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

Background: This study assessed the safety and performance of the Omnipod(®) personalized model predictive control (MPC) algorithm using an investigational device in adults with type 1 diabetes in response to overestimated and missed meal boluses and extended boluses for high-fat meals. Materials an...

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Autores principales: Buckingham, Bruce A., Christiansen, Mark P., Forlenza, Gregory P., Wadwa, R. Paul, Peyser, Thomas A., Lee, Joon Bok, O'Connor, Jason, Dassau, Eyal, Huyett, Lauren M., Layne, Jennifer E., Ly, Trang T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Mary Ann Liebert, Inc. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6114075/
https://www.ncbi.nlm.nih.gov/pubmed/30070928
http://dx.doi.org/10.1089/dia.2018.0138
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author Buckingham, Bruce A.
Christiansen, Mark P.
Forlenza, Gregory P.
Wadwa, R. Paul
Peyser, Thomas A.
Lee, Joon Bok
O'Connor, Jason
Dassau, Eyal
Huyett, Lauren M.
Layne, Jennifer E.
Ly, Trang T.
author_facet Buckingham, Bruce A.
Christiansen, Mark P.
Forlenza, Gregory P.
Wadwa, R. Paul
Peyser, Thomas A.
Lee, Joon Bok
O'Connor, Jason
Dassau, Eyal
Huyett, Lauren M.
Layne, Jennifer E.
Ly, Trang T.
author_sort Buckingham, Bruce A.
collection PubMed
description Background: This study assessed the safety and performance of the Omnipod(®) personalized model predictive control (MPC) algorithm using an investigational device in adults with type 1 diabetes in response to overestimated and missed meal boluses and extended boluses for high-fat meals. Materials and Methods: A supervised 54-h hybrid closed-loop (HCL) study was conducted in a hotel setting after a 7-day outpatient open-loop run-in phase. Adults aged 18–65 years with type 1 diabetes and HbA1c 6.0%–10.0% were eligible. Primary endpoints were percentage time in hypoglycemia <70 mg/dL and hyperglycemia ≥250 mg/dL. Glycemic responses for 4 h to a 130% overestimated bolus and a missed meal bolus were compared with a 100% bolus for identical meals, respectively. The 12-h postprandial responses to a high-fat meal were compared using either a standard or extended bolus. Results: Twelve subjects participated in the study, with (mean ± standard deviation): age 35.4 ± 14.1 years, diabetes duration 16.5 ± 9.3 years, HbA1c 7.7 ± 0.9%, and total daily dose 0.58 ± 0.19 U/kg. Outcomes for the 54-h HCL period were mean glucose 153 ± 15 mg/dL, percentage time <70 mg/dL [median (interquartile range)]: 0.0% (0.0–1.2%), 70–180 mg/dL: 76.1% ± 8.0%, and ≥250 mg/dL: 4.5% ± 3.6%. After both the 100% and 130% boluses, postprandial percentage time <70 mg/dL was 0.0% (0.0–0.0%) (P = 0.50). After the 100% and missed boluses, postprandial percentage time ≥250 mg/dL was 0.2% ± 0.6% and 10.3% ± 16.5%, respectively (P = 0.06). Postprandial percentages time ≥250 mg/dL and <70 mg/dL were similar with standard or extended boluses for a high-fat meal. Conclusions: The Omnipod personalized MPC algorithm performed well and was safe during day and night use in response to overestimated, missed, and extended meal boluses in adults with type 1 diabetes.
