Diabetes technology in people with diabetes and advanced chronic kidney disease.

Diabetes is the leading cause and a common comorbidity of advanced chronic kidney disease. Glycaemic management in this population is challenging and characterised by frequent excursions of hypoglycaemia and hyperglycaemia. Current glucose monitoring tools, such as HbA1c, fructosamine and glycated albumin, have biases in this population and provide information only on mean glucose exposure. Revolutionary developments in glucose sensing and insulin delivery technology have occurred in the last decade. Newer factory-calibrated continuous glucose monitors provide real-time glucose data, with predictive alarms, allowing improved assessment of glucose excursions and preventive measures, particularly during and between dialysis sessions. Furthermore, integration of continuous glucose monitors and their predictive alerts with automated insulin delivery systems enables insulin administration to be decreased or stopped proactively, leading to improved glycaemic management and diminishing glycaemic fluctuations. While awaiting regulatory approval, emerging studies, expert real-world experience and clinical guidelines support the use of diabetes technology devices in people with diabetes and advanced chronic kidney disease.

Macroergonomic components of the patient work system shaping dyadic care management during adolescence: a case study of type 1 diabetes.

The role of the social, physical, and organisational environments in shaping how patients and their caregivers perform work remains largely unexplored in human factors/ergonomics literature. This study recruited 19 dyads consisting of a parent and their child with type 1 diabetes to be interviewed individually and analysed using a macroergonomic framework. Our findings aligned with the macroergonomic factors as presented in previous models, while highlighting the need to expand upon certain components to gain a more comprehensive representation of the patient work system as relevant to dyadic management. Examples of design efforts that should follow from these findings include expanding existing data sharing options to include information from the external environment and capitalising on the capabilities of artificial intelligence as a decision support system. Future research should focus on longitudinally assessing patient work systems throughout transition periods in addition to more explicitly exploring the roles of social network members.

Work performed by patients and their caregivers is shaped by the social, physical, and organisational contexts they are embedded within. This paper explored how adolescents with type 1 diabetes managed their health alongside their parents in the context of these macroergonomic factors. These findings have implications for research and design.

A Randomized Trial of Closed-Loop Control in Children with Type 1 Diabetes.

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.).

Sleep and diabetes-specific psycho-behavioral outcomes of a new automated insulin delivery system in young children with type 1 diabetes and their parents.

BACKGROUND: Data on the use of Control-IQ, the latest FDA-approved automated insulin delivery (AID) system for people with T1D 6 years of age or older is still scarce, particularly regarding nonglycemic outcomes. Children with T1D and their parents are at higher risk for sleep disturbances. This study assesses sleep, psycho-behavioral and glycemic outcomes of AID compared to sensor-augmented pump therapy (SAP) therapy in young children with T1D and their parents. METHODS: Thirteen parents and their young children (ages 7-10) on insulin pump therapy were enrolled. Children completed an initial 4-week study with SAP using their own pump and a study CGM followed by a 4-week phase of AID. Sleep outcomes for parents and children were evaluated through actigraphy watches. Several questionnaires were administered at baseline and at the end of each study phase. CGM data were used to assess glycemic outcomes. RESULTS: Actigraphy data did not show any significant change from SAP to AID, except a reduction of number of parental awakenings during the night (p = 0.036). Parents reported statistically significant improvements in Pittsburgh Sleep Quality Index total score (p = 0.009), Hypoglycemia Fear Survey total score (p = 0.011), diabetes-related distress (p = 0.032), and depression (p = 0.023). While on AID, time in range (70-180 mg/dL) significantly increased compared to SAP (p < 0.001), accompanied by a reduction in hyperglycemia (p = 0.001). CONCLUSIONS: These results suggest that use of AID has a positive impact on glycemic outcomes in young children as well as sleep and diabetes-specific quality of life outcomes in their parents.

Closed loop control in adolescents and children during winter sports: Use of the Tandem Control-IQ AP system.

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.

