Glucose metrics improvement in youths with type 1 diabetes using the Ambulatory Glucose Profile report: A real-world study

Aims: In this study, we aimed to analyze the possible change in Time In Range (TIR) in subjects with type 1 diabetes (T1D) using the Ambulatory Glucose Profile (AGP) and to identify the main socio-demographic and clinical predictors of sustained use. Methods: 143 youths wearing instant-scanning CGM received structured counseling on the AGP report interpretation, and who were able to use AGP at least every 14 days were enrolled in group A (n = 100), whereas no users were considered as group B (n = 43). Socio-demographic data at the enrollment, clinical data, and glucose metrics were collected at baseline and during quarterly consultations. Metabolic outcomes were evaluated during follow-up, and a comparison between groups A and B was performed. Results: In group A compared to group B, at 12 months, the percentage of sensor usage and TIR were higher (p = 0.04 and p = 0.02), and Time Above Range and HbA1c were lower (p = 0.0004, p < 0.0001, respectively). Multiple logistic regression anal...

Aims: In this study, we aimed to analyze the possible change in Time In Range (TIR) in subjects with type 1 diabetes (T1D) using the Ambulatory Glucose Profile (AGP) and to identify the main socio-demographic and clinical predictors of sustained use. Methods: 143 youths wearing instant-scanning CGM received structured counseling on the AGP report interpretation, and who were able to use AGP at least every 14 days were enrolled in group A (n = 100), whereas no users were considered as group B (n = 43). Socio-demographic data at the enrollment, clinical data, and glucose metrics were collected at baseline and during quarterly consultations. Metabolic outcomes were evaluated during follow-up, and a comparison between groups A and B was performed. Results: In group A compared to group B, at 12 months, the percentage of sensor usage and TIR were higher (p = 0.04 and p = 0.02), and Time Above Range and HbA1c were lower (p = 0.0004, p &lt; 0.0001, respectively). Multiple logistic regression analysis did not show a significant relationship between sustained AGP software usage and the variables analyzed. Conclusions: Systematic use of the AGP software was feasible and showed improved metabolic control in youths with T1D. This may be related to increased sensor usage and more informed decisions.