GargSK, WeinzimerSA, TamborlaneWV, et al.: Glucose outcomes with the in-home use of a hybrid closed-loop insulin delivery system in adolescents and adults with type 1 diabetes. Diabetes Technol Ther, 2017; 19:155–163.
4.
AndelinM, KropffJ, MatulevivieneV, et al.: Assessing the accuracy of continuous glucose monitoring (CGM) calibrated with capillary values using capillary or venous glucose levels as a reference. J Diabetes Sci Technol, 2016; 10:876–884.
5.
KovatchevBP, PatekSD, OrtizEA, BretonMD: Assessing sensor accuracy for non-adjunct use of continuous glucose monitoring. Diabetes Technol Ther, 2015; 17:177–186.
6.
GarciaA, Rack-GomerAL, BhavarajuNC, et al.: an advanced continuous glucose monitor for the artificial pancreas. J Diabetes Sci Technol, 2013; 7:1436–1445.
7.
ChristiansenM, BaileyT, WatkinsE, et al.: A new-generation continuous glucose monitoring system: improved accuracy and reliability compared with a previous-generation system. Diabetes Technol. Ther, 2013; 15:881–888.
8.
BaileyTS, ChangA, ChristiansenM: Clinical accuracy of a continuous glucose monitoring system with an advanced algorithm. J Diabetes Sci Technol, 2015; 9:209–214.
9.
WangY, VaddirajuS, GuB, et al.: Foreign body reaction to implantable biosensors: effects of tissue trauma and implant size. J Diabetes Sci Technol, 2015; 9:966–977.
10.
WisniewskiN, KlitzmanB, MillerB, ReichertWM: Decreased analyte transport through implanted membranes: differentiation of biofouling from tissue effects. J Biomed Mater Res, 2001; 57:513–521.
11.
JosephJI, TorjmanMC: Implantable Glucose Sensors, Encyclopedia of Biomaterial and Biomedical Engineering, 2nd Ed., Vol 2; edited by WnekG. and BowlinoG.Informa Healthcare Inc.; 2008; pp 1174–1181.
12.
KluehU: Analysis: on the path to overcoming glucose-sensor-induced reactions. J Diabetes Sci Technol, 2013; 7:452–454.
13.
KluehU, LiuZ, FeldmanB, et al.: Metabolic biofouling of glucose sensors in vivo: role of tissue microhemorrhages. J Diabetes Sci Technol, 2011; 5:583–595.
14.
KvistPH, IburgT, BieleckiM, et al.: Biocompatibility of electrochemical glucose sensors implanted in the subcutis of pigs. Diabetes Technol Ther, 2006; 8:463–475.
15.
AndersonJ, RodriguezA, ChangD: Foreign body reaction to biomaterials. Semin Immunol, 2008; 20:86–100.
16.
DungelP, LongN, YuB, et al.: Study of the effects of tissue reactions on the function of implanted glucose sensors. J Biomed Mater Res, 2007; 85A:699–706.
17.
WardKW: A review of the foreign-body response to subcutaneously-implanted devices: the role of macrophages and cytokines in biofouling and fibrosis. J Diabetes Sci Technol, 2008; 2:768–777.
18.
HeltonK, RatnerB, WisniewskiN: Biomechanics of the sensor tissue interface-effects of motion, pressure, and design on sensor performance and the foreign body response-part I: theoretical framework. J Diabetes Sci Technol, 2011; 5:632–646.
19.
SharkawyAA, KlitzmanB, TruskeyGA, ReichertWM: Engineering the tissue which encapsulates subcutaneous implants. I. Diffusion properties. J Biomed Mater Res, 1997; 37:401–412.
20.
SharkawyAA, KlitzmanB, TruskeyGA, ReichertWM: Engineering the tissue which encapsulates subcutaneous implants. II. Plasma-tissue exchange properties. J Biomed Mater Res, 1998; 40:586–597.
21.
