Automated Insulin Delivery with Remote Real-Time Continuous Glucose Monitoring for Hospitalized Patients with Diabetes: A Multicenter, Single-Arm, Feasibility Trial
Year: 2023
Type: article
Study design: Clinical Trial
Abstract: Introduction: Multiple daily injection insulin therapy frequently fails to meet hospital glycemic goals and is prone to hypoglycemia. Automated insulin delivery (AID) with remote glucose monitoring offers a solution to these shortcomings. Research Design and Methods: In a single-arm multicenter pilot trial, we tested the feasibility, safety, and effectiveness of the Omnipod 5 AID System with real-time continuous glucose monitoring (CGM) for up to 10 days in hospitalized patients with insulin-requiring diabetes on nonintensive care unit medical–surgical units. Primary endpoints included the proportion of time in automated mode and percent time-in-range (TIR 70–180 mg/dL) among participants with >48 h of CGM data. Safety endpoints included incidence of severe hypoglycemia and diabetes-related ketoacidosis (DKA). Additional glycemic endpoints, CGM accuracy, and patient satisfaction were also explored. Results: Twenty-two participants were enrolled; 18 used the system for a total of 96 days (mean 5.3 ± 3.1 days per patient), and 16 had sufficient CGM data required for analysis. Median percent time in automated mode was 95% (interquartile range 92%–98%) for the 18 system users, and the 16 participants with >48 h of CGM data achieved an overall TIR of 68% ± 16%, with 0.17% ± 0.3% time <70 mg/dL and 0.06% ± 0.2% time <54 mg/dL. Sensor mean glucose was 167 ± 21 mg/dL. There were no DKA or severe hypoglycemic events. All participants reported satisfaction with the system at study end. Conclusions: The use of AID with a disposable tubeless patch-pump along with remote real-time CGM is feasible in the hospital setting. These results warrant further investigation in randomized trials.
Authors: Georgia M. Davis, Michael S. Hughes, Sue A. Brown, Judy Sibayan, M. Citlalli Perez-Guzman, Meaghan Stumpf, Zachary Thompson, Marina Basina, Ronak M. Patel, Joi Hester, Amalia Abraham, Trang T. Ly, Cherie Chaney, Marilyn Tan, Liana Hsu, Craig Kollman, Roy W. Beck, Rayhan Lal, Bruce Buckingham, Francisco J. Pasquel
Language: English
Subfield: Endocrinology, Diabetes and Metabolism
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Awards: Training Research Leaders in Type 1 Diabetes, Metabolic Phenotyping During Stress Hyperglycemia in Cardiac Surgery Patients, Perioperative Stress Hyperglycemia in General and Vascular Surgery Patients, The Optimal Pathway to Implanted Autonomous Insulin Delivery, Stanford Diabetes Research Center, Diabetes, Endocrinology and Metabolism Training Grant, Georgia Center for Diabetes Translation Research
OpenAlex ID: W4385798381
