"Obviously, Nothing's Gonna Happen in Five Minutes": How Adolescents and Young Adults Infrastructure Resources to Learn Type 1 Diabetes Management.

Learning personalized self-management routines is pivotal for people with type 1 diabetes (T1D), particularly early in diagnosis. Context-aware technologies, such as hybrid closed-loop (HCL) insulin pumps, are important tools for diabetes self-management. However, clinicians have observed that practices using these technologies involve significant individual differences. We conducted interviews with 20 adolescents and young adults who use HCL insulin pump systems for managing T1D, and we found that these individuals leverage both technological and non-technological means to maintain situational awareness about their condition. We discuss how these practices serve to infrastructure their self-management routines, including medical treatment, diet, and glucose measurement-monitoring routines. Our study provides insights into adolescents' and young adults' lived experiences of using HCL systems and related technology to manage diabetes, and contributes to a more nuanced understanding of how the HCI community can support the contextualized management of diabetes through technology design.

Frequency and Causes of Nocturnal Alarms in Youth and Young Adults With Type 1 Diabetes Using a First-Generation Hybrid Closed-Loop System.

Background: Meeting glycemic recommendations is challenging for youth with type 1 diabetes. Diabetes technology, including continuous glucose monitoring (CGM) and hybrid closed-loop (HCL) automated insulin delivery systems, significantly increase achievement of glycemic targets; however, many youth struggle to sustain use of early HCL systems. Nocturnal alarm fatigue contributes to disrupted sleep and device discontinuation. Methods: We examined the frequency and causes of nocturnal (10:00 p.m. to 6:00 a.m.) alarms in pediatric patients (N = 76, median age 14.5 years [interquartile range 11.8-17.0 years, range 7-24 years]) starting on a first-generation HCL system in a prospective observational study. Device data were analyzed with linear mixed-effects models to examine change across time at 3-month intervals for 12 months. Results: At baseline (HCL system in nonautomated mode), participants averaged 3.3 ± 0.6 alarms per night. In the 2 weeks after starting HCL (automated) mode, alarm frequency significantly increased to 5.4 ± 0.5 times per night (P <0.001). Alarm frequency decreased through the remainder of the observational period; however, CGM sensor and HCL system use also declined. The types of alarms were evenly distributed among sensor maintenance, sensor threshold, pump, and HCL-specific alarms. Conclusion: These data show that HCL system nocturnal alarms are frequent and may be barriers to sleep quality and device use. Further research is needed to assess the impact of diabetes technology on sleep and to determine method to improve sleep quality with technology use.

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

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

Safety and Feasibility Evaluation of Automated User Profile Settings Initialization and Adaptation With Control-IQ Technology.

BACKGROUND: Optimization of automated insulin delivery (AID) settings is required to achieve desirable glycemic outcomes. We evaluated safety and efficacy of a computerized system to initialize and adjust insulin delivery settings for the t:slim X2 insulin pump with Control-IQ technology in adults with type 1 diabetes (T1D). METHODS: After a 2-week continuous glucose monitoring (CGM) run-in period, adults with T1D using multiple daily injections (MDI) (N = 33, mean age 36.1 years, 57.6% female, diabetes duration 19.7 years) were transitioned to 13 weeks of Control-IQ technology usage. A computerized algorithm generated recommendations for initial pump settings (basal rate, insulin-to-carbohydrate ratio, and correction factor) and weekly follow-up settings to optimize glycemic outcomes. Physicians could override the automated settings changes for safety concerns. RESULTS: Time in range 70 to 180 mg/dL improved from 45.7% during run-in to 69.1% during the last 30 days of Control-IQ use, a median improvement of 18.8% (95% confidence interval [CI]: 13.6-23.9, P < .001). This improvement was evident early in the study and was sustained over 13 weeks. Time <70 mg/dL showed a gradual decreasing trend over time. Percentage of participants achieving HbA1c <7% went from zero at baseline to 55% at study end (P < .001). Only six of the 318 automated settings adaptations (1.9%) were overridden by study investigators. CONCLUSIONS: Computerized initiation and adaptation of Control-IQ technology settings from baseline MDI therapy was safe in adults with T1D. The use of this simplified system for onboarding and optimizing Control-IQ technology may be useful to increase uptake of AID and reduce staff and patient burden in clinical care.

Smartphone Bolus Feature Increases Number of Insulin Boluses in People With Low Bolus Frequency.

