Running and fueling for runs with type 1 diabetes

This blog post is not for you. (Well that sounds mean, doesn’t it? It’s not meant to be mean. But this post is written for a very small subset of people like me who are stumbling around on page 16 of Google trying to find someone sharing experiences and specific details around methods (both successful and less so) for fueling for longer endurance events such as full marathons or ultramarathons with type 1 diabetes. So – please don’t be offended, but also don’t be surprised if you don’t find this post very useful!)

I’ve started running again, and more, this year, and am now to the point where I’m considering running another full marathon sometime next year. As I adventure into running longer distances, and more miles, I’m reflecting on what I did in my first full marathon that worked related to diabetes, and what I want to try to do differently. This post is logging some of my experiences and notes to date, in honor of fellow page-16-of-Google-seekers, rather than waiting til after I run another full (if I do) and there continuing to be not much info out there.

Some background on my running:

I’m not a runner. And not a good runner. I never liked running. But, I walked the Seattle half marathon in December 2012 and thought it might be fun to then walk the full marathon in December 2013. However, I also tried snowboarding for the first time in January 2013 and majorly damaged my knee. I could barely walk the few blocks to work every day, let alone do my normal activities. It took several months, and several PT sessions, to get back to normal. But part of my frustration and pain manifested into the idea that I should recover enough to still walk that full marathon in December. And in order to be off the course by the time it closed, I would need to run a little bit. And I could barely walk, and never ran, so I would need to do some training to be able to run a mile or two out of the 26.2 I planned to otherwise walk. So I set off to teach myself how to run with the idea of walk/running the full, which evolved into a plan to run/walk it, and mostly eventually run it. And that’s what I did.

Now – this marathon was December 2013. This was right when we created DIYPS, and a year before we closed the loop, so I was in full, old-school traditional manual diabetes mode. And it sucked quite a bit. But now, almost 5 years later, with the benefit of everything I’ve learned from DIYPS and OpenAPS about insulin and food timing etc., here’s what I realized was happening – and why – in some of my training runs.

What I worried about was going low during the runs. So, I generally would set a low temporary basal rate to reduce insulin during the run, and try to run before dinner instead of after (to reduce the likelihood of running with a lot of active insulin in my body). I would also eat some kind of snack – I think for energy as well as making sure I didn’t go low. I would also carry a bottle of Gatorade to drink along the way.

With the benefit of 5 years of lots of learning/thinking about all the mechanics of diabetes, here’s what was happening:

Per the visualization, the carbs would hit in about 15 minutes. If I reduced insulin at the time of the run, it would drive my blood sugar up as well, over a longer time frame (after around 45+ minutes as the lack of insulin really started to kick in and previous basal impact tailed off). The combination of these usually meant that I would rise toward the middle or end of my short and medium runs, and end up high. In longer runs, I would go higher, then low – and sip gatorade, and have some roller coaster after that.

Now, this was frustrating in training runs, but I did ok for my long runs and my marathon had pretty decent BGs with no lows. However, knowing everything I know now, and commencing a new burst of running, I want to try to do better.

Here’s what I’ve been doing this year in 2018:

My original interest in running was to set a mileage goal for the year, because I didn’t run very much last year (around 50 miles, mostly throughout summer), and I wanted to try to run more regularly throughout the year to get a more regular dose of physical activity. (I am very prone to looking at Seattle weather in October-December and January-March and wanting to stay inside!) That mileage goal was ambitious for me since I didn’t plan to race/train for any distance. To help me stick to it, I divided it by 12 to give myself monthly sub-goals that I would try to hit as a way to stay on top of making regular progress to the goal.

(Ps – pro tip – it doesn’t matter how small or big your goal is. If you track % progress toward whatever your mileage goal is, it’s really nice! And it allows you to compete/compare progress, even if your friends have a much bigger mileage goal than you. That way everyone can celebrate progress, and you don’t have to tell people exactly what your mileage goal might be. What’s tiny for you is big for others; and what’s big for you may be small to others – and that doesn’t matter at all!)

