596760
research-article2015
DSTXXX10.1177/1932296815596760Journal of Diabetes Science and TechnologyDehennis et al
Special Section
Multisite Study of an Implanted Continuous Glucose Sensor Over 90 Days in Patients With Diabetes Mellitus
Journal of Diabetes Science and Technology 2015, Vol. 9(5) 951–956 © 2015 Diabetes Technology Society Reprints and permissions: sagepub.com/journalsPermissions.nav DOI: 10.1177/1932296815596760 dst.sagepub.com
Andrew Dehennis, PhD1, Mark A. Mortellaro, PhD1, and Sorin Ioacara, MD, PhD2
Abstract Background: Continuous glucose monitoring (CGM), which enables real-time glucose display and trend information as well as real-time alarms, can improve glycemic control and quality of life in patients with diabetes mellitus. Previous reports have described strategies to extend the useable lifetime of a single sensor from 1-2 weeks to 28 days. The present multisite study describes the characterization of a sensing platform achieving 90 days of continuous use for a single, fully implanted sensor. Method: The Senseonics CGM system is composed of a long-term implantable glucose sensor and a wearable smart transmitter. Study subjects underwent subcutaneous implantation of sensors in the upper arm. Eight-hour clinic sessions were performed every 14 days, during which sensor glucose values were compared against venous blood lab reference measurements collected every 15 minutes using mean absolute relative differences (MARDs). Results: All subjects (mean ± standard deviation age: 43.5 ± 11.0 years; with 10 sensors inserted in men and 14 in women) had type 1 diabetes mellitus. Most (22 of 24) sensors reported glucose values for the entire 90 days. The MARD value was 11.4 ± 2.7% (range, 8.1-19.5%) for reference glucose values between 40-400 mg/dl. There was no significant difference in MARD throughout the 90-day study (P = .31). No serious adverse events were noted. Conclusions: The Senseonics CGM, composed of an implantable sensor, external smart transmitter, and smartphone app, is the first system that uses a single sensor for continuous display of accurate glucose values for 3 months. Keywords continuous glucose monitoring, diabetes mellitus, fluorescent sensor, hypoglycemia alarms, implantable sensors, wearable device Glucose monitoring is a necessary component of glycemic control, and the optimal mode of glucose monitoring would provide data both for preprandial and postprandial glucose excursions, minimize the need for finger stick measurements, and be convenient to promote compliance.1-6 Macrovascular and microvascular outcomes in patients with diabetes mellitus are dependent on glycemic control, yet a significant proportion of patients with diabetes mellitus do not achieve glycemic control target levels of hemoglobin A1c (HbA1c) ≤ 7%, as recommended by the American Diabetes Association.7,8 As patients with diabetes live longer, systems that technologically enable informative, actionable, and continuous glycemic measurements have the potential to positively impact various aspects of diabetes care.9 Ultimately, continuous glucose data would enable a closed loop system for an artificial pancreas delivery system.10,11
One of the technological solutions that could enable better reductions in glycemic variability is the development of an implantable continuous glucose monitoring (CGM) system, several of which have been developed.12-17 However, the sensors used by those devices have a relatively short duration of use ( 180 mg/dl (P = .19 with 1-way ANOVA) (Table 1). In addition, the percentage of CGM sensor data within 20 mg/dl or 20% of reference measurements was determined at 3 different glucose levels; 91% of sensor measurements were calculated to be within 20 mg/ dl for reference glucose measurements of ≤ 70 mg/dl, 86% of sensor data were within 20% of reference glucose measurements between 71-180 mg/dl, and 88% of sensor data were within 20% of reference glucose measurements > 180 mg/dl.
Enrolled subjects ranged in age from 22 to 65 years (mean age, 43.5 ± 11.0 years) and included 10 sensors inserted in men and 14 in women. All individuals had been diagnosed with type 1 diabetes mellitus for at least 6 months.
