In Silico Simulation of Long-Term Type 1 Diabetes Glycemic Control Treatment Outcomes
| dc.contributor.author | Wong, X.W. | |
| dc.contributor.author | Chase, Geoff | |
| dc.contributor.author | Hann, C.E. | |
| dc.contributor.author | Lotz, T. | |
| dc.contributor.author | Lin, J. | |
| dc.contributor.author | Le Compte, A.J. | |
| dc.contributor.author | Shaw, Geoff | |
| dc.date.accessioned | 2009-06-08T20:48:38Z | |
| dc.date.available | 2009-06-08T20:48:38Z | |
| dc.date.issued | 2008 | en |
| dc.description | Invited journal symposium paper | en |
| dc.description.abstract | Objectives: The goals of this study were to develop (1) a safe and effective protocol for the clinical control of type 1 diabetes using conventional self-monitoring blood glucose (SMBG) measurements and multiple daily injections with insulin analogues, and (2) an in silico simulation tool of type 1 diabetes to predict long-term glycemic control outcomes of clinical interventions. Methods: The virtual patient method was used to develop a simulation tool for type 1 diabetes using data from a type 1 diabetes patient cohort (n = 40). The tool was used to test the adaptive protocol (AC) and a conventional intensive insulin therapy (CC) against results from a representative control cohort. Optimal and suboptimal basal insulin replacements were evaluated as a function of SMBG frequency in conjunction with the (AC and CC) prandial control protocols. Results: In long-term glycemic control, the AC protocol significantly decreased hemoglobin A1c in conditions of suboptimal basal insulin replacement for SMBG frequencies =6/day, and reduced the occurrence of mild and severe hypoglycemia by 86–100% over controls, over all SMBG frequencies in conditions of optimal basal insulin. | en |
| dc.identifier.citation | Wong, X.W., Chase, J.G., Hann, C.E., Lotz, T., Lin, J., Le Compte, A.J., Shaw, G.M. (2008) In Silico Simulation of Long-Term Type 1 Diabetes Glycemic Control Treatment Outcomes. Journal of Diabetes Science and Technology, 2(3), pp. 436-449. | en |
| dc.identifier.issn | 1932-2968 | |
| dc.identifier.uri | http://hdl.handle.net/10092/2526 | |
| dc.language.iso | en | |
| dc.publisher | University of Canterbury. Mechanical Engineering. | en |
| dc.rights.uri | https://hdl.handle.net/10092/17651 | en |
| dc.subject.marsden | Fields of Research::290000 Engineering and Technology::291500 Biomedical Engineering::291504 Biomechanical engineering | en |
| dc.subject.marsden | Fields of Research::320000 Medical and Health Sciences::321000 Clinical Sciences::321004 Endocrinology | en |
| dc.title | In Silico Simulation of Long-Term Type 1 Diabetes Glycemic Control Treatment Outcomes | en |
| dc.type | Journal Article |