This being said, impressions can be misleading. Allow me a little rant here: the Internet is full of advice for Type 1 Diabetics, often offered in good faith by T1Ds trying to help others, but rarely supported by hard cold facts. Irrational stuff such as "my BGs are always higher on full moons" or "my CGM is always spot-on when I don't eat cheese" can often be read on boards (OK, I am possibly exaggerating a bit, but not by much...) But the truth is that my own impressions are in no way more valid than the absurd statements above if they aren't grounded in factual reality. Since I don't have Libre sensors at the moment and can't productively continue my technical investigations, I decided to document that impression of responsiveness a bit more extensively.
As you probably all know, the Dexcom G4 provides a sensor glucose value every 5 minutes, the Libre has spot checks available every minute and an "historical" value is computed every 15 minutes from the stored spot values. That is that value that you are able to download from the Abbott software.
These differences in time scale make a direct measurement to measurement accuracy test a bit tricky from a methodological point of view. I am sure the marketing departments of either company could come up with a flawed comparison if they were going head to head. Since I needed to have a sufficient number of data points for a correct comparison, I decided to compare the Dexcom 5 minutes data with the Libre historical 15 minutes data.
I also needed to exclude problematic measures from the comparison. The Libre missed a couple of hours when my son forgot to scan himself at school. The Dexcom lost signal from time to time, one of the sensors fell off, it had its restart, etc... I could, however, find a continuous 8000 minutes run where both sensors were operating simultaneously without any specific issues.
Then, I had to deal with the issue of having two possibly incomplete time series sampled at a different frequency. The way I chose to deal with that problem was to create two virtual sensors that sample the data every minute, fill-in the measured data for both sensors and interpolate the intermediate measures (linear interpolation). You can see the result of that interpolation below - the virtual Libre 1 minute sensor is in green, the virtual Dexcom 1 minute sensor is in Red.
As you can see, both sensors were well behaved during that particular period. The good news is that, globally, they saw the same thing. This is confirmed by a Pearson coefficient of correlation of 0.926 between the two virtual sensors over the whole period.
In order to estimate the difference in reaction time of the sensors, I assumed the Libre sensor was indeed faster based on our impressions and, of course, on the correlation with BG meter measurements during the test. Note: I am not publishing a direct Dexcom vs Libre vs meter MARDs at this point as I would not want to give a false impression based on a single Libre sensor.
The short story is that the Libre was consistently faster than the Dex throughout the test. But how much faster?
The best way to find out is simply to shift our virtual sensors in time, minute by minute, and see at what shift we we get the best correlation between the two data streams. Remember that we are not trying to find out which sensor was the most correct in absolute terms, but just trying to establish without a doubt if our initial impression of speed can be factually confirmed.
The answer can be found below: the optimal correlation between the two sensors occurs if you either delay the Libre signal or advance the Dexcom signal by 9 minutes. Yes, the correlation differences are, relatively speaking, small. But keep in mind that these differences only come from periods where IG is changing. The 8000 minutes involved contain long stretches of relatively stable IGs where, of course, reaction time has no impact. The clear peak and dome like aspect of the time dependent correlation curve removes any doubt about the validity of the result.
In other words, the Libre will generally inform you of a change in interstitial glucose 9 minutes before the Dexcom does. In practice, that really makes a difference, especially if you take into account the fact that the Libre spot checks also seem to be ahead of the Libre historical data (maybe more about this later.)
Why is that so?
The Dexcom (non AP) algorithm is relatively well understood, thanks to the abundant literature on the topic and the fact that raw data can be intercepted. I won't go into details here, but we can say that it is delayed, in addition to the physiological BG-IG delay, by design. That design is a design that is constrained by the possible inaccuracies of a single Dexcom sensor measurement and it relies on the averaging of data and the application of a calibration "curve". It definitely seems that the Libre sensor provides more reliable data, but that is a complex issue that requires digging a bit deeper in the accuracy of spot checks. Indeed, it could be argued that the processing of immediate data into historical data could retroactively improve the apparent accuracy of the Libre. However, the Libre individual spot checks taken in real time correlate very well with the historical data - they are, as stated above even faster - and that seems to indicate that Abbott is clearly ahead either in its sensor reliability on a single measure or in its algorithms. Dexcom as just filed a request with the FDA for a sensor production process modification, let's hope this leads to an improvement in reliability.