Sensor life Of the 24 sensors implanted, 22 reported glucose values for the entire 90-day study period. One CGM system stopped displaying glucose at day 55 and another at day 84 when their self-diagnostics indicated sensor performance had decreased below a factory-set threshold. Ex vivo chemical analysis performed after sensor removal showed loss of fluorescence due to chemical degradation of the indicator moieties, the mechanism of which has been previously described.18 The daily calibration points enable the system to account for this loss of fluorescence in vivo with a real-time assessment of the indicators sensitivity to glucose variations. This assessment enables updates to the fluorescent baseline and the responsiveness corresponding to the chemical kinetics for the degradation mechanisms.23
954
Journal of Diabetes Science and Technology 9(5)
Figure 2. Analysis of mean absolute relative difference (MARD) according to the proportion of sensors. The figure illustrates that 50% of the sensors have a MARD ≤ 11%, while 90% of the sensors have a MARD ≤ 16%
Table 1. Sensor Accuracy at High and Low Glucose Levels. Reference glucose range (mg/dl)
Number of paired system-reference readings
MARDa/MADb
116 2101 1369
9.6 mg/dl 11.4% 11.0%
≤70 71-180 >180 a
For glucose values ≥ 70 mg/dl, quantitative differences from reference glucose were assessed by mean absolute relative difference (MARD). For glucose values ≤ 70 mg/dl, mean absolute difference (MAD) was calculated.
b
To assess sensory accuracy over time, the MARD was calculated for and compared among each in-clinic session (~2-week intervals) (Figure 3). This analysis showed that there was no significant difference in MARD over time (P = .31).
Safety No serious adverse events were noted throughout the entire study period in any of the patients.
Discussion The present multisite study showed successful in-clinic and home use of the Senseonics CGM system over 90 days in subjects with diabetes mellitus. Specifically 22 of 24 (92%)
sensors reported glucose continuously for 90 days, and the MARD for all 24 sensors was 11.4 ± 2.7% against venous reference glucose values. CGMs have the potential to facilitate glycemic control (through enhanced compliance with glucose monitoring and through characterization of postprandial glucose excursions), improve quality of life (by minimizing the inconvenience and pain associated with frequent finger sticks), and improve the safety of insulin therapy (by detecting hypoglycemia). Indeed, meta-analyses suggest that CGM use is associated with significant HbA1c lowering when compared with SMBG.24 Furthermore, sensor-augmented insulin pump therapy with a low-glucose-suspend function significantly reduces nocturnal hypoglycemia, and CGMs form the underpinning for the “artificial pancreas” or the closed-loop system as the optimal insulin delivery system.25
955
Dehennis et al Acknowledgments
MARD (%)
25 20
The authors thank Steve Walters for management of the clinical study and Oliver Chen for statistical analysis of the data.
15
Declaration of Conflicting Interests
10
The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: Andrew Dehennis and Mark Mortellaro are employees of Senseonics, Inc and receive salary and stock from the company. Sorin Ioacara is the principal investigator for clinical studies performed by Senseonics in Romania.
5 0
1
15
30
45
60
75
90
Sensor Days
Funding Figure 3. Sensor accuracy over time during the 90-day study period. To assess sensory accuracy over time, the mean absolute relative difference (MARD) was calculated for and compared among each in-clinic session (~2-week intervals). This analysis showed that there was no significant difference in sensory accuracy over time (P = .31 according to the Skillings–Mack test). Values are means, and bars represent standard deviations.
The Senseonics CGM system has several advantages over other CGM devices. First, the Senseonics fully implantable sensor has improved longevity relative to sensors from other CGM systems. Indeed, the sensor lifespan of other commercially available CGMs is typically 5 to 7 days, possibly because those CGM sensors utilize enzymes that have a limited lifespan due to thermal degradation.26 By contrast, the Senseonics CGM sensor detects glucose via a nonenzymatic, abiotic methodology that is not subject to degradation or to the stability limitations inherent to enzyme-based systems.18 In addition, transcutaneous sensors of other CGMs protrude from the skin and do not allow for resolution of an acute inflammatory response, thereby limiting sensor accuracy and performance. The Senseonics sensor is fully inserted into the interstitial tissue, thus allowing the body to heal the insertion wound and resolve the acute inflammatory response. Second, the glucose measurement accuracy of the Senseonics CGM system, as assessed by MARDs, was 11.4%, which is similar to the MARD of the system reported in a 28-day study (11.6%) and which is comparable to the MARD of other commercially available CGM systems.27
Conclusions The Senseonics CGM, composed of an implantable sensor, external smart transmitter, and smartphone app, is the first system that uses a single sensor to provide continuous glucose measurements with very good accuracy over a 3-month period. Abbreviations ANOVA, analysis of variance; BMI, body mass index; CGM, continuous glucose monitoring; HbA1c, hemoglobin A1c; MAD, mean absolute difference; MARD, mean absolute relative difference; SD, standard deviation; SMBG, self-monitored blood glucose.
