733-P: Postprandial Glucose Variability in People with Type 1 Diabetes Is Individual and Impacted by Physiological and Clinical Parameters

Abstract

Aim: To assess whether postprandial glucose responses (PPGRs) are individual in people with type 1 diabetes (T1DM) and influenced by personal physiological and clinical parameters. Methods: We assessed physiological and clinical parameters of one-hundred and twenty individuals with type 1 diabetes (mean±SD: Age 31±7years, BMI 26.9±2.3kg.m2, HbA1c 7.6±0.8% [55.8±8.2mmol/moL]) and captured postprandial interstitial glucose responses via continuous glucose monitoring (CGM) in response to two carbohydrate-based standardised meals (shredded wheat [SW] or millet oat-porridge [OP]), twice, on four separate occasions. Each meal was matched for energy, fibre, and macronutrient composition, glycaemic index (GI), and insulin administration. Results: Despite identical energy, fibre, and macronutrient content, GI, and prandial insulin administration, the average PPGR differed significantly between OP and SW, respectively (IG AUC: 1807±588 vs. 1678±533 mmol.L.min-1; p=0.05). PPGRs to each meal type showed a high degree of reproducibility within individuals (OP r=0.994, p<0.001 vs. SW r=0.987 p<0.001), but large interpersonal variation within each meal type (CV%: OP 32.5% vs. SW 31.7%). Higher PPGR was positively associated with PPGR variability (r=0.698, p<0.001), HbA1c (r=0.223, p=0.014), BMI (r=0.316, p<0.001), and age (r=0.277, p<0.001). Conclusions: Using a total of 19,200 glucose measurements, we show that PPGR in individuals with type 1 diabetes is interpersonal and influenced by BMI, age, and HbA1c. We show that identification of personal characteristics is a promising means for designing effective nutritional interventions to predict and control glycaemic responses to food in this population. Disclosure C.F.B. Dingena: None. A. Marsh: None. R. Ajjan: Advisory Panel; Self; Eli Lilly and Company, Merck Sharp & Dohme Corp., Novo Nordisk Inc., Takeda Pharmaceutical Company Limited. Other Relationship; Self; Abbott. M. Campbell: None.

Application of Machine Learning to Assess Interindividual Variability in Rapid-Acting Insulin Responses After Subcutaneous Injection in People With Type 1 Diabetes

“…Existing treatment guidelines focus on individualising insulin dose, adjusting as necessary according to meal composition and the results of regular glucose monitoring 1 . However, we suggest that current recommendations are limited in that they do not account for individual physiological and clinical characteristics which are a known source of heterogeneity in response to insulin therapy 22 . It was not our intention to establish distinct subtypes of T1D representative of different aetiologies, and we do not claim that the clustering applied here is in anyway an optimal classification for T1D vascular risk.…”

New Contributions Towards Meal and Exercise Announcement-Free Artificial Pancreas Systems

“…Moreover, other factors such as emotional or physical stress, illness, hormonal changes, and microbiome shape the postprandial glucose excursion (Gingras et al 2018a;Wilson et al 2021). Thus, identical meals can result in different glucose levels between days or individuals (Rasmussen 1993;Dingena et al 2020).…”