Heart rate informed artificial pancreas system enhances glycemic control during exercise in adolescents with T1D.

OBJECTIVE: To evaluate the safety and performance of using a heart rate (HR) monitor to inform an artificial pancreas (AP) system during exercise among adolescents with type 1 diabetes (T1D). MATERIALS AND METHODS: In a randomized, cross-over trial, adolescents with T1D age 13 - 18 years were enrolled to receive on separate days either the unmodified UVa AP (stdAP) or an AP system connected to a portable HR monitor (AP-HR) that triggered an exercise algorithm for blood glucose (BG) control. During admissions participants underwent a structured exercise regimen. Hypoglycemic events and CGM tracings were compared between the two admissions, during exercise and for the full 24-hour period. RESULTS: Eighteen participants completed the trial. While number of hypoglycemic events during exercise and rest was not different between visits (0.39 AP-HR vs 0.50 stdAP), time below 70 mg dL -1 was lower on AP-HR compared to stdAP, 0.5±2.1% vs 7.4±12.5% (P = 0.028). Time with BG within 70-180 mg dL -1 was higher for the AP-HR admission vs stdAP during the exercise portion and overall (96% vs 87%, and 77% vs 74%), but these did not reach statistical significance (P = 0.075 and P = 0.366). CONCLUSIONS: Heart rate signals can safely and efficaciously be integrated in a wireless AP system to inform of physical activity. While exercise contributes to hypoglycemia among adolescents, even when using an AP system, informing the system of exercise via a HR monitor improved time <70 mg dL -1 . Nonetheless, it did not significantly reduce the total number of hypoglycemic events, which were low in both groups.

Use of an artificial pancreas among adolescents for a missed snack bolus and an underestimated meal bolus.

OBJECTIVE: The objective of this study was to evaluate the safety and performance of the artificial pancreas (AP) in adolescents with type 1 diabetes (T1D) following insulin omission for food. RESEARCH DESIGN AND METHODS: In a randomized, cross-over trial, adolescents with T1D aged 13-18 yr were enrolled in a randomized, cross-over trial. On separate days, received either usual care (UC) through their home insulin pump or used an AP system (Diabetes Assistant platform, continuous glucose monitor, and insulin pump). Approximately 1 h after admission, participants in both groups received an unannounced snack of 30 g carbohydrate, and 4 h later they received an 80 g lunch, for which both groups only received 75% of the calculated insulin dose to cover carbohydrates. On the UC day (but not the AP day), they received their full high blood glucose (BG) correction factor at lunch. Each admission lasted approximately 8 h. RESULTS: A total of 16 participants completed the trial. On the AP day (compared to UC), mean BG was lower (197 ± 10 vs. 235 ± 14 mg/dL) and time in range 70-180 mg/dL was higher (43% ± 7 vs. 19% ± 7) (both p < 0.05) overall; these results held in the time following the snack and meal (also p < 0.05). During the trial, there were no differences between groups in the rate of hypoglycemia <70 mg/dL. CONCLUSIONS: The AP provided improvements in short-term glycemic control without increases in hypoglycemia following missed insulin for food in adolescents. Thus, the AP partly compensates for missed insulin boluses for food, a common occurrence in adolescent diabetes care. Further testing is needed in longer-term settings.

The Diabetes Technology Society Error Grid and Trend Accuracy Matrix for Glucose Monitors.

