Hormones #2

Post-lunch BG climbs to 195, which I knew was unusual given what she’d packed for lunch.  Didn’t notice anything with a crazy carb count on her NS.  But those SMBs were really such a nice visual that my loop and I were on the same page about what to do about it.


I ventured a quick text to check in.  I hate doing that, but she was home from school and I wouldn’t be interrupting class…so I did.  I asked.


Woah.  Wasn’t expecting that one.  We are still a little variable on when that pesky thing is coming…so this caught me off guard.  Three weeks…not four.  Ok.

Things had been so steady for the last several days (*except on beach party with cupcakes, teenagers, and suspended pumps for extended times a couple days ago).  I mean, look…so steady, right?  That was yesterday.

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And then today….with the same food basically.  But that red arrow was The Change.


If I could offer a hug to an inanimate object, it may be going to autosens.  I took a peek to see if things really had been *that steady* or if we had actually been getting a lot of help that I wasn’t aware of.

My suspicions were correct.  What had looked like a calm day, was actually the result of increasing ISF and Basal adjustments, as well as auto lower temp targets, behind the scenes.  From yesterday to today…basals went from 0.8 to 1.05. ISF went from 40 to 30.3.  The storm was held at bay until this afternoon when the big hormones hit just after lunch.


We adjusted her basals to 1.3 (based on where we had to adjust them to last month) and autosens is predicting we may need more…we will let it sit here for a little bit if we need to nudge in that direction in a few hours.

I can’t say how nice it is to take what is normally a horrible time (hormone swings) and make it limited to just a few hours of pain-in-the-butt.  The old way (non-autosens and non-looping) was days of pain.

Under the hood of OpenAPS

(Pull up a chair, this is a bit of an involved post)

UAM is “unannounced meals” feature in oref1 for OpenAPS.  You can read about UAM features and its development in Dana’s blog post here.

Here’s how my thought process has gone on UAM since I first read about it:

1st thought: Oh, I won’t need that since we always enter our carbs and prebolus.  UAM won’t offer me any improvements since we always “announce” our meals.

2nd thought: Well, there are times (ahem, school snack bar) where Anna or I have some hard carb counts.  I wonder if maybe when we were 20% off on a carb count, perhaps UAM might help then?  Because if we are 20% off on a carb count, that would sort of be like having 20% of an unannounced meal, right?  Hmmmm…let’s try enabling it and see.

3rd thought: Wow, that worked really well.  But WHY did it work well?  How is it different?  Oh piss…I’d better roll up my sleeves and look at code.

And that is how I ended up learning more about oref0’s logic for setting temp basal and (now with oref1) setting SMBs.

Side Note: If you care to do the same as I’ve done…the logic for how oref0 sets temp basal and gives SMBs is laid out in a file called determine-basal.js in GitHub.  This same file is pulled into your rig when you build your loop.  I’m not a code person, but a slow and methodical read of the file can provide some insight into the logic for how temp basals are set.  Plus, there’s certain lines in that file that start with “//”…those are plain english notes to help readers understand the code that follows the note.  If you start with the // lines, that may help anchor some of your read of the file.

When I went to the first endo appointment after diagnosis, I was shocked that they didn’t have a flow chart to tell us how to dose insulin.  Like those decisions flow charts that say “if answer is yes, go to this next square…if the answer is no, go to the other square.”  As I came to learn the hard way, the answer to “How much should I dose for a BG of 250 mg/dl?” will have about 18 questions that follow it before you can give an answer.  What’s her ISF?  What’s her IOB?  Is she exercising?  Is her BG rising or falling?  Did she eat recently?  How long ago did she eat?  How much did she eat?  How confident are you in the carb count?  Is she stressed/excited/nervous?   And so on.  It’s no wonder finding a babysitter for a T1D kid is almost impossible.

The same complications exist for loop logic.  Depending on whether BGs are rising/falling/steady, how fast BGs are rising, whether food is at play, and whether temp targets…how does your loop take those into account?   I’d previously heard OpenAPS developer Scott Leibrand refer to “blending” things like this into his loop, but I didn’t quite understand the term until I really looked into the determine-basal.js code.

