Analyzing the Potential of Advanced Insulin Dosing Strategies in Patients With Type 2 Diabetes: Results From a Hybrid In Silico Study

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BACKGROUND: The ongoing improvement of continuous glucose monitoring (CGM) sensors and of insulin pumps are paving the way for a fast implementation of artificial pancreas (AP) for type 1 diabetes (T1D) patients. The case for type 2 diabetes (T2D) patients is less obvious since usually some residual beta cell function allows for simpler therapy approaches, and even multiple daily injections (MDI) therapy is not very widespread. However, the number of insulin dependent T2D patients is vastly increasing and therefore a need for understanding chances and challenges of an automated insulin therapy arises. Based on this background, this article analyzes conditions under which the use of more advanced therapeutic approaches, particularly AP, could bring a substantial improvement and should be considered as a viable therapy option.

METHOD: Data of 14 insulin-treated T2D patients on MDI wearing a CGM device and deviation analysis methods were used to estimate the expected improvements in the clinical outcome by using self-monitoring of blood glucose (SMBG) with advanced carbohydrate counting, a full AP or intermediate approaches, either CGM measurements with MDI therapy or SMBG with insulin pump. HbA1C and time in range (70-140 mg/dl, 70-180 mg/dl, respectively) were used as a performance measure. Outcome measures beyond glycemic control (eg, compliance, patient acceptance) have not been analyzed in this study.

RESULTS: AP has the potential to improve the condition of many poorly controlled insulin-treated T2D patients. However, as the interpatient variability is much higher than in T1D, a prescreening is recommended to select suitable patients.

CONCLUSIONS: Clinical criteria need to be developed for inclusion/exclusion of T2D patients for AP related therapies.

Original languageEnglish
JournalJournal of Diabetes Science and Technology
Volume12
Issue number5
Pages (from-to)1029-1040
Number of pages12
ISSN1932-2968
DOIs
Publication statusPublished - 2018

ID: 216310445