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.

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.

Accuracy of a breath ketone analyzer to detect ketosis in adults and children with type 1 diabetes.

OBJECTIVE: To assess the accuracy of a breath ketone analyzer to detect ketosis in adults and children with type 1 diabetes. RESEARCH DESIGN AND METHODS: This is a proof-of-concept, prospective study comparing breath ketone analyzer and blood ketone meter to detect ketosis. RESULTS: A total of 500 measurements from 19 adults and children with type 1 diabetes were analyzed. There was a significant association between the breath ketone analyzer and blood ketone meter results in non-fasting adults (p = 0.0066), but not in children (p = 0.4579). In adults, a cut-off of 3.9 PPM on the breath ketone analyzer maximized the Youden Index with an AUC of 0.73. This cut-off for the breath ketone analyzer had 94.7% sensitivity and 54.2% specificity to detect ketosis (≥0.6 mmol/L in blood ketone meter). CONCLUSIONS: The breath ketone analyzer may be considered as a non-invasive screening tool to rule out ketosis in adults with type 1 diabetes.