SharkawyAA, KlitzmanB, TruskeyGA, ReichertWM: Engineering the tissue which encapsulates subcutaneous implants. III. Effective tissue response times. J Biomed Mater Res, 1998; 40:598–605.
22.
WoodwardSC: How fibroblasts and giant cells encapsulate implants: considerations in design of glucose sensors. Diabetes Care, 1982; 5:278–280.
23.
GerritsenM, JansenJA, KrosA, et al.: Influence of inflammatory cells and serum on the performance of implantable glucose sensors. J Biomed Mater Res, 2001; 54:69–75.
24.
KluehU, CzajkowskiC, LudzinskaI, et al.: Impact of CCL2 and CCR2 chemokine/receptor deficiencies on macrophage recruitment and continuous glucose monitoring in vivo. Biosens Bioelectron, 2016; 86:262–269.
25.
NovakMT, ReichertWM: Modeling the physiological factors affecting glucose sensor function in vivo. J Diabetes Sci Technol, 2015; 9:993–998.
26.
KamathA, MahalingamA, BraukerJ: Analysis of time lags and other sources of error of the DexCom SEVEN continuous glucose monitor. Diabetes Technol Ther, 2009; 11:689–695.
27.
HuntTK: The physiology of wound healing. Ann Emerg Med, 1988; 17:1265–1273.
28.
KluehU, FraileyJT, QiaoY, et al.: Cell based metabolic barriers to glucose diffusion: macrophages and continuous glucose monitoring. Biomaterials, 2014; 35:3145–3153.
29.
BraukerJH, Carr-BrendelVE, MartinsonLA, et al.: Neovascularization of synthetic membranes directed by membrane microarchitecture. J Biomed Mater Res, 1995; 29:1517–1524.
30.
KluehU, AntarO, QiaoY, KreutzerDL: Role of vascular networks in extending glucose sensor function: impact of angiogenesis and lymphangiogenesis on continuous glucose monitoring in vivo. J Biomed Mater Res A, 2014; 102:3512–3522.
31.
KingC, AndersonSM, BretonM, et al.: Modeling of calibration effectiveness and blood-to-interstitial glucose dynamics as potential confounders of the accuracy of continuous glucose sensors during hyperinsulinemic clamp. J Diabetes Sci Technol, 2007; 1:317–322.
32.
RiglaM, PonsB, RebasaP, et al.: Human subcutaneous tissue response to glucose sensors: macrophages accumulation impact on sensor accuracy. Diabetes Technol Ther, 2018; 20:296–302.
33.
BaileyTS, AhmannA, BrazgR, et al.: Accuracy and acceptability of the 6-day Enlite continuous subcutaneous glucose sensor. Diabetes Technol Ther, 2014; 16:277–283.
34.
BiagiL, RamkissoonMC, FacchinettiA, et al.: Modeling the error of the Medtronic Paradigm Veo Enlite glucose sensor. Sensors, 2017; 17:pii: E1361.
35.
Medtronic: Carelink iPro: Therapy Management Software for Diabetes User Guide.. Medtronic MiniMed. 2016. www.medtronicdiabetes.com (accessed March30, 2018).
36.
FacchinettiA, Del FaveroS, SparacinoG, et al.: Modeling the glucose sensor error. IEEE Trans Biomed Eng, 2014; 61:620–629.
37.
KirchsteigerH, HeinemannL, FreckmannG, et al.: Performance comparison of CGM systems: MARD values are not always a reliable indicator of CGM system accuracy. J Diabetes Sci Technol, 2015; 9:1030–1040.
38.
ReitererF, PolterauerP, SchoemakerM, et al.: Significance and reliability of MARD for the accuracy of CGM systems. J Diabetes Sci Technol, 2017; 11:59–67.
39.
KollmanC, WilsonDM, WysockiT, et al.: Limitations of statistical measures of error in assessing the accuracy of continuous glucose sensors. Diabetes Technol Ther, 2005; 7:665–672; discussion 673–674.