This has worked really well. The first few months I scraped by in keeping up with my monthly goal. Except for February, when I had three weeks of flu and bronchitis, so I surged in March to finish February’s miles and March’s miles. I then settled back into a regular amount, meeting my monthly goals…and then surged again in August, so I was able to finish my yearly mileage in the middle of September! Wahoo! I didn’t plan to stop there, though, so I planned to keep running, and that’s where the idea of running the Seattle half (always the Sunday after Thanksgiving) popped up again, and maybe a full next year. I started adding some longer runs (two 7.5 miles; a 9.35 miler, and now a 13 miler) over the past month, and have felt really good about those, which has enabled me to start thinking more carefully about what I did last time BG-wise and why this time is so much easier.

Earlier in the year, even on my short runs (one mile or so), I quickly realized that because of the shorter peak of Fiasp, I was less likely to have previous insulin activity drive me low during the run. Within the first handful of runs, I stopped eating a snack or some carbs before the run. I also stopped setting a super high target an hour before my run. I gradually moved into just avoiding >1.5u of insulin on board before short runs; and for longer runs, setting a target of ~110 about 30 minutes before I walked out the door, mostly to avoid any of that insulin activity dosed that would kick in right after I started running. (Keep in mind when I talk about setting targets: I’m using OpenAPS, my DIY closed loop system that does automatic insulin dosing; and for fellow DIY closed loop users, I’m also using exercise mode settings so I can set lower targets like 110 and the targets also automatically adjust my sensitivity and recalculate IOB accordingly. So without those settings, I’d probably set the target to 130 or so.)

And this has worked quite well for me.

Is it perfect? No, I do still go low sometimes..but probably <10% of my runs instead of 50% of them, which is a huge improvement. Additionally, because of having OpenAPS running to pick up the rebound, there’s not usually much of a rebound and resulting roller coaster like I would have in 2013. Additionally, because autosensitivity is running, it picks up within a few hours of any additional sensitivity to insulin, and I don’t have any overnight lows after running. Yay!

However, that all assumes I’m running at a normal-for-my-body or slower speed.

There’s a nice (annoying) phenomenon that if you sprint/run faster than your body can really handle, your liver is going to dump and your BG will spike as a result:

I didn’t ever notice this in 2013, but I’ve now run enough and at varying paces to really understand what my fitness level is, and see very obvious spikes due to surges like this when I’m sprinting too fast. Some days, if I run too fast (even for a mile), I’ll have a surge up to 180 or 200 mg/dL, and that’ll be higher than my BG is for the rest of that 24 hour period. Which is annoying. Funny, but annoying. Not a big deal, because after my run OpenAPS can take care of bringing my down safely.

But other than the running-too-fast-spikes, my BGs have been incredible during and following my runs. As I thought about contributing factors to what’s working well, this is what’s likely been contributing:

  • with a mix of Fiasp & another short-acting insulin, I’m less likely to have the ‘whoosh’ effect of any IOB
  • but I’m also not starting with much IOB, because I tend to run first thing, or several hours after a meal
  • and of course, I have a DIY closed loop that takes care of any post-run sensitivity and insulin adjustments automatically

As I thought more about how much I’ve been running first thing in the morning/day, and usually not eating breakfast, that made me start reading about fasted long runs, or glycogen depleted runs, or low carb runs. People call them all these things, and I’m putting them in the post for my fellow page-16-of-Google-seekers. I call it “don’t eat breakfast before you run” long runs.

Now, some caveats before I go further into detail about what’s been working for me:

  • Your Diabetes May Vary (YDMV). in fact, it will. and so will your fitness level. what works for you may not be this. what works for you will probably not work for me. So, use this as input as one more blog post that you’ve read about a potential method, and then tweak and try what works for you. And you do you.
  • I’m not doing low carb. (And different people have different definitions of low carb, but I don’t think I’m meeting any of the definitions). What I’m talking about is not eating breakfast, a snack, or a meal before my runs in the morning. When I return from runs, I eat lunch, or a snack/meal, and the rest of my day is the usual amount/type of food that I would eat. (And since I have celiac, often times my gluten free food can be higher carb than a typical diet may be. It depends on whether I’m eating at home or eating out.) So, don’t take away anything related to overall carb consumption, because I’m not touching that! That’s a different topic. (And YDMV there, too.)
  • What I’m doing doesn’t seem to match anything I’ve read for non-T1D runners and what they do (or at least, the ones who are blogging about it).

