A diabetic patient occasionally undergoes a detailed monitoring of their glucose levels. Over the course of a few days, a monitoring system provides a detailed track of their interstitial fluid glucose levels measured in their subcutaneous tissue. A discrepancy in the blood and interstitial fluid glucose levels is unimportant because the blood glucose levels are not measured continuously. Approximately five blood glucose level samples are taken per day, and the interstitial fluid glucose level is usually measured every 5min. An increased frequency of blood glucose level sampling would cause discomfort for the patient; thus, there is a need for methods to estimate blood glucose levels from the glucose levels measured in subcutaneous tissue. The Steil-Rebrin model is widely used to describe the relationship between blood and interstitial fluid glucose dynamics. However, we measured glucose level patterns for which the Steil-Rebrin model does not hold. Therefore, we based our research on a different model that relates present blood and interstitial fluid glucose levels to future interstitial fluid glucose levels. Using this model, we derived an improved model for calculating blood glucose levels. In the experiments conducted, this model outperformed the Steil-Rebrin model while introducing no additional requirements for glucose sample collection. In subcutaneous tissue, 26.71% of the calculated blood glucose levels had absolute values of relative differences from smoothed measured blood glucose levels less than or equal to 5% using the Steil-Rebrin model. However, the same difference interval was encountered in 63.01% of the calculated blood glucose levels using the proposed model. In addition, 79.45% of the levels calculated with the Steil-Rebrin model compared with 95.21% of the levels calculated with the proposed model had 20% difference intervals.
We developed a new model of glucose dynamics. The model calculates blood glucose level as a function of transcapillary glucose transport. In previous studies, we validated the model with animal experiments. We used analytical method to determine model parameters. In this study, we validate the model with subjects with type 1 diabetes. In addition, we combine the analytic method with meta-differential evolution. To validate the model with human patients, we obtained a data set of type 1 diabetes study that was coordinated by Jaeb Center for Health Research. We calculated a continuous blood glucose level from continuously measured interstitial fluid glucose level. We used 6 different scenarios to ensure robust validation of the calculation. Over 96% of calculated blood glucose levels fit A+B zones of the Clarke Error Grid. No data set required any correction of model parameters during the time course of measuring. We successfully verified the possibility of calculating a continuous blood glucose level of subjects with type 1 diabetes. This study signals a successful transition of our research from an animal experiment to a human patient. Researchers can test our model with their data on-line at https://diabetes.zcu.cz.
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