INTRODUCTION: An error grid compares measured versus reference glucose concentrations to assign clinical risk values to observed errors. Widely used error grids for blood glucose monitors (BGMs) have limited value because they do not also reflect clinical accuracy of continuous glucose monitors (CGMs). METHODS: Diabetes Technology Society (DTS) convened 89 international experts in glucose monitoring to (1) smooth the borders of the Surveillance Error Grid (SEG) zones and create a user-friendly tool-the DTS Error Grid; (2) define five risk zones of clinical point accuracy (A-E) to be identical for BGMs and CGMs; (3) determine a relationship between DTS Error Grid percent in Zone A and mean absolute relative difference (MARD) from analyzing 22 BGM and nine CGM accuracy studies; and (4) create trend risk categories (1-5) for CGM trend accuracy. RESULTS: The DTS Error Grid for point accuracy contains five risk zones (A-E) with straight-line borders that can be applied to both BGM and CGM accuracy data. In a data set combining point accuracy data from 18 BGMs, 2.6% of total data pairs equally moved from Zones A to B and vice versa (SEG compared with DTS Error Grid). For every 1% increase in percent data in Zone A, the MARD decreased by approximately 0.33%. We also created a DTS Trend Accuracy Matrix with five trend risk categories (1-5) for CGM-reported trend indicators compared with reference trends calculated from reference glucose. CONCLUSION: The DTS Error Grid combines contemporary clinician input regarding clinical point accuracy for BGMs and CGMs. The DTS Trend Accuracy Matrix assesses accuracy of CGM trend indicators.

Continuous glucose monitoring for inpatient diabetes management: an update on current evidence and practice.

Over the last few years, several exciting changes in continuous glucose monitoring (CGM) technology have expanded its use and made CGM the standard of care for patients with type 1 and type 2 diabetes using insulin therapy. Consequently, hospitals started to notice increased use of these devices in their hospitalized patients. Furthermore during the coronavirus disease 2019 (COVID) pandemic, there was a critical need for innovative approaches to glycemic monitoring, and several hospitals started to implement CGM protocols in their daily practice. Subsequently, a plethora of studies have demonstrated the efficacy and safety of CGM use in the hospital, leading to clinical practice guideline recommendations. Several studies have also suggested that CGM has the potential to become the standard of care for some hospitalized patients, overcoming the limitations of current capillary glucose testing. Albeit, there is a need for more studies and particularly regulatory approval. In this review, we provide a historical overview of the evolution of glycemic monitoring in the hospital and review the current evidence, implementation protocols, and guidance for the use of CGM in hospitalized patients.

Effect of an Automated Advice Algorithm (CloudConnect) on Adolescent-Parent Diabetes-Specific Communication and Glycemic Management: A Randomized Trial.

INTRODUCTION: Because adolescence is a time of difficult management of Type 1 diabetes (T1D) in part from adolescent-parent shared responsibility of T1D management, our objective was to assess the effects of a decision support system (DSS) CloudConnect on T1D-related communication between adolescents and their parents and on glycemic management. METHODS: We followed 86 participants including 43 adolescents with T1D (not on automated insulin delivery systems, AID) and their parents/care-giver for a 12-week intervention of UsualCare + CGM or CloudConnect, which included a Weekly Report of automated T1D advice, including insulin dose adjustments, based on data from continuous glucose monitors (CGM), Fitbit and insulin use. Primary outcome was T1D-specific communication and secondary outcomes were hemoglobin A1c, time-in-target range (TIR) 70-180 mg/dl, and additional psychosocial scales. RESULTS: Adolescents and parents reported a similar amount of T1D-related communication in both the UsualCare + CGM or CloudConnect groups and had similar levels of final HbA1c. Overall blood glucose time in range 70-180 mg/dl and time below 70 mg/dl were not different between groups. Parents but not children in the CloudConnect group reported less T1D-related conflict; however, compared to the UsualCare + CGM group, adolescents and parents in the CloudConnect reported a more negative tone of T1D-related communication. Adolescent-parent pairs in the CloudConnect group reported more frequent changes in insulin dose. There were no differences in T1D quality of life between groups. CONCLUSIONS: While feasible, the CloudConnect DSS system did not increase T1D communication or provide improvements in glycemic management. Further efforts are needed to improve T1D management in adolescents with T1D not on AID systems.

Feasibility of Spotlight Consultations Tool in Routine Care: Real-World Evidence.

