ReviewMetabolites2026
Metabolic Responses to Exercise and Nutritional Strategies in Type 1 Diabetes Using Automated Insulin Delivery Systems: A Narrative Review.
Review in Metabolites, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND/
objectivesAutomated insulin delivery (AID) systems have improved the management of type 1 diabetes (T1D), but exercise and nutrition remain challenging because they rapidly alter glucose flux, substrate oxidation, hepatic glucose output, insulin requirements, and fuel availability. This narrative review aimed to synthesize current evidence on the interaction between AID systems, physical activity, and nutritional strategies from a metabolism-oriented perspective.
methodsA narrative bibliographic approach was used to integrate evidence from clinical trials, observational studies, technical studies, consensus statements, and reviews involving people with T1D across different life stages, including pediatric, adolescent, adult, and pregnancy-related contexts, when available. The review focused on AID systems, exercise physiology, nutritional strategies, meal announcement, bolus adjustment, dual-hormone systems, metabolic biomarkers, and emerging metabolomic approaches.
resultsAID systems generally improve time in range and reduce hypoglycemia across several user groups, although most exercise- and nutrition-specific evidence comes from adult and pediatric/adolescent cohorts rather than pregnancy-specific exercise studies. Exercise-related glucose responses remain highly dependent on user input, exercise modality, insulin on board, meal timing, and metabolic state. Planned exercise announcement, prandial bolus reduction before postprandial activity, and individualized carbohydrate intake remain key strategies. Biomarkers such as lactate, ketone bodies, non-esterified fatty acids, and counter-regulatory hormones may help explain interindividual variability and support future personalization.
conclusionsNutrition and exercise management in AID users should be interpreted as a dynamic metabolic interface among exogenous insulin, endogenous counter-regulation, substrate availability, and algorithmic control. Emerging approaches, including activity sensors, adaptive algorithms, dual-hormone systems, digital twins, and metabolomics-informed personalization, may improve safety and reduce user burden, but several remain exploratory and require further validation in diverse free-living conditions.
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Registered trials
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