Official websites use. Share sensitive information only on official, secure websites. Krasser; Pernelle K. Mader, MD. To evaluate the efficacy and safety of the new coated subcutaneous infusion set with Lantern Technology over 7 days of wear and to determine whether the novel cannula design facilitates consistent insulin flow over an extended wear time. Sixteen type 1 diabetes patients age The patients participated in three 8-hour euglycemic clamp experiments Study Days 1, 4, and 7 and spent the days between the experiments Study Days 3, 4, 5, and 6 at home routinely managing diabetes with CSII and FGM.
There was no incidence of severe hypoglycemia or ketoacidosis during the study period. The coated infusion set with Lantern Technology could be safely used during extended wear. These findings need to be confirmed in a larger scale trial under routine conditions. Type 2 diabetes mellitus T2DM not only creates a huge public health burden but also contributes to a tremendous patient burden due to intensive and complex self-management regimens.
Adherence to these complex regimens on a day-to-day basis is particularly challenging. The objective of this study is to dynamically forecast glucose levels in patients with T2DM based on their mobile health lifestyle data on diet, activity, and weight control and to alarm unusual lifestyle regimens in order to achieve better glucose control.
We used data from 10 T2DM patients who were overweight or obese in a behavioral lifestyle intervention using mobile tools for monitoring diet, physical activity, weight, and blood glucose daily over 6 months.
We developed a deep learning model based on dynamic convolutional neural networks to estimate and forecast the trajectory of glucose levels in individual patients. The proposed neural network utilized several layers of computational nodes to model how mobile health data i. Given past lifestyle regimens data, the deep learning network monitored the patient daily regiments e. Using machine learning methodologies to analyze mobile health data can be effective in developing more individualized lifestyle interventions and glucose control for T2DM management.
