Dynamic insulin sensitivity index: Importance in diabetes

Gianluigi Pillonetto, Andrea Caumo, Claudio Cobelli

Research output: Contribution to journalArticlepeer-review

Abstract

The classical minimal model (MM) index of insulin sensitivity, S I, does not account for how fast or slow insulin action takes place. In a recent work, we proposed a new dynamic insulin sensitivity index, S ID, which is able to take into account the dynamics of insulin action as well. The new index is a function of two MM parameters, namely SI and p2, the latter parameter governing the speed of rise and decay of insulin action. We have previously shown that in normal glucose tolerant subjects SID provides a more comprehensive picture of insulin action on glucose metabolism than S I. The aim of this study is to show that resorting to S ID rather SI is even more appropriate when studying diabetic patients who have a low and slow insulin action. We analyzed insulinmodified intravenous glucose tolerance test studies performed in 10 diabetic subjects and mixed meal glucose tolerance test studies exploiting the triple tracer technique in 14 diabetic subjects. We derived both SI and SID resorting to Bayesian and Fisherian identification strategies. The results show that SID is estimated more precisely than SI when using the Bayesian approach. In addition, the less laborintensive Fisherian approach can still be used to obtain reliable point estimates of SID but not of SI. These results suggest that SID yields a comprehensive, precise, and cost-effective assessment of insulin sensitivity in subjects with impaired insulin action like impaired glucose tolerant subjects or diabetic patients.

Original languageEnglish
JournalAmerican Journal of Physiology - Endocrinology and Metabolism
Volume298
Issue number3
DOIs
Publication statusPublished - Mar 2010

Keywords

  • Bayesian estimation
  • Diabetes
  • Insulin resistance
  • Markov chain Monte Carlo strategy
  • Model
  • Parameter estimation

ASJC Scopus subject areas

  • Physiology
  • Endocrinology, Diabetes and Metabolism
  • Physiology (medical)

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