BACKGROUND: The t:connect mobile app from Tandem Diabetes Care recently added a feature to allow t:slim X2 insulin pump users to initiate an insulin bolus from their personal smartphone. User experience and user interface considerations prioritized safety and ease of use, and we examined whether the smartphone bolus feature changed bolus behavior in individuals who bolused less than three times/day. METHODS: We performed a retrospective analysis of t:slim X2 insulin pump users in the United States who had remotely updated their insulin pump software to be compatible with the smartphone bolus version of the app and who gave less than three boluses per day prior to the smartphone bolus update. RESULTS: Of the 4470 early adopters who met these criteria, the median number of boluses was 2.2 per day (prior to smartphone bolus update) versus 2.7 per day (after smartphone bolus update), equating to approximately half a bolus more delivered per day (P < .001). Overall, a median of one bolus per day was administered by smartphone app as opposed to being initiated from the screen on the insulin pump. CONCLUSION: This analysis found a significant increase in bolusing behavior among early adopters of the smartphone bolus feature of the t:connect mobile app.

Real-World Use of Control-IQ Technology Is Associated with a Lower Rate of Severe Hypoglycemia and Diabetic Ketoacidosis Than Historical Data: Results of the Control-IQ Observational (CLIO) Prospective Study.

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

Therapy Settings Associated with Optimal Outcomes for t:slim X2 with Control-IQ Technology in Real-World Clinical Care.

Objective: To determine insulin dosing parameters that are associated with and predict optimal outcomes for people using t:slim X2 with Control-IQ technology (CIQ). Methods: Retrospective deidentified data from CIQ users were analyzed to determine the effect of Correction Factor, Carbohydrate-to-Insulin (C:I) Ratio, and basal rate settings (standardized by total daily insulin [TDI]) on glycemic control. We performed an associative analysis followed by linear regressions to determine the relative importance of the settings and confounding variables (e.g., age or number of user-initiated boluses) in predicting consensus glycemic outcomes. Results: Data from 20,764 individuals were analyzed (median age 39 years [interquartile range 19, 59], 55% female, TDI 46.4 U [33-65.2]). More aggressive Correction Factor settings, C:I ratio settings, and basal programs were all strongly associated with higher time in range (TIR, 70-180 mg/dL) and to a lesser degree to higher time <70 mg/dL. In linear regression, more aggressive Correction Factor predicted higher TIR, lower coefficient of variation, and importantly had only negligible impact on time below range. Higher basal rate settings and lower C:I ratio predicted increased TIR as well as increased hypoglycemia. The most important predictor in all glycemic outcomes was the average number of user-given boluses per day. Conclusion: Basal rates, C:I ratios, and Correction Factor settings all impact glycemic outcomes in CIQ users in usual clinical care. The correction Factor setting may be the most impactful "lever to pull" for clinicians and CIQ users to optimize TIR while not increasing hypoglycemia.

Situational Awareness and Proactive Engagement Predict Higher Time in Range in Adolescents and Young Adults Using Hybrid Closed-Loop.

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

Increasing Use of Diabetes Devices: What Do Health Care Professionals Need?

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

Health Care Professional Experiences and Opinions on Depression and Suicide in People With Diabetes.

OBJECTIVE: People with diabetes have an increased risk of depression, intentional self-injury and self-harm (ISI), and suicide compared with the general population. This study aimed to explore experiences and awareness of health care professionals (HCPs) regarding depression, ISI, and suicide, and understand resource use and needs among HCPs who care for persons with diabetes (PWD). METHODS: Health care professionals who see children and/or adults with type 1 diabetes or type 2 diabetes anonymously completed an online survey about their experiences, opinions, barriers, and needs surrounding identification and care of PWD with depression, ISI, and suicide. RESULTS: One hundred twenty-nine HCPs participated. The majority were medical doctors (MDs) or advanced practice providers (APPs). Only a quarter of MDs and APPs felt very comfortable asking about ISI or suicidal ideation (SI), whereas 20% felt they had received appropriate training to support those with ISI or SI. The primary needs reported include more training on how to ask, respond, and support those expressing ISI and SI. Health care professionals reported wanting better access to resources for PWD. DISCUSSION: The HCPs tend to underestimate SI in the diabetes population and rates of training were low. Areas to address include providing education and training to HCPs to improve identification and management of ISI and suicide risk. These data can inform the development of mechanisms to improve discussions of depression and suicide and of resources to help HCPs support PWD.

Effect of Tight Glycemic Control on Pancreatic Beta Cell Function in Newly Diagnosed Pediatric Type 1 Diabetes: A Randomized Clinical Trial.

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.