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was funded by Senseonics, Inc, a privately held company.
References 1. Klonoff DC. Benefits and limitations of self-monitoring of blood glucose. J Diabetes Sci Technol. 2007;1(1):130-132. 2. Farmer A, Wade A, Goyder E, et al. Impact of self monitoring of blood glucose in the management of patients with noninsulin treated diabetes: open parallel group randomised trial. BMJ. 2007;335(7611):132. 3. Brownlee M, Hirsch IB. Glycemic variability: a hemoglobin A1c-independent risk factor for diabetic complications. JAMA. 2006;295(14):1707-1708. 4. Rizzo MR, Marfella R, Barbieri M, et al. Relationships between daily acute glucose fluctuations and cognitive performance among aged type 2 diabetic patients. Diabetes Care. 2010;33(10):2169-2174. 5. Heinemann L. Overcoming obstacles: new management options. Eur J Endocrinol. 2004;151(suppl 2):T23-T27. 6. Skyler JS. The economic burden of diabetes and the benefits of improved glycemic control: the potential role of a continuous glucose monitoring system. Diabetes Technol Ther. 2000;2(suppl 1):S7-S12. 7. American Diabetes Association. Standards of medical care in diabetes—2014. Diabetes Care. 2014;37(suppl 1):S14-S80. 8. Mannucci E, Monami M, Dicembrini I, Piselli A, Porta M. Achieving HbA1c targets in clinical trials and in the real world: a systematic review and meta-analysis. J Endocrinol Invest. 2014;37(5):477-495. 9. Ioacara S, Guja C, Fica S, Ionescu-Tirgoviste C. The dynamics of life expectancy over the last six decades in elderly people with diabetes. Diab Res Clin Pract. 2013;99(2):217-222. 10. Hovorka R. The future of continuous glucose monitoring: closed loop. Curr Diabetes Rev. 2008;4(3):269-279. 11. Bruttomesso D, Farret A, Costa S, et al. Closed-loop artificial pancreas using subcutaneous glucose sensing and insulin delivery and a model predictive control algorithm: preliminary studies in Padova and Montpellier. J Diabetes Sci Technol. 2009;3(5):1014-1021. 12. Matuleviciene V, Joseph JI, Andelin M, et al. A clinical trial of the accuracy and treatment experience of the Dexcom G4 sensor (Dexcom G4 system) and Enlite sensor (guardian REALtime system) tested simultaneously in ambulatory patients with type 1 diabetes. Diabetes Technol Ther. 2014;16(11):759-767.
956 13. Zschornack E, Schmid C, Pleus S, et al. Evaluation of the performance of a novel system for continuous glucose monitoring. J Diabetes Sci Technol. 2013;7(4):815-823. 14. Garcia A, Rack-Gomer AL, Bhavaraju NC, et al. Dexcom G4AP: an advanced continuous glucose monitor for the artificial pancreas. J Diabetes Sci Technol. 2013;7(6):1436-1445. 15. McGarraugh G, Brazg R, Richard W. FreeStyle Navigator continuous glucose monitoring system with TRUstart algorithm, a 1-hour warm-up time. J Diabetes Sci Technol. 2011;5(1):99-106. 16. Kamath A, Mahalingam A, Brauker J. Analysis of time lags and other sources of error of the DexCom SEVEN continuous glucose monitor. Diabetes Technol Ther. 2009;11(11): 689-695. 17. Mastrototaro J, Shin J, Marcus A, Sulur, G, STAR 1 Clinical Trial Investigators. The accuracy and efficacy of real-time continuous glucose monitoring sensor in patients with type 1 diabetes. Diabetes Technol Ther. 2008;10(5):385-390. 18. Colvin AE, Jiang H. Increased in vivo stability and functional lifetime of an implantable glucose sensor through platinum catalysis. J Biomed Mater Res A. 2013;101(5):1274-1282. 19. Mortellaro M, Dehennis A. Performance characterization of an abiotic and fluorescent-based continuous glucose monitoring system in patients with type 1 diabetes. Biosens Bioelectron. 2014;61:227-231. 20. International Conference on Harmonisation Working Group. ICH harmonised tripartite guideline: guideline for good clinical practice E6 (R1). Paper presented at: International Conference on Harmonisation of Technical Requirements
