Michele Schiavon, Italy
University of Padova Department of Information EngineeringPresenter of 2 Presentations
INTRA-INDIVIDUAL VARIABILITY IN SUBCUTANEOUS INSULIN ABSORPTION DURING HYBRID CLOSED-LOOP MEAL STUDY IN YOUTHS WITH TYPE 1 DIABETES: A MODELING ANALYSIS
Abstract
Background and Aims
Intra-individual variability in insulin absorption after subcutaneous (SC) infusion may impair glycemic outcomes and has not been widely studied in the hybrid closed-loop (HCL) setting. Our aim was to ascertain the intra-individual variability in SC insulin absorption by means of a previously validated model (Schiavon et al., IEEE 2018) during a standardized HCL meal study.
Methods
Ten youths with T1D (age=20.9±3.7 y; BMI=23.6±4.5 kg/m2; TDD= 50.6±16.3 U/day) underwent two consecutive, standardized meal studies (70g carbohydrate breakfast and lunch meals) on the same day during DiAs HCL (CGM: Dexcom G4 Platinum with software 505; Insulin pump: Tandem t:slimTM) treatment. Pre-meal insulin bolus was determined based on subjects’ insulin to carbohydrate ratio and was delivered at the beginning of each meal. Plasma insulin aspart concentrations were measured every 10min for 4h during each meal and were used to estimate, for each subject and for each meal, a set of SC insulin absorption parameters (Figure A). The primary metric to assess intra-individual variability of model-derived parameters was the between-meals coefficient of variation (CV %).
Results
As shown in Figure B, mean values of model parameters have been similar between meals (p=NS); however mean intra-individual variability (CV) ranged from 34-94%, with the highest CV for the model parameter representing the direct absorption of non-monomeric insulin to plasma (ka1).
Conclusions
Our preliminary results suggest high intra-individual variability in SC insulin absorption during HCL treatment and underline the importance of optimizing insulin delivery algorithms to account for such variability to improve treatment outcomes.
PLASMA-TO-INTERSTITIUM GLUCOSE KINETICS: IN SILICO STUDY OF EXPERIMENT DESIGN VARIABLES
Abstract
Background and Aims
Recently, we showed that a linear two-compartment model (Schiavon et al., DTT 2015) is able to describe plasma-to-interstitial fluid (ISF) glucose kinetics both in steady as well as non-steady state conditions (Schiavon et al., ATTD 2019) using multi-tracer plasma and microdialysis data. The model allows estimation of plasma-to-ISF equilibration time (τ). However, on average, slower kinetics and greater variability was shown in non-steady than steady state conditions. Here we aim to test in silico the role that experiment design variables may have on τ estimation.
Methods
The 100 virtual adult population of the UVA/Padova T1D simulator (Visentin at al., JDST 2018) was used to simulate plasma-to-ISF glucose kinetics in fasting (steady state) and postprandial (non-steady state) conditions. In addition, a primed-constant i.v. infusion of glucose tracer was simulated. Measurements of glucose concentrations and tracer enrichments were simulated in both plasma and ISF. Different experimental settings were simulated while τ estimation was performed by fitting the model to ISF glucose tracer data using plasma measurements as forcing functions.
Results
The model is able to describe the data in the various experimental settings. An effect of sampling schedule and data pooling in both steady state and non-steady state conditions have been observed. The role of measuring glucose concentration in ISF has also been assessed.
Conclusions
Experiment design is critical to accurately assess plasma-to-ISF glucose kinetics and should be taken into account in evaluating the plasma-to-ISF equilibration time.