Cited by 168Diabetes Management and ResearchDiabetes Management and EducationDiabetes Treatment and Management

The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.

Clinical Accuracy of a Continuous Glucose Monitoring System With an Advanced Algorithm

Open access

Bailey, Timothy S., Chang, Anna, Christiansen, Mark·2015·Journal of Diabetes Science and Technology

DOI 10.1177/1932296814559746PMC PMC4604574

Open this paper in CoChat — free account Open PDF

Abstract

Background: We assessed the performance of a modified Dexcom G4 Platinum system with an advanced algorithm, in comparison with frequent venous samples measured on a laboratory reference (YSI) during a clinic session and in comparison to self-monitored blood glucose (SMBG) during home use. Methods: Fifty-one subjects with diabetes were enrolled in a prospective multicenter study. Subjects wore 1 sensor for 7-day use and participated in one 12-hour in-clinic session on day 1, 4, or 7 to collect YSI reference venous glucose every 15 minutes and capillary SMBG test every 30 minutes. Carbohydrate consumption and insulin dosing and timing were manipulated to obtain data in low and high glucose ranges. Results: In comparison with the laboratory reference method (n = 2,263) the system provided a mean and median absolute relative differences (ARD) of 9.0% and 7.0%, respectively. The mean absolute difference for CGM was 6.4 mg/dL when the YSIs were within hypoglycemia ranges (≤ 70 mg/dL). The percentage in the clinically accurate Clarke error grid A zone was 92.4% and in the benign error B zone was 7.1%. Majority of the sensors (73%) had an aggregated MARD in reference to YSI ≤ 10%. The MARD of CGM-SMBG for home use was 11.3%. Conclusions: The study showed that the point and rate accuracy, clinical accuracy, reliability, and consistency over the duration of wear and across glycemic ranges were superior to current commercial real-time CGM systems. The performance of this CGM is reaching that of a self-monitoring blood glucose meter in real use environment.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

Integrity signals

Registry

Crossref · 10.1177/1932296814559746

Cites

24 of 24 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Evaluating clinical accuracy of systems for self-monitoring of blood glucose
Clarke, W. L., Cox, D., Gonder-Frederick, L. A., Carter, W., & Pohl, S. L. (1987) · Diabetes Care · doi:10.2337/diacare.10.5.622 · Cited by 1,435
System accuracy evaluation of 43 blood glucose monitoring systems for self-monitoring of blood glucose according to DIN EN ISO 15197
Freckmann, G., Schmid, C., Baumstark, A., Pleus, S., Link, M., & Haug, C. (2012) · Journal of Diabetes Science and Technology · doi:10.1177/193229681200600510 · Cited by 237
“Turn it Off!”: Diabetes Device Alarm Fatigue Considerations for the Present and the Future
Shivers, J. P., Mackowiak, L., Anhalt, H., & Zisser, H. (2013) · Journal of Diabetes Science and Technology · doi:10.1177/193229681300700324 · Cited by 159
A New-Generation Continuous Glucose Monitoring System: Improved Accuracy and Reliability Compared with a Previous-Generation System
Christiansen, M. P., Bailey, T. S., Watkins, E., Liljenquist, D. R., Price, D. A., Nakamura, K., Boock, R. J., & Peyser, T. A. (2013) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2013.0077 · Cited by 140
Self-citation
A Comparative Effectiveness Analysis of Three Continuous Glucose Monitors
Damiano, E. R., McKeon, K., El-Khatib, F. H., Zheng, H., Nathan, D. M., & Russell, S. J. (2014) · Journal of Diabetes Science and Technology · doi:10.1177/1932296814532203 · Cited by 139
Accuracy of two continuous glucose monitoring systems: a head‐to‐head comparison under clinical research centre and daily life conditions
Kropff, J., Bruttomesso, D., Doll, W., Farret, A., Galasso, S., Luijf, Y. M., Mader, J. K., Place, J., Boscari, F., Pieber, T. R., et al. (2014) · Diabetes Obesity and Metabolism · doi:10.1111/dom.12378 · Cited by 132
Glycemic Variability Is Higher in Type 1 Diabetes Patients with Microvascular Complications Irrespective of Glycemic Control
Šoupal, J., Škrha, J., Fajmon, M., Horová, E., Mráz, M., Škrha, J., & Prázný, M. (2014) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2013.0205 · Cited by 122
Evaluating the Accuracy, Reliability, and Clinical Applicability of Continuous Glucose Monitoring (CGM): Is CGM Ready for Real Time?
Mazze, R. S., Strock, E. S., Borgman, S. K., Wesley, D., Stout, P. J., & Racchini, J. R. (2009) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2008.0041 · Cited by 116
Accuracy and Acceptability of the 6-Day Enlite Continuous Subcutaneous Glucose Sensor
Bailey, T. S., Ahmann, A., Brazg, R., Christiansen, M. P., Garg, S. K., Watkins, E., Welsh, J. B., & Lee, S. W. (2014) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2013.0222 · Cited by 106
Self-citation
Accuracy Evaluation of Five Blood Glucose Monitoring Systems Obtained from the Pharmacy: A European Multicenter Study with 453 Subjects
Tack, C. J., Pohlmeier, H., Behnke, T., Schmid, V., Grenningloh, M., Forst, T. M., & Pfützner, A. (2011) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2011.0170 · Cited by 91