Most of the recommendations I’ve read for glycogen depletion runs is to only do it for a few of your long runs in a marathon training cycle; that you should still eat breakfast before a full marathon; and you should only do fasted/glycogen depletion for slow, easy long runs.

I’m not sure yet (again, not in a full marathon cycle training), but I actually think based on my runs to date that I will do ok (or better) if I start without breakfast, and take applesauce/gatorade every once in a while as I feel I need it for energy, and otherwise managing my BG line. If I start a downtick, I’d sip some carbs. If I started dropping majorly, I’d definitely eat more. But so far, managing BG rather than trying to prescriptively plan carbs (for breakfast, or the concept of 30-60 per hour), works a lot better for me.

Part of the no-breakfast-works-better-for-me might be because the longevity of insulin in your body is actually like 6 hours (or more). Most non-T1D runners talk about a meal 3 hours before the start of your race. And they’re right that the peak and the bulk of insulin would be gone by then, but you’d still have a fair bit of residual insulin active for the first several hours of your race, and the body’s increased sensitivity to that insulin during exercise is likely what contributes to a lot of low BGs in us T1 runners. There’s also a lot of talk about how fasting during training runs teaches your body to better burn fat; and how running your race (such as a marathon) where you do carb during the race (whether that’s to manage BGs or more proactively) will make your body feel better since it has more fuel than you’re used to. That’s probably true; but given the lower insulin action during a run (because you’ve been fasted, and you may be on a lower temp basal rate to start), you’re likely to have a larger spike from a smaller amount of carbs, so the carb-ing you do before or during these long runs or a marathon race may need to be lower than what a non-T1D might do.

tl;dr – running is going better for me and BG management has been easier; I’m going to keep experimenting with some fasted runs as I build up to longer mileage; and YDMV. Hope some of this was helpful, and if you’ve done no-breakfast-long-runs-or-races, I’d love to hear how it worked for you and what during-race fueling strategy you chose as a result!

Another kids book by @DanaMLewis – this time about celiac disease

When I wrote my first book for kids about diabetes devices, I had an idea that I might write more kids books for my nieces and nephews. While my first book was inspired by a verbatim conversation with my niece, my next book is inspired instead by a cute story of my nephews, combined with a burst of frustration about living with celiac.

This new book, “Parker’s Peanut Butter”, wrote itself in my head while I was on a trip in Germany. The hotel I was staying at, despite many early communications about needing safe, gluten-free food, did not get gluten free at all. Being told “this dish is ‘usually’ gluten free” was incredibly frustrating. That night, I began drafting this story to help explain celiac – and cross-contamination – to kids.

The next day, with the book top of mind, I was at a meeting where artists had been hired to help document and crystallize some of what was happening at the meeting. I had seen some live illustrators before document various sessions at conferences, but these two artists were in a class of their own. They did such an amazing job capturing the key themes, quotes, and their illustrations were simple yet effective – and incredibly quick on the spot. I was in awe. I had an idea that wow, if someone like them would illustrate my next book, it would probably be fairly simple for them to do two dozen illustrations. (And yes – I know it is their incredible skill and artistry that makes it possible for them to do “quick” and “simple” yet incredibly powerful illustrations!) But, this is a zero-budget project: for every two books purchased, that yields enough for me to purchase an author-priced copy to donate to hospitals, libraries, school libraries, etc. I knew there was a really slim chance that other artists would be interested in contributing art to my book. (My amazing aunt was gracious enough to illustrate my first one! <3) However, you never get a yes if you don’t ask. So I crossed my fingers and approached the artists, explaining the project and showing them my first book. They seemed at least open to the possibility, so I promised to email and follow up after I got home. I emailed when I got back, and Beatrice said yes to illustrating! I was thrilled. And so “Parker’s Peanut Butter” came to fruition.
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As of today, the book is done and available on Amazon here! (Note: that’s an affiliate link, as are the other links to my books from DIYPS.org)

Like my other book, there is no ‘profit’ – I’ve priced it so that every two purchases on Amazon will fund an author-priced copy that I will donate to libraries, etc. (And if you’d like to coordinate directing a donation of 10 or more books in a batch somewhere, let me know!)

The story about the peanut butter and the hot tub is true (which I think is/was hilarious). I combined it, though, with a conversation I had with Parker about celiac from one time when he wanted to know why I wasn’t eating the other pizza on the table.

