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Performance of an Automated Insulin Delivery System: Results of Early Phase Feasibility Studies
Background: Automated insulin delivery (AID) systems have demonstrated improvements in time-in-range (TIR, blood glucose 70–180 mg/dL) without increasing hypoglycemia. Testing a closed-loop system in an inpatient environment with supervised challenges allows for initial evaluation of performance and...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Mary Ann Liebert, Inc., publishers
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7906863/ https://www.ncbi.nlm.nih.gov/pubmed/32940537 http://dx.doi.org/10.1089/dia.2020.0318 |
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author | Christiansen, Mark Bartee, Amy Lalonde, Amy Jones, Richard E. Katz, Michelle Wolpert, Howard Brazg, Ronald |
author_facet | Christiansen, Mark Bartee, Amy Lalonde, Amy Jones, Richard E. Katz, Michelle Wolpert, Howard Brazg, Ronald |
author_sort | Christiansen, Mark |
collection | PubMed |
description | Background: Automated insulin delivery (AID) systems have demonstrated improvements in time-in-range (TIR, blood glucose 70–180 mg/dL) without increasing hypoglycemia. Testing a closed-loop system in an inpatient environment with supervised challenges allows for initial evaluation of performance and safety of the system. Methods: Adults with type 1 diabetes (T1D) were enrolled into two similar studies (n = 10 per study), with 3-day inpatient analysis periods. Participants tested a Lilly hybrid closed-loop (HCL) system comprising an investigational insulin pump, insulin lispro, a pump-embedded model predictive control algorithm, a continuous glucose monitor (CGM), and an external dedicated controller. Each protocol included meal-related and exercise challenges to simulate real-world diabetes self-management errors. Only study staff interacted with the HCL system. Performance was assessed using standard CGM metrics overall and within prespecified periods. Results: Participants (25% male) had mean ± standard deviation (SD) age 44.7 ± 14.2 years, T1D duration 30.2 ± 11.1 years, A1C 7.2% ± 0.8%, and insulin usage 0.53 ± 0.21 U/(kg·day). Percentage TIR 70–180 mg/dL (mean ± SD) was 81.2 ± 8.4 overall, 85.2 ± 8.1 outside of challenge periods, 97.3 ± 5.3 during the nocturnal periods, and 74.5 ± 16.2 for the postprandial periods. During challenge periods, percentage TIR for the overbolus challenge was 65.4 ± 29.2 and that for the delayed bolus challenge was 57.1 ± 25.1. No adverse events (AEs), serious AEs, or unanticipated adverse device events occurred while participants were using the HCL system. Conclusions: In participants with T1D, Lilly AID system demonstrated expected algorithm performance and safety with satisfactory glycemic outcomes overall and in response to simulated diabetes management challenges. Additional studies in less supervised conditions and with broader patient populations are warranted. ClinicalTrials.gov Registration number NCT03743285, NCT03849612. |
format | Online Article Text |
id | pubmed-7906863 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Mary Ann Liebert, Inc., publishers |
record_format | MEDLINE/PubMed |
spelling | pubmed-79068632021-02-26 Performance of an Automated Insulin Delivery System: Results of Early Phase Feasibility Studies Christiansen, Mark Bartee, Amy Lalonde, Amy Jones, Richard E. Katz, Michelle Wolpert, Howard Brazg, Ronald Diabetes Technol Ther Original Articles Background: Automated insulin delivery (AID) systems have demonstrated improvements in time-in-range (TIR, blood glucose 70–180 mg/dL) without increasing hypoglycemia. Testing a closed-loop system in an inpatient environment with supervised challenges allows for initial evaluation of performance and safety of the system. Methods: Adults with type 1 diabetes (T1D) were enrolled into two similar studies (n = 10 per study), with 3-day inpatient analysis periods. Participants tested a Lilly hybrid closed-loop (HCL) system comprising an investigational insulin pump, insulin lispro, a pump-embedded model predictive control algorithm, a continuous glucose monitor (CGM), and an external dedicated controller. Each protocol included meal-related and exercise challenges to simulate real-world diabetes self-management errors. Only study staff interacted with the HCL system. Performance was assessed using standard CGM metrics overall and within prespecified periods. Results: Participants (25% male) had mean ± standard deviation (SD) age 44.7 ± 14.2 years, T1D duration 30.2 ± 11.1 years, A1C 7.2% ± 0.8%, and insulin usage 0.53 ± 0.21 U/(kg·day). Percentage TIR 70–180 mg/dL (mean ± SD) was 81.2 ± 8.4 overall, 85.2 ± 8.1 outside of challenge periods, 97.3 ± 5.3 during the nocturnal periods, and 74.5 ± 16.2 for the postprandial periods. During challenge periods, percentage TIR for the overbolus challenge was 65.4 ± 29.2 and that for the delayed bolus challenge was 57.1 ± 25.1. No adverse events (AEs), serious AEs, or unanticipated adverse device events occurred while participants were using the HCL system. Conclusions: In participants with T1D, Lilly AID system demonstrated expected algorithm performance and safety with satisfactory glycemic outcomes overall and in response to simulated diabetes management challenges. Additional studies in less supervised conditions and with broader patient populations are warranted. ClinicalTrials.gov Registration number NCT03743285, NCT03849612. Mary Ann Liebert, Inc., publishers 2021-03-01 2021-02-25 /pmc/articles/PMC7906863/ /pubmed/32940537 http://dx.doi.org/10.1089/dia.2020.0318 Text en © Eli Lilly and Company, 2021; Published by Mary Ann Liebert, Inc. This Open Access article is distributed under the terms of the Creative Commons Attribution Noncommercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited. |
spellingShingle | Original Articles Christiansen, Mark Bartee, Amy Lalonde, Amy Jones, Richard E. Katz, Michelle Wolpert, Howard Brazg, Ronald Performance of an Automated Insulin Delivery System: Results of Early Phase Feasibility Studies |
title | Performance of an Automated Insulin Delivery System: Results of Early Phase Feasibility Studies |
title_full | Performance of an Automated Insulin Delivery System: Results of Early Phase Feasibility Studies |
title_fullStr | Performance of an Automated Insulin Delivery System: Results of Early Phase Feasibility Studies |
title_full_unstemmed | Performance of an Automated Insulin Delivery System: Results of Early Phase Feasibility Studies |
title_short | Performance of an Automated Insulin Delivery System: Results of Early Phase Feasibility Studies |
title_sort | performance of an automated insulin delivery system: results of early phase feasibility studies |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7906863/ https://www.ncbi.nlm.nih.gov/pubmed/32940537 http://dx.doi.org/10.1089/dia.2020.0318 |
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