Show all 24 references

Research works printed but not linked: 5

Christiansen M, 2013, Diabetes Technol Ther, 5, 1
Kropff J, 2014, Diabetes Obes Metab
Brauker JH, 2007, Review of Endocrinology
Pettus J, 2014, Diabetes Technol Ther, 16, 198
Hessler DM, Paper presented at: 71st American Diabetes Association meeting

Sorted by citations

Type 1 diabetes
DiMeglio, L. A., Evans-Molina, C., & Oram, R. A. (2018) · The Lancet · doi:10.1016/s0140-6736(18)31320-5 · Cited by 1,561
Effect of Continuous Glucose Monitoring on Glycemic Control in Adults With Type 1 Diabetes Using Insulin Injections: The DIAMOND Randomized Clinical Trial
Beck, R. W., Riddlesworth, T., Ruedy, K., Ahmann, A., Bergenstal, R., Haller, S., Kollman, C., Kruger, D., McGill, J. B., Polonsky, W., et al. (2017) · JAMA · doi:10.1001/jama.2016.19975 · Cited by 1,185
Electrochemical glucose sensors in diabetes management: an updated review (2010–2020)
Teymourian, H., Barfidokht, A., & Wang, J. (2020) · Chemical Society Reviews · doi:10.1039/d0cs00304b · Cited by 915
Artificial intelligence for diabetes management and decision support: Literature review
Contreras, I., & Vehi, J. (2018) · Journal of Medical Internet Research · doi:10.2196/10775 · Cited by 560
ISPAD Clinical Practice Consensus Guidelines 2018: Glycemic control targets and glucose monitoring for children, adolescents, and young adults with diabetes
DiMeglio, L. A., Acerini, C. L., Codner, E., Craig, M. E., Hofer, S. E., Pillay, K., & Maahs, D. M. (2018) · Pediatric Diabetes · doi:10.1111/pedi.12737 · Cited by 604
Continuous glucose monitoring sensors for diabetes management: A review of technologies and applications
Cappon, G., Vettoretti, M., Sparacino, G., & Facchinetti, A. (2019) · Diabetes & Metabolism Journal · doi:10.4093/dmj.2019.0121 · Cited by 477
The impact of continuous glucose monitoring on markers of quality of life in adults with type 1 diabetes: further findings from the DIAMOND randomized clinical trial
Polonsky, W. H., Hessler, D., Ruedy, K. J., & Beck, R. W. (2017) · Diabetes Care · doi:10.2337/dc17-0133 · Cited by 346
REPLACE-BG: a randomized trial comparing continuous glucose monitoring with and without routine blood glucose monitoring in adults with well-controlled type 1 diabetes
Aleppo, G., Ruedy, K. J., Riddlesworth, T. D., Kruger, D. F., Peters, A. L., Hirsch, I., Bergenstal, R. M., Toschi, E., Ahmann, A. J., Shah, V. N., et al. (2017) · Diabetes Care · doi:10.2337/dc16-2482 · Cited by 329
Continuous glucose monitoring: A review of the technology and clinical use
Klonoff, D. C., Ahn, D., & Drincic, A. (2017) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2017.08.005 · Cited by 320
Artificial intelligence in diabetes management: Advancements, opportunities, and challenges
Guan, Z., Li, H., Liu, R., Cai, C., Liu, Y., Li, J., Wang, X., Huang, S., Wu, L., Liu, D., et al. (2023) · Cell Reports Medicine · doi:10.1016/j.xcrm.2023.101213 · Cited by 287
“Errors in CGM also increase the difﬁculty of predicting BG values (approximately 9% of the mean absolute relative difference for the best sensors 70 ).”
Background
A randomized controlled pilot study of continuous glucose monitoring and flash glucose monitoring in people with type 1 diabetes and impaired awareness of hypoglycaemia
Reddy, M., Jugnee, N., El Laboudi, A., Spanudakis, E., Anantharaja, S., & Oliver, N. (2018) · Diabetic Medicine · doi:10.1111/dme.13561 · Cited by 245
Wearable Continuous Glucose Monitoring Sensors: A Revolution in Diabetes Treatment
Cappon, G., Acciaroli, G., Vettoretti, M., Facchinetti, A., & Sparacino, G. (2017) · Electronics · doi:10.3390/electronics6030065 · Cited by 247
Outcome measures for artificial pancreas clinical trials: a consensus report
Maahs, D. M., Buckingham, B. A., Castle, J. R., Cinar, A., Damiano, E. R., Dassau, E., DeVries, J. H., Doyle, F. J., Griffen, S. C., Haidar, A., et al. (2016) · Diabetes Care · doi:10.2337/dc15-2716 · Cited by 211
Accuracy of a Factory-Calibrated, Real-Time Continuous Glucose Monitoring System During 10 Days of Use in Youth and Adults with Diabetes
Wadwa, R. P., Laffel, L. M., Shah, V. N., & Garg, S. K. (2018) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2018.0150 · Cited by 203
ISPAD Clinical Practice Consensus Guidelines 2018: diabetes technologies
Sherr, J. L., Tauschmann, M., Battelino, T., de Bock, M., Forlenza, G., Roman, R., Hood, K. K., & Maahs, D. M. (2018) · Pediatric Diabetes · doi:10.1111/pedi.12731 · Cited by 197
Continuous glucose monitoring sensors: past, present and future algorithmic challenges
Facchinetti, A. (2016) · Sensors · doi:10.3390/s16122093 · Cited by 176
