Performance of the Omnipod Personalized Model Predictive Control Algorithm with Meal Bolus Challenges in Adults with Type 1 Diabetes-Reference-Cited by-同舟云学术

Performance of the Omnipod Personalized Model Predictive Control Algorithm with Meal Bolus Challenges in Adults with Type 1 Diabetes

Published:2018-09 Issue:9 Volume:20 Page:585-595
ISSN:1520-9156
Container-title:Diabetes Technology & Therapeutics
language:en
Short-container-title:Diabetes Technology & Therapeutics

Author:

Buckingham Bruce A.¹,Christiansen Mark P.²,Forlenza Gregory P.³,Wadwa R. Paul³,Peyser Thomas A.⁴,Lee Joon Bok⁵,O'Connor Jason⁵,Dassau Eyal⁶,Huyett Lauren M.⁵,Layne Jennifer E.⁵,Ly Trang T.⁵

Affiliation:

1. Division of Pediatric Endocrinology, Department of Pediatrics, Stanford University, Stanford, California.

2. Diablo Clinical Research, Walnut Creek, California.

3. Barbara Davis Center for Diabetes, University of Colorado School of Medicine, Aurora, Colorado.

4. ModeAGC LLC, Palo Alto, California.

5. Insulet Corporation, Billerica, Massachusetts.

6. Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts.

Publisher

Mary Ann Liebert Inc

Subject

Medical Laboratory Technology,Endocrinology,Endocrinology, Diabetes and Metabolism

Link

https://www.liebertpub.com/doi/pdf/10.1089/dia.2018.0138

Reference26 articles.

1. Expectations and Attitudes of Individuals With Type 1 Diabetes After Using a Hybrid Closed Loop System

2. What End Users and Stakeholders Want From Automated Insulin Delivery Systems

3. Effect of artificial pancreas systems on glycaemic control in patients with type 1 diabetes: a systematic review and meta-analysis of outpatient randomised controlled trials

4. Safety of a Hybrid Closed-Loop Insulin Delivery System in Patients With Type 1 Diabetes

5. Glucose Outcomes with the In-Home Use of a Hybrid Closed-Loop Insulin Delivery System in Adolescents and Adults with Type 1 Diabetes

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