Abstract

Introduction: Type 1 diabetes guidelines recommend that mealtime insulin dosing accounts for fat and protein. However, implementation remains a challenge. Aim: To evaluate an individual’s glycemic response to a high fat, high protein meal (HFHP) and develop a personalized ‘metabolic digital twin’ (MDTwin) capable of predicting an optimal insulin dose and delivery pattern which accounts for meal fat and protein. Method: Participants (n=9) using pump therapy; mean age 13.9 ±3.2 years (5 male), T1D duration 4.8 ±3.8 years, and HbA1c 49 mmol/mol (6.7 ±0.6%) wore Dexcom G5 CGMS and were given an insulin dual wave bolus (insulin to carbohydrate ratio [ICR] x1, ICRx1.2, ICRx1.4 or ICRx1.6) and ate a HFHP (C:30g, F:40g, P:50g) on 4 mornings. Individual MDTwins were fitted by System Identification methodology combined with a statistical quantification using the ICRx1 and ICRx1.6 CGMS traces. MDTwins were validated using the ICRx1.2 and ICRx1.4 traces. Results: The MDTwins identified individual insulin and distribution requirements to achieve optimal postprandial glycemic control (Figure). MDTwins identified marked inter-individual variability in insulin dose and distribution requirements. Conclusion: MDTwins can potentially be used to inform and individualize insulin dosing strategies for meal fat and protein to produce optimal glycemic outcomes. Further research is required. Disclosure T.A. Smith: None. M.M. Seron: None. G.C. Goodwin: None. A.M. Medioli: None. B.R. King: None. C.E. Smart: None. M. Harris: None. D.N. ONeal: None. J. Rafferty: None. P. Howley: None. Funding Diabetes Australia

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