Claudio Cobelli1, Michele Schiavon1, Chiara Dalla Man1, Ananda Basu2, Rita Basu2. 1. 1 Department of Information Engineering, University of Padova , Padova, Italy . 2. 2 Endocrine Research Unit, Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Department of Internal Medicine, Mayo Clinic and Foundation , Rochester, Minnesota.
Abstract
BACKGROUND: Glucose sensors measure glucose concentration in the interstitial fluid (ISF), remote from blood. ISF glucose is well known to be "delayed" with respect to blood glucose (BG). However, ISF glucose is not simply a shifted-in-time version of BG but exhibits a more complex pattern. METHODS: To gain insight into this problem, one can use linear systems theory. However, this may lose a more clinical readership, thus we use simulation and two case studies to convey our thinking in an easier way. In particular, we consider BG concentration measured after meal and exercise in 12 healthy volunteers, whereas ISF glucose is simulated using a well-accepted model of blood-ISF glucose kinetics, which permits calculation of the equilibration time, a parameter characterizing the system. Two metrics are defined: blood and ISF glucose difference at each time point and time to reach the same glucose value in blood and ISF. RESULTS: The simulation performed and the two metrics show that the relationship between blood-ISF glucose profiles is more complex than a pure shift in time and that the pattern depends on both equilibration time and BG. CONCLUSIONS: In this in silico study, we have illustrated, with simple case studies, the meaning of the of ISF glucose with respect to BG. Understanding that ISF glucose is not just a shifted-in-time version but a distorted mirror of BG is important for a correct use of continuous glucose monitoring for diabetes management.
BACKGROUND:Glucose sensors measure glucose concentration in the interstitial fluid (ISF), remote from blood. ISF glucose is well known to be "delayed" with respect to blood glucose (BG). However, ISF glucose is not simply a shifted-in-time version of BG but exhibits a more complex pattern. METHODS: To gain insight into this problem, one can use linear systems theory. However, this may lose a more clinical readership, thus we use simulation and two case studies to convey our thinking in an easier way. In particular, we consider BG concentration measured after meal and exercise in 12 healthy volunteers, whereas ISF glucose is simulated using a well-accepted model of blood-ISF glucose kinetics, which permits calculation of the equilibration time, a parameter characterizing the system. Two metrics are defined: blood and ISF glucose difference at each time point and time to reach the same glucose value in blood and ISF. RESULTS: The simulation performed and the two metrics show that the relationship between blood-ISF glucose profiles is more complex than a pure shift in time and that the pattern depends on both equilibration time and BG. CONCLUSIONS: In this in silico study, we have illustrated, with simple case studies, the meaning of the of ISF glucose with respect to BG. Understanding that ISF glucose is not just a shifted-in-time version but a distorted mirror of BG is important for a correct use of continuous glucose monitoring for diabetes management.
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