Journal of Diabetes Science and Technology 9(5) for Registration of Pharmaceuticals for Human Use; June 10, 1996; Washington, DC. Available at: http://www.ich.org/ fileadmin/Public_Web_Site/ICH_Products/Guidelines/ Efficacy/E6_R1/Step4/E6_R1__Guideline.pdf. 21. World Medical Association Declaration of Helsinki, Ethical principles for medical research involving human subjects. Available at: http://www.wma.net/en/30publications/10policies/b3/. 22. Clarke WL, Cox D, Gonder-Frederick LA, Carter W, Pohl SL. Evaluating clinical accuracy of systems for self-monitoring of blood glucose. Diabetes Care. 1987;10:622-628. 23. Wang X, Mdingi C, Dehennis A, Colvin AE. Algorithm for an implantable fluorescence based glucose sensor. Paper presented at: 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society; August 28-September 1, 2012; San Diego, CA. 24. Poolsup N, Suksomboon N, Kyaw AM. Systematic review and meta-analysis of the effectiveness of continuous glucose monitoring (CGM) on glucose control in diabetes. Diabetol Metab Syndr. 2013;5:39. 25. Choudhary P, Shin J, Wang Y, et al. Insulin pump therapy with automated insulin suspension in response to hypoglycemia: reduction in nocturnal hypoglycemia in those at greatest risk. Diabetes Care. 2011;34(9):2023-2025. 26. Ginsberg BH. The current environment of CGM technologies. J Diabetes Sci Technol. 2007;1(1):117-121. 27. Damiano ER, El-Khatib FH, Zheng H, Nathan DM, Russell SJ. A comparative effectiveness analysis of three continuous glucose monitors. Diabetes Care. 2013;36(2):251-259.
research-article2015
DSTXXX10.1177/1932296815596760Journal of Diabetes Science and TechnologyDehennis et al
Special Section
Multisite Study of an Implanted Continuous Glucose Sensor Over 90 Days in Patients With Diabetes Mellitus
Journal of Diabetes Science and Technology 2015, Vol. 9(5) 951–956 © 2015 Diabetes Technology Society Reprints and permissions: sagepub.com/journalsPermissions.nav DOI: 10.1177/1932296815596760 dst.sagepub.com
Andrew Dehennis, PhD1, Mark A. Mortellaro, PhD1, and Sorin Ioacara, MD, PhD2
Abstract Background: Continuous glucose monitoring (CGM), which enables real-time glucose display and trend information as well as real-time alarms, can improve glycemic control and quality of life in patients with diabetes mellitus. Previous reports have described strategies to extend the useable lifetime of a single sensor from 1-2 weeks to 28 days. The present multisite study describes the characterization of a sensing platform achieving 90 days of continuous use for a single, fully implanted sensor. Method: The Senseonics CGM system is composed of a long-term implantable glucose sensor and a wearable smart transmitter. Study subjects underwent subcutaneous implantation of sensors in the upper arm. Eight-hour clinic sessions were performed every 14 days, during which sensor glucose values were compared against venous blood lab reference measurements collected every 15 minutes using mean absolute relative differences (MARDs). Results: All subjects (mean ± standard deviation age: 43.5 ± 11.0 years; with 10 sensors inserted in men and 14 in women) had type 1 diabetes mellitus. Most (22 of 24) sensors reported glucose values for the entire 90 days. The MARD value was 11.4 ± 2.7% (range, 8.1-19.5%) for reference glucose values between 40-400 mg/dl. There was no significant difference in MARD throughout the 90-day study (P = .31). No serious adverse events were noted. Conclusions: The Senseonics CGM, composed of an implantable sensor, external smart transmitter, and smartphone app, is the first system that uses a single sensor for continuous display of accurate glucose values for 3 months. Keywords continuous glucose monitoring, diabetes mellitus, fluorescent sensor, hypoglycemia alarms, implantable sensors, wearable device Glucose monitoring is a necessary component of glycemic control, and the optimal mode of glucose monitoring would provide data both for preprandial and postprandial glucose excursions, minimize the need for finger stick measurements, and be convenient to promote compliance.1-6 Macrovascular and microvascular outcomes in patients with diabetes mellitus are dependent on glycemic control, yet a significant proportion of patients with diabetes mellitus do not achieve glycemic control target levels of hemoglobin A1c (HbA1c) ≤ 7%, as recommended by the American Diabetes Association.7,8 As patients with diabetes live longer, systems that technologically enable informative, actionable, and continuous glycemic measurements have the potential to positively impact various aspects of diabetes care.9 Ultimately, continuous glucose data would enable a closed loop system for an artificial pancreas delivery system.10,11
