Abstract
Background:
Even though a Clinical and Laboratory Standards Institute proposal exists on the design of studies and
performance criteria for continuous glucose monitoring (CGM) systems, it has not yet led to a consistent
evaluation of different systems, as no consensus has been reached on the reference method to evaluate them
or on acceptance levels. As a consequence, performance assessment of CGM systems tends to be inconclusive,
and a comparison of the outcome of different studies is difficult.
Materials and Methods:
Published information and available data (as presented in this issue of Journal of Diabetes Science and Technology
by Freckmann and coauthors) are used to assess the suitability of several frequently used methods
[International Organization for Standardization, continuous glucose error grid analysis, mean absolute relative
deviation (MARD), precision absolute relative deviation (PARD)] when assessing performance of CGM systems
in terms of accuracy and precision.
Results:
The combined use of MARD and PARD seems to allow for better characterization of sensor performance.
The use of different quantities for calibration and evaluation, e.g., capillary blood using a blood glucose (BG)
meter versus venous blood using a laboratory measurement, introduces an additional error source. Using BG
values measured in more or less large intervals as the only reference leads to a significant loss of information in
comparison with the continuous sensor signal and possibly to an erroneous estimation of sensor performance
during swings. Both can be improved using data from two identical CGM sensors worn by the same patient
in parallel.
| Original language | English |
|---|---|
| Pages (from-to) | 824-832 |
| Number of pages | 8 |
| Journal | Journal of Diabetes Science and Technology |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - Jul 2013 |
Fields of science
- 203 Mechanical Engineering
- 202034 Control engineering
- 202012 Electrical measurement technology
- 206 Medical Engineering
- 202027 Mechatronics
- 202003 Automation
- 203027 Internal combustion engines
- 207109 Pollutant emission
JKU Focus areas
- Mechatronics and Information Processing