Association of HbA1c to BOLUS Scores Among Youths with Type 1 Diabetes

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.

Real-World Use of a New Hybrid Closed Loop Improves Glycemic Control in Youth with Type 1 Diabetes

Objective: To describe real-world outcomes for youth using the Tandem t:slim X2 insulin pump with Control-IQ technology ("Control-IQ") for 6 months at a large pediatric clinic. Methods: Youth with type 1 diabetes, who started Control-IQ for routine care, were prospectively followed. Data on system use and glycemic control were collected before Control-IQ start, and at 1, 3, and 6 months after start. Mixed models assessed change across time; interactions with baseline hemoglobin A1c (HbA1c) and age were tested. Results: In 191 youth (median age 14, 47% female, and median HbA1c 7.6%), percent time with glucose levels 70-180 mg/dL (time-in-range [TIR]) improved from 57% at baseline to 66% at 6 months (P < 0.001). The proportion of participants reaching TIR target (>70%) doubled from 23.5% at baseline to 47.8% at 3 months, sustaining at 46.7% at 6 months (P < 0.001). Glucose management indicator (approximation of HbA1c) improved from 7.5% at baseline to 7.1% at 3 months and 7.2% at 6 months (P < 0.001). Those with higher baseline HbA1c experienced the most substantial improvements in glycemic control. Percent time using the Control-IQ feature was 86.4% at 6 months, and <4% of cohort discontinued use. Conclusion: The Control-IQ system clinically and significantly improved glycemic control in a large sample of youth. System use was high at 6 months, with only a small proportion discontinuing use, indicating potential for sustaining results long term.

Insulin Metrics: Need for Development of Consensus Standards for Reporting of Insulin Dosing Data

The advent of connected insulin pens will generate an avalanche of digital insulin data, especially in the context of prandial- and multiple daily injection-insulin regimens. There is a need for the diabetes community to develop standards for such data, analogous to what has been achieved using the ambulatory glucose profile and associated metrics for glucose, permitting harmonization of data reporting for multiple devices and facilitating integration of glucose, insulin, food intake, and physical activity data. Several studies have estimated the timing of meals by analyses of glucose excursions but using diverse criteria. There is need for uniform criteria for multiple types of insulin boluses, including premeal, perimeal, delayed, missed, and correction boluses to facilitate research studies and patient care. This article contains a first preliminary proposal for standards regarding reporting of insulin dosing data. Clinical usage of these reports will require sensitive communication between health care providers and patients.

A Digital Health Intervention (SweetGoals) for Young Adults With Type 1 Diabetes: Protocol for a Factorial Randomized Trial

BACKGROUND

Many young adults with type 1 diabetes (T1D) struggle with the complex daily demands of adherence to their medical regimen and fail to achieve target range glycemic control. Few interventions, however, have been developed specifically for this age group.

OBJECTIVE

In this randomized trial, we will provide a mobile app (SweetGoals) to all participants as a "core" intervention. The app prompts participants to upload data from their diabetes devices weekly to a device-agnostic uploader (Glooko), automatically retrieves uploaded data, assesses daily and weekly self-management goals, and generates feedback messages about goal attainment. Further, the trial will test two unique intervention components: (1) incentives to promote consistent daily adherence to goals, and (2) web health coaching to teach effective problem solving focused on personalized barriers to self-management. We will use a novel digital direct-to-patient recruitment method and intervention delivery model that transcends the clinic.

METHODS

A 2x2 factorial randomized trial will be conducted with 300 young adults ages 19-25 with type 1 diabetes and (Hb)A_1c ≥ 8.0%. All participants will receive the SweetGoals app that tracks and provides feedback about two adherence targets: (a) daily glucose monitoring; and (b) mealtime behaviors. Participants will be randomized to the factorial combination of incentives and health coaching. The intervention will last 6 months. The primary outcome will be reduction in A_1c. Secondary outcomes include self-regulation mechanisms in longitudinal mediation models and engagement metrics as a predictor of outcomes. Participants will complete 6- and 12-month follow-up assessments. We hypothesize greater sustained A_1c improvements in participants who receive coaching and who receive incentives compared to those who do not receive those components.

RESULTS

Data collection is expected to be complete by February 2025. Analyses of primary and secondary outcomes are expected by December 2025.

CONCLUSIONS

Successful completion of these aims will support dissemination and effectiveness studies of this intervention that seeks to improve glycemic control in this high-risk and understudied population of young adults with T1D.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04646473; https://clinicaltrials.gov/ct2/show/NCT04646473.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/27109.

Pump It Up! A randomized clinical trial to optimize insulin pump self-management behaviors in adolescents with type 1 diabetes

Individuals with type 1 diabetes (T1D) must engage in a variety of complex and burdensome self-management behaviors daily to maintain near normal blood glucose levels and prevent complications. There is a need for interventions to improve use of sophisticated diabetes technologies, such as insulin pumps, during adolescence - a very high-risk developmental period for individuals with T1D. All diabetes devices, including insulin pumps, store large amounts of behavioral data that can be downloaded and analyzed to evaluate adherence to recommended T1D self-management behaviors. The overall objective of the present study, Pump it Up!, was to use objectively downloaded insulin pump data to inform and test two interventions to optimize insulin pump use in adolescents with T1D and their caregivers. Multiphase Optimization Strategy (MOST) was used to achieve the overall goal of this study - to separately test the main effect of the Pump It Up! Personalized T1D Self-Management Behaviors Feedback Report and the main effect of Pump It Up! Problem-Solving Skills intervention to improve T1D self-management behaviors using a 2 × 2 factorial design. The purpose of this paper is to describe the Pump It Up! study design and rationale, and participant baseline characteristics. Longitudinal data analyses will be conducted, and moderating effects of psychosocial factors will be examined in relation to primary (insulin pump self-management behaviors) and secondary (A1C) outcomes.

