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76     CHAPTER 4 Consequences of SMBG systems inaccuracy




                         [72] Kovatchev BP, Breton M, Man CD, Cobelli C. In silico preclinical trials: a proof of
                             concept in closed-loop control of type 1 diabetes. Journal of Diabetes Science and Tech-
                             nology 2009;3(1):44e55.
                         [73] Wilinska ME, et al. Overnight closed-loop insulin delivery with model predictive con-
                             trol: assessment of hypoglycemia and hyperglycemia risk using simulation studies.
                             Journal of Diabetes Science and Technology 2009;3(5):1109e20.
                         [74] Gonder-Frederick  L,  Cox  D,  Kovatchev  B,  Schlundt  D,  Clarke  W.
                             A biopsychobehavioral model of risk of severe hypoglycemia. Diabetes Care 1997;
                             20(4):661e9.
                         [75] Shepard JA, Gonder-Frederick L, Vajda K, Kovatchev B. Patient perspectives on
                             personalized glucose advisory systems for type 1 diabetes management. Diabetes Tech-
                             nology and Therapeutics 2012;14(10):858e61.
                         [76] Campos-Na ´n ˜ez E, Fortwaengler K, Breton MD. Clinical impact of blood glucose moni-
                             toring accuracy: an in-silico study. Journal of Diabetes Science and Technology 2017;
                             11(6):1187e95.
                         [77] Patek SD, et al. Empirical representation of blood glucose variability in a compart-
                             mental model. In: Kirchsteiger H, Jørgensen JB, Renard E, del Re L, editors. Prediction
                             methods for blood glucose concentration: design, use and evaluation. Cham: Springer
                             International Publishing; 2016. p. 133e57.
                         [78] Kovatchev BP, Patek SD, Ortiz EA, Breton MD. Assessing sensor accuracy for non-
                             adjunct use of continuous glucose monitoring. Diabetes Technology and Therapeutics
                             2015;17(3):177e86.
                         [79] Facchinetti A, Favero SD, Sparacino G, Castle JR, Ward WK, Cobelli C. Modeling the
                             glucose sensor error. IEEE Transactions on Biomedical Engineering 2014;61(3):
                             620e9.
                         [80] Breton MD, Hinzmann R, Campos-Nan ˜ez E, Riddle S, Schoemaker M, Schmelzeisen-
                             Redeker G. Analysis of the accuracy and performance of a continuous glucose moni-
                             toring sensor prototype: an in-silico study using the UVA/PADOVA type 1 diabetes
                             simulator. Journal of Diabetes Science and Technology 2017;11(3):545e52.
                         [81] Vettoretti M, Facchinetti A, Sparacino G, Cobelli C. A model of self-monitoring blood
                             glucose measurement error. Journal of Diabetes Science and Technology 2017;11(4):
                             724e35.
                         [82] Fabris C, Patek SD, Breton MD. Are risk indices derived from CGM interchangeable
                             with SMBG-based indices? Journal of Diabetes Science and Technology 2016;10(1):
                             50e9.
                         [83] Nathan DM, Kuenen J, Borg R, Zheng H, Schoenfeld D, Heine RJ. Translating the A1c
                             assay into estimated average glucose values. Diabetes Care 2008;31(8):1473e8.
                         [84] Fritzen K, Heinemann L, Schnell O. Modeling of diabetes and its clinical impact. Jour-
                             nal of Diabetes Science and Technology 2018;12(5):976e84.
                         [85] McQueen RB, et al. Association between glycated hemoglobin and health utility for
                             type 1 diabetes. The Patient: Patient-Centered Outcomes Research Jun. 2014;7(2):
                             197e205.
                         [86] McQueen RB, Breton MD, Ott M, Koa H, Beamer B, Campbell JD. Economic value of
                             improved accuracy for self-monitoring of blood glucose devices for type 1 diabetes in
                             Canada. Journal of Diabetes Science and Technology 2016;10(2):366e77.
                         [87] McQueen RB, et al. Economic value of improved accuracy for self-monitoring of blood
                             glucose devices for type 1 and type 2 diabetes in England. Journal of Diabetes Science
                             and Technology 2018;12(5):992e1001.
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