In Diabetes technology & therapeutics ; h5-index 40.0
<b>Background:</b> The Patient Empowerment through Predictive Personalised Decision Support (PEPPER) system provides personalised 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, personalised carbohydrate recommendations and dynamic bolus insulin constraint. We evaluated the safety and feasibility of the PEPPER system compared to a standard bolus calculator. <b>Methods:</b> This was an open-labelled multicentre randomized controlled cross-over 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 wash-out period. The primary end-point was percentage time in range (TIR, 3.9mmol/L-10.0mmol/L (70-180mg/dL)). Secondary outcomes included glycaemic variability, quality of life, and outcomes on the safety system and insulin recommender. <b>Results:</b> 54 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 hypoglycaemia with the PEPPER system despite no objective difference in time spent in hypoglycaemia. <b><b>Conclusions:</b></b> The PEPPER system was safe but did not change glycaemic 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.
Avari Parizad, Leal Yenny, Herrero Pau, Wos Marzena, Jugnee Narvada, Arnoriaga-Rodríguez María, Thomas Maria, Liu Chengyuan, Massana Quim, Lopez Beatriz, Nita Lucian, Martin Clare, Fernandez-Real J M, Oliver Nick, Fernandez Merce, Reddy Monika