One of the technological solutions that could enable better reductions in glycemic variability is the development of an implantable continuous glucose monitoring (CGM) system, several of which have been developed.12-17 However, the sensors used by those devices have a relatively short duration of use ( 180 mg/dl (P = .19 with 1-way ANOVA) (Table 1). In addition, the percentage of CGM sensor data within 20 mg/dl or 20% of reference measurements was determined at 3 different glucose levels; 91% of sensor measurements were calculated to be within 20 mg/ dl for reference glucose measurements of ≤ 70 mg/dl, 86% of sensor data were within 20% of reference glucose measurements between 71-180 mg/dl, and 88% of sensor data were within 20% of reference glucose measurements > 180 mg/dl.
Enrolled subjects ranged in age from 22 to 65 years (mean age, 43.5 ± 11.0 years) and included 10 sensors inserted in men and 14 in women. All individuals had been diagnosed with type 1 diabetes mellitus for at least 6 months.
Sensor life Of the 24 sensors implanted, 22 reported glucose values for the entire 90-day study period. One CGM system stopped displaying glucose at day 55 and another at day 84 when their self-diagnostics indicated sensor performance had decreased below a factory-set threshold. Ex vivo chemical analysis performed after sensor removal showed loss of fluorescence due to chemical degradation of the indicator moieties, the mechanism of which has been previously described.18 The daily calibration points enable the system to account for this loss of fluorescence in vivo with a real-time assessment of the indicators sensitivity to glucose variations. This assessment enables updates to the fluorescent baseline and the responsiveness corresponding to the chemical kinetics for the degradation mechanisms.23
954
Journal of Diabetes Science and Technology 9(5)
Figure 2. Analysis of mean absolute relative difference (MARD) according to the proportion of sensors. The figure illustrates that 50% of the sensors have a MARD ≤ 11%, while 90% of the sensors have a MARD ≤ 16%
Table 1. Sensor Accuracy at High and Low Glucose Levels. Reference glucose range (mg/dl)
Number of paired system-reference readings
MARDa/MADb
116 2101 1369
9.6 mg/dl 11.4% 11.0%
≤70 71-180 >180 a
For glucose values ≥ 70 mg/dl, quantitative differences from reference glucose were assessed by mean absolute relative difference (MARD). For glucose values ≤ 70 mg/dl, mean absolute difference (MAD) was calculated.
b
To assess sensory accuracy over time, the MARD was calculated for and compared among each in-clinic session (~2-week intervals) (Figure 3). This analysis showed that there was no significant difference in MARD over time (P = .31).
Safety No serious adverse events were noted throughout the entire study period in any of the patients.
Discussion The present multisite study showed successful in-clinic and home use of the Senseonics CGM system over 90 days in subjects with diabetes mellitus. Specifically 22 of 24 (92%)
sensors reported glucose continuously for 90 days, and the MARD for all 24 sensors was 11.4 ± 2.7% against venous reference glucose values. CGMs have the potential to facilitate glycemic control (through enhanced compliance with glucose monitoring and through characterization of postprandial glucose excursions), improve quality of life (by minimizing the inconvenience and pain associated with frequent finger sticks), and improve the safety of insulin therapy (by detecting hypoglycemia). Indeed, meta-analyses suggest that CGM use is associated with significant HbA1c lowering when compared with SMBG.24 Furthermore, sensor-augmented insulin pump therapy with a low-glucose-suspend function significantly reduces nocturnal hypoglycemia, and CGMs form the underpinning for the “artificial pancreas” or the closed-loop system as the optimal insulin delivery system.25
955
Dehennis et al Acknowledgments
MARD (%)
25 20
The authors thank Steve Walters for management of the clinical study and Oliver Chen for statistical analysis of the data.