Accuracy and Longevity of an Implantable Continuous Glucose Sensor in the PRECISE Study: A 180-Day, Prospective, Multicenter, Pivotal Trial
Kropff, J., Choudhary, P., Neupane, S., Barnard-Kelly, K. D., Bain, S. C., Kapitza, C., Forst, T. M., Link, M., DEHENNIS, A. D., & DeVries, J. H. (2016) · Diabetes Care · doi:10.2337/dc16-1525 · Cited by 171
Benefits and Limitations of MARD as a Performance Parameter for Continuous Glucose Monitoring in the Interstitial Space
Heinemann, L., Schoemaker, M., Schmelzeisen-Redecker, G., Hinzmann, R., Kassab, A., Freckmann, G., Reiterer, F., & Del Re, L. (2020) · Journal of Diabetes Science and Technology · doi:10.1177/1932296819855670 · Cited by 170
Technology in the management of type 1 diabetes mellitus — current status and future prospects
Tauschmann, M., & Hovorka, R. (2018) · Nature Reviews Endocrinology · doi:10.1038/s41574-018-0044-y · Cited by 165
A Prospective Multicenter Evaluation of the Accuracy of a Novel Implanted Continuous Glucose Sensor: PRECISE II
Christiansen, M. P., Klaff, L. J., Brazg, R., Chang, A. R., Levy, C. J., Lam, D. W.-H., Denham, D. S., Atiee, G. J., Bode, B. W., Walters, S. J., et al. (2018) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2017.0142 · Cited by 146
Self-citation
A review of optical methods for continuous glucose monitoring
Jernelv, I. L., Mileńko, K., Fuglerud, S. S., Hjelme, D. R., Ellingsen, R., & Aksnes, A. (2018) · Applied Spectroscopy Reviews · doi:10.1080/05704928.2018.1486324 · Cited by 137
Evaluation of subcutaneous glucose monitoring systems under routine environmental conditions in patients with type 1 diabetes
Aberer, F., Hajnsek, M., Rumpler, M., Zenz, S., Baumann, P. M., Elsayed, H., Puffing, A., Treiber, G. M., Pieber, T. R., Sourij, H., et al. (2017) · Diabetes Obesity and Metabolism · doi:10.1111/dom.12907 · Cited by 132
American Association Of Clinical Endocrinologists And American College Of Endocrinology 2016 Outpatient Glucose Monitoring Consensus Statement
Bailey, T. S., Grunberger, G., Bode, B. W., Handelsman, Y., Hirsch, I. B., Jovanovič, L., Roberts, V. L., Rodbard, D., Tamborlane, W. V., & Walsh, J. S. A. (2016) · Endocrine Practice · doi:10.4158/ep151124.cs · Cited by 130
Self-citation
Recommendations for Using Real-Time Continuous Glucose Monitoring (rtCGM) Data for Insulin Adjustments in Type 1 Diabetes
Pettus, J., & Edelman, S. V. (2016) · Journal of Diabetes Science and Technology · doi:10.1177/1932296816663747 · Cited by 122
Type-1 Diabetes Patient Decision Simulator for In Silico Testing Safety and Effectiveness of Insulin Treatments
Vettoretti, M., Facchinetti, A., Sparacino, G., & Cobelli, C. (2017) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2017.2746340 · Cited by 110
HbA1c and Glucose Management Indicator Discordance: A Real-World Analysis
Perlman, J. E., Gooley, T. A., MCNULTY, B. K., Meyers, J., & Hirsch, I. B. (2020) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2020.0501 · Cited by 101
Continuous glucose monitoring: Current use in diabetes management and possible future applications
Vettoretti, M., Cappon, G., Acciaroli, G., Facchinetti, A., & Sparacino, G. (2018) · Journal of Diabetes Science and Technology · doi:10.1177/1932296818774078 · Cited by 96
Direct Evidence of Acetaminophen Interference with Subcutaneous Glucose Sensing in Humans: A Pilot Study
Basu, A., Veettil, S., Dyer, R. B., Peyser, T. A., & Basu, R. (2016) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2015.0410 · Cited by 94
Wearable physiological systems and technologies for metabolic monitoring
Gao, W., Brooks, G. A., & Klonoff, D. C. (2018) · Journal of Applied Physiology · doi:10.1152/japplphysiol.00407.2017 · Cited by 91
Clinical Performance Evaluation of Continuous Glucose Monitoring Systems: A Scoping Review and Recommendations for Reporting
Freckmann, G., Eichenlaub, M., Waldenmaier, D., Pleus, S., Wehrstedt, S., Haug, C., Witthauer, L., Jendle, J., Hinzmann, R., Thomas, A., et al. (2023) · Journal of Diabetes Science and Technology · doi:10.1177/19322968231190941 · Cited by 86
Improved Accuracy of Continuous Glucose Monitoring Systems in Pediatric Patients with Diabetes Mellitus: Results from Two Studies
Laffel, L. M. (2016) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2015.0380 · Cited by 86
Continuous glucose monitoring in critically ill patients with COVID-19: Results of an emergent pilot study
Sadhu, A. R., Serrano, I. A., Xu, J., Nisar, T., Lucier, J., Pandya, A. R., & Patham, B. (2020) · Journal of Diabetes Science and Technology · doi:10.1177/1932296820964264 · Cited by 84
Rate-of-Change Dependence of the Performance of Two CGM Systems During Induced Glucose Swings
