Learning from #WeAreNotWaiting – it seems commercial loops have similar caveats…

As a member of the looping community, the last couple of weeks have been interesting, as I’ve started to see questions come up in Facebook groups associated with some of the commercial offerings that have long been asked in the #WeAreNotWaiting world.

On the one hand, it’s good to see that the penetration of commercial hybrid closed loop systems is reaching a level that enough people are using them to be asking these questions. On the other, it’s vaguely disconcerting that people are having to ask these questions and that the experience of those who have previously looped with open source systems is really all that seems to be out there.

Let’s take a couple of examples and you’ll see where this is going….

Dealing with the system pushing you low when getting started

There have been reports of people suffering from commercial systems causing lows when they first get used, as either they learn about the user or the user needs to adjust settings, dependent on which system is in use. This is a pretty simple one to resolve, as users of open source systems will be able to explain.

If the system you’re using isn’t quite dialled in properly, then somehow you need to tell it not to give you as much insulin. In all the systems 9open source and commercial) there’s one common, and very simple, way opf doing that. Set a higher target glucose. Admittedly, in some of the less flexible systems, that means using the exercise target, but it should have the desired effect, stopping insulin delivery earlier and therefore reducing the amount of insulin on board and avoiding hypos. A relatively simple solution that you should only really need to use for a short time while the system gets tuned in.

Re-using CGM sensors to extend their life and reduce the cost to the user

You have a T:Slim, and you want to use Control-IQ, but to do that you have to pay for Dexcom sensors out of your own pocket. Why not use the sensor extension tricks to do so. Couldn’t be easier, right, but are you aware of the caveats related to that and how they might affect the system you’re using?

  • A code restart will put the transmitter into “Insertion trauma” calibration mode for around 36 hours, which can throw the readings off by quite some way, impacting the algorithm you are using;
  • If you’re restarting sensors you need to be careful about the data quality that’s coming off the sensor. Keep a close eye on the system and make sure it’s not too noisy. While the algorithm manufacturers will have included features to cope with poor data quality, you need to know when to change it and be aware of what the risks are.

Dealing with meals

There have been some reports by people about issues with managing meals in some systems, and while not all systems have it, where there’s the equivalent of the CamAPS “Boost” function, you might want to consider using it pre-meal to get that little bit of extra insulin on-board, along the lines of “Eating Soon” in the Open Source world.

It’s likely that the system doesn’t allow you a significantly lower target and will only boost for a shorter period, but it’s better than nothing.

Dealing with Exercise

Pretty much every single system comes with an exercise target or equivalent. Learning the timing for engaging this and how you manage carbohydrate and bolusing around it is critical in getting the bets out of a system for your ability to use it when exercising, something that users of open source solutions have been doing for nearly five years.

While it may come as a surprise that those using commercial systems are encountering similar features that can be handled in similar ways, it perhaps shouldn’t. Using closed loops requires adjustments, regardless of how they were developed and rely on similar technologies for inputs.

Perhaps what this tells us is that users of open source solutions could have a part to play in helping those using commercial systems learn about living with closed loop systems, indeed Dana’s book, “Automated Insulin Delivery: How artificial pancreas “closed loop” systems can aid you in living with diabetes” seeks to do just that.  Alongside this, perhaps it would also be worthwhile for healthcare professionals to engage with Open Source solution users and forums to learn the tips and tricks of the trade.

It would seem that a hybrid closed loop is a hybrid closed loop after all, regardless of who coded it…


  1. I am using tandem with control iq. For exercise just the exercise setting doesn’t do well. Yes it raises target but leaves me without insulin for so long there is a price to pay later. So what i do is make an exercise profile that gives way to little insulin so it forces it to constantly give me some at a constant rate. I do even raise to the 145 target. I leave it at the 110 target. The insulin amt is limited by system and works wonderfully that way. I stay close to target without going low. Every once and a while i actually have to take a small bolus. Then when i finish exercise i take another small bolus as a help and turn on normal profile. It is fantastic

  2. I’ve had Control IQ since the beginning of August & this article reflects my experiences well. You still have to put work in, but once settings are adjusted that workload is much reduced.
    From messages I’ve read, the aspect many people find most difficult is whether they need to adjust basals, or adjust correction ratios.

Leave a Reply

Your email address will not be published.