The Identification of Insulin Saturation Effects During the Dynamic Insulin Sensitivity Test
Paul D Docherty 1, J. Geoffrey Chase 1, Christopher E. Hann *, 1, Thomas F. Lotz1, J. Lin1, Kirsten A. McAuley 2, Geoffrey M. Shaw 3
Identifiers and Pagination:Year: 2010
First Page: 141
Last Page: 148
Publisher Id: TOMINFOJ-4-141
Article History:Received Date: 19/03/2010
Revision Received Date: 15/04/2010
Acceptance Date: 13/05/2010
Electronic publication date: 27/7/2010
Collection year: 2010
open-access license: This is an open access article licensed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited.
Many insulin sensitivity (SI) tests identify a sensitivity metric that is proportional to the total available insulin and measured glucose disposal despite general acceptance that insulin action is saturable. Accounting for insulin action saturation may aid inter-participant and/or inter-test comparisons of insulin efficiency, and model-based glycaemic regulation.
Eighteen subjects participated in 46 dynamic insulin sensitivity tests (DIST, low-dose 40-50 minute insulin-modified IVGTT). The data was used to identify and compare SI metrics from three models: a proportional model (SIL), a saturable model (SIS and Q50) and a model similar to the Minimal Model (SG and SIG). The three models are compared using inter-trial parameter repeatability, and fit to data.
The single variable proportional model produced the metric with least intra-subject variation: 13.8% vs 40.1%/55.6%, (SIS/I50) for the saturable model and 15.8%/88.2% (SIG/SG) for the third model. The average plasma insulin concentration at half maximum action (I50) was 139.3 mU·L-1, which is comparable to studies which use more robust stepped EIC protocols.
The saturation model and method presented enables a reasonable estimation of an overall patient-specific saturation threshold, which is a unique result for a test of such low dose and duration. The detection of previously published population trends and significant bias above noise suggests that the model and method successfully detects actual saturation signals. Furthermore, the saturation model allowed closer fits to the clinical data than the other models, and the saturation parameter showed a moderate distinction between NGT and IFG-T2DM subgroups. However, the proposed model did not provide metrics of sufficient resolution to enable confidence in the method for either SI metric comparisons across dynamic tests or for glycamic control.