Roche announced that it has received the CE Mark for its Accu-Chek SmartGuide continuous glucose monitoring (CGM) solution. This significant milestone paves the way for the solution to be made available to people living with type 1 and type 2 diabetes over the age of 18 on flexible insulin therapy. Despite CGM technology's demonstrated positive impact on glycaemic control, a significant proportion of people living with diabetes still do not meet glycaemic targets - even when using a CGM system.

Moreover, they typically encounter an average of two hypoglycaemic episodes a week, with 1-2 of these being severe enough to require medical intervention each year. Notably, nighttime hypoglycaemia is associated with reduced quality of life, increased anxiety, and fear. The persistent fear of hypoglycaemia, hypoglycaemia unawareness, sleep disruption, and diabetes-related distress among CGM users frequently correlates with elevated glucose levels.

The Accu-Chek SmartGuide CGM solution aims to address those critical unmet needs. Every five minutes, the Accu-Chek SmartGuide CGM sensor sends glucose values measured in real time to the Accu-Chek SmartGuide app. The Accu-Chek SmartGuide Predict app then utilises those glucose values and other available information to detect glucose patterns and predict future glucose levels.

Its integrated AI-enabled predictive algorithms indicate hypoglycaemia risk within the next 30 minutes, continuously forecast how glucose levels will develop within the next two hours, and estimate the risk of nocturnal hypoglycaemia. As such, Roche?s new CGM solution is designed to alleviate people living with diabetes? and caregivers?

concerns about nighttime hypoglycaemia and lower its risk. It aims to support informed therapy self-management decisions, enabling proactive intervention before glucose levels require immediate attention. Clinical evaluations have demonstrated the new CGM solution's high system accuracy, with an overall mean absolute relative difference (MARD) of 9.2% and 99.8% of measured glucose values falling within zones A and B on the Parkes Error Grid.

The evaluation of the predictive capabilities showed that all advanced predictive features exceeded high performance requirements as e.g. accuracy, sensitivity, specificity, and events detected.