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Article Abstract
This report details the case of a 41-year-old woman who was diagnosed with insulinoma. As the patient developed severe life-threatening hypoglycemia, we introduced Dexcom G4 Platinum (DG4P), a modern continuous glucose-monitoring system (CGM). The algorithm of the sensor glucose (SG) values of CGM is based on patients with diabThis report details the case of a 41-year-old woman who was diagnosed with insulinoma. As the patient developed severe life-threatening hypoglycemia, we introduced Dexcom G4 Platinum (DG4P), a modern continuous glucose-monitoring system (CGM). The algorithm of the sensor glucose (SG) values of CGM is based on patients with diabetes; therefore, we evaluated the accuracy of DG4P in this patient. The mean absolute relative differences and absolute differences between SG of DG4P and self-monitoring of blood sugar values were 10.8%±8.3% and 6.8±5.7 mg/dL, respectively, in the hypoglycemic region, which verifies DG4P's accuracy. DG4P was found to be useful for monitoring hypoglycemia not only in patients with diabetes but also in those with insulinoma.etes; therefore, we evaluated the accuracy of DG4P in this patient. The mean absolute relative differences and absolute differences between SG of DG4P and self-monitoring of blood sugar values were 10.8%±8.3% and 6.8±5.7 mg/dL, respectively, in the hypoglycemic region, which verifies DG4P's accuracy. DG4P was found to be useful for monitoring hypoglycemia not only in patients with diabetes but also in those with insulinoma.
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A case of insulinoma-induced hypoglycemia managed by Dexcom G4 Platinum.
Neuro Endocrinol Lett
September 2022
Department of Medicine and Molecular Science, Gunma University Graduate School of Medicine, 3-39-15 Showa-machi, Maebashi, Gunma 371-8511, Japan.
This report details the case of a 41-year-old woman who was diagnosed with insulinoma. As the patient developed severe life-threatening hypoglycemia, we introduced Dexcom G4 Platinum (DG4P), a modern continuous glucose-monitoring system (CGM). The algorithm of the sensor glucose (SG) values of CGM is based on patients with diabThis report details the case of a 41-year-old woman who was diagnosed with insulinoma.
View Article and Find Full Text PDFAnalysis of "Simple Post-Processing of Continuous Glucose Monitoring Measurements Improves Endpoints in Clinical Trials".
J Diabetes Sci Technol
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Alfter, Germany.
Jensen et al used continuous glucose monitoring (CGM) data of the Dexcom G4 Platinum (DG4P) sensor obtained in a clinical efficacy and safety study of Novo Nordisk's new insulin Fiasp® to calculate the CGM time delay versus plasma glucose (PG) and self-measured blood glucose (SMBG) measurements (9-10 min). Shifting the CGM signal by 9 min backward in time versus PG and SMBG data improved the analytical accuracy of the DG4P sensor and the reliability of clinical research endpoint (hypoglycemia, postprandial glucose increments) detection. Since this method takes advantage of post-processing of CGM data, it is particularly suited for the optimization of data processing in clinical studies.
View Article and Find Full Text PDFToward Calibration-Free Continuous Glucose Monitoring Sensors: Bayesian Calibration Approach Applied to Next-Generation Dexcom Technology.
Diabetes Technol Ther
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Department of Information Engineering, University of Padova, Padova, Italy .
Background: Continuous glucose monitoring (CGM) sensors need to be calibrated twice/day by using self-monitoring of blood glucose (SMBG) samples. Recently, to reduce the calibration frequency, we developed an online calibration algorithm based on a multiple-day model of sensor time variability and Bayesian parameter estimation. When applied to Dexcom G4 Platinum (DG4P) sensor data, the algorithm allowed the frequency of calibrations to be reduced to one-every-four-days without significant worsening of sensor accuracy.
View Article and Find Full Text PDFFreeStyle Libre and Dexcom G4 Platinum sensors: Accuracy comparisons during two weeks of home use and use during experimentally induced glucose excursions.
Nutr Metab Cardiovasc Dis
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Division of Metabolic Diseases, Department of Medicine, University of Padova, Padova, Italy. Electronic address:
Background And Aims: This study compared the accuracy of the FreeStyle Libre (Abbott, Alameda, CA) and Dexcom G4 Platinum (DG4P, Dexcom, San Diego, CA) CGM sensors.
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From Two to One Per Day Calibration of Dexcom G4 Platinum by a Time-Varying Day-Specific Bayesian Prior.
Diabetes Technol Ther
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Department of Information Engineering, University of Padova, Padova, Italy .
Background: In the DexCom G4 Platinum (DG4P) continuous glucose monitoring (CGM) sensor, the raw current signal generated by glucose-oxidase is transformed to glucose concentration by a calibration function whose parameters are periodically updated by matching self-monitoring of blood glucose references, usually twice a day, to compensate for sensor variability in time. The aim of this work is to reduce DG4P calibration frequency to once a day by a recently proposed Bayesian calibration algorithm, which employs a time-varying calibration function and suitable day-specific priors.
Methods: The database consists of 57 CGM signals that are collected by the DG4P for 7 days.