So how does that blending work?  Traditionally, you’d start loop math using just insulin and carbs to predict future BGs.  You’d approximate how the insulin would behave based on published insulin effectiveness curves (like peaking insulin activity around 60-90 minutes and then tailing off) and you’d approximate carb absorption (like the Loop system does using the model from Think Like A Panceas).  You’d add the downward effect of insulin and the upward effect of carbs and voila…a predicted BG curve blending insulin and carb effects.

But, a good loop will go beyond that simple approximation to try to help with things that are happening outside the perfect-world scenario.  Things like “retrospective correction” and “BG momentum” in Loop system attempt to incorporate the “wtf is happening now? I’m not sure.” part of diabetes into a better BG prediction.

OpenAPS does this refinement through the use of several different predicted BG curves.  Ever wonder WHY OpenAPS has all those purple lines showing in Nightscout?  This is the reason why…those lines are the drivers of the logic.  They help blend the various scenarios about rising/falling/steady BGs, recent food, and activity to come up with a better chosen predicted BG curve.  And a better predicted BG curve should yield a better loop decision…avoiding lows and quicker recovery from high BGs.

Ready for this?  OpenAPS has the following types of “basic” predicted BG curves:

  • IOBpredBGs: based on insulin only
  • COBpredBGs: carbs and insulin together
  • UAMpredBGs: “floating carbs” and insulin together

That’s not the exhaustive list of curves used though…depending on the situation (rising BGs or falling BGs, for example), OpenAPS also does other calculations using the predictedBG curves (for example, minPredBG and avePredBG) to help provide for safe looping.

Basically, determine-basal.js has a whole bunch of “if this (is happening), then do that (use THAT particular predBG curve to determine the delivery of insulin)”.  For example, IF carbs are on-board and UAM and SMB are enabled, and BG is rising but not as much as expected, and IOB is negative, and prediction is above target…THEN use the XXXpredBG curve to calculate how much insulin to deliver.  If you change any one of those IF inputs…like BG is instead dropping and faster than expected…then OpenAPS is going to make a different decision about how to adjust insulin delivery and may use a different predBG curve to do that.

So, determine-basal.js is that complicated set of 18 questions involving “IF this and this and this and this but not that or that, THEN that” that we all used to go through before giving a dose of insulin.  It even has an IF-term called “Deviation” which is basically a measure of how far off expected BG behavior you are.  Looking at the deviation term is a big part of the OpenAPS decision IF-logic.  We’ve all used it before…”dang it, she SHOULD be dropping right now, but she isn’t!”

That’s where UAM and floating carbs come into play in a new way.  Previously, looping was constrained mathematically around meal-times by the amount of carbs entered.  The COBpredBG curve could only go so far in its prediction of BGs because it was limited to the carbs entered.

UAMpredBG is not restricted to the carb entry you’ve provided.  In a way, it doesn’t “trust” your carb entry as much.  It fact-checks your carb entry by looking at deviation comparisons.   More mathematically stated, UAM is predicting the future BGs based on the slope (rate of change in BG) of your actual BGs during meals.  [“during meals” is user-defined as either having carbs on board, an eating soon temp target, and/or a bolus given].  So, if your BGs are rising during a meal and they continue to rise beyond what was predicted on carbs alone (strong deviations happening), UAM is going to carry that prediction forward…regardless of the carbs you entered.  And it will carry that forward until the slope stops and things settle down.  Without UAM, that continued BG prediction up would’ve been restricted shortly after the meal was eaten by the fact that the carbs would’ve decayed ( COB=0 ) fairly quickly based on the rise in BG.

So, do you ever find that perhaps you under-counted carbs?  You’ve watched a meal’s BG climb after unknown sauces and unidentified ingredients were clearly playing a part in the meal?  The recovery to target BG in that situation can be slowed by the fact that the carbs were eventually all “used up” by the loop logic to explain the rise in BG.  Any additional rise the loop had no explanation for, and tended to treat delicately (slowly).

With UAM, the curve says “I can see these deviations were not expected.  I will help.  Even if the deviations go beyond simple explanation of what COB would expect.”  So that mathematical freedom helps for poor carb counting.  (It’s not unlimited freedom, there are still safety mechanisms in place.)

