Abstract
Background Because declining glucose levels should be detected quickly in persons with Type1 diabetes, a lag between blood glucose and subcutaneous sensor glucose can be problematic. It is unclear whether the magnitude of sensor lag is lower during falling glucose than during rising glucose. Methods Initially, we analysed 95 data segments during which glucose changed and during which very frequent reference blood glucose monitoring was performed. However, to minimize confounding effects of noise and calibration error, we excluded data segments in which there was substantial sensor error. After these exclusions, and combination of data from duplicate sensors, there were 72 analysable data segments (36 for rising glucose, 36 for falling). We measured lag in two ways: (1) the time delay at the vertical mid-point of the glucose change (regression delay); and (2) determination of the optimal time shift required to minimize the difference between glucose sensor signals and blood glucose values drawn concurrently. Results Using the regression delay method, the mean sensor lag for rising vs. falling glucose segments was 8.9min (95%CI 6.1-11.6) vs. 1.5min (95%CI -2.6 to 5.5, P<0.005). Using the time shift optimization method, results were similar, with a lag that was higher for rising than for falling segments [8.3 (95%CI 5.8-10.7) vs. 1.5min (95%CI -2.2 to 5.2), P<0.001]. Commensurate with the lag results, sensor accuracy was greater during falling than during rising glucose segments. Conclusions In Type1 diabetes, when noise and calibration error are minimized to reduce effects that confound delay measurement, subcutaneous glucose sensors demonstrate a shorter lag duration and greater accuracy when glucose is falling than when rising.
Original language | English (US) |
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Pages (from-to) | 1067-1073 |
Number of pages | 7 |
Journal | Diabetic Medicine |
Volume | 29 |
Issue number | 8 |
DOIs | |
State | Published - Aug 2012 |
Keywords
- Biotechnology
- Continuous blood glucose monitoring
- Type1 diabetes
ASJC Scopus subject areas
- Internal Medicine
- Endocrinology, Diabetes and Metabolism
- Endocrinology