Page 316 - Glucose Monitoring Devices
P. 316
References 323
[10] Cengiz E, Swan KL, Tamborlane WV, Steil GM, Steffen AT, Weinzimer SA. Is an auto-
matic pump suspension feature safe for children with type 1 diabetes? An exploratory
analysis with a closed-loop system. Diabetes Technology and Therapeutics 2009;11(4):
207e10.
[11] Sherr JL, et al. Safety of nighttime 2-hour suspension of basal insulin in pump-treated
type 1 diabetes even in the absence of low glucose. Diabetes Care 2014;37(3):773e9.
[12] Agrawal P, Welsh JB, Kannard B, Askari S, Yang Q, Kaufman FR. Usage and effective-
ness of the low glucose suspend feature of the Medtronic Paradigm Veo insulin pump.
Journal of Diabetes Science and Technology 2011;5(5):1137e41.
[13] Renard E, et al. Day and night closed-loop glucose control in patients with type 1 dia-
betes under free-living conditions: results of a single-arm 1-month experience
compared with a previously reported feasibility study of evening and night at home.
Diabetes Care 2016:dc160008.
[14] Harvey RA, et al. Clinical evaluation of an automated artificial pancreas using zone-
model predictive control and health monitoring system. Diabetes Technology and Ther-
apeutics 2014;16(6):348e57.
[15] Nimri R, et al. Night glucose control with MD-logic artificial pancreas in home setting:
a single blind, randomized crossover trial-interim analysis. Pediatric Diabetes 2014;15:
91e9.
[16] Kropff J, et al. 2 month evening and night closed-loop glucose control in patients with
type 1 diabetes under free-living conditions: a randomised crossover trial. Lancet Dia-
betes and Endocrinology 2015;3(12):939e47.
[17] Dassau E, et al. Multicenter outpatient randomized crossover trial of zone-MPC artifi-
cial pancreas in type 1 diabetes: effects of initialization strategies. In: Diabetes, vol. 64;
2015. A59e60.
[18] Doyle FJ, Huyett LM, Lee JB, Zisser HC, Dassau E. Closed-loop artificial pancreas sys-
tems: engineering the algorithms. Diabetes Care 2014;37(5):1191e7.
[19] Patek SD, et al. In silico preclinical trials: methodology and engineering guide to
closed-loop control in type 1 diabetes mellitus. Journal of Diabetes Science and Tech-
nology 2009;3(2):269e82.
[20] Lee JB, Dassau E, Gondhalekar R, Seborg DE, Pinsker JE, Doyle III FJ. Enhanced
model predictive control (eMPC) strategy for automated glucose control. Industrial
and Engineering Chemistry Research 2016;55(46):11857e68.
[21] Kovatchev B, Tamborlane WV, Cefalu WT, Cobelli C. The artificial pancreas in 2016: a
digital treatment ecosystem for diabetes. Diabetes Care 2016;39(7):1123e6.
[22] Toffanin C, Messori M, Di Palma F, De Nicolao G, Cobelli C, Magni L. Artificial
pancreas: model predictive control design from clinical experience. Journal of Diabetes
Science and Technology 2013;7(6):1470e83.
[23] Renard E, et al. Reduction of hyper-and hypoglycemia during two months with a wear-
able artificial pancreas from dinner to breakfast in patients with type 1 diabetes. In: Dia-
betes, vol. 64; 2015. A237e8.
[24] Nimri R, Atlas E, Ajzensztejn M, Miller S, Oron T, Phillip M. Feasibility study of auto-
mated overnight closed-loop glucose control under MD-logic artificial pancreas in pa-
tients with type 1 diabetes: the DREAM project. Diabetes Technology and Therapeutics
2012;14(8):728e35.
[25] Steil GM, Rebrin K, Darwin C, Hariri F, Saad MF. Feasibility of automating insulin de-
livery for the treatment of type 1 diabetes. Diabetes 2006;55(12):3344e50.