Like the diabetes devices book, I used simple tools (Microsoft Powerpoint!) to lay out the book and CreateSpace to publish it. (You can read here about the exact process I took to create & publish the book). I hope this inspires others to consider writing & creating more books with characters living with chronic conditions like diabetes, celiac, food allergies, and more to have diverse representation of the challenges we all live with.

PS – if you’re an artist & interested in helping illustrate a future book, please let me know! I’d also love to hear what stories & perspectives you’d love to see in future kids books, if I write more.

Hormones, CGM preferences, DIY, and why so many things are YDMV even when #WeAreNotWaiting

I posted one of my Nightscout graphs yesterday, showing a snapshot of my morning:

I hadn’t eaten, and my blood sugar still spiked up. I’ve noticed this happens in the mornings sometimes. When I have mentioned it over the years, people are quick to tell me my basal rates are wrong, and I should adjust them because dawn phenomenon. But actually, this isn’t dawn phenomenon. This happens after I physically get up and start moving for the day, whether that happens at 4am, or 6am, or 10am, or even waking up after noon. So, it’s not a basal thing, and modifying my basal rates doesn’t fix it. (And this is why I wanted to add wake-up mode to my suite of tools, to help address this.)

To me, this is a great example, (as I mentioned in my Twitter thread), of why diabetes is so hard: sooooo many things impact BG levels, and in many cases, we PWDs just have to roll with it and respond the best we can. In my case, #OpenAPS did a great job responding to the spike and bringing me back down within an hour or so.

One of the questions that popped up yesterday in response to that graph, though, was about the BG line: how did I have two BG lines?

The answer: I wear a G4 sensor, and usually have 2 receivers running off the same transmitter and sensor. One receiver is Share-d to my phone, and uploads to NS via the interwebz. The other receiver, although Share-capable, doesn’t (because the company only allows you to pair one receiver and upload via Share). I leave that CGM plugged into a rig to enable it to be a backup for offline looping. When online, this rig with the plugged in CGM uploads BGs from that receiver to NS.

Sometimes, because of different start/stop times and therefore differing calibration records, the receivers “drift” from each other, making it obvious on the graph when that happens.

Because if you give a mouse a cookie, other questions come up, someone had also asked me why I’m using G4, and why not G5. Someone else asked me in a different channel why I’m not using G5 and xDrip+ (a DIY option that doesn’t use Dexcom app or a Dexcom receiver for receiving the data or processing it), or another DIY tool to process my CGM data.

Now, as always, what I chose to use is my personal preference. It’s colored by my preference for what equipment I’m willing to carry; what phone I want to use; what data I want to have; my safety backup preferences; what my insurance covers and what I can afford; where I live; etc. So, just because I use this method, doesn’t mean I expect anyone else to want to do it. It’s just what I do. I don’t try to convince other people to use this method, and I also hope others can share info about what works for them without trying to hammer me over the head because what I’m doing is different. This is where YDMV (your diabetes may vary) comes in. It’s so true, and even within “people who DIY”, there’s a ton of variation – and that’s a good thing! I adore having options to find what works for me, and I want to have other people have options and choices to choose what works for them.

That being said, here’s the answer to how I run my CGMs and some of the things that have factored into my choice to not DIY CGM receivers/data processing most of the time:

