Dorsa Majdpour1, Michael A Tsoukas2, Jean-François Yale2, Anas El Fathi3, Joanna Rutkowski3, Jennifer Rene4, Natasha Garfield4, Laurent Legault5, Ahmad Haidar6. 1. Department of Biomedical Engineering, McGill University, Montréal, Québec, Canada; The Research Institute of McGill University Health Centre, Montréal, Québec, Canada. 2. The Research Institute of McGill University Health Centre, Montréal, Québec, Canada; Royal Victoria Hospital, McGill University Health Centre, Montréal, Québec, Canada. 3. Department of Biomedical Engineering, McGill University, Montréal, Québec, Canada. 4. Royal Victoria Hospital, McGill University Health Centre, Montréal, Québec, Canada. 5. The Research Institute of McGill University Health Centre, Montréal, Québec, Canada; Montreal Children's Hospital, McGill University Health Centre, Montréal, Québec, Canada. 6. Department of Biomedical Engineering, McGill University, Montréal, Québec, Canada. Electronic address: ahmad.haidar@mcgill.ca.
Abstract
OBJECTIVES: A fully automated insulin-pramlintide-glucagon artificial pancreas that alleviates the burden of carbohydrate counting without degrading glycemic control was iteratively enhanced until convergence through pilot experiments on adults with type 1 diabetes. METHODS: Nine participants (age, 37±13 years; glycated hemoglobin, 7.7±0.7%) completed two 27-hour interventions: a fully automated multihormone artificial pancreas and a comparator insulin-alone artificial pancreas with carbohydrate counting. The baseline algorithm was a model-predictive controller that administered insulin and pramlintide in a fixed ratio, with boluses triggered by a glucose threshold, and administered glucagon in response to low glucose levels. RESULTS: The baseline multihormone dosing algorithm resulted in noninferior time in target range (3.9 to 10.0 mmol/L) (71%) compared with the insulin-alone arm (70%) in 2 participants, with minimal glucagon delivery. The algorithm was modified to deliver insulin and pramlintide more aggressively to increase time in range and maximize the benefits of glucagon. The modified algorithm displayed a similar time in range for the multihormone arm (79%) compared with the insulin-alone arm (83%) in 2 participants, but with undesired glycemic fluctuations. Subsequently, we reduced the glucose threshold that triggers glucagon boluses. This resulted in inferior glycemic control for the multihormone arm (81% vs 91%) in 2 participants. Thereafter, a model-based meal-detection algorithm to deliver insulin and pramlintide boluses closer to mealtimes was added and glucagon was removed. The final dual-hormone system had comparable time in range (81% vs 83%) in the last 3 participants. CONCLUSION: The final version of the fully automated system that delivered insulin and pramlintide warrants a randomized controlled trial.
OBJECTIVES: A fully automated insulin-pramlintide-glucagon artificial pancreas that alleviates the burden of carbohydrate counting without degrading glycemic control was iteratively enhanced until convergence through pilot experiments on adults with type 1 diabetes. METHODS: Nine participants (age, 37±13 years; glycated hemoglobin, 7.7±0.7%) completed two 27-hour interventions: a fully automated multihormone artificial pancreas and a comparator insulin-alone artificial pancreas with carbohydrate counting. The baseline algorithm was a model-predictive controller that administered insulin and pramlintide in a fixed ratio, with boluses triggered by a glucose threshold, and administered glucagon in response to low glucose levels. RESULTS: The baseline multihormone dosing algorithm resulted in noninferior time in target range (3.9 to 10.0 mmol/L) (71%) compared with the insulin-alone arm (70%) in 2 participants, with minimal glucagon delivery. The algorithm was modified to deliver insulin and pramlintide more aggressively to increase time in range and maximize the benefits of glucagon. The modified algorithm displayed a similar time in range for the multihormone arm (79%) compared with the insulin-alone arm (83%) in 2 participants, but with undesired glycemic fluctuations. Subsequently, we reduced the glucose threshold that triggers glucagon boluses. This resulted in inferior glycemic control for the multihormone arm (81% vs 91%) in 2 participants. Thereafter, a model-based meal-detection algorithm to deliver insulin and pramlintide boluses closer to mealtimes was added and glucagon was removed. The final dual-hormone system had comparable time in range (81% vs 83%) in the last 3 participants. CONCLUSION: The final version of the fully automated system that delivered insulin and pramlintide warrants a randomized controlled trial.
Authors: Marco Infante; David A Baidal; Michael R Rickels; Andrea Fabbri; Jay S Skyler; Rodolfo Alejandro; Camillo Ricordi Journal: Artif Organs Date: 2021-07-15 Impact factor: 2.663