15
Declaration of Conflicting Interests
10
The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: Andrew Dehennis and Mark Mortellaro are employees of Senseonics, Inc and receive salary and stock from the company. Sorin Ioacara is the principal investigator for clinical studies performed by Senseonics in Romania.
5 0
1
15
30
45
60
75
90
Sensor Days
Funding Figure 3. Sensor accuracy over time during the 90-day study period. To assess sensory accuracy over time, the mean absolute relative difference (MARD) was calculated for and compared among each in-clinic session (~2-week intervals). This analysis showed that there was no significant difference in sensory accuracy over time (P = .31 according to the Skillings–Mack test). Values are means, and bars represent standard deviations.
The Senseonics CGM system has several advantages over other CGM devices. First, the Senseonics fully implantable sensor has improved longevity relative to sensors from other CGM systems. Indeed, the sensor lifespan of other commercially available CGMs is typically 5 to 7 days, possibly because those CGM sensors utilize enzymes that have a limited lifespan due to thermal degradation.26 By contrast, the Senseonics CGM sensor detects glucose via a nonenzymatic, abiotic methodology that is not subject to degradation or to the stability limitations inherent to enzyme-based systems.18 In addition, transcutaneous sensors of other CGMs protrude from the skin and do not allow for resolution of an acute inflammatory response, thereby limiting sensor accuracy and performance. The Senseonics sensor is fully inserted into the interstitial tissue, thus allowing the body to heal the insertion wound and resolve the acute inflammatory response. Second, the glucose measurement accuracy of the Senseonics CGM system, as assessed by MARDs, was 11.4%, which is similar to the MARD of the system reported in a 28-day study (11.6%) and which is comparable to the MARD of other commercially available CGM systems.27
Conclusions The Senseonics CGM, composed of an implantable sensor, external smart transmitter, and smartphone app, is the first system that uses a single sensor to provide continuous glucose measurements with very good accuracy over a 3-month period. Abbreviations ANOVA, analysis of variance; BMI, body mass index; CGM, continuous glucose monitoring; HbA1c, hemoglobin A1c; MAD, mean absolute difference; MARD, mean absolute relative difference; SD, standard deviation; SMBG, self-monitored blood glucose.
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was funded by Senseonics, Inc, a privately held company.
References 1. Klonoff DC. Benefits and limitations of self-monitoring of blood glucose. J Diabetes Sci Technol. 2007;1(1):130-132. 2. Farmer A, Wade A, Goyder E, et al. Impact of self monitoring of blood glucose in the management of patients with noninsulin treated diabetes: open parallel group randomised trial. BMJ. 2007;335(7611):132. 3. Brownlee M, Hirsch IB. Glycemic variability: a hemoglobin A1c-independent risk factor for diabetic complications. JAMA. 2006;295(14):1707-1708. 4. Rizzo MR, Marfella R, Barbieri M, et al. Relationships between daily acute glucose fluctuations and cognitive performance among aged type 2 diabetic patients. Diabetes Care. 2010;33(10):2169-2174. 5. Heinemann L. Overcoming obstacles: new management options. Eur J Endocrinol. 2004;151(suppl 2):T23-T27. 6. Skyler JS. The economic burden of diabetes and the benefits of improved glycemic control: the potential role of a continuous glucose monitoring system. Diabetes Technol Ther. 2000;2(suppl 1):S7-S12. 7. American Diabetes Association. Standards of medical care in diabetes—2014. Diabetes Care. 2014;37(suppl 1):S14-S80. 8. Mannucci E, Monami M, Dicembrini I, Piselli A, Porta M. Achieving HbA1c targets in clinical trials and in the real world: a systematic review and meta-analysis. J Endocrinol Invest. 2014;37(5):477-495. 9. Ioacara S, Guja C, Fica S, Ionescu-Tirgoviste C. The dynamics of life expectancy over the last six decades in elderly people with diabetes. Diab Res Clin Pract. 2013;99(2):217-222. 10. Hovorka R. The future of continuous glucose monitoring: closed loop. Curr Diabetes Rev. 2008;4(3):269-279. 11. Bruttomesso D, Farret A, Costa S, et al. Closed-loop artificial pancreas using subcutaneous glucose sensing and insulin delivery and a model predictive control algorithm: preliminary studies in Padova and Montpellier. J Diabetes Sci Technol. 2009;3(5):1014-1021. 12. Matuleviciene V, Joseph JI, Andelin M, et al. A clinical trial of the accuracy and treatment experience of the Dexcom G4 sensor (Dexcom G4 system) and Enlite sensor (guardian REALtime system) tested simultaneously in ambulatory patients with type 1 diabetes. Diabetes Technol Ther. 2014;16(11):759-767.