Pleus, S., Schoemaker, M., Morgenstern, K., Schmelzeisen‐Redeker, G., Haug, C., Link, M., Zschornack, E., & Freckmann, G. (2015) · Journal of Diabetes Science and Technology · doi:10.1177/1932296815578716 · Cited by 84
Cutaneous Complications With Continuous or Flash Glucose Monitoring Use: Systematic Review of Trials and Observational Studies
Asarani, N. A. M., Reynolds, A. N., Styles, S. E., de Bock, M. I., & Wheeler, B. J. (2019) · Journal of Diabetes Science and Technology · doi:10.1177/1932296819870849 · Cited by 81
Personalized blood glucose prediction: A hybrid approach using grammatical evolution and physiological models
Contreras, I., Oviedo, S., Vettoretti, M., VISENTIN, R., & Vehı́, J. (2017) · PLoS ONE · doi:10.1371/journal.pone.0187754 · Cited by 80
Long-term implantable glucose biosensors
Bobrowski, T., & Schuhmann, W. W. (2018) · Current Opinion in Electrochemistry · doi:10.1016/j.coelec.2018.05.004 · Cited by 77
Accuracy, Utilization, and Effectiveness Comparisons of Different Continuous Glucose Monitoring Systems
Welsh, J. B., Gao, P., Derdzinski, M., Puhr, S., Johnson, T. K., Walker, T. C., & Graham, C. (2019) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2018.0374 · Cited by 72
Optical sensors for continuous glucose monitoring
Yu, Z., Jiang, N., Kazarian, S. G., Taşoğlu, S., & Yetisen, A. K. (2021) · Progress in Biomedical Engineering · doi:10.1088/2516-1091/abe6f8 · Cited by 66
Continuous glucose monitoring: a review of the evidence, opportunities for future use and ongoing challenges
Wood, A. J., O'Neal, D. N., Furler, J., & Ekinci, E. I. (2018) · Internal Medicine Journal · doi:10.1111/imj.13770 · Cited by 66
Basics and use of continuous glucose monitoring (CGM) in diabetes therapy
Freckmann, G. (2020) · Journal of Laboratory Medicine · doi:10.1515/labmed-2019-0189 · Cited by 72
Measurement Performance of Two Continuous Tissue Glucose Monitoring Systems Intended for Replacement of Blood Glucose MonitoringParts of the data have previously been presented at the 77th Scientific Sessions of the American Diabetes Association in San Diego, CA; June 9–13, 2017 and at the 17th Annual Diabetes Technology Meeting in Bethesda, MD, November 2–4, 2017.Trial number: DRKS00011920; registered at the Deutsches Register Klinischer Studien (German clinical trials register), an approved Primary Register in the WHO International Clinical Trials Registry Platform.
Freckmann, G., Link, M., Pleus, S., Westhoff, A., Kamecke, U., & Haug, C. (2018) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2018.0105 · Cited by 64
Standardization process of continuous glucose monitoring: Traceability and performance
Freckmann, G., Nichols, J. H., Hinzmann, R., Klonoff, D. C., Ju, Y., Diem, P., Makris, K., & Slingerland, R. J. (2021) · Clinica Chimica Acta · doi:10.1016/j.cca.2020.12.025 · Cited by 62
A Neural-network-based approach to personalize insulin bolus calculation using continuous glucose monitoring
Cappon, G., Vettoretti, M., Marturano, F., Facchinetti, A., & Sparacino, G. (2018) · Journal of Diabetes Science and Technology · doi:10.1177/1932296818759558 · Cited by 62
Clinical Implications of Accuracy Measurements of Continuous Glucose Sensors
Bailey, T. S. (2017) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2017.0050 · Cited by 60
Self-citation
Modeling Transient Disconnections and Compression Artifacts of Continuous Glucose Sensors
Facchinetti, A., Favero, S. D., Sparacino, G., & Cobelli, C. (2016) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2015.0250 · Cited by 60
Nonadjunctive Use of Continuous Glucose Monitoring for Diabetes Treatment Decisions
Castle, J. R., & Jacobs, P. G. (2016) · Journal of Diabetes Science and Technology · doi:10.1177/1932296816631569 · Cited by 58
Comparator Data Characteristics and Testing Procedures for the Clinical Performance Evaluation of Continuous Glucose Monitoring Systems
Eichenlaub, M., Pleus, S., Rothenbühler, M., Bailey, T. S., Bally, L., Brazg, R., Bruttomesso, D., Diem, P., Boija, E. E., Fokkert, M. J., et al. (2024) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2023.0465 · Cited by 51
Self-citation
Developing Insulin Delivery Devices with Glucose Responsiveness
Wang, Z., Wang, J., Kahkoska, A. R., Buse, J. B., & Gu, Z. (2020) · Trends in Pharmacological Sciences · doi:10.1016/j.tips.2020.11.002 · Cited by 49
Is it possible to constantly and accurately monitor blood sugar levels, in people with Type 1 diabetes, with a discrete device (non‐invasive or invasive)?
Avari, P., Reddy, M., & Oliver, N. S. (2019) · Diabetic Medicine · doi:10.1111/dme.13942 · Cited by 46
