97-LB: Bringing Simulation Technologies to People with T1D: A Pilot Study

Background: Researchers have extensively used metabolic simulators as a fast, inexpensive, and safe way of testing novel treatment strategies. This work aims to bring this technology to people with T1D to enable unique patient/data interactions. Methods: A 5-week pilot study was carried out in 15 ad...

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Published inDiabetes (New York, N.Y.) Vol. 70; no. Supplement_1
Main Authors COLMEGNA, PATRICIO, BISIO, ALESSANDRO, MCFADDEN, RYAN, WAKEMAN, CHRISTIAN A., OLIVERI, MARY C., NASS, RALF, BRETON, MARC D.
Format Journal Article
LanguageEnglish
Published New York American Diabetes Association 01.06.2021
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ISSN0012-1797
1939-327X
DOI10.2337/db21-97-LB

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Abstract Background: Researchers have extensively used metabolic simulators as a fast, inexpensive, and safe way of testing novel treatment strategies. This work aims to bring this technology to people with T1D to enable unique patient/data interactions. Methods: A 5-week pilot study was carried out in 15 adults with T1D using Control-IQ technology (age 36±13 years, HbA1c 6.5±0.7%) to evaluate acceptance of the proposed Web-Based Simulation Tool (WST). The study consisted of 1 week of observation (Phase 1) and 4 weeks of interaction with WST (Phase 2). Data were automatically collected via Tandem Diabetes Care t:connect web application, and used to generate personalized models of the participants’ glucose metabolism. Results: Success rate in generating models was 86.4%, achieving an average MARD of 7.4±3.2%. Interaction time was 15.8±10.7 min per week. Comparing Phases 1 and 2, no variation was detected in time in range 70-180 mg/dl (80.1 [70.4,89.6]% vs. 80 [69.7,87.9]%). Time in 70-250 mg/dl increased slightly (94.2 [90.3,95.7]% vs. 96.2 [92.1,97.9]%), especially overnight (92.8 [88.3,98.2]% vs. 97.2 [91.8,99.6]%), and for participants who modified their pump settings based on WST simulations (90 [88.7,92.4]% vs. 94.5 [87.1,99.6]%). One subject tested COVID positive during the study and was excluded from this analysis due to abnormal hyperglycemia. Analysis of Diabetes Distress Scale (DDS)-17 pre and post-system use shows a reduction in diabetes-related distress (2.2 [1.7,3.4] vs. 2 [1.7,2.4]). Trust, ease of use, and usefulness scores were 80 [60,80]%, 60 [60,80]%, and 80 [60,80]%, respectively. During the follow up interviews, 10 participants reported they enjoyed using WST and would implement it into their diabetes management; 2 did not like the system but see the potential of it for other people; 3 participants did not like the system at all. Conclusions: Evidence from this study suggests that simulation technologies may empower people with T1D, making them more confident in their diabetes self-management.
AbstractList Background: Researchers have extensively used metabolic simulators as a fast, inexpensive, and safe way of testing novel treatment strategies. This work aims to bring this technology to people with T1D to enable unique patient/data interactions. Methods: A 5-week pilot study was carried out in 15 adults with T1D using Control-IQ technology (age 36±13 years, HbA1c 6.5±0.7%) to evaluate acceptance of the proposed Web-Based Simulation Tool (WST). The study consisted of 1 week of observation (Phase 1) and 4 weeks of interaction with WST (Phase 2). Data were automatically collected via Tandem Diabetes Care t:connect web application, and used to generate personalized models of the participants' glucose metabolism. Results: Success rate in generating models was 86.4%, achieving an average MARD of 7.4±3.2%. Interaction time was 15.8±10.7 min per week. Comparing Phases 1 and 2, no variation was detected in time in range 70-180 mg/dl (80.1 [70.4,89.6]% vs. 80 [69.7,87.9]%). Time in 70-250 mg/dl increased slightly (94.2 [90.3,95.7]% vs. 96.2 [92.1,97.9]%), especially overnight (92.8 [88.3,98.2]% vs. 97.2 [91.8,99.6]%), and for participants who modified their pump settings based on WST simulations (90 [88.7,92.4]% vs. 94.5 [87.1,99.6]%). One subject tested COVID positive during the study and was excluded from this analysis due to abnormal hyperglycemia. Analysis of Diabetes Distress Scale (DDS)-17 pre and post-system use shows a reduction in diabetes-related distress (2.2 [1.7,3.4] vs. 2 [1.7,2.4]). Trust, ease of use, and usefulness scores were 80 [60,80]%, 60 [60,80]%, and 80 [60,80]%, respectively. During the follow up interviews, 10 participants reported they enjoyed using WST and would implement it into their diabetes management; 2 did not like the system but see the potential of it for other people; 3 participants did not like the system at all. Conclusions: Evidence from this study suggests that simulation technologies may empower people with T1D, making them more confident in their diabetes self-management.
Background: Researchers have extensively used metabolic simulators as a fast, inexpensive, and safe way of testing novel treatment strategies. This work aims to bring this technology to people with T1D to enable unique patient/data interactions. Methods: A 5-week pilot study was carried out in 15 adults with T1D using Control-IQ technology (age 36±13 years, HbA1c 6.5±0.7%) to evaluate acceptance of the proposed Web-Based Simulation Tool (WST). The study consisted of 1 week of observation (Phase 1) and 4 weeks of interaction with WST (Phase 2). Data were automatically collected via Tandem Diabetes Care t:connect web application, and used to generate personalized models of the participants’ glucose metabolism. Results: Success rate in generating models was 86.4%, achieving an average MARD of 7.4±3.2%. Interaction time was 15.8±10.7 min per week. Comparing Phases 1 and 2, no variation was detected in time in range 70-180 mg/dl (80.1 [70.4,89.6]% vs. 80 [69.7,87.9]%). Time in 70-250 mg/dl increased slightly (94.2 [90.3,95.7]% vs. 96.2 [92.1,97.9]%), especially overnight (92.8 [88.3,98.2]% vs. 97.2 [91.8,99.6]%), and for participants who modified their pump settings based on WST simulations (90 [88.7,92.4]% vs. 94.5 [87.1,99.6]%). One subject tested COVID positive during the study and was excluded from this analysis due to abnormal hyperglycemia. Analysis of Diabetes Distress Scale (DDS)-17 pre and post-system use shows a reduction in diabetes-related distress (2.2 [1.7,3.4] vs. 2 [1.7,2.4]). Trust, ease of use, and usefulness scores were 80 [60,80]%, 60 [60,80]%, and 80 [60,80]%, respectively. During the follow up interviews, 10 participants reported they enjoyed using WST and would implement it into their diabetes management; 2 did not like the system but see the potential of it for other people; 3 participants did not like the system at all. Conclusions: Evidence from this study suggests that simulation technologies may empower people with T1D, making them more confident in their diabetes self-management.
Author BRETON, MARC D.
WAKEMAN, CHRISTIAN A.
NASS, RALF
COLMEGNA, PATRICIO
OLIVERI, MARY C.
MCFADDEN, RYAN
BISIO, ALESSANDRO
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Snippet Background: Researchers have extensively used metabolic simulators as a fast, inexpensive, and safe way of testing novel treatment strategies. This work aims...
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SubjectTerms Diabetes
Diabetes mellitus
Glucose metabolism
Hyperglycemia
Simulation
Title 97-LB: Bringing Simulation Technologies to People with T1D: A Pilot Study
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