ArticleDiabetes technology & therapeutics2013
Evaluating the accuracy and large inaccuracy of two continuous glucose monitoring systems.
Article in Diabetes technology & therapeutics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
24 citing papers in PubMed.
- Lag Time Remains with Newer Real-Time Continuous Glucose Monitoring Technology During Aerobic Exercise in Adults Living with Type 1 Diabetes.Diabetes technology & therapeutics · 2019Trial
- Assessing the Accuracy of Continuous Glucose Monitoring (CGM) Calibrated With Capillary Values Using Capillary or Venous Glucose Levels as a Reference.Journal of diabetes science and technology · 2016Trial
- Accuracy of Continuous Glucose Monitoring During Three Closed-Loop Home Studies Under Free-Living Conditions.Diabetes technology & therapeutics · 2015Trial
- Accuracy of subcutaneous continuous glucose monitoring in critically ill adults: improved sensor performance with enhanced calibrations.Diabetes technology & therapeutics · 2014Trial
- Clinical Performance Evaluation of Continuous Glucose Monitoring Systems: A Scoping Review and Recommendations for Reporting.Journal of diabetes science and technology · 2023Article
- Development platform for artificial pancreas algorithms.PloS one · 2020Article
- Benefits and Limitations of MARD as a Performance Parameter for Continuous Glucose Monitoring in the Interstitial Space.Journal of diabetes science and technology · 2020Article
- Measurement Performance of Two Continuous Tissue Glucose Monitoring Systems Intended for Replacement of Blood Glucose Monitoring.Diabetes technology & therapeutics · 2018Article
- Limits to the Evaluation of the Accuracy of Continuous Glucose Monitoring Systems by Clinical Trials.Biosensors · 2018Article
- Future of Automated Insulin Delivery Systems.Diabetes technology & therapeutics · 2017Review
- Analysis of the Accuracy and Performance of a Continuous Glucose Monitoring Sensor Prototype: An In-Silico Study Using the UVA/PADOVA Type 1 Diabetes Simulator.Journal of diabetes science and technology · 2017Article
- Significance and Reliability of MARD for the Accuracy of CGM Systems.Journal of diabetes science and technology · 2017Article
- Key Points from the Updated Guidelines on Exercise and Diabetes.Frontiers in endocrinology · 2017Article
- Physical Activity/Exercise and Diabetes: A Position Statement of the American Diabetes Association.Diabetes care · 2016Review
- A Review of Safety and Design Requirements of the Artificial Pancreas.Annals of biomedical engineering · 2016Review
- Coming of age: the artificial pancreas for type 1 diabetes.Diabetologia · 2016Review
- Performance Comparison of CGM Systems: MARD Values Are Not Always a Reliable Indicator of CGM System Accuracy.Journal of diabetes science and technology · 2015Article
- Effect of Continuous Glucose Monitoring Accuracy on Clinicians' Retrospective Decision Making in Diabetes: A Pilot Study.Journal of diabetes science and technology · 2015Article
- Evaluation of stochastic adjustment for glucose sensor bias during closed-loop insulin delivery.Diabetes technology & therapeutics · 2014Article
- Current Trends in Continuous Glucose Monitoring.Journal of diabetes science and technology · 2014Review
Corrections and comments
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Authors and funding
13 authors.
Funding
Abstract
objectiveThis study evaluated the accuracy and large inaccuracy of the Freestyle Navigator (FSN) (Abbott Diabetes Care, Alameda, CA) and Dexcom SEVEN PLUS (DSP) (Dexcom, Inc., San Diego, CA) continuous glucose monitoring (CGM) systems during closed-loop studies. RESEARCH DESIGN AND
methodsPaired CGM and plasma glucose values (7,182 data pairs) were collected, every 15-60 min, from 32 adults (36.2±9.3 years) and 20 adolescents (15.3±1.5 years) with type 1 diabetes who participated in closed-loop studies. Levels 1, 2, and 3 of large sensor error with increasing severity were defined according to absolute relative deviation greater than or equal to ±40%, ±50%, and ±60% at a reference glucose level of ≥6 mmol/L or absolute deviation greater than or equal to ±2.4 mmol/L,±3.0 mmol/L, and ±3.6 mmol/L at a reference glucose level of <6 mmol/L.
resultsMedian absolute relative deviation was 9.9% for FSN and 12.6% for DSP. Proportions of data points in Zones A and B of Clarke error grid analysis were similar (96.4% for FSN vs. 97.8% for DSP). Large sensor over-reading, which increases risk of insulin over-delivery and hypoglycemia, occurred two- to threefold more frequently with DSP than FSN (once every 2.5, 4.6, and 10.7 days of FSN use vs. 1.2, 2.0, and 3.7 days of DSP use for Level 1-3 errors, respectively). At levels 2 and 3, large sensor errors lasting 1 h or longer were absent with FSN but persisted with DSP.
conclusionsFSN and DSP differ substantially in the frequency and duration of large inaccuracy despite only modest differences in conventional measures of numerical and clinical accuracy. Further evaluations are required to confirm that FSN is more suitable for integration into closed-loop delivery systems.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.