Six-Month Effectiveness of Advanced vs. Standard Hybrid Closed-Loop System in Children and Adolescents With Type 1 Diabetes Mellitus

INTRODUCTION

The purpose of this study was to assess the effectiveness of advanced- (a-HCL) vs. standard-hybrid closed-loop (s-HCL) systems use up to 6 months of treatment in a real-world setting of children and adolescents with T1DM.

METHODS

We retrospectively evaluated all T1DM pediatric users of MiniMed™ 670G system (s-HCL) and 780G system (a-HCL). HbA1c and BMI were collected at baseline and three and six months after HCL start. Data on glycemic control were extracted from reports generated with CareLink™ Personal Software in Manual Mode, at HCL start, after one, three, and six months after HCL beginning.

RESULTS

The study included 44 individuals with a median age of 13.3 years (range 2- 21 years), 20 on s-HCL, and 24 on a-HCL. a-HCL users had a significantly lower HbA1c compared to s-HCL after six months of HCL use (7.1 vs. 7.7%). Significant differences in HbA1c between a-HCL and s-HCL users were found in children aged 7-14 years (7.1 vs. 7.7% after six months) and in those with a worse (HbA1c >8%) glycemic control at the beginning (7.1 vs. 8.1% after six months). No significant changes in HbA1c were found in a-HCL users that previously used a s-HCL system. Nevertheless, only the use of a-HCL significantly predicted a lower HbA1c after six months. All sensor-specific measures of glycemic control improved from Manual to Auto mode, in both s-HCL and a-HCL, without increasing time spent in hypoglycemia. However, the percentage of individuals with TIR>70% increased significantly in a-HCL users, who attained this target earlier and more stably: younger age, a higher rate of auto-correction, and a lower amount of CHO inserted predicted a TIR>70%. BMI SDS did not significantly change throughout the study period.

CONCLUSION

This real-world study suggests that effectiveness might be greater in a-HCL than in s-HCL, with significant changes in HbA1c, and reaching earlier and more stably the target of TIR >70%, without increasing hypoglycemia or BMI. At the same time, previous users of s-HCL systems did not show any further improvement with a-HCL. Children under the age of 14 years of age, not represented in previous studies, seem to benefit the most from a-HCL pumps as well as individuals with the worst glycemic control.

Mealtime insulin bolus adherence and glycemic control in adolescents on insulin pump therapy

Poor self-management contributes to insufficient glycemic control in adolescents with type 1 diabetes (T1DM). We assessed the effects on glycemic control of adherence to self-measurement of blood glucose (SMBG) and insulin boluses in 90 adolescents with T1DM on insulin pump therapy over a 2-month period. We compared the number of insulin boluses and SMBGs around main meals to the "gold standard" of optimal diabetes management (SMBGs and a bolus before each main meal and SMBG before bedtime). The mean (95% CI) HbA1c levels were 2.9(1.7 to 4.0) mmol/mol lower for every additional insulin bolus and 3.1(1.6 to 4.5) mmol/mol lower for every additional SMBG. Patients performing SMBG and bolusing around each main meal had considerably lower HbA1c levels than those unable to do (95% CI for difference 4.3 to 10.4 mmol/mol and 11.5 to 20.1 mmol/mol respectively). For each additional mealtime bolus/day, the odds ratio of achieving target HbA1c levels of <58 mmol/mol was 6.73 (95% CI 2.94-15.38), after adjustment for gender, age, diabetes duration, and affective responses to SMBG in a multiple logistic regression model.Conclusion: Glycemic control in adolescents with T1DM on insulin pump therapy is strongly dependent on adherence to insulin boluses around mealtimes. What is Known: • In mixed groups of children and adolescents, insulin bolus frequency and self-monitoring of blood glucose (SMBG) frequency were determinants of HbA1c levels. • Adherence to insulin boluses and SMBG is particularly challenging in adolescents. What is New: • In adolescents on insulin pump therapy, each additional insulin bolus, particularly around mealtime, was significantly associated with approximately 3 mmol/mol lower HbA1c levels. • This beneficial effect of mealtime bolusing was strongest for the evening meal.

Hope and mealtime insulin boluses are associated with depressive symptoms and glycemic control in youth with type 1 diabetes mellitus

Adherence to treatment regimen is associated with improved glycemic control and is particularly problematic during adolescence for those with type 1 diabetes mellitus (T1DM). Both glycemic control and adherence may be negatively impacted by poor psychological outcomes in adolescence, such as depressive symptoms and low hopefulness. The purpose of this study was to examine associations between the mealtime insulin bolus score (BOLUS), a more robust proxy measure of adherence than frequency of blood glucose monitoring or self-report, with depressive symptoms, hope, and hemoglobin A1c (HbA1c). Ninety adolescents completed measures of hope (Children's Hope Scale) and depressive symptoms (Center for Epidemiologic Studies-Depression Scale), as well as lab-based measures of HbA1c and mealtime insulin bolus scores (BOLUS). Higher levels of hope were associated with lower levels of depressive symptoms, more frequent mealtime insulin boluses, and better glycemic control. Higher levels of BOLUS behavior were associated with lower depressive symptoms and better glycemic control. Both BOLUS behavior and hope independently and significantly impacted the relationship between depressive symptoms and HbA1c, suggesting a possible mediation. Since hope and BOLUS were each associated with the relationship between depressive symptoms and glycemic control, following confirmation of this relationship in a longitudinal study, clinics may consider measuring hope and BOLUS among youth with high depressive symptoms and further investigating BOLUS behavior and hope as potential intervention targets to improve glycemic control.