Six of the best: UK CGM error grids

As I’ve previously discussed, I’ve been running a side by side trial of the currently available CGM systems in the UK. It focused on those that are available now, or very soon, on the NHS prescription tariff, and should be available via your UK GP.

I also added in the Medtrum Nano, as an alternative that’s not yet made any reference to doing the same thing, and the Dexcom G6, which is used to drive my closed loop.

During the course of this process, the following CGMs were in use:

  • Dexcom G6
  • Dexcom ONE
  • GlucoRX Aidex
  • Glucomen Day
  • Libre2
  • Medtrum Nano

This is the reference document that is currently being provided within the NHS. As you can see, we are missing the Libre3, Dexcom G7 and Medtronic offerings in this test:

The intention was to use the same reference data for all the sensors to provide a comparison.

Unfortunately, during the course of the two weeks, I lost sensors.

Libre2 fell off quickly, and the replacement didn’t arrive in time to participate. As a result, a previous set of data using the same fingerprick device has been used to provide an error grid.

Glucomen Day fell off after 4 days, so a spare was applied and the trial continued.

The first set of error grids shows all the data collected during the period for each of the devices. I’ll also show the MARD vs fingerpricks (MARDf).

I’ve included a MARDf excluding Day 1 value as well, as we know that Day 1 is generally worse in our experiences with Libre and Dexcom..

Full dataset error grids

This initial error grid overlays data from all the sensors to try and give an idea of how the different sensors compare.

What it tends to highlight is that the three newcomers (Medtrum, Glucomen and GlucoRX) showed more incidents of dispersed readings at high and low levels than the incumbents (Dexcom and Libre). It also shows that, in general, most of the sensors, appeared to provide values slightly higher than the fingersticks.

The individual plots make it easier to see what’s going on.

As mentioned, the Libre2 data is from a different dataset so shouldn’t be considered representative for this test, and is included for illustration only.

GlucoRX Aidex
Glucomen Day
Dexcom G6
Decom ONE
Medtrum Nano
Abbott Freestyle Libre2

What’s clear from all the individual plots is just how widely the data points are dispersed on pretty much every sensor other than the big providers.

What’s perhaps more concerning are the numbers in Zone C, where the blood level is much lower than the sensor indicated reading and could present a significant risk to the user.

This is much higher for the newcomers.

Suffice to say, these error grids clearly show the differences in found in using the sensors.

MARD vs Fingerpricks

Based on the data captured during the 10 or 14 days of using each of the sensors, I’ve calculated a MARD value versus the fingerprick data from a Contour Next One metre. As mentioned previously, this is described as MARDf. Also included in the table are the manufacturers’ stated MARD values, registering the sensor vs a Yellow Springs Instruments analyzer.

As can be seen here, the dispersion shown in the error grids is reflected, unsurprisingly, in the MARDf values that came about from this test.

It’s worth noting that the Dexcom 9.0% value (as reported in their accuracy study of a factory calibrated sensor) is a composite number made up of both adult outcomes (9.8%) and paediatric outcomes (7.7%). It’s also worth noting that the same data was used in both the G6 and ONE manuals, further cementing the point that the glucose sensing and translation components are identical.

In previous similar tests I’ve done of the Glucomen Day, GLucoRX Aidex and other Medtrum sensors, I’ve seen results that were not widely different from these.

Previously, the values were:

SensorPrevious MARDf
GlucoRX Aidex15.1%
Glucomen Day19.6%
Medtrum A614.9%

Based on this, I don’t consider the numbers this time around to be an aberration, in fact, they’re very much in line with previous experiments. In many ways, this is disappointing.

All of this analysis comes with the caveat that this is n=1, and that we’re talking about only one or two of these sensors. On this individual, even where nsensor>1, some of them really aren’t very accurate.

Conclusions so far, and additional analysis

Given previous experience of many of these sensors, I was unsurprised, if a little underwhelmed, by the performance I saw when I put them head to head. While there are six sensors, I think descibing them as “Six of the best” may be a little generous to some of the offerings.

Before we draw final conclusions on the accuracy/safety of these devices, I’ll have a further dig into the analysis of the data, and produce a view of the results showing what percentage of pairs were within the FDA iCGM standard. This is 15mg/dl when reference value was below 3.9mmol/l, 15% above that, for each sensor. That will give a better idea of how they perform in comparison to the FDA standard for use with closed loops.

Thus far, I think we can conclude that while all provide CGM capabilities, all CGMs are not created equal. However much you cover off features in the software, if the key component isn’t particularly effective, is it really worth the money?


    • We’ll, it’s probably more for Europe as some of these are available in various European countries as well.