Practical Considerations on the Use of Continuous Glucose Monitoring in Pediatrics and Older Adults and Nonadjunctive Use
Forlenza, G. P., Argento, N. B., & Laffel, L. M. (2017) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2017.0034 · Cited by 47
Time Lag and Accuracy of Continuous Glucose Monitoring During High Intensity Interval Training in Adults with Type 1 Diabetes
Li, A., Riddell, M. C., Potashner, D., Brown, R. E., & Aronson, R. (2019) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2018.0387 · Cited by 44
Comparisons of Fifth-, Sixth-, and Seventh-Generation Continuous Glucose Monitoring Systems
Welsh, J. B., Psavko, S., Zhang, X., Gao, P., & Balo, A. K. (2022) · Journal of Diabetes Science and Technology · doi:10.1177/19322968221099879 · Cited by 43
A Review of Safety and Hazards Associated With the Artificial Pancreas
Ramkissoon, C. M., Aufderheide, B., Bequette, B. W., & Vehı́, J. (2017) · IEEE Reviews in Biomedical Engineering · doi:10.1109/rbme.2017.2749038 · Cited by 41
Applications and pitfalls of hemoglobin A1C and alternative methods of glycemic monitoring
Lundholm, M. D., Emanuele, M. A., Ashraf, A., & Nadeem, S. (2020) · Journal of Diabetes and its Complications · doi:10.1016/j.jdiacomp.2020.107585 · Cited by 42
Differences for percentage times in glycemic range between continuous glucose monitoring and capillary blood glucose monitoring in adults with type 1 diabetes: analysis of the REPLACE-BG dataset
Avari, P., Uduku, C., George, D., Herrero, P., Reddy, M., & Oliver, N. (2020) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2019.0276 · Cited by 40
Continuous glucose monitoring in subjects undergoing bariatric surgery: Diurnal and nocturnal glycemic patterns
Lupoli, R., Lembo, E., Ciciola, P., Schiavo, L., Pilone, V., & Capaldo, B. (2020) · Nutrition Metabolism and Cardiovascular Diseases · doi:10.1016/j.numecd.2020.06.029 · Cited by 41
Non-invasive and minimally invasive glucose monitoring devices: a systematic review and meta-analysis on diagnostic accuracy of hypoglycaemia detection
Lindner, N., Kuwabara, A., & Holt, T. (2021) · Systematic Reviews · doi:10.1186/s13643-021-01644-2 · Cited by 42
Hypoglycemic Accuracy and Improved Low Glucose Alerts of the Latest Dexcom G4 Platinum Continuous Glucose Monitoring System
Peyser, T. A., Nakamura, K., Price, D. A., Bohnett, L. C., Hirsch, I. B., & Balo, A. K. (2015) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2014.0415 · Cited by 37
Accuracy of Continuous Glucose Monitoring During Three Closed-Loop Home Studies Under Free-Living Conditions
Thabit, H., Leelarathna, L., Wilinska, M. E., Elleri, D., Allen, J. M., Lubina-Solomon, A., Walkinshaw, E., Stadler, M., Choudhary, P., Mader, J. K., et al. (2015) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2015.0062 · Cited by 37
Reduction of Blood Glucose Measurements to Calibrate Subcutaneous Glucose Sensors: A Bayesian Multiday Framework
Acciaroli, G., Vettoretti, M., Facchinetti, A., Sparacino, G., & Cobelli, C. (2017) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2017.2706974 · Cited by 36
Performance and Usability of Three Systems for Continuous Glucose Monitoring in Direct Comparison
Freckmann, G., Link, M., Kamecke, U., Haug, C., Baumgartner, B., & Weitgasser, R. (2019) · Journal of Diabetes Science and Technology · doi:10.1177/1932296819826965 · Cited by 34
Continuous Glucose Monitoring: A Perspective on Its Past, Present, and Future Applications for Diabetes Management
Mariani, H., Layden, B. T., & Aleppo, G. (2017) · Clinical Diabetes · doi:10.2337/cd16-0008 · Cited by 33
Accuracy of a CGM Sensor in Pediatric Subjects With Type 1 Diabetes. Comparison of Three Insertion Sites: Arm, Abdomen, and Gluteus
Faccioli, S., Favero, S. D., VISENTIN, R., Bonfanti, R., Iafusco, D., Rabbone, I., Marigliano, M., Schiaffini, R., Bruttomesso, D., Cobelli, C., et al. (2017) · Journal of Diabetes Science and Technology · doi:10.1177/1932296817706377 · Cited by 32
Unblinded CGM Should Replace Blinded CGM in the Clinical Management of Diabetes
Ahn, D. T., Pettus, J., & Edelman, S. V. (2016) · Journal of Diabetes Science and Technology · doi:10.1177/1932296816632241 · Cited by 30
FDA Approval of Nonadjunctive Use of Continuous Glucose Monitors for Insulin Dosing
Shapiro, A. R. (2017) · JAMA · doi:10.1001/jama.2017.12075 · Cited by 26
Relationship Between Time-in-Range, HbA1c, and the Glucose Management Indicator in Pregnancies Complicated by Type 1 Diabetes
Shah, V. N., Snell‐Bergeon, J. K., Demmitt, J. K., Joshee, P., Garcetti, R., Pyle, L. L., & Polsky, S. (2021) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2021.0093 · Cited by 25
