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This is an article I recently wrote looking at the the use of third part add-ons with Freestyle Libre. Hope it helps people.
https://www.diabettech.com/xdrip/li...using-a-third-party-transmitter-a-case-study/
Abstract
Introduction
As a result of increased use of third party add-on transmitters to the Libre system to convert them into CGM, and the use of these with DIY APS systems, a case study to look at accuracy and the effects of calibration on accuracy was undertaken.
Method
Libre was used with MiaoMiao and xDrip to capture two datasets using xDrip auto-calibration and twice daily calibration. The data was uploaded to NightScout for storage and analysis was undertaken using the Diabetes Technology Society Surveillance Error Grid, Modified Bland-Altman plot and standard MARD, Bias and Standard Deviation analyses.
Results
The key result was that when a sensor produced data using the Abbott algorithm that was widely variable from blood tests, it tended to have more variance in the data produced by xDrip than when a sensor behaved well. In addition, as the sensor aged variance in the final two days on twice daily calibration was greater. Finally, less frequent sensor calibration appeared to result in better accuracy and a negative bias, however confounding factors early in the calibration cycle may have affected these results.
Conclusions
While frequency of calibration appears to play a part in the accuracy of the data produced using third party add-ons to the Libre, sensor age and sensor native behaviour appear to play more important roles. Users need to be aware of this when they start to use a third party add-on system.
https://www.diabettech.com/xdrip/li...using-a-third-party-transmitter-a-case-study/
Abstract
Introduction
As a result of increased use of third party add-on transmitters to the Libre system to convert them into CGM, and the use of these with DIY APS systems, a case study to look at accuracy and the effects of calibration on accuracy was undertaken.
Method
Libre was used with MiaoMiao and xDrip to capture two datasets using xDrip auto-calibration and twice daily calibration. The data was uploaded to NightScout for storage and analysis was undertaken using the Diabetes Technology Society Surveillance Error Grid, Modified Bland-Altman plot and standard MARD, Bias and Standard Deviation analyses.
Results
The key result was that when a sensor produced data using the Abbott algorithm that was widely variable from blood tests, it tended to have more variance in the data produced by xDrip than when a sensor behaved well. In addition, as the sensor aged variance in the final two days on twice daily calibration was greater. Finally, less frequent sensor calibration appeared to result in better accuracy and a negative bias, however confounding factors early in the calibration cycle may have affected these results.
Conclusions
While frequency of calibration appears to play a part in the accuracy of the data produced using third party add-ons to the Libre, sensor age and sensor native behaviour appear to play more important roles. Users need to be aware of this when they start to use a third party add-on system.
