Safety and feasibility of the PEPPER adaptive bolus advisor and safety system; a randomized control study
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Accepted version
Author(s)
Type
Journal Article
Abstract
Background: The Patient Empowerment through Predictive Personalized Decision Support (PEPPER) system provides personalized bolus advice for people with type 1 diabetes. The system incorporates an adaptive insulin recommender system (based on case-based reasoning, an artificial intelligence methodology), coupled with a safety system, which includes predictive glucose alerts and alarms, predictive low-glucose suspend, personalized carbohydrate recommendations, and dynamic bolus insulin constraint. We evaluated the safety and efficacy of the PEPPER system compared to a standard bolus calculator.
Methods: This was an open-labeled multicenter randomized controlled crossover study. Following 4-week run-in, participants were randomized to PEPPER/Control or Control/PEPPER in a 1:1 ratio for 12 weeks. Participants then crossed over after a washout period. The primary end-point was percentage time in range (TIR, 3.9–10.0 mmol/L [70–180 mg/dL]). Secondary outcomes included glycemic variability, quality of life, and outcomes on the safety system and insulin recommender.
Results: Fifty-four participants on multiple daily injections (MDI) or insulin pump completed the run-in period, making up the intention-to-treat analysis. Median (interquartile range) age was 41.5 (32.3–49.8) years, diabetes duration 21.0 (11.5–26.0) years, and HbA1c 61.0 (58.0–66.1) mmol/mol. No significant difference was observed for percentage TIR between the PEPPER and Control groups (62.5 [52.1–67.8] % vs. 58.4 [49.6–64.3] %, respectively, P = 0.27). For quality of life, participants reported higher perceived hypoglycemia with the PEPPER system despite no objective difference in time spent in hypoglycemia.
Conclusions: The PEPPER system was safe, but did not change glycemic outcomes, compared to control. There is wide scope for integrating PEPPER into routine diabetes management for pump and MDI users. Further studies are required to confirm overall effectiveness.
Methods: This was an open-labeled multicenter randomized controlled crossover study. Following 4-week run-in, participants were randomized to PEPPER/Control or Control/PEPPER in a 1:1 ratio for 12 weeks. Participants then crossed over after a washout period. The primary end-point was percentage time in range (TIR, 3.9–10.0 mmol/L [70–180 mg/dL]). Secondary outcomes included glycemic variability, quality of life, and outcomes on the safety system and insulin recommender.
Results: Fifty-four participants on multiple daily injections (MDI) or insulin pump completed the run-in period, making up the intention-to-treat analysis. Median (interquartile range) age was 41.5 (32.3–49.8) years, diabetes duration 21.0 (11.5–26.0) years, and HbA1c 61.0 (58.0–66.1) mmol/mol. No significant difference was observed for percentage TIR between the PEPPER and Control groups (62.5 [52.1–67.8] % vs. 58.4 [49.6–64.3] %, respectively, P = 0.27). For quality of life, participants reported higher perceived hypoglycemia with the PEPPER system despite no objective difference in time spent in hypoglycemia.
Conclusions: The PEPPER system was safe, but did not change glycemic outcomes, compared to control. There is wide scope for integrating PEPPER into routine diabetes management for pump and MDI users. Further studies are required to confirm overall effectiveness.
Date Issued
2021-03-01
Date Acceptance
2020-09-16
Citation
Diabetes Technology and Therapeutics, 2021, 23 (3), pp.175-186
ISSN
1520-9156
Publisher
Mary Ann Liebert
Start Page
175
End Page
186
Journal / Book Title
Diabetes Technology and Therapeutics
Volume
23
Issue
3
Copyright Statement
© 2020 Owner. Final publication is available from Mary Ann Liebert, Inc., publishers https://doi.org/10.1089/dia.2020.0301
Sponsor
Commission of the European Communities
Grant Number
689810
Subjects
Adaptive bolus calculator
Artificial intelligence
Case-based reasoning
PEPPER
Personalized carbohydrate recommendations
Predictive glucose alarms
Predictive low-glucose suspend
Type 1 diabetes
Endocrinology & Metabolism
1103 Clinical Sciences
1116 Medical Physiology
Publication Status
Published
Date Publish Online
2020-10-13
