Decision Support in Diabetes Care: The Challenge of Supporting Patients in Their Daily Living Using a Mobile Glucose Predictor

Journal of Diabetes Science and Technology
Carmen Pérez-GandíaM Elena Hernando

Abstract

In type 1 diabetes mellitus (T1DM), patients play an active role in their own care and need to have the knowledge to adapt decisions to their daily living conditions. Artificial intelligence applications can help people with type 1 diabetes in decision making and allow them to react at time scales shorter than the scheduled face-to-face visits. This work presents a decision support system (DSS), based on glucose prediction, to assist patients in a mobile environment. The system's impact on therapeutic corrective actions has been evaluated in a randomized crossover pilot study focused on interprandial periods. Twelve people with type 1 diabetes treated with insulin pump participated in two phases: In the experimental phase (EP) patients used the DSS to modify initial corrective decisions in presence of hypoglycemia or hyperglycemia events. In the control phase (CP) patients were asked to follow decisions without knowing the glucose prediction. A telemedicine platform allowed participants to register monitoring data and decisions and allowed endocrinologists to supervise data at the hospital. The study period was defined as a postprediction (PP) time window. After knowing the glucose prediction, participants modified the initial ...Continue Reading

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Citations

Jul 23, 2020·Nature Metabolism·Nichole S TylerPeter G Jacobs
Jul 9, 2020·SAGE Open Medicine·Mary MallappallilMoro Salifu
Jun 11, 2020·Sensors·Nichole S Tyler, Peter G Jacobs
Mar 26, 2021·Diabetes/metabolism Research and Reviews·Omar DiouriUNKNOWN HYPO-RESOLVE Consortium

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Software Mentioned

GlucoP
Windows Mobile
DIACRONO

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