Background: A cause of suboptimal accuracy in amperometric glucose sensors is the presence of a background current (current produced in the absence of glucose) that is not accounted for. We hypothesized that a mathematical correction for the estimated background current of a commercially available sensor would lead to greater accuracy compared to a situation in which we assumed the background current to be zero. We also tested whether increasing the frequency of sensor calibration would improve sensor accuracy. Methods: This report includes analysis of 20 sensor datasets from seven human subjects with type 1 diabetes. Data were divided into a training set for algorithm development and a validation set on which the algorithm was tested. A range of potential background currents was tested. Results: Use of the background current correction of 4nA led to a substantial improvement in accuracy (improvement of absolute relative difference or absolute difference of 3.5-5.5 units). An increase in calibration frequency led to a modest accuracy improvement, with an optimum at every 4h. Conclusions: Compared to no correction, a correction for the estimated background current of a commercially available glucose sensor led to greater accuracy and better detection of hypoglycemia and hyperglycemia. The accuracy-optimizing scheme presented here can be implemented in real time.
ASJC Scopus subject areas
- Endocrinology, Diabetes and Metabolism
- Medical Laboratory Technology