the calibration of continuous glucose monitors. The objective of this study was to compare the accuracy of commercially available glucose meters in a challenging laboratory study using samples with a wide range of reference BG and hemoglobin values., Methods: Fresh, discarded blood samples from a hospital STAT laboratory were either used without modification, spiked with a glucose solution, or incubated at 37°C to produce 347 samples with an even distribution across reference BG levels from 20 to 440 mg/dl and hemoglobin values from 9 to 16 g/dl. We measured the BG of each sample with 17 different commercially available glucose meters and the reference method (YSI 2300) at the same time. We determined the mean absolute relative difference (MARD) for each glucose meter, overall and stratified by reference BG and by hemoglobin level., Results: The accuracy of different meters widely, exhibiting a range of MARDs from 5.6% to 20.8%. Accuracy was lower in the hypoglycemic range, but was not consistently lower in samples with anemic blood hemoglobin levels., Conclusions: The accuracy of commercially available glucose meters varies widely. Although the sample mix in this study was much more challenging than those that would be collected under most use conditions, some meters were robust to these challenges and exhibited high accuracy in this setting. These data on relative accuracy and robustness to challenging samples may be useful in informing the choice of a glucose meter.