Tissue Response to Subcutaneous Infusion Catheter
Zhang, E., & Cao, Z. (2019) · Journal of Diabetes Science and Technology · doi:10.1177/1932296819837972 · Cited by 24
Comparative Accuracy Analysis of a Real-time and an Intermittent-Scanning Continuous Glucose Monitoring System
Link, M., Kamecke, U., Waldenmaier, D., Pleus, S., Garcia, A., Haug, C., & Freckmann, G. (2019) · Journal of Diabetes Science and Technology · doi:10.1177/1932296819895022 · Cited by 23
Performance of a new real‐time continuous glucose monitoring system: A multicenter pilot study
Zhou, J., Zhang, S., Li, L., Wang, Y., Lu, W., Sheng, C., Li, Y., Bao, Y., & Jia, W. (2018) · Journal of Diabetes Investigation · doi:10.1111/jdi.12699 · Cited by 22
From Two to One Per Day Calibration of Dexcom G4 Platinum by a Time-Varying Day-Specific Bayesian Prior
Acciaroli, G., Vettoretti, M., Facchinetti, A., Sparacino, G., & Cobelli, C. (2016) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2016.0088 · Cited by 22
Nonadjunctive Use of Continuous Glucose Monitors for Insulin Dosing: Is It Safe?
Shapiro, A. R. (2017) · Journal of Diabetes Science and Technology · doi:10.1177/1932296816688303 · Cited by 22
Cost-effectiveness of G5 Mobile continuous glucose monitoring device compared to self-monitoring of blood glucose alone for people with type 1 diabetes from the Canadian societal perspective
Chaugule, S., & Graham, C. (2017) · Journal of Medical Economics · doi:10.1080/13696998.2017.1360312 · Cited by 22
Insulin Sensitivity Index-Based Optimization of Insulin to Carbohydrate Ratio: In Silico Study Shows Efficacious Protection Against Hypoglycemic Events Caused by Suboptimal Therapy
Schiavon, M., Man, C. D., & Cobelli, C. (2018) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2017.0248 · Cited by 22
Hypoglycemia Reduction and Accuracy of Continuous Glucose Monitoring
Kovatchev, B. P. (2015) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2015.0144 · Cited by 22
Insulin pump therapy is associated with higher rates of mild diabetic ketoacidosis compared to injection therapy: A 2‐year Swedish national survey of children and adolescents with type 1 diabetes
Wersäll, J. H., Adolfsson, P., Forsander, G., & Hanas, R. (2022) · Pediatric Diabetes · doi:10.1111/pedi.13377 · Cited by 21
Glycaemic variability-based classification of impaired glucose tolerance vs. type 2 diabetes using continuous glucose monitoring data
Longato, E., Acciaroli, G., Facchinetti, A., Hakaste, L., Tuomilehto, J., Maran, A., & Sparacino, G. (2018) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2018.03.007 · Cited by 19
A Model of Self-Monitoring Blood Glucose Measurement Error
Vettoretti, M., Facchinetti, A., Sparacino, G., & Cobelli, C. (2017) · Journal of Diabetes Science and Technology · doi:10.1177/1932296817698498 · Cited by 18
Glucose Sensing in the Subcutaneous Tissue: Attempting to Correlate the Immune Response with Continuous Glucose Monitoring Accuracy
Joseph, J. I., EISLER, G. J., Diaz, D., Khalf, A., Loeum, C., & Torjman, M. C. (2018) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2018.0106 · Cited by 20
Application of Machine Learning Algorithm and Artificial Intelligence in Improving Metabolic Syndrome related complications: A review
Ghosh, J., Choudhury, S. R., Singh, K., & Koner, S. (2024) · International Journal of Advancement in Life Sciences Research · doi:10.31632/ijalsr.2024.v07i02.004 · Cited by 18
Redundancy in Glucose Sensing
Sharifi, A., Varsavsky, A., Ulloa, J., Horsburgh, J. C., McAuley, S. A., Krishnamurthy, B., Jenkins, A. J., Colman, P. G., Ward, G. M., MacIsaac, R. J., et al. (2015) · Journal of Diabetes Science and Technology · doi:10.1177/1932296815612096 · Cited by 16
Design of clinical trials to assess diabetes treatment: Minimum duration of continuous glucose monitoring data to estimate time‐in‐ranges with the desired precision
Camerlingo, N., Vettoretti, M., Sparacino, G., Facchinetti, A., Mader, J. K., Choudhary, P., & Favero, S. D. (2021) · Diabetes Obesity and Metabolism · doi:10.1111/dom.14483 · Cited by 16
Methodology for Safe and Secure AI in Diabetes Management
Foppen, R. J. G., Gioia, V. L., Gupta, S., Johnson, C. L., Giantsidis, J., & Papademetris, M. (2024) · Journal of Diabetes Science and Technology · doi:10.1177/19322968241304434 · Cited by 16
Accuracy Assessment of the GlucoMen® Day CGM System in Individuals with Type 1 Diabetes: A Pilot Study
Hochfellner, D. A., Simic, A., Taucher, M. T., Sailer, L. S., Kopanz, J., Pöttler, T., & Mader, J. K. (2022) · Biosensors · doi:10.3390/bios12020106 · Cited by 15
