BACKGROUND: Glucose variability has been identified as a predictor of hypoglycemia and has been associated with mortality in critically ill patients without diabetes. A popular metric to quantify glucose variability is the mean amplitude of glycemic excursions (MAGE). The "ruler and pencil" approach to calculate MAGE is operator-dependent and time-consuming for analysis of continuous glucose monitoring data. Therefore, several computer software programs have been developed for the automated calculation of MAGE. The aim of our study was to evaluate the agreement of currently available MAGE calculators when applied to the same set of continuous glucose monitoring (CGM) traces. MATERIALS AND METHODS: Four software programs for calculation of MAGE were identified and used to calculate MAGE of 21 CGM traces from seven patients with type 1 diabetes. Subsequently, the median MAGE per calculator was calculated. The correlation between the MAGE calculators was evaluated by Spearman's correlation analysis. Between-group comparison was performed using analysis of variance. RESULTS: The median MAGE (interquartile range) per calculator was 8.7 (7.1-10.7), 6.7 (5.5-8.6), 6.7 (5.2-8.6), and 5.8 (4.3-7.1), which was statistically different overall (P<0.001). The correlation coefficients between the calculators ranged from 0.787 to 0.999. CONCLUSIONS: Available computer programs developed to calculate MAGE show varying agreement. Although software programs for the calculation of MAGE would seem attractive to assess glucose variability, their use has limitations by different outcomes, in the absence of a gold standard.
BACKGROUND:Glucose variability has been identified as a predictor of hypoglycemia and has been associated with mortality in critically illpatients without diabetes. A popular metric to quantify glucose variability is the mean amplitude of glycemic excursions (MAGE). The "ruler and pencil" approach to calculate MAGE is operator-dependent and time-consuming for analysis of continuous glucose monitoring data. Therefore, several computer software programs have been developed for the automated calculation of MAGE. The aim of our study was to evaluate the agreement of currently available MAGE calculators when applied to the same set of continuous glucose monitoring (CGM) traces. MATERIALS AND METHODS: Four software programs for calculation of MAGE were identified and used to calculate MAGE of 21 CGM traces from seven patients with type 1 diabetes. Subsequently, the median MAGE per calculator was calculated. The correlation between the MAGE calculators was evaluated by Spearman's correlation analysis. Between-group comparison was performed using analysis of variance. RESULTS: The median MAGE (interquartile range) per calculator was 8.7 (7.1-10.7), 6.7 (5.5-8.6), 6.7 (5.2-8.6), and 5.8 (4.3-7.1), which was statistically different overall (P<0.001). The correlation coefficients between the calculators ranged from 0.787 to 0.999. CONCLUSIONS: Available computer programs developed to calculate MAGE show varying agreement. Although software programs for the calculation of MAGE would seem attractive to assess glucose variability, their use has limitations by different outcomes, in the absence of a gold standard.
Authors: Thomas A Peyser; Andrew K Balo; Bruce A Buckingham; Irl B Hirsch; Arturo Garcia Journal: Diabetes Technol Ther Date: 2017-12-11 Impact factor: 6.118
Authors: Francisco Gude; Pablo Díaz-Vidal; Cintia Rúa-Pérez; Manuela Alonso-Sampedro; Carmen Fernández-Merino; Jesús Rey-García; Carmen Cadarso-Suárez; Marcos Pazos-Couselo; José Manuel García-López; Arturo Gonzalez-Quintela Journal: J Diabetes Sci Technol Date: 2016-12-13
Authors: Tim Vigers; Christine L Chan; Janet Snell-Bergeon; Petter Bjornstad; Philip S Zeitler; Gregory Forlenza; Laura Pyle Journal: PLoS One Date: 2019-10-11 Impact factor: 3.240