BACKGROUND: Burnout in people with diabetes and healthcare professionals (HCPs) is at an all-time high. Spotlight AQ, a novel "smart" adaptive patient questionnaire, is designed to improve consultations by rapidly identifying patient priorities and presenting these in the context of best-practice care pathways to aid consultations. We aimed to determine Spotlight AQ's feasibility in routine care. MATERIALS AND METHODS: The Spotlight prototype tool was trialed at three centers: two UK primary care centers and one US specialist center (June-September 2020). Participants with type 1 (T1D) or type 2 diabetes (T2D) completed the questionnaire prior to their routine consultations. Results were immediately available and formed the basis of the clinical discussion and decision-making within the clinic visit. RESULTS: A convenience sample of 49 adults took part, n=31 T1D, (n=18 female); and n=18 T2D (n=10 male, n=4 female, n=4 gender unreported). Each identified two priority concerns. "Psychological burden of diabetes" was the most common priority concern (T1D n = 27, 87.1%) followed by "gaining more skills about particular aspects of diabetes" (T1D n=19, 61.3%), "improving support around me" (n=8, 25.8%) and "diabetes-related treatment issues" (n=8, 25.8%). Burden of diabetes was widespread as was lack of confidence around self-management. Similarly, psychological burden of diabetes was the primary concern for participants with T2D (n=18,100%) followed by "gaining more skills about aspects of diabetes" (n=7, 38.9%), "improving support around me" (n=7, 38.9%) and "diabetes-related treatment issues" (n=4; 22.2%). CONCLUSIONS: Spotlight AQ is acceptable and feasible for use in routine care. Gaining more skills and addressing the psychological burden of diabetes are high-priority areas that must be addressed to reduce high levels of distress.

The Impact of a Recently Approved Automated Insulin Delivery System on Glycemic, Sleep, and Psychosocial Outcomes in Older Adults With Type 1 Diabetes: A Pilot Study.

BACKGROUND: Older adults with type 1 diabetes (≥65 years) are often under-represented in clinical trials of automated insulin delivery (AID) systems. We sought to test the efficacy of a recently FDA-approved AID system in this population. METHODS: Participants with type 1 diabetes used sensor-augmented pump (SAP) therapy for four weeks and then used an AID system (Control-IQ) for four weeks. In addition to glucose control variables, patient-reported outcomes (PRO) were assessed with questionnaires and sleep parameters were assessed by actigraphy. RESULTS: Fifteen older adults (mean age 68.7 ± 3.3, HbA1c of 7.0 ± 0.8) completed the pilot trial. Glycemic outcomes improved during AID compared to SAP. During AID use, mean glucose was 146.0 mg/dL; mean percent time in range (TIR, 70-180 mg/dL) was 79.6%; median time below 70 mg/dL was 1.1%. The AID system was in use 92.6% ± 7.0% of the time. Compared to SAP, while participants were on AID the TIR increased significantly (+10%, P = .002) accompanied by a reduction in both time above 180 mg/dL (-6.9%, P = .005) and below 70 mg/dl (-0.4%, P = .053). Diabetes-related distress decreased significantly while using AID (P = .028), but sleep parameters remained unchanged. CONCLUSIONS: Use of this AID system in older adults improved glycemic control with high scores in ease of use, trust, and usability. Participants reported an improvement in diabetes distress with AID use. There were no significant changes in sleep.

Extended Use of the Control-IQ Closed-Loop Control System in Children With Type 1 Diabetes.

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.

Predictors of Time-in-Range (70-180 mg/dL) Achieved Using a Closed-Loop Control System.

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.

Social Inequality and Diabetes: A Commentary.

Socioeconomic inequality of access to healthcare is seen across the spectrum of healthcare, including diabetes. Health inequalities are defined as the 'preventable, unfair and unjust differences in health status between groups, populations or individuals that arise from the unequal distribution of social, environmental and economic conditions within societies, which determine the risk of people getting ill, their ability to prevent sickness or opportunities to take action and access treatment when ill health occurs' (NHS England; https://www.england.nhs.uk/about/equality/equality-hub/resources/). Access to diabetes technologies has improved glycaemic and quality-of-life outcomes for many users. Inability to access such devices, however, is evidenced in National Diabetes Audit data, with a reported tenfold variation in insulin pump use by people with type 1 diabetes across specialist centres. This variation suggests a lack of access to healthcare systems that should be investigated. This article highlights some of the key issues surrounding healthcare inequalities in the management of diabetes.

