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High Resolution Clinical Model-Based Assessment of Insulin Sensitivity

Type 2 diabetes has reached epidemic proportions worldwide. The resulting increase
in chronic and costly diabetes related complications has potentially catastrophic
implications for healthcare systems, and economies and societies as a
whole. One of the key pathological factors leading to type 2 diabetes is insulin
resistance (IR), which is the reduced or impaired ability of the body to make use
of available insulin to maintain normal blood glucose levels.
Diagnosis of developing IR is possible up to 10 years before the diagnosis of
type 2 diabetes, providing an invaluable opportunity to intervene and prevent or
delay the onset of the disease. However, an accurate, yet simple, test to provide
a widespread clinically feasible early diagnosis of IR is not yet available. Current
clinically practicable tests cannot yield more than a crude surrogate metric that
allows only a threshold-based assessment of an underlying disorder, and thus
delay its diagnosis.
This thesis develops, analyses and pilots a model-based insulin sensitivity
test that is simple, short, physiological and cost efficient. It is thus useful in a
practical clinical setting for wider clinical screening. The method incorporates
physiological knowledge and modelling of glucose, insulin and C-peptide kinetics
and their pharmaco-dynamics. The clinical protocol is designed to produce
data from a dynamic perturbation of the metabolic system that enables a unique
physiologically valid assessment of metabolic status. A combination of a-priori information
and a convex integral-based identification method guarantee a unique,
robust and automated identification of model parameters.
In addition to a high resolution insulin sensitivity metric, the test also yields
a clinically valuable and accurate assessment of pancreatic function, which is also
a good indicator of the progression of the metabolic defect. The combination of these two diagnostic metrics allow a clinical assessment of a more complete
picture of the overall metabolic dysfunction. This outcome can assist the clinician
in providing an earlier and much improved diagnosis of insulin resistance and
metabolic status and thus more optimised treatment options.
Test protocol accuracy is first evaluated in Monte Carlo simulations and subsequently
in a clinical pilot study. Both validations yield comparable results in
repeatability and robustness. Repeatability and resolution of the test metrics
are very high, particularly when compared to current clinical standard surrogate
fasting or oral glucose tolerance assessments. Additionally, the model based insulin
sensitivity metric is shown to be highly correlated to the highly complex,
research focused gold standard euglycaemic clamp test.
Various reduced sample and shortened protocols are also proposed to enable
effective application of the test in a wider range of clinical and laboratory settings.
Overall, test time can be as short as 30 minutes with no compromise in diagnostic
performance. A suite of tests is thus created and made available to match varying
clinical and research requirements in terms of accuracy, intensity and cost. Comparison
between metrics obtained from all protocols is possible, as they measure
the same underlying effects with identical model-based assumptions.
Finally, the proposed insulin sensitivity test in all its forms is well suited for
clinical use. The diagnostic value of the test can assist clinical diagnosis, improve
treatment, and provide for higher resolution and earlier diagnosis than currently
existing clinical and research standards. High risk populations can therefore be
diagnosed much earlier and the onset of complications delayed. The net result
will thus improve overall healthcare, reduce costs and save lives.

Identiferoai:union.ndltd.org:canterbury.ac.nz/oai:ir.canterbury.ac.nz:10092/1571
Date January 2007
CreatorsLotz, Thomas Friedhelm
PublisherUniversity of Canterbury. Mechanical Engineering
Source SetsUniversity of Canterbury
LanguageEnglish
Detected LanguageEnglish
TypeElectronic thesis or dissertation, Text
RightsCopyright Thomas Friedhelm Lotz, http://library.canterbury.ac.nz/thesis/etheses_copyright.shtml

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