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spelling pubmed-61140752018-09-05 Performance of the Omnipod Personalized Model Predictive Control Algorithm with Meal Bolus Challenges in Adults with Type 1 Diabetes Buckingham, Bruce A. Christiansen, Mark P. Forlenza, Gregory P. Wadwa, R. Paul Peyser, Thomas A. Lee, Joon Bok O'Connor, Jason Dassau, Eyal Huyett, Lauren M. Layne, Jennifer E. Ly, Trang T. Diabetes Technol Ther Original Articles Background: This study assessed the safety and performance of the Omnipod(®) personalized model predictive control (MPC) algorithm using an investigational device in adults with type 1 diabetes in response to overestimated and missed meal boluses and extended boluses for high-fat meals. Materials and Methods: A supervised 54-h hybrid closed-loop (HCL) study was conducted in a hotel setting after a 7-day outpatient open-loop run-in phase. Adults aged 18–65 years with type 1 diabetes and HbA1c 6.0%–10.0% were eligible. Primary endpoints were percentage time in hypoglycemia <70 mg/dL and hyperglycemia ≥250 mg/dL. Glycemic responses for 4 h to a 130% overestimated bolus and a missed meal bolus were compared with a 100% bolus for identical meals, respectively. The 12-h postprandial responses to a high-fat meal were compared using either a standard or extended bolus. Results: Twelve subjects participated in the study, with (mean ± standard deviation): age 35.4 ± 14.1 years, diabetes duration 16.5 ± 9.3 years, HbA1c 7.7 ± 0.9%, and total daily dose 0.58 ± 0.19 U/kg. Outcomes for the 54-h HCL period were mean glucose 153 ± 15 mg/dL, percentage time <70 mg/dL [median (interquartile range)]: 0.0% (0.0–1.2%), 70–180 mg/dL: 76.1% ± 8.0%, and ≥250 mg/dL: 4.5% ± 3.6%. After both the 100% and 130% boluses, postprandial percentage time <70 mg/dL was 0.0% (0.0–0.0%) (P = 0.50). After the 100% and missed boluses, postprandial percentage time ≥250 mg/dL was 0.2% ± 0.6% and 10.3% ± 16.5%, respectively (P = 0.06). Postprandial percentages time ≥250 mg/dL and <70 mg/dL were similar with standard or extended boluses for a high-fat meal. Conclusions: The Omnipod personalized MPC algorithm performed well and was safe during day and night use in response to overestimated, missed, and extended meal boluses in adults with type 1 diabetes. Mary Ann Liebert, Inc. 2018-09-01 2018-09-01 /pmc/articles/PMC6114075/ /pubmed/30070928 http://dx.doi.org/10.1089/dia.2018.0138 Text en © Bruce A. Buckingham, et al., 2018; Published by Mary Ann Liebert, Inc. This Open Access article is distributed under the terms of the Creative Commons License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.
spellingShingle Original Articles
Buckingham, Bruce A.
Christiansen, Mark P.
Forlenza, Gregory P.
Wadwa, R. Paul
Peyser, Thomas A.
Lee, Joon Bok
O'Connor, Jason
Dassau, Eyal
Huyett, Lauren M.
Layne, Jennifer E.
Ly, Trang T.
Performance of the Omnipod Personalized Model Predictive Control Algorithm with Meal Bolus Challenges in Adults with Type 1 Diabetes
title Performance of the Omnipod Personalized Model Predictive Control Algorithm with Meal Bolus Challenges in Adults with Type 1 Diabetes
title_full Performance of the Omnipod Personalized Model Predictive Control Algorithm with Meal Bolus Challenges in Adults with Type 1 Diabetes
title_fullStr Performance of the Omnipod Personalized Model Predictive Control Algorithm with Meal Bolus Challenges in Adults with Type 1 Diabetes
title_full_unstemmed Performance of the Omnipod Personalized Model Predictive Control Algorithm with Meal Bolus Challenges in Adults with Type 1 Diabetes
title_short Performance of the Omnipod Personalized Model Predictive Control Algorithm with Meal Bolus Challenges in Adults with Type 1 Diabetes
title_sort performance of the omnipod personalized model predictive control algorithm with meal bolus challenges in adults with type 1 diabetes
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6114075/
https://www.ncbi.nlm.nih.gov/pubmed/30070928
http://dx.doi.org/10.1089/dia.2018.0138
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