Case in point…that mini McMuffin of unknown carb count.


See how the UAMpredBG is headed to 294, while the other predictions have lower eventual BG predictions?  UAM is taking into account that Deviation of 67 and COB of 16g…saying “wow, you have NOT shown the BG behavior that I would’ve expected at this point in time for the carbs and bolus you’ve told me about.  I’m gonna trust your carb entry less and instead trust the deviations more.  If my predictions are right, you will need 1.85 additional units of insulin to control this unexpected deviation.  But, predictions can change.  So let’s give you a SMB of 0.4 units to help with that right now.  If I’ve overshot my estimate, I can suspend enough basal later to fix. But that 0.4 is a good help right now for your deviations I’m seeing.  Let’s try that, we will regroup with the next BG and see where you are.”

The next BG reading comes in and loop has some new information to consider.  BG has slowed down and there’s more insulin on board from the 0.4 SMB.

Screen Shot 2017-05-22 at 11.16.08 AM

Deviation is now a smaller number (the slope of the rising BGs has decreased), we are moving closer to what the expected behavior should be.  In fact, the UAMpredBG curve now predicts an eventual BG of 104 and the insulin required is now -0.12 units.  So, loop will suspend basals and wait for the next BG to come in…and go through all of its IFs and THENs again before deciding what to do with insulin.  The loop is beginning to be able to trust cob again; it has delivered enough insulin to cover the carbs that we undercounted and, through SMBs help too, we are going to spend less time out of range.

What about situations where you OVER counted carbs?  Will UAM be able to help there too?  Yes.  When UAM is not seeing enough carb absorption compared to what you’ve told it to expect (“hey, you promised me 25g carbs and I’m only seeing enough BG impact to trust that you ate 10g of carbs”), then the loop will hold off on basal insulin and dosing until the BGs catch up.  (See…it’s comparing those COBpredBG curves with the UAMpredBG curves to make decisions.  All those little purple lines and deviation values are part of the logic sequence to deliver insulin.)

Because UAMpredBG curve is not limited so much by your actual carb entry, it will tend to have a much more variable prediction after each new BG entry.  It will predict very high eventual BG if your BG is strongly rising, and then it will predict lower BG if your BG is dropping.  So, if and when, you decide to enable UAM…don’t be surprised by seeing an ever-changing UAM curve, that’s an expected result since it isn’t quite so restricted by your carb entry.

As I understand it, it took several iterations for Scott and Dana to figure out the proper blending (IFs and THENs) of UAM into the oref0 determine-basal.js code.  Then there’s been many early users that have put it to the test to validate or improve the blending.

Where I’d previously thought that UAM had very little value, because we always enter our meals and prebolus…turns out I was wrong.  I’m not a carb-counting expert.  I get it wrong sometimes.  And UAM helps mop-up my harder carb counts, in both directions.  When I’m right on carb counts, UAM plays almost no role…but with UAM I’m not going to be nearly as BG-impacted when I do get things wrong.



OpenAPS and UAM

Now that we’ve had some time with SMBs enabled, I was ready to consider trying the other new feature called UAM (unannounced meals).  I wasn’t previously interested in this feature much, because (I’m lucky) Anna has only forgotten about 2 boluses in her 2+ years of mostly independent bolusing.  So meals generally don’t go unannounced.  I didn’t imagine there would be much value in a feature named “unannounced meals”.

But, then on some random school mornings…I am reminded that I should keep my options open.  School “nutrition” break is at 10:10am.  By 10:15am, I see a bolus come in on Nightscout.  And I think to myself “Huh, I wonder what that will be because I know she didn’t pack a snack today.”  By 10:30am, I see the BGs starting to climb and I wonder how it will go.