Effect of Verapamil on Pancreatic Beta Cell Function in Newly Diagnosed Pediatric Type 1 Diabetes: A Randomized Clinical Trial.

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.

Evaluation of a New Clinical Tool to Enhance Clinical Care of Control-IQ Users.

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

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

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

Multicenter, Randomized Trial of a Bionic Pancreas in Type 1 Diabetes.

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.).

Positive Impact of the Bionic Pancreas on Diabetes Control in Youth 6-17 Years Old with Type 1 Diabetes: A Multicenter Randomized Trial.

Objective: To evaluate the insulin-only configuration of the iLet® bionic pancreas (BP) in youth 6-17 years old with type 1 diabetes (T1D). Research Design and Methods: In this multicenter, randomized, controlled trial, 165 youth with T1D (6-17 years old; baseline HbA1c 5.8%-12.2%; 35% using multiple daily injections, 36% using an insulin pump without automation, 4% using an insulin pump with low glucose suspend, and 25% using a hybrid closed-loop system before the study) were randomly assigned 2:1 to use BP (n = 112) with insulin aspart or insulin lispro (BP group) or to a control group (n = 53) using their personal standard care insulin delivery (SC group) plus real-time continuous glucose monitoring (CGM). The primary outcome was HbA1c at 13 weeks. Results: Mean HbA1c decreased from 8.1% ± 1.2% at baseline to 7.5% ± 0.7% at 13 weeks with BP versus 7.8% ± 1.1% at both baseline and 13 weeks with SC (adjusted difference = -0.5%, 95% CI -0.7% to -0.2%, P < 0.001). Participants with baseline HbA1c ≥9.0% (n = 34) decreased mean HbA1c from 9.7% ± 0.8% to 7.9% ± 0.6% after 13 weeks with BP compared with 9.7% ± 0.5% to 9.8% ± 0.8% with SC. Over 13 weeks, mean time in range (TIR) 70-180 mg/dL increased by 10% (2.4 h per day) and mean CGM glucose was reduced by 15 mg/dL with BP compared with SC (P < 0.001). Analyses of time >180 mg/dL, time >250 mg/dL, and standard deviation of CGM glucose favored BP (P < 0.001). Time <54 mg/dL was low at baseline (median 0.2%) and not significantly different between groups over 13 weeks (P = 0.24). A severe hypoglycemia event occurred in 3 (2.7%) participants in the BP group and in 1 (1.9%) in the SC group. Conclusions: In youth 6-17 years old with T1D, use of insulin-only configuration of BP improved HbA1c, TIR, and hyperglycemic metrics without increasing CGM-measured hypoglycemia compared with standard of care. Improvement in glycemic metrics was most pronounced in participants with high baseline HbA1c levels. Clinical Trial Registry: clinicaltrials.gov; NCT04200313.

Novel predictors of daily fluctuations in glycemia and self-management in adolescents and young adults with type 1 diabetes.

AIMS: To understand morning biopsychosocial factors that predict glycemia, adherence, and goal attainment in adolescents and young adults (AYA) with type 1 diabetes (T1D) on a daily basis. METHODS: Eight-eight AYA (mean 17.6 ± 2.6 years, 54% female, HbA1c 7.9 ± 1.4%, diabetes duration 8.5 ± 4.5 years) with T1D who use Continuous Glucose Monitoring (CGM) completed a 2-week prospective study. Participants chose a self-management goal to focus on during participation. For six days, participants prospectively completed a 25-item Engagement Prediction Survey to assess biopsychosocial factors to predict daily diabetes outcomes and an end-of-day Goal Survey. Lasso and mixed-model regression were used to determine items in the Engagement Prediction Survey most predictive of perceived goal attainment, CGM Time-in-Range (TIR, 70-180 mg/dl), sensor mean glucose, number of insulin boluses and hyperglycemia response (bolus within 30 min of high alert or glucose <200 mg/dl within 2 hours). RESULTS: A 7-item model (including current glucose, planning/wanting to manage diabetes, wanting to skip self-management, feeling good about self, health perception and support needs) explained 16.7% of the daily variance in TIR, 18.6% of mean sensor glucose, 2.1% of the number of boluses, 14% of hyperglycemia response, and 28.7% of goal attainment perceptions. The mean absolute change in day-to-day TIR was 16%, sensor glucose was 30 mg/dl, and the number of boluses was 2. AYA reported more positive Engagement Prediction Survey responses on mornings when they awoke with lower glucose levels. CONCLUSIONS: Morning biopsychosocial state factors predict glycemic and adherence outcomes in AYA with diabetes and could be a novel intervention target for future behavioural interventions.