We present a new mobile platform to be used in clinical trials aimed at both collecting data and assessing new technologies and treatments for diabetes care. The main components of the platform are a mobile app, that automatically collects data from continuous glucose monitoring sensors and activity trackers, and also allows users to manually log daily events; a cloud database for safe data storage; a web interface, which allows clinicians to monitor patients’ status in real-time. The platform is modular and highly customizable for a multitude of purposes in clinical research. Preliminary tests performed for daily-life data gathering by both clinicians and users are extremely encouraging.

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To investigate the effect of empagliflozin on glucose dynamics in individuals suffering from postbariatric hypoglycaemia (PBH) after Roux-en-Y gastric bypass (RYGB). MethodsTwenty-two adults with PBH after RYGB were randomized to empagliflozin 25 mg or placebo once daily over 20 days in a randomized, double-blind, placebo-controlled, crossover trial. The primary efficacy outcome was the amplitude of plasma glucose

Postbariatric hypoglycemia (PBH) is an increasingly recognized late metabolic complication of bariatric surgery, characterized by low blood glucose levels 1–3 h after a meal, particularly if the meal contains rapid-acting carbohydrates. PBH can often be effectively managed through appropriate nutritional measures, which remain the cornerstone treatment today. However, their implementation in daily life continues to challenge both patients and health care providers. Emerging digital technologies may allow for more informed and improved decision-making through better access to relevant data to manage glucose levels in PBH. Examples include applications for automated food analysis from meal images, digital receipts of purchased food items or integrated platforms allowing the connection of continuously measured glucose with food and other health-related data. The resulting multi-dimensional data can be processed with artificial intelligence systems to develop prediction algorithms and decision support systems with the aim of improving glucose control, safety, and quality of life of PBH patients. Digital innovations, however, face trade-offs between user burden vs. amount and quality of data. Further challenges to their development are regulatory non-compliance regarding data ownership of the platforms acquiring the required data, as well as user privacy concerns and compliance with regulatory requirements. Through navigating these trade-offs, digital solutions could significantly contribute to improving the management of PBH.

Bariatric surgery increases postprandial glucose excursions with higher peaks and lower nadirs. Etiologically linked is the phenomenon of postbariatric hypoglycaemia (PBH), an increasingly recognized metabolic disorder. Continuous glucose monitoring (CGM) has become an important tool in the diagnosis and management of PBH. The Ambulatory Glucose Profile (AGP) is an internationally recognized and standardized format that provides structured and graphical compilation of CGM data to guide treatment decisions in people with diabetes. However, its applicability to patients suffering from bariatric surgery-induced dysglycaemia, such as PBH, remains limited. Based on the collection of CGM data in healthy individuals and post-bariatric surgery patients with and without PBH, we selected a set of summary statistics that are important to diagnose the condition, decide on and evaluate the efficacy of therapeutic strategies. We propose a novel AGPr which contains the following: %time spent with non-physiological glucose values, the diurnal distribution of hypoglycaemic events (including level and duration) and information on postprandial glucose excursions by colour-coding of rate of glucose change and variability metrics. The new AGPr uses data generated by CGM to provide a rapid visual presentation of glucose dynamics and hypoglycemia burden in post-bariatric surgery individuals. Disclosure L.Cossu: None. G.Cappon: Consultant; Dexcom, Inc. D.Herzig: None. A.Facchinetti: None. L.Bally: Research Support; Dexcom, Inc., Ypsomed AG. Funding University of Padova, Italy (SID-Networking Project 2021)