Forecasting and Preventing Post-Bariatric Hypoglycaemia WP 1

Obesity is a major global public health concern, for which the most effective therapy is bariatric surgery. Beyond weight loss, bariatric surgery exerts powerful effects on glucose metabolism, achieving complete type 2 diabetes remission in up to 70% of cases. An exaggeration of these effects, however, can result in an increasingly recognized metabolic complication known as postprandial hyperinsulinaemic hypoglycaemia or post-bariatric hypoglycaemia (PBH). The condition manifests 1-3 years after surgery with meal-induced hypoglycaemic episodes. Emerging data suggests that PBH is more frequent than previously thought and affects approximately 30% of postoperative patients, more commonly after gastric bypass than sleeve gastrectomy. Of note, asymptomatic PBH is common, as shown in studies using continuous glucose monitoring (CGM). It is known from extensive research in people with diabetes that recurrent episodes of hypoglycaemia impair counter regulatory defences against subsequent events, predisposing patients to severe hypoglycaemia.

Despite the increasing prevalence of PBH, clinical implications in this population are still unclear. Anecdotal evidence from patients with PBH suggests a high burden for these patients due to the recurrent hypoglycaemias with possibly debilitating consequences. It is well established that even mild hypoglycaemia (plasma glucose of 3.4 mmol/L) in diabetic and non-diabetic patients impairs various cognitive domains. Of note, some of the cognitive functions remain impaired for up to 75 min, even when the hypoglycaemia is corrected. Further concerns exist from observational studies showing associations between PBH during pregnancy and poor foetal growth.

Thus, it is important to timely detect and treat hypoglycaemia with an intervention that allows quick recovery of glycaemia to a safe level, thereby alleviating symptoms and eliminating the risk of potentially hazardous sequelae. Recently, CGM devices have become standard tools for glucose monitoring in patients with diabetes. CGM allows measuring glucose levels every 5 min and the continuous access to real-time data offering several approaches for the prediction of glucose levels or associated events. Such solutions empower patients to take proactive decisions before reaching critical glucose levels. Apart from glucose levels, meal information, physical activity or other physiological parameters may augment prediction performance of hypoglycaemic events. While most engineering work focuses on the prediction of hypoglycaemia in the diabetic population, only preliminary work has been done in the PBH population.

Given the potentially hazardous consequences of hypoglycaemia, development of hypoglycaemia management strategies to adequately predict and treat critical blood glucose levels in the PBH population are urgently needed. Such strategies have to significantly lower the burden of PBH and increase patient safety.

The overall aim or this study is to prevent hypoglycaemic events in patients with PBH and to develop a sustainable hypoglycaemia correction strategy.

The primary objective of WP 1 is to develop a hypoglycaemia prediction model based on sensor glucose data. Furthermore, the investigators will try to improve the prediction by including further data streams such as information about meal intake, heart rate and activity data.