956 13. Zschornack E, Schmid C, Pleus S, et al. Evaluation of the performance of a novel system for continuous glucose monitoring. J Diabetes Sci Technol. 2013;7(4):815-823. 14. Garcia A, Rack-Gomer AL, Bhavaraju NC, et al. Dexcom G4AP: an advanced continuous glucose monitor for the artificial pancreas. J Diabetes Sci Technol. 2013;7(6):1436-1445. 15. McGarraugh G, Brazg R, Richard W. FreeStyle Navigator continuous glucose monitoring system with TRUstart algorithm, a 1-hour warm-up time. J Diabetes Sci Technol. 2011;5(1):99-106. 16. Kamath A, Mahalingam A, Brauker J. Analysis of time lags and other sources of error of the DexCom SEVEN continuous glucose monitor. Diabetes Technol Ther. 2009;11(11): 689-695. 17. Mastrototaro J, Shin J, Marcus A, Sulur, G, STAR 1 Clinical Trial Investigators. The accuracy and efficacy of real-time continuous glucose monitoring sensor in patients with type 1 diabetes. Diabetes Technol Ther. 2008;10(5):385-390. 18. Colvin AE, Jiang H. Increased in vivo stability and functional lifetime of an implantable glucose sensor through platinum catalysis. J Biomed Mater Res A. 2013;101(5):1274-1282. 19. Mortellaro M, Dehennis A. Performance characterization of an abiotic and fluorescent-based continuous glucose monitoring system in patients with type 1 diabetes. Biosens Bioelectron. 2014;61:227-231. 20. International Conference on Harmonisation Working Group. ICH harmonised tripartite guideline: guideline for good clinical practice E6 (R1). Paper presented at: International Conference on Harmonisation of Technical Requirements
Journal of Diabetes Science and Technology 9(5) for Registration of Pharmaceuticals for Human Use; June 10, 1996; Washington, DC. Available at: http://www.ich.org/ fileadmin/Public_Web_Site/ICH_Products/Guidelines/ Efficacy/E6_R1/Step4/E6_R1__Guideline.pdf. 21. World Medical Association Declaration of Helsinki, Ethical principles for medical research involving human subjects. Available at: http://www.wma.net/en/30publications/10policies/b3/. 22. Clarke WL, Cox D, Gonder-Frederick LA, Carter W, Pohl SL. Evaluating clinical accuracy of systems for self-monitoring of blood glucose. Diabetes Care. 1987;10:622-628. 23. Wang X, Mdingi C, Dehennis A, Colvin AE. Algorithm for an implantable fluorescence based glucose sensor. Paper presented at: 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society; August 28-September 1, 2012; San Diego, CA. 24. Poolsup N, Suksomboon N, Kyaw AM. Systematic review and meta-analysis of the effectiveness of continuous glucose monitoring (CGM) on glucose control in diabetes. Diabetol Metab Syndr. 2013;5:39. 25. Choudhary P, Shin J, Wang Y, et al. Insulin pump therapy with automated insulin suspension in response to hypoglycemia: reduction in nocturnal hypoglycemia in those at greatest risk. Diabetes Care. 2011;34(9):2023-2025. 26. Ginsberg BH. The current environment of CGM technologies. J Diabetes Sci Technol. 2007;1(1):117-121. 27. Damiano ER, El-Khatib FH, Zheng H, Nathan DM, Russell SJ. A comparative effectiveness analysis of three continuous glucose monitors. Diabetes Care. 2013;36(2):251-259.