Nutrition break is never about quality food.  The things sold by the school for nutrition break usually involve chip bags, mini donuts, twizzlers, and the like.  These snacks are problematic because  (1) we don’t have a lot of practice for these foods because we don’t generally have lots of these particular foods around the house and (2) they are being eaten at a time where she doesn’t have a lot of time or interest in babysitting her BGs or IOB.  Also problematic is that pesky independence that Anna is really quite interested in.  She doesn’t want to tell me what she’s eating, nor does she want to have me telling her how to bolus things much these days.  She will tend to still ask me for input on new food boluses when it’s just the family around…but when she’s around her high school buddies at school?  Forget about it.  So, iteratively improving her bolus techniques for these foods is hard to do given the lack of communication on these snacks.

Anyways, I turned on UAM on Sunday late night with the thought that maybe Anna and I would have some help during those nutrition snacks.  My theory wasn’t that she isn’t bolusing or entering carbs…but that perhaps the carb counting on those snacks was particularly difficult and our desire to keep her independent probably wasn’t going to allow for much improvement on proper carb count/bolus techniques for the snacks. I really do value her growing self-confidence and want to cultivate it by not hovering on every new food and new bolus…but those nutrition snacks test those limits.

I didn’t tell Anna about the new feature, but she must have had that sixth sense because on Monday’s nutrition break…she decided to test it.  My pebble started to alert me around 10:45pm that her BGs had climbed above 130.  When I pulled up NS, there was 50g of bolused carbs entered.  BGs were climbing, but SMBs were started.  I sat patiently as I could.  But, eventually the curiosity got to me when she got to about 180 mg/dl.

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So nice of her to be testing the new feature with exactly the part that I thought it might help with…some random new food that she was completely guessing the carb count on (without me involved).

Things went awesome…I was so impressed.  Somehow the rapid rise from that mini-McMuffin was halted pretty well and the decline back to target was looking smooth.

Screen Shot 2017-05-22 at 11.51.51 AMSadly though…that experiment would have to end early.  Her rig’s battery came loose and looping stopped.  She couldn’t see that the wire had come loose so we just lived out the rest of the day old-school…no looping. (but look at how well those BGs slid in close to target of 90 even after 43 minutes of no looping.  UAM/SMBs sure did estimate that needed amount of suspension pretty accurately from a fair bit ahead of time)

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When she came home on Monday and I suggested that maybe she could run the experiment again…she was more than happy to oblige.  So, today she got the mini McMuffin again and did the same bolus and same carb entry.  Started the meal looking pretty similar to Monday.


The UAM/SMBs worked together to control that peak BG as best as possible…looked good.  I like how even though clearly the sandwich may have been a little different carb count (or her prebolus time was a little longer today?), the loop was reacting well to the BG behavior rather than simply the carb count.


But then I got a little leery when I saw this…was the bottom falling out?


My worries were unfounded.  The loop’s math was solid.  We gently landed pretty much at our target of 90 mg/dl.


I’d say the experiment has been a solid success.  One of the biggest things I notice is the way the loop successfully managed this same meal without prejudice.  What do I mean by that?  It reacted to the ACTUAL BGs that it was seeing really well rather than seeming overwhelmed by strictly the carbs entered.  At the peak BG on Monday, Anna was carrying about 5.34 units of IOB.  At the peak BG on Tuesday, Anna was carrying about 3 units of IOB.  To have both of those peaks resolve close to target without overshooting or needing a low treatment or intervention is pretty impressive.

The question is “If it was UAM that did this, HOW did UAM do this?”  I spent a good portion of the day exploring the answer to that question.  And the answer probably deserves its own post.

There’s a line in the movie Labyrinth where the main character Sarah has an epiphany and says to the evil Goblin King “You have no power over me.”  I feel like I’ve just gotten to say to the snack bar “You have no power over me.”

Doritos are still devilish on BGs compared to a low-carb muffin, but at least the BGs are being handled better than if I stared at them and tried to micromanage with 8 text messages and distractions.  Anna comes home and tells me about the things she did with friends and her homework…no need to discuss how to do the snack bar “better” the next day.  What a freedom.

OpenAPS and hormones and SMB

One of the most commonly asked questions I see is “How does OpenAPS handle periods?”  Well, lucky me!  I happen to have a teenage girl using OpenAPS…and a blog.  And she is open to bribes to allow me to opine on periods and type 1 diabetes in a public settings.

