Head-to-head comparison between flash and continuous glucose monitoring systems in outpatients with type 1 diabetes

Purpose Continuous glucose monitoring (CGM) is being increasingly used in clinical practice. The flash glucose monitoring (FGM) and CGM are different systems of interstitial glucose recording. We aimed to determine the agreement between the factory-calibrated FGM FreeStyle Libre (FSL) and the gold-s...

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Bibliographic Details
Published in:Journal of endocrinological investigation 2016-12, Vol.39 (12), p.1391-1399
Main Authors: Bonora, B., Maran, A., Ciciliot, S., Avogaro, A., Fadini, G. P.
Format: Article
Language:English
Subjects:
Adult
Autoimmune diseases
Biomarkers - blood
Blood glucose
Blood Glucose - analysis
Blood Glucose Self-Monitoring - methods
Calibration
Diabetes mellitus
Diabetes Mellitus, Type 1 - blood
Diabetes Mellitus, Type 1 - drug therapy
Diabetes Mellitus, Type 1 - epidemiology
Endocrinology
Female
Glucose monitoring
Humans
Hyperglycemia - blood
Hyperglycemia - etiology
Hyperglycemia - prevention & control
Hypoglycemia - blood
Hypoglycemia - etiology
Hypoglycemia - prevention & control
Immunology
Male
Medicine
Medicine & Public Health
Metabolic Diseases
Middle Aged
Original Article
Outpatients
Prognosis
Retrospective Studies
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Summary:Purpose Continuous glucose monitoring (CGM) is being increasingly used in clinical practice. The flash glucose monitoring (FGM) and CGM are different systems of interstitial glucose recording. We aimed to determine the agreement between the factory-calibrated FGM FreeStyle Libre (FSL) and the gold-standard CGM Dexcom G4 Platinum (DG4P). Methods We analyzed data from n  = 8 outpatients with type 1 diabetes, who wore the FSL and DG4P for up to 14 days during their habitual life. We aligned FSL and DG4P recordings to obtain paired glucose measures. We calculated correlation coefficients, mean absolute relative difference (MARD), percentages in Clarke error grid areas, time spent in hyperglycaemia, target glycaemia, or hypoglycaemia, as well as glucose variability with both sensors. Comparison with self-monitoring of blood glucose (SMBG) was also performed. Results Patients varied in terms of age, diabetes duration, and HbA1c (from 5.9 to 9.6 %). In the pooled analysis of 10,020 paired values, there was a good correlation between FSL and DG4P ( r 2  = 0.76; MARD = 18.1 ± 14.8 %) with wide variability among patients. The MARD was significantly higher during days 11–14 than in days 1–10, and during hypoglycaemia (19 %), than in normoglycaemia (16 %) or hyperglycaemia (13 %). Average glucose profiles and MARD versus SMBG were similar between the two sensors. Time spent in normo-, hyper-, or hypoglycaemia, and indexes of glucose variability was similarly estimated by the two sensors. Conclusions In outpatients with type 1 diabetes, we found good agreement between the FSL and DG4P. No significant difference was detected in the estimation of clinical diagnostic parameters.
ISSN:1720-8386
0391-4097
1720-8386
DOI:10.1007/s40618-016-0495-8