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Content Provider | IEEE Xplore Digital Library |
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Author | Natalucci, S. Boemi, M. Carnevali, R. Fumelli, P. Burattini, R. |
Copyright Year | 1999 |
Description | Author affiliation: Dipt. di Elettronica e Autom., Ancona Univ., Italy (Natalucci, S.) |
Abstract | A standard intravenous glucose tolerance test (IVGTT) was performed in five non-diabetic patients with essential hypertension (under long-term pharmacological treatment) and five normotensive control subjects. A two-compartment minimal model (2CMM) of glucose kinetics was applied to estimate indexes of glucose effectiveness and insulin sensitivity by means of a maximum a posteriori (MAP) Bayesian estimation technique. These estimates were contrasted to those obtained from the application of the classic minimal model (1CMM). Both the 2CMM and the 1CMM yielded estimates of glucose effectiveness and insulin sensitivity indexes that document severe insulin resistance and impaired glucose effectiveness in non-diabetic hypertensive patients. The index of glucose effectiveness provided by the 2CMM was, on average, 70% (in the hypertensive group) and 56% (in the normotensive group) of the corresponding estimate provided by the MM. The 2CMM index of insulin sensitivity was, on average, 140% and 142% of the corresponding estimate provided by the 1CMM. These results confirm that the Bayesian identification of the 2CMM improves the accuracy of glucose effectiveness and of insulin sensitivity estimates over the classic single-pool description (1CMM) of glucose kinetics. |
File Size | 109589 |
File Format | |
ISBN | 0780356748 |
ISSN | 1094687X |
DOI | 10.1109/IEMBS.1999.804158 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 1999-10-13 |
Publisher Place | USA |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Sugar Insulin Hypertension Kinetic theory Bayesian methods Diabetes Testing Medical treatment Diseases Yield estimation |
Content Type | Text |
Resource Type | Article |
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