1058-P: The Use of Metabolic Digital Twins to Personalize Mealtime Insulin Dosing in Type 1 Diabetes Clinical Management
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’ (M...
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Veröffentlicht in: | Diabetes (New York, N.Y.) N.Y.), 2019-06, Vol.68 (Supplement_1) |
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Zusammenfassung: | 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. |
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ISSN: | 0012-1797 1939-327X |
DOI: | 10.2337/db19-1058-P |