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Automated Insulin Delivery with Remote Real-Time Continuous Glucose Monitoring for Hospitalized Patients with Diabetes: A Multicenter, Single-Arm, Feasibility Trial.
Davis, Georgia M; Hughes, Michael S; Brown, Sue A; Sibayan, Judy; Perez-Guzman, M Citlalli; Stumpf, Meaghan; Thompson, Zachary; Basina, Marina; Patel, Ronak M; Hester, Joi; Abraham, Amalia; Ly, Trang T; Chaney, Cherie; Tan, Marilyn; Hsu, Liana; Kollman, Craig; Beck, Roy W; Lal, Rayhan; Buckingham, Bruce; Pasquel, Francisco J.
Affiliation
  • Davis GM; Division of Endocrinology, Metabolism, and Lipids, Department of Medicine, Emory University School of Medicine, Atlanta, Georgia, USA.
  • Hughes MS; Division of Endocrinology, Gerontology and Metabolism, Department of Medicine, Stanford University, Stanford, California, USA.
  • Brown SA; Division of Endocrinology, Center for Diabetes Technology, University of Virginia, Charlottesville, Virginia, USA.
  • Sibayan J; Jaeb Center for Health Research, Tampa, Florida, USA.
  • Perez-Guzman MC; Division of Endocrinology, Metabolism, and Lipids, Department of Medicine, Emory University School of Medicine, Atlanta, Georgia, USA.
  • Stumpf M; Division of Endocrinology, Center for Diabetes Technology, University of Virginia, Charlottesville, Virginia, USA.
  • Thompson Z; Jaeb Center for Health Research, Tampa, Florida, USA.
  • Basina M; Division of Endocrinology, Gerontology and Metabolism, Department of Medicine, Stanford University, Stanford, California, USA.
  • Patel RM; Division of Endocrinology, Center for Diabetes Technology, University of Virginia, Charlottesville, Virginia, USA.
  • Hester J; Division of Endocrinology, Metabolism, and Lipids, Department of Medicine, Emory University School of Medicine, Atlanta, Georgia, USA.
  • Abraham A; Division of Endocrinology, Metabolism, and Lipids, Department of Medicine, Emory University School of Medicine, Atlanta, Georgia, USA.
  • Ly TT; Insulet Corporation, Acton, Massachusetts, USA.
  • Chaney C; Division of Endocrinology, Center for Diabetes Technology, University of Virginia, Charlottesville, Virginia, USA.
  • Tan M; Division of Endocrinology, Gerontology and Metabolism, Department of Medicine, Stanford University, Stanford, California, USA.
  • Hsu L; Division of Pediatric Endocrinology, Department of Pediatrics, Stanford University, Stanford, California, USA.
  • Kollman C; Jaeb Center for Health Research, Tampa, Florida, USA.
  • Beck RW; Jaeb Center for Health Research, Tampa, Florida, USA.
  • Lal R; Division of Endocrinology, Gerontology and Metabolism, Department of Medicine, Stanford University, Stanford, California, USA.
  • Buckingham B; Division of Pediatric Endocrinology, Department of Pediatrics, Stanford University, Stanford, California, USA.
  • Pasquel FJ; Division of Pediatric Endocrinology, Department of Pediatrics, Stanford University, Stanford, California, USA.
Diabetes Technol Ther ; 25(10): 677-688, 2023 10.
Article in En | MEDLINE | ID: mdl-37578778
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.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Diabetic Ketoacidosis / Diabetes Mellitus, Type 1 / Hypoglycemia Type of study: Clinical_trials Aspects: Implementation_research Limits: Humans Language: En Journal: Diabetes Technol Ther Journal subject: ENDOCRINOLOGIA / TERAPEUTICA Year: 2023 Document type: Article Affiliation country: United States Country of publication: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Diabetic Ketoacidosis / Diabetes Mellitus, Type 1 / Hypoglycemia Type of study: Clinical_trials Aspects: Implementation_research Limits: Humans Language: En Journal: Diabetes Technol Ther Journal subject: ENDOCRINOLOGIA / TERAPEUTICA Year: 2023 Document type: Article Affiliation country: United States Country of publication: United States