  1. Hi. Great comparisons, regardless of n=1 limitations! Have you compared out of pocket costs for the various CGM’s, or is that not relevant with the NHS? CGM coverage and out of pocket cost vary dramatically across plans available the USA.

    • From a UK perspective, we can compare on tariff costs, where you may find some are lower cost, but perhaps not as accurate, or over the counter costs to buy direct. There isn’t really the insurance coverage and out of pocket model.

      For what it’s worth, the pricing on the NHS is £2.50 per day for Dexcom ONE and Libre2, and £2.14 or so for Aidex. We don’t know the rate for the Glucomen Day, but that should be published at the end of this month.

    • The Libre2 fell off. I applied it on a hot day and it never properly took.

      The Glucomen kept presenting sensor errors, then automatically ended the session. The Glucomen folk think it had moved around within its pocket, which caused the issue.

      • Try Skin Tac wipes. Using these I have only had a Libre come off when it is knocked off.

        • I’m not a regular Libre user anymore. In the past I never had any issues with Libre adhesion, it was just that one. Indeed, the one I’m wearing now has stuck with no issues.

  2. Fantastic review and very relevant for the UK market as we move into ‘CGM for all’ – Looking forward to your next article to compare final results.

    In my experience the L2 suffers from ‘insertion trauma’ and the best way to avoid inaccurate readings in the fist day or so is to insert 24hrs before starting it. Do the other sensors have the same issue?

    I’m hoping to swap to the Dexcom One when it becomes available for a repeat prescription (currently at least) – so very keen to see which comes out as 1st, 2nd, 3rd on your eval – Many thanks for all the work put in

    • All sensors suffer insertion trauma. What’s different is how the calibration algorithms from different manufacturers handle it.

      Dexcom’s on G6 and ONE is quite aggressive compared to many, but seems to work quite well for a lot of people. Libre2 seems to be a bit more iffy (I’m currently running one alongside a ONE to try and give a better impression of their comparative performance).

      The other sensors were noisy enough in general use for day 1 to matter less, as the MARDf figures show, which really isn’t a good thing.

    • No, I didn’t. I don’t have any Guardian sensors, and the chart came from the DSN Forum, rather than me. They were deliberately left out of this trial.

      If Medtronic want to provide Guardian sensors for testing, I’ll accept them, but given that to provide full accuracy on G3, you need 4x daily calibration, and the factory calibrated G4 sensors are only available with the 780G, and not standalone, there seemed little point in pursuing it hard.

      As a purchase, G3 is also by far the most expensive option available to an out of pocket purchaser in the UK, with a start up cost for a one month pack of £585 , nearly double the price of the Dexcom ONE three month pack at £299 and 3.6x the Dexcom G6 one month starter kit at £159.

      So, yes, the results were left out, but quite deliberately so, as the system is far too expensive for most, and not available on prescription for anyone.

      • OK, thank you for your reply…
        I’m wearing the guardian G3/780G loop for more then a year now…it needs 3 calibrations the first day, then 2 calibrations each next day. Not 4. Sensor dies after a week.

        • Therein lies the problem though. It’s a seven day sensor that costs a fortune as a standalone CGM, and is the only one sold as requiring more than one calibration per day.

          And if you look at the user manual, to get Dexcom G6 comparable MARD requires twice daily calibration. To get G7 or L3 comparable MARD you need 3 or 4 times daily.

          And of course G4 isn’t standalone.

  3. Hi Tm. Great post and thank you very much for your help once more to better comprehend the CGM offerings in the market. Are you going to add the data also for Libre 2 later on the article? Andy if I got it correctly you are using MARDf as a metric because MARD is calculated against lab testing?

    • Hi Nick, I’m using MARDf, because I don’t own a Yellow Springs Instruments glucose analyzed, which runs of venous blood(!) so is a little impractical for a longer term test.

      Instead it’s a more practical test that compares against fingerprick data that you’d use to make treatment decisions if you didn’t have a CGM that was indicated for treatment.

      Libre data will be added at a later date, as I’m currently wearing one at the moment and will be able to report back on that when done.

  4. thank you very much for your prompt response. I had no intention to underestimate your results and forgive me if I left such an impression. My experience – through my son – it is more than obvious that CGM vendors should use MARDf and not MARD (now that I am sure what exactly they are), because this is the everyday of a T1D. I also needed to know the exact meaning in order to share your article in my Facebook Group for Diabetes in Greece ( in which we are trying hard to educate people for the tech solutions that can help them manage their diabetes more conveniently, and because someone could ask about the differences, I need to be able to respond. Thank you very much for your hard work (also on the Dynamic ISF front).

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