دورية أكاديمية

Artificial Pancreas: In Silico Study Shows No Need of Meal Announcement and Improved Time in Range of Glucose With Intraperitoneal vs. Subcutaneous Insulin Delivery

التفاصيل البيبلوغرافية
العنوان: Artificial Pancreas: In Silico Study Shows No Need of Meal Announcement and Improved Time in Range of Glucose With Intraperitoneal vs. Subcutaneous Insulin Delivery
المؤلفون: Chiara Toffanin, Lalo Magni, Claudio Cobelli
المصدر: IEEE TRANSACTIONS ON MEDICAL ROBOTICS AND BIONICS 3(2) 306-314
سنة النشر: 2022
المجموعة: Zenodo
مصطلحات موضوعية: Closed-loop glucose control, model predictive control (MPC), mathematical modeling, simulation, automated insulin delivery systems
الوصف: Contemporary Artificial Pancreas (AP) consists of a subcutaneous (SC) glucose sensor, a SC insulin pump and a control algorithm. Even the most advanced systems are far from optimal, in particular due to the non-physiologic nature of SC route. While SC insulin delivery is convenient and minimally invasive, it introduces delays to insulin action that make tight control difficult, particularly during meals. In addition frequent patient interventions are needed, e.g., at mealtime. The intraperitoneal (IP) insulin delivery could address this major challenge since it exhibits a faster pharmacokinetics/pharmacodynamics, hence making easier to quickly respond to glycemic disturbances. A 1-day hospital closed-loop study has shown significant improvements of IP glucose control vs SC AP, and that meal announcement is not necessary. However, the IP AP has not been tested in more realistic everyday life conditions. In this work we have performed an in silico study of 14 days of an IP AP by using the UVA/Padova simulator which includes intra- and inter-day variability of insulin sensitivity and several real life scenarios. We show superiority of IP AP vs SC AP in terms of quality of glucose control (time in range 87% IP vs 80% SC) without the need of a meal announcement.
نوع الوثيقة: article in journal/newspaper
اللغة: English
العلاقة: info:eu-repo/grantAgreement/EC/H2020/951933/; https://zenodo.org/record/6592403Test; https://doi.org/10.1109/TMRB.2021.3075775Test; oai:zenodo.org:6592403
DOI: 10.1109/TMRB.2021.3075775
الإتاحة: https://doi.org/10.1109/TMRB.2021.3075775Test
https://zenodo.org/record/6592403Test
حقوق: info:eu-repo/semantics/closedAccess
رقم الانضمام: edsbas.7AB0F700
قاعدة البيانات: BASE