title: Continuous glucose monitoring and trend accuracy: news about a trend compass.
abstract: Continuous glucose monitoring (CGM) devices are being increasingly used to monitor glycemia in people with diabetes. One advantage with CGM is the ability to monitor the trend of sensor glucose (SG) over time. However, there are few metrics available for assessing the trend accuracy of CGM devices. The aim of this study was to develop an easy to interpret tool for assessing trend accuracy of CGM data. SG data from CGM were compared to hourly blood glucose (BG) measurements and trend accuracy was quantified using the dot product. Trend accuracy results are displayed on the Trend Compass, which depicts trend accuracy as a function of BG. A trend performance table and Trend Index (TI) metric are also proposed. The Trend Compass was tested using simulated CGM data with varying levels of error and variability, as well as real clinical CGM data. The results show that the Trend Compass is an effective tool for differentiating good trend accuracy from poor trend accuracy, independent of glycemic variability. Furthermore, the real clinical data show that the Trend Compass assesses trend accuracy independent of point bias error. Finally, the importance of assessing trend accuracy as a function of BG level is highlighted in a case example of low and falling BG data, with corresponding rising SG data. This study developed a simple to use tool for quantifying trend accuracy. The resulting trend accuracy is easily interpreted on the Trend Compass plot, and if required, performance table and TI metric.
authors.affiliation: Department of Mechanical Engineering, University of Canterbury, New Zealand matthew.signal@canterbury.ac.nz.
authors.forename: Matthew
authors.initials: M
authors.lastname: Signal
authors.affiliation: Medtronic Diabetes, Northridge, California, USA.
authors.forename: Rebecca
authors.initials: R
authors.lastname: Gottlieb
authors.affiliation: Department of Mechanical Engineering, University of Canterbury, New Zealand.
authors.forename: Aaron
authors.initials: A
authors.lastname: Le Compte
authors.affiliation: Department of Mechanical Engineering, University of Canterbury, New Zealand.
authors.forename: J Geoffrey
authors.initials: JG
authors.lastname: Chase
mesh_terms: D000465:Algorithms; D001786:Blood Glucose / Q000032:analysis*; D015190:Blood Glucose Self-Monitoring / Q000592:standards*; D006801:Humans
chemical_list: D001786:Blood Glucose
keywords: Trend Compass; accuracy; blood glucose; continuous glucose monitoring; metric; trend