We used autotune previously on our OpenAPS rigs, but ended up disabling it as a part of our normal loop operations*.  I still run it as a once-in-awhile check, but mostly now depend on autosens for making our basal and ISF adjustments.

A quick note:  Autotune runs once per day (shortly after midnight) to create a new “autotune-profile” that your rig will use for the day with basals and ISFs based on the tune it performs.  The degree to which this autotune-profile can differ from the profile stored in your pump is based on the settings you have in your preferences for OpenAPS.  Once that autotune-profile is generated, changes to your pump settings will not affect the loop until autotune runs again at midnight.  And even then, the new pump settings are only a starting point for autotune to use.

The reason we disabled autotune was two-fold…(1) I don’t like being locked into a profile for the whole day necessarily because (2) hormones (or medicine) can cause us some pretty dramatic changes.  It’s not every month that we get hit super hard.  But, certainly sometimes, the swings needed in our pump settings are really more than you could reasonably ask from an automated program. And they happen in the matter of a couple hours or even less.

We switched to using just autosens for helping us with basal and ISF changes.  It has worked TREMENDOUSLY well.  We have numerous times that it has been able to fairly quickly (within 2 hours or less) detect periods of changing insulin needs and kept us steady, even when I wasn’t paying close attention.

But, every once in awhile, those hormones just come on really strong and fast.  More than autosens can control.  Sunday morning was one of those times.  The morning started off nice and steady.  No signs of problems in her basal rates.


But, when she woke up in the morning around 10am, she informed me her period had started.  Which then led to this by lunch time.  No food involved, and that BG was climbing.


When I saw the SMBs start up shortly after a manual bolus and no food…I knew that it was time to take this basal change more seriously.  Those little SMBs are a good visual clue when it’s time to take more action, I love that.  This was our first time going through a hormonal change with SMBs enabled.

The first thing I did was go to autosens to see what it was autosens doing for me.  And I could see that it was trying to help bring down that high by using temp targets…adjusting target down to 80 from 90 mg/dl to help.  Good.  But, it was also Mother’s Day and I was at the movies on a date with my husband.  Kids were home alone, and I left things alone for the rig to watch and do what it could.  No basal adjustments were made manually at that point.


But, by later that evening, it was clear that the period was not going to simply autosens away, this swing was bigger than some of the others we had.  The SMBs were again a useful visual clue that things weren’t settling down, even with a good front loading of insulin. We were holding steady, not coming back to range.


So, we started to make some manual adjustments to basal, and used autosens to “validate”, in a way, our changes.  If we kept seeing no drop in BGs and autosens adjusting stronger…we knew we needed more.  So, we bumped up from 0.8 to 0.85.  And then from 0.85 to 0.90…


In the end, we have adjusted from a basal of 0.8 u/hour to a basal of 1.3 u/hour to keep her BGs steady.  Which actually corresponded to the amount I would’ve guessed on the correction boluses that it was taking to keep her steady (although above target).  It’s taken us almost 24 hours to make those adjustments, moving about 0.05 or 0.1 u/hour increase at a time. (I did them incrementally and watched how the changes behaved before adjusting again.)  I could’ve just jumped to 1.3 u/hour, as it is a basal rate we are used to with periods, but I didn’t want to overshoot and the loop was doing a good job of keeping her reasonably close to range despite needing over 60% more insulin than usual.

Where do we stand now?  Close to 24 hours since the insulin-resistance started…


Looking at her autosens right now, it’s still seeing that 1.3 u/hour isn’t cutting it and is using a 1.55 u/hour (and a stronger ISF).  Which doesn’t surprise me given the recent SMBs needed to keep her in range.


I will just opt to let the rig take care of things for the rest of Anna’s school day before we make anymore changes to her pump settings.  These insulin-resistant parts of her cycle are powerfully strong, and used to be really hard to know what to do with.  But, between autosens’ numbers and SMBs visuals, this was much easier to navigate without stress or high BGs.  Making changes to her basal wasn’t as mentally burdensome as it used to be.  And hooray for SMBs keeping an insanely good job on controlling hormone-related climbs.

And now I have to bribe Anna for the permission to post.