Run-to-run control of meal-related insulin dosing.

BACKGROUND This study was designed to determine if it was feasible to use a run-to-run algorithm to improve postprandial glucose concentrations in individuals with type 1 diabetes mellitus (T1DM). METHODS Fourteen subjects were recruited for this 10-week study. During the initial phases of the study, the following information was derived for each subject: basal insulin infusion rates, insulin-to-carbohydrate ratios, insulin correction factors for hyperglycemia, and insulin sensitivities. During the final phases, the algorithm was used to suggest preprandial insulin doses, with a goal of bringing the postprandial glucose into a predetermined target range within 3-7 days. RESULTS In the single-meal phase (phase 5), 33% of the subject-meal responses were convergent in 3-4 days to a clinically acceptable range, 33% always stayed in range, and 33% had divergent responses, incorrect sensitivities, and/or other mitigating circumstances. In the three-meal phase (phase 6), 41% of the subject-meal responses were convergent in 3-4 days to a clinically acceptable range, 26% were always in range, and 33% had divergent responses, incorrect sensitivities, and/or other mitigating circumstances. CONCLUSIONS Overall, we were able to safely demonstrate that run-to-run control can be used to manage meal-related insulin in subjects with T1DM.

[1]  R. Bergman,et al.  Physiologic evaluation of factors controlling glucose tolerance in man: measurement of insulin sensitivity and beta-cell glucose sensitivity from the response to intravenous glucose. , 1981, The Journal of clinical investigation.

[2]  A M Albisser,et al.  Controlled Study in Diabetic Children Comparing Insulin-Dosage Adjustment by Manual and Computer Algorithms , 1990, Diabetes Care.

[3]  E. Renard,et al.  Feasibility of Intraperitoneal Insulin Therapy With Programmable Implantable Pumps in IDDM: A multicenter study , 1995, Diabetes Care.

[4]  A Peters,et al.  [Analytic design and clinical application of an intelligent control system for pharmacotherapy with insulin--2]. , 1996, Biomedizinische Technik. Biomedical engineering.

[5]  R. Holman,et al.  Randomized controlled pilot trial of a hand-held patient-oriented, insulin regimen optimizer. , 1996, Medical informatics = Medecine et informatique.

[6]  D. Nathan,et al.  Long-Term Therapy of IDDM With an Implantable Insulin Pump , 1997, Diabetes Care.

[7]  T. Deutsch,et al.  Compartmental models for glycaemic prediction and decision-support in clinical diabetes care: promise and reality. , 1998, Computer methods and programs in biomedicine.

[8]  Yoshiaki Ohkami,et al.  Rotational motion-damper for the capture of an uncontrolled floating satellite , 1998 .

[9]  J. Chiasson,et al.  The use of information technology for the management of intensive insulin therapy in type 1 diabetes mellitus. , 2003, Diabetes & metabolism.

[10]  A. King,et al.  A bolus calculator is an effective means of controlling postprandial glycemia in patients on insulin pump therapy. , 2003, Diabetes technology & therapeutics.

[11]  Dominique Bonvin,et al.  Dynamic optimization of batch processes: II. Role of measurements in handling uncertainty , 2003, Comput. Chem. Eng..

[12]  Circe Tsui,et al.  Management of insulin therapy in urban diabetes patients is facilitated by use of an intelligent dosing system. , 2004, Diabetes technology & therapeutics.

[13]  R. Hovorka,et al.  Nonlinear model predictive control of glucose concentration in subjects with type 1 diabetes. , 2004, Physiological measurement.

[14]  B. Gopakumaran,et al.  Analysis: "intelligent dosing system": a useful computer program for diabetes management? , 2004, Diabetes technology & therapeutics.