Insulin sensitivity is a crucial parameter of glucose metabolism. The standard measures of insulin sensitivity obtained by an euglycaemic hyperinsulinaemic clamp, Si(clamp), or by the minimal model (MM), SI, do not account for the dynamics of insulin action, i.e., how fast or slow insulin action reaches its plateau value. This is an important physiological information. In this paper we formally define a new insulin sensitivity index which also incorporates information on the dynamics of insulin action, SD(I), show its properties, and exemplify how it can be measured both with the clamp and the MM method. Then, by resorting to real and synthetic data, we show both in IVGTT MM and clamp studies why this new index SD(I) offers, in comparison with SI, a more comprehensive picture of the control of insulin on glucose.

A new dynamic index of insulin sensitivity / G. Pillonetto, A. Caumo, G. Sparacino, C. Cobelli. - In: IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING. - ISSN 0018-9294. - 53:3(2006 Mar), pp. 1597487.369-1597487.379. [10.1109/TBME.2005.869654]

A new dynamic index of insulin sensitivity

A. Caumo
Secondo
;
2006

Abstract

Insulin sensitivity is a crucial parameter of glucose metabolism. The standard measures of insulin sensitivity obtained by an euglycaemic hyperinsulinaemic clamp, Si(clamp), or by the minimal model (MM), SI, do not account for the dynamics of insulin action, i.e., how fast or slow insulin action reaches its plateau value. This is an important physiological information. In this paper we formally define a new insulin sensitivity index which also incorporates information on the dynamics of insulin action, SD(I), show its properties, and exemplify how it can be measured both with the clamp and the MM method. Then, by resorting to real and synthetic data, we show both in IVGTT MM and clamp studies why this new index SD(I) offers, in comparison with SI, a more comprehensive picture of the control of insulin on glucose.
Bayesian estimation; Diabetes; Glucose clamp; Insulin resistance; Markov chain Monte Carlo; Minimal model
Settore ING-INF/06 - Bioingegneria Elettronica e Informatica
mar-2006
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/160555
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