Independent cohort cross-validation of the real-time DISTq estimation of insulin sensitivity (2011)
Type of ContentJournal Article
PublisherUniversity of Canterbury. Electrical and Computer Engineering
University of Canterbury. Mechanical Engineering
AuthorsDocherty, P.D., Chase, J.G., Lotz, T.F., Hann, C.E., Shaw, G.M., Berkeley, J.E., TeMorenaga, L., Mann, J.I., McAuley, K.show all
Insulin sensitivity (SI) is useful in the diagnosis, screening and treatment of diabetes. However, most current tests cannot provide an accurate, immediate or real-time estimate. The DISTq method does not require insulin or C-peptide assays like most SI tests, thus enabling real-time, low-cost SI estimation. The method uses a-posteriori parameter estimations in the absence of insulin or C-peptide assays to simulate accurate, patient-specific, insulin concentrations that enable SI identification. Mathematical functions for the a-posteriori parameter estimates were generated using data from 46 fully sampled DIST tests (glucose, insulin and C-peptide). SI values found using the DISTq from the 46 test pilot cohort and a second independent 218 test cohort correlated R=0.890 and R=0.825, respectively, to the fully sampled (including insulin and C-peptide assays) DIST SI metrics. When the a-posteriori insulin estimation functions were derived using the second cohort, correlations for the pilot and second cohorts reduced to 0.765 and 0.818, respectively. These results show accurate SI estimation is possible in the absence of insulin or C-peptide assays using the proposed method. Such estimates may only need to be generated once and then used repeatedly in the future for isolated cohorts. The reduced correlation using the second cohort was due to this cohort’s bias towards low SI insulin resistant subjects, limiting the dataset’s ability to generalise over a wider range. All the correlations remain high enough for the DISTq to be a useful test for a number of clinical applications. The unique real-time results can be generated within minutes of testing as no insulin and C-peptide assays are required and may enable new clinical applications.
CitationDocherty, P.D., Chase, J.G., Lotz, T.F., Hann, C.E., Shaw, G.M., Berkeley, J.E., TeMorenaga, L., Mann, J.I., McAuley, K. (2011) Independent cohort cross-validation of the real-time DISTq estimation of insulin sensitivity. Computer Methods and Programs in Biomedicine, 102(2), pp. 94-104.
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Keywordsinsulin sensitivity test; diabetes risk assessment; physiological modelling
ANZSRC Fields of Research09 - Engineering::0903 - Biomedical Engineering::090302 - Biomechanical Engineering
11 - Medical and Health Sciences::1103 - Clinical Sciences::110306 - Endocrinology