Model-Based Sensor-Augmented Pump Therapy. (March 2013)
- Record Type:
- Journal Article
- Title:
- Model-Based Sensor-Augmented Pump Therapy. (March 2013)
- Main Title:
- Model-Based Sensor-Augmented Pump Therapy
- Authors:
- Grosman, Benyamin
Voskanyan, Gayane
Loutseiko, Mikhail
Roy, Anirban
Mehta, Aloke
Kurtz, Natalie
Parikh, Neha
Kaufman, Francine R.
Mastrototaro, John J.
Keenan, Barry - Abstract:
- Background: In insulin pump therapy, optimization of bolus and basal insulin dose settings is a challenge. We introduce a new algorithm that provides individualized basal rates and new carbohydrate ratio and correction factor recommendations. The algorithm utilizes a mathematical model of blood glucose (BG) as a function of carbohydrate intake and delivered insulin, which includes individualized parameters derived from sensor BG and insulin delivery data downloaded from a patient's pump. Methods: A mathematical model of BG as a function of carbohydrate intake and delivered insulin was developed. The model includes fixed parameters and several individualized parameters derived from the subject's BG measurements and pump data. Performance of the new algorithm was assessed using n = 4 diabetic canine experiments over a 32 h duration. In addition, 10 in silico adults from the University of Virginia/Padova type 1 diabetes mellitus metabolic simulator were tested. Results: The percentage of time in glucose range 80–180 mg/dl was 86%, 85%, 61%, and 30% using model-based therapy and [78%, 100%] (brackets denote multiple experiments conducted under the same therapy and animal model), [75%, 67%], 47%, and 86% for the control experiments for dogs 1 to 4, respectively. The BG measurements obtained in the simulation using our individualized algorithm were in 61–231 mg/dl min-max envelope, whereas use of the simulator's default treatment resulted in BG measurements 90–210 mg/dl min-maxBackground: In insulin pump therapy, optimization of bolus and basal insulin dose settings is a challenge. We introduce a new algorithm that provides individualized basal rates and new carbohydrate ratio and correction factor recommendations. The algorithm utilizes a mathematical model of blood glucose (BG) as a function of carbohydrate intake and delivered insulin, which includes individualized parameters derived from sensor BG and insulin delivery data downloaded from a patient's pump. Methods: A mathematical model of BG as a function of carbohydrate intake and delivered insulin was developed. The model includes fixed parameters and several individualized parameters derived from the subject's BG measurements and pump data. Performance of the new algorithm was assessed using n = 4 diabetic canine experiments over a 32 h duration. In addition, 10 in silico adults from the University of Virginia/Padova type 1 diabetes mellitus metabolic simulator were tested. Results: The percentage of time in glucose range 80–180 mg/dl was 86%, 85%, 61%, and 30% using model-based therapy and [78%, 100%] (brackets denote multiple experiments conducted under the same therapy and animal model), [75%, 67%], 47%, and 86% for the control experiments for dogs 1 to 4, respectively. The BG measurements obtained in the simulation using our individualized algorithm were in 61–231 mg/dl min-max envelope, whereas use of the simulator's default treatment resulted in BG measurements 90–210 mg/dl min-max envelope. Conclusions: The study results demonstrate the potential of this method, which could serve as a platform for improving, facilitating, and standardizing insulin pump therapy based on a single download of data. … (more)
- Is Part Of:
- Journal of diabetes science and technology. Volume 7:Number 2(2013)
- Journal:
- Journal of diabetes science and technology
- Issue:
- Volume 7:Number 2(2013)
- Issue Display:
- Volume 7, Issue 2 (2013)
- Year:
- 2013
- Volume:
- 7
- Issue:
- 2
- Issue Sort Value:
- 2013-0007-0002-0000
- Page Start:
- 465
- Page End:
- 477
- Publication Date:
- 2013-03
- Subjects:
- insulin therapy -- model-based insulin therapy -- sensor-augmented pump
Diabetes -- Periodicals
Medical technology -- Periodicals
Diabetes Mellitus -- Periodicals
616.462005 - Journal URLs:
- http://ejournals.ebsco.com/direct.asp?JournalID=712321 ↗
http://www.jodsat.org/about.html ↗
http://online.sagepub.com/ ↗ - DOI:
- 10.1177/193229681300700224 ↗
- Languages:
- English
- ISSNs:
- 1932-2968
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 25839.xml