Literature DB >> 16532763

A new dynamic index of insulin sensitivity.

Gianluigi Pillonetto1, Andrea Caumo, Giovanni Sparacino, Claudio Cobelli.   

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.

Entities:  

Mesh:

Substances:

Year:  2006        PMID: 16532763     DOI: 10.1109/TBME.2005.869654

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  9 in total

1.  Dynamics of insulin action in hypertension: assessment from minimal model interpretation of intravenous glucose tolerance test data.

Authors:  Roberto Burattini; Micaela Morettini; Francesco Di Nardo; Massimo Boemi
Journal:  Med Biol Eng Comput       Date:  2011-03-30       Impact factor: 2.602

2.  Advantages of the single delay model for the assessment of insulin sensitivity from the intravenous glucose tolerance test.

Authors:  Simona Panunzi; Andrea De Gaetano; Geltrude Mingrone
Journal:  Theor Biol Med Model       Date:  2010-03-18       Impact factor: 2.432

3.  Dynamic insulin sensitivity index: importance in diabetes.

Authors:  Gianluigi Pillonetto; Andrea Caumo; Claudio Cobelli
Journal:  Am J Physiol Endocrinol Metab       Date:  2009-11-17       Impact factor: 4.310

4.  A novel mathematical model detecting early individual changes of insulin resistance.

Authors:  Claudia Eberle; Wulf Palinski; Christoph Ament
Journal:  Diabetes Technol Ther       Date:  2013-08-06       Impact factor: 6.118

5.  Dimensional analysis of MINMOD leads to definition of the disposition index of glucose regulation and improved simulation algorithm.

Authors:  Aparna Nittala; Soumitra Ghosh; Darko Stefanovski; Richard Bergman; Xujing Wang
Journal:  Biomed Eng Online       Date:  2006-07-14       Impact factor: 2.819

6.  Good agreement between hyperinsulinemic-euglycemic clamp and 2 hours oral minimal model assessed insulin sensitivity in adolescents.

Authors:  Anne-Marie Carreau; Danielle Xie; Yesenia Garcia-Reyes; Haseeb Rahat; Kai Bartlette; Cecilia Diniz Behn; Laura Pyle; Kristen J Nadeau; Melanie Cree-Green
Journal:  Pediatr Diabetes       Date:  2020-07-31       Impact factor: 3.409

Review 7.  The oral minimal model method.

Authors:  Claudio Cobelli; Chiara Dalla Man; Gianna Toffolo; Rita Basu; Adrian Vella; Robert Rizza
Journal:  Diabetes       Date:  2014-04       Impact factor: 9.461

Review 8.  Next-generation, personalised, model-based critical care medicine: a state-of-the art review of in silico virtual patient models, methods, and cohorts, and how to validation them.

Authors:  J Geoffrey Chase; Jean-Charles Preiser; Jennifer L Dickson; Antoine Pironet; Yeong Shiong Chiew; Christopher G Pretty; Geoffrey M Shaw; Balazs Benyo; Knut Moeller; Soroush Safaei; Merryn Tawhai; Peter Hunter; Thomas Desaive
Journal:  Biomed Eng Online       Date:  2018-02-20       Impact factor: 2.819

Review 9.  Diabetes technology: markers, monitoring, assessment, and control of blood glucose fluctuations in diabetes.

Authors:  Boris P Kovatchev
Journal:  Scientifica (Cairo)       Date:  2012-10-17
  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.