Diabetes has become a major public health problem in the world. In this context, early assessment of glycemic control is essential in order to avoid life-threatening health complications. A panel of diabetes experts have recently proposed a list of recommendations when using Continuous Glucose Monitoring (CGM) for glycemic control assessment including a minimum of two weeks of CGM data. A recent study has further introduced a metric called Glucose Profile Indicator (GPI) for CGM based diabetes management including a subset of the recommended CGM metrics. In this pilot study, it was investigated if less than two weeks of CGM data would impact the performance of GPI compared to the proposed two weeks of CGM data. Furthermore, logistic regression (LR) was used to examine if an improvement could be achieved taking as input the CGM metrics used to quantify GPI. The population mean accuracy for accumulated day 1 to 13 varied between 72.8 ± 2.0% − 98.3 ± 0.4% with no clear sign of improvement using LR. Hence, this indicates a trade-off between the amount of available CGM data and the precision in which the GPI outcome using all 14 days can be achieved when considering features of the GPI alone. Future work is needed to investigate if this trade-off can be improved by the use of additional features of the CGM.
|Title of host publication||Proceedings of 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)|
|Publication status||Published - 2019|
|Event||2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society - CityCube Berlin, Berlin, Germany|
Duration: 23 Jul 2019 → 27 Jul 2019
|Conference||2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society|
|Period||23/07/2019 → 27/07/2019|