Modelling the effect of insulin on the disposal of meal-attributable glucose in type 1 diabetes
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文摘
The management of postprandial glucose excursions in type 1 diabetes has a major impact on overall glycaemic control. In this work, we propose and evaluate various mechanistic models to characterize the disposal of meal-attributable glucose. Sixteen young volunteers with type 1 diabetes were subject to a variable-target clamp which replicated glucose profiles observed after a high-glycaemic-load (\(n=8\)) or a low-glycaemic-load (\(n=8\)) evening meal. [6,6-\(^{2}\hbox {H}_2\)] and [U-\(^{13}\hbox {C}\);1,2,3,4,5,6,6-\(^{2}\hbox {H}_{7}\)] glucose tracers were infused to, respectively, mimic: (a) the expected post-meal suppression of endogenous glucose production and (b) the appearance of glucose due to a standard meal. Six compartmental models (all a priori identifiable) were proposed to investigate the remote effect of circulating plasma insulin on the disposal of those glucose tracers from the non-accessible compartments, representing e.g. interstitium. An iterative population-based parameter fitting was employed. Models were evaluated attending to physiological plausibility, posterior identifiability of their parameter estimates, accuracy—via weighted fitting residuals—and information criteria (i.e. parsimony). The most plausible model, best representing our experimental data, comprised: (1) a remote effect x of insulin active above a threshold \(x_{C}\) = 1.74 (0.81–2.50) \(\cdot \,10^{-2}\) min\(^{-1}\) [median (inter-quartile range)], with parameter \(x_{C}\) having a satisfactory support: coefficient of variation CV = 42.33 (31.34–65.34) %, and (2) steady-state conditions at the onset of the experiment (\(t=0\)) for the compartment representing the remote effect, but not for the masses of the tracer that mimicked endogenous glucose production. Consequently, our mechanistic model suggests non-homogeneous changes in the disposal rates for meal-attributable glucose in relation to plasma insulin. The model can be applied to the in silico simulation of meals for the optimization of postprandial insulin infusion regimes in type 1 diabetes.

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