The Use of a Smart Bolus Calculator Informed by Real-time Insulin Sensitivity Assessments Reduces Postprandial Hypoglycemia Following an Aerobic Exercise Session in Individuals With Type 1 Diabetes.

OBJECTIVE: Insulin dosing in type 1 diabetes (T1D) is oftentimes complicated by fluctuating insulin requirements driven by metabolic and psychobehavioral factors impacting individuals' insulin sensitivity (IS). In this context, smart bolus calculators that automatically tailor prandial insulin dosing to the metabolic state of a person can improve glucose management in T1D. RESEARCH DESIGN AND METHODS: Fifteen adults with T1D using continuous glucose monitors (CGMs) and insulin pumps completed two 24-h admissions in a hotel setting. During the admissions, participants engaged in an early afternoon 45-min aerobic exercise session, after which they received a standardized dinner meal. The dinner bolus was computed using a standard bolus calculator or smart bolus calculator informed by real-time IS estimates. Glucose control was assessed in the 4 h following dinner using CGMs and was compared between the two admissions. RESULTS: The IS-informed bolus calculator allowed for a reduction in postprandial hypoglycemia as quantified by the low blood glucose index (2.02 vs. 3.31, P = 0.006) and percent time <70 mg/dL (8.48% vs. 15.18%, P = 0.049), without increasing hyperglycemia (high blood glucose index: 3.13 vs. 2.09, P = 0.075; percent time >180 mg/dL: 13.24% vs. 10.42%, P = 0.5; percent time >250 mg/dL: 2.08% vs. 1.19%, P = 0.317). In addition, the number of hypoglycemia rescue treatments was reduced from 12 to 7 with the use of the system. CONCLUSIONS: The study shows that the proposed IS-informed bolus calculator is safe and feasible in adults with T1D, appropriately reducing postprandial hypoglycemia following an exercise-induced IS increase.

Safety and Efficacy of Initializing the Control-IQ Artificial Pancreas System Based on Total Daily Insulin in Adolescents with Type 1 Diabetes.

Objective: To assess the safety and efficacy of a simplified initialization for the Tandem t:slim X2 Control-IQ hybrid closed-loop system, using parameters based on total daily insulin ("MyTDI") in adolescents with type 1 diabetes under usual activity and during periods of increased exercise. Research Design and Methods: Adolescents with type 1 diabetes 12-18 years of age used Control-IQ for 5 days at home using their usual parameters. Upon arrival at a 60-h ski camp, participants were randomized to either continue Control-IQ using their home settings or to reinitialize Control-IQ with MyTDI parameters. Control-IQ use continued for 5 days following camp. The effect of MyTDI on continuous glucose monitoring outcomes were analyzed using repeated measures analysis of variance (ANOVA): baseline, camp, and at home. Results: Twenty participants were enrolled and completed the study; two participants were excluded from the analysis due to absence from ski camp (1) and illness (1). Time in range was similar between both groups at home and camp. A tendency to higher time <70 mg/dL in the MyTDI group was present but only during camp (median 3.8% vs. 1.4%, P = 0.057). MyTDI users with bolus/TDI ratios >40% tended to show greater time in the euglycemic range improvements between baseline and home than users with ratios <40% (+16.3% vs. -9.0%, P = 0.012). All participants maintained an average of 95% time in closed loop (84.1%-100%). Conclusions: MyTDI is a safe, effective, and easy way to determine insulin parameters for use in the Control-IQ artificial pancreas. Future modifications to account for the influence of carbohydrate intake on MyTDI calculations might further improve time in range.

Successful At-Home Use of the Tandem Control-IQ Artificial Pancreas System in Young Children During a Randomized Controlled Trial.

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.