From Data to Clinical Action: New Directions in Diabetes Management at ATTD 2026
BARCELONA, Spain, March 25, 2026 /PRNewswire/ -- At ATTD 2026, AI was positioned as a key driver in the evolution of diabetes care. As CGM becomes standard practice, the focus is shifting from data acquisition to data interpretation and application.
Rather than viewing CGM as a passive monitoring tool, discussions emphasized its role in enabling patient education and behavior change. The emerging consensus suggests that clinical value lies not only in accurate readings, but in helping patients understand how daily actions influence glucose outcomes.
From Data to Action: AI in GS3
During the symposium, SIBIONICS presented its GS3 system as an example of integrating AI into routine diabetes management. The system incorporates AI-supported voice logging, allowing users to record meals, activity, and medication through natural speech, which are then automatically structured into analyzable health data.
In addition, AI-driven meal analysis links dietary intake with subsequent glucose responses, while multi-day pattern recognition highlights recurring hyperglycemic events and their potential triggers. These features aim to contextualize glucose fluctuations rather than present isolated values.
Clinicians and diabetes educators at the session noted that simplifying data input and interpretation may reduce patient burden and improve adherence. By translating glucose data into understandable cause-and-effect relationships, such tools may support more effective self-management and facilitate patient-provider communication.
CKM and Multimodal Monitoring
The application of continuous ketone monitoring (CKM) was also discussed, particularly in individuals using SGLT-2 inhibitors. CKM provides additional insight into metabolic status, complementing CGM by capturing ketone dynamics.
Real-world observations suggest that combining glucose and ketone data may reveal patterns not evident through single-parameter monitoring. This integrated approach has potential implications for early risk identification and for guiding more individualized therapeutic strategies.
Academic Leadership and Global Expertise
The symposium was chaired by Prof. Lutz Heinemann (Germany) and Dr. Federico Bertuzzi (Italy), both widely recognized for their contributions to diabetes technology and clinical practice, providing scientific leadership for the session.
The program further featured presentations from internationally recognized experts, including Dr. Talita Trevisan (Brazil), who shared insights from real-world CGM evidence; Dr. Hande Turan (Turkey), who discussed CGM accuracy in pediatric type 1 diabetes; Dr. Ahmad Haidar (Canada), who presented on the application of CKM in SGLT-2 inhibitor users; and Dr. Wei Qiang (China), who introduced next-generation AI-powered CGM approaches.
Together, these contributions reflected a multidisciplinary perspective across clinical research, real-world evidence, and emerging technologies.
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