Patient decision-making of CGM sensor driven insulin therapies in type 1 diabetes: In silico assessment
Vettoretti, M., Facchinetti, A., Sparacino, G., & Cobelli, C. (2015) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2015.7318868 · Cited by 15
Efficacy and safety of a morning injection of insulin glargine 300 units/mL versus insulin glargine 100 units/mL in adult patients with type 1 diabetes: A multicentre, randomized controlled trial using continuous glucose monitoring
Pettus, J., Gill, J., Paranjape, S., Stewart, J. A., Malla, S., Edelman, S. V., Bergenstal, R. M., & Bode, B. W. (2019) · Diabetes Obesity and Metabolism · doi:10.1111/dom.13751 · Cited by 15
The Rationale for Continuous Glucose Monitoring-based Diabetes Treatment Decisions and Non-adjunctive Continuous Glucose Monitoring Use
Price, D. A., & Walker, T. C. (2016) · touchREVIEWS in Endocrinology · doi:10.17925/ee.2016.12.01.24 · Cited by 17
Moving Toward a Unified Platform for Insulin Delivery and Sensing of Inputs Relevant to an Artificial Pancreas
Graf, A., McAuley, S. A., Sims, C. M., Ulloa, J., Jenkins, A. J., Voskanyan, G. R., & O'Neal, D. N. (2016) · Journal of Diabetes Science and Technology · doi:10.1177/1932296816682762 · Cited by 14
Data Reliability and Quality in Body Area Networks for Diabetes Monitoring
Huzooree, G., Khedo, K. K., & Joonas, N. (2018) · EAI/Springer Innovations in Communication and Computing · doi:10.1007/978-3-030-00865-9_4 · Cited by 13
Electrochemical Glucose Biosensors for Diabetes Care
Ocvirk, G., Buck, H., & DuVall, S. H. (2016) · Bioanalytical reviews · doi:10.1007/11663_2016_3 · Cited by 13
Effect of Arterialization on Venous Blood Glucose Concentrations and Implications for Observed Continuous Glucose Monitoring Accuracy
Pleus, S., Link, M., Hinzmann, R., Öter, Ş., Eichenlaub, M., Baumstark, A., Haug, C., & Freckmann, G. (2023) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2023.0489 · Cited by 12
Intraperitoneal Glucose Sensing is Sometimes Surprisingly Rapid
Fougner, A. L., KÃ¶lle, K., SkjÃ¦rvold, N. K., Elvemo, N.-A. L., Hjelme, D. R., Ellingsen, R., Carlsen, S. M., & Stavdahl, Ø. (2016) · Modeling Identification and Control A Norwegian Research Bulletin · doi:10.4173/mic.2016.2.4 · Cited by 12
Catalytic Biosensors Operating under Quasi‐Equilibrium Conditions for Mitigating the Changes in Substrate Diffusion
Muhs, A., Bobrowski, T., Lielpētere, A., & Schuhmann, W. W. (2022) · Angewandte Chemie International Edition · doi:10.1002/anie.202211559 · Cited by 12
Predicting Insulin Treatment Scenarios with the Net Effect Method: Domain of Validity
Vettoretti, M., Facchinetti, A., Sparacino, G., & Cobelli, C. (2016) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2016.0148 · Cited by 12
Design of a Real-time Self-adjusting Calibration Algorithm to Improve the Accuracy of Continuous Blood Glucose Monitoring
Jia, Z., Huang, L., Liu, H., Huang, Y., Li, W., Pi, X., & Zheng, X. (2019) · Applied Biochemistry and Biotechnology · doi:10.1007/s12010-019-03142-7 · Cited by 11
Choosing the duration of continuous glucose monitoring for reliable assessment of time in range: A new analytical approach to overcome the limitations of correlation‐based methods
Camerlingo, N., Vettoretti, M., Sparacino, G., Facchinetti, A., Mader, J. K., Choudhary, P., & Favero, S. D. (2021) · Diabetic Medicine · doi:10.1111/dme.14758 · Cited by 10
Continuous Glucose Monitoring Use in Clinical Trials for On-Market Diabetes Drugs
Fox, B. Q., Benjamin, P. F., Aqeel, A., Fitts, E., Flynn, S., Levine, B., Maslak, E., Milner, R. L., Ose, B. M., Poeschla, M., et al. (2021) · Clinical Diabetes · doi:10.2337/cd20-0049 · Cited by 12
Feasibility of an Orthogonal Redundant Sensor incorporating Optical plus Redundant Electrochemical Glucose Sensing
McAuley, S. A., Dang, T. T., Horsburgh, J. C., Bansal, A., Ward, G. M., Aroyan, S., Jenkins, A. J., MacIsaac, R. J., Shah, R. V., & O'Neal, D. N. (2016) · Journal of Diabetes Science and Technology · doi:10.1177/1932296816629982 · Cited by 10
Continuous Glucose Monitoring for the Internist
Lee, G. S., & Lupsa, B. C. (2021) · Medical Clinics of North America · doi:10.1016/j.mcna.2021.06.004 · Cited by 9
A New Index of Insulin Sensitivity from Glucose Sensor and Insulin Pump Data: In Silico and In Vivo Validation in Youths with Type 1 Diabetes
Schiavon, M., Galderisi, A., Basu, A., Kudva, Y. C., Cengiz, E., & Dalla Man, C. (2023) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2022.0397 · Cited by 8
Retrofitting Real-Life Dexcom G5 Data
Favero, S. D., Facchinetti, A., Sparacino, G., & Cobelli, C. (2017) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2016.0413 · Cited by 8

Authors: Bailey, T. S., Chang, A., & Christiansen, M.
Affiliations: AMCR Institute (US)
John Muir Health (US)
Diablo Clinical Research (US)
Corresponding author: Bailey, Timothy S.
ORCID: Bailey, Timothy S.
Venue: Journal of Diabetes Science and Technology
Publisher: SAGE Publications
Published: 2014-11-03
Volume: 9
Issue: 2
Pages: 209-214
ISSN: 1932-2968 (ISSN-L)
DOI: 10.1177/1932296814559746
PMC: PMC4604574
OpenAlex: W2165138941
Cited by: 168
References: 24
Citations by year: 2026: 7 · 2025: 7 · 2024: 9 · 2023: 7 · 2022: 7 · 2021: 14 · 2020: 15 · 2019: 23 · 2018: 21 · 2017: 30 · 2016: 18 · 2015: 10
FWCI: 15.54
Type: journal article
Language: en
Open access: bronze
doi.org
Licence: journals.sagepub.com/page/policies/text-and-data-mining-license (tdm)
Locations: Journal of Diabetes Science and Technology (publishedVersion)
Europe PMC (PubMed Central) (publishedVersion)
PubMed Central (publishedVersion)
PubMed (publishedVersion)
Funders: Dexcom
Topics: Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Education
Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Treatment and Management
Keywords: continuous glucose monitoring, diabetes mellitus, clinical accuracy, hypoglycemia, self-monitoring of blood glucose, Clarke error grid, mean absolute relative difference, sensor reliability, insulin dose
MeSH terms: Adult, Aged, Aged, 80 and over, Algorithms, Blood Glucose, Diabetes Mellitus, Female, Humans, Male, Middle Aged, Blood Glucose Self-Monitoring, Young Adult

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Clinical Accuracy of a Continuous Glucose Monitoring System With an Advanced Algorithm

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Self-check

Citations

Cites

Cited by

Related

Metadata

Record

About these checks