  • With two G4 receivers, I can keep one in my pocket, paired to my phone and uploading via Share. When I’m out and about in the city or usually during the day, this is what I carry. When I run, I take the Share receiver.
  • But, I also like emergency back-ups. I like keeping a receiver plugged into an #OpenAPS rig so that if connectivity goes out/down, I can keep looping without a break in my stride. So, I could keep my Share receiver plugged into the rig, but that would involve me unplugging and replugging fairly frequently when I run errands or actually go for a short run, and meh. Hassle. So I keep “non-Share” receiver as the one that’s usually plugged into my ‘offline’ rig.
  • Having the G4 receiver plugged into the rig enables me to see raw data. Raw data is nice for a couple of things: assessing the health of my sensor (if it gets jumpy compared to the filtered data, I know the quality of the sensor is decreasing, and that helps me decide when to change it); giving me a clue to what’s going on when the filtered data goes to ??? or during the start up of a new sensor; and actually being able to run my rig and loop off some* of the raw data when I need to. (*With OpenAPS, you can choose to loop off of it within a certain range, and there’s an option to only set a certain amount of correction for a proportion of what otherwise would be proposed, with a higher level of raw data.)
  • With two receivers running, that also gives me more flexibility around sensor changes. Technically, the sensor is approved for 7 days. At the end of the 7 days, the receiver stops giving you data and forces you to “start” a new sensor session. That could be by inserting a new sensor; or it could be the same sensor on your body. But either way, theoretically it’s a 2 hour ‘warm up’ period from that session where you can’t see data. With 2 receivers, I can stagger the end and start of sensor sessions. I usually set a calendar alarm to restart one of the receivers on the night of the 6th day of the session, allowing me more flexibility on day 7 to choose when to restart or change my sensor.
  • This also means I can choose to “hot swap” when actually changing a sensor. I may choose to not hit ‘stop’ and ‘start’ on a sensor session on one of the receivers, but rather shut it off for about 30 minutes, and just do the stop/start on the other receiver (leaving it plugged into a rig to upload raw data to NS, and be able to see where the new sensor’s readings come in compared to the old one). When I power the non-restarted receiver back on about 30m after swapping the transmitter over to the new receiver (as soon as the raw readings have flattened out), it usually either goes to “no signal” for a few minutes, and then comes back with some data, an hour or more before the restarted sensor allows me to calibrate it and get data. There are downsides to this method: the data on the receiver that didn’t get restarted can be fairly inaccurate, as it’s still using the calibrations from the old sensor. So I don’t always do that, but when it’s more important to me to be able to see relative trend of where BG is (flat, or dropping or spiking), it’s nice to have that option. And since I often soak my new CGM sensors, the data from “day 1” of the sensor after a session “start” on the receiver is often better than if it was truly day 1 of the sensor being in my body.

Phew. Maybe that sounds like a lot of work, but the above setup works well for me for a variety of reasons, and also allows me the flexibility and choice for when I change sensors, when I am forced to be without data or potentially not loop, etc. Given that my schedule varies a lot, it helps since I’m not consistently in the same time zone and what works for starting or changing sensors one week in one part of the world doesn’t always align with convenience exactly 168 hours (7 days) later in another part of the world that I’m in, doing something differently.

Some of the reasons I haven’t switched to G5 include the fact that the transmitters only last for ~3 months instead of 6+ months; I’ve observed many people being frustrated by sensor not talking to the phone even when it’s right beside them; there’s no raw data on G5; you can’t have multiple receivers paired with your transmitter; etc.

Now, you might say, but that’s using Dexcom’s app, etc. With DIY solutions, those limitations don’t apply! And that’s true, to a degree – savvy folks in the community have figured out how to make it so you don’t *have* to use Dexcom’s app to display or process the data; you can replace the batteries on the transmitter; etc. But, just like my method above of using raw data isn’t necessarily going to work for everyone or might not be something someone else choose to do, the DIY options that go with G5 (or even G4 in some cases), aren’t something I believe is the right thing to do for me.

A lot of it comes down to safety. When we first started designing my DIY closed loop, we spent eons discussing how we could do this safely for me. And that evolved into further discussions about how other people could do this safely, too. A core of the OpenAPS Reference Design is that we are using already approved and vetted devices that exist on the market (e.g. existing pumps and CGMs). Those devices include approved and vetted methods for CGM data processing, too, which is even more important when the CGM data is being used to dose insulin as in OpenAPS. Now – this is not a requirement we can enforce: people can do what they want, and some people are even using non-CGMs (such as the Libre, a “Flash Glucose Monitoring” solution, plus a DIY NFC reader) as a CGM source for looping. But, whether it’s a DIY app or algorithm on CGM data, or a different glucose measuring device that’s not a CGM, that’s choice has some safety implications that I hope people are aware of.

First, the background for those who aren’t familiar: the CGM companies display a processed (“filtered”) version of the CGM data. That’s part of their proprietary stuff, but there’s reasons behind it: the raw data can be hectic and weird, and individual readings aren’t the point, anyway. The beauty of CGM is you can see the trends in addition to the estimated BG number.  In some scenarios, such as during sensor starts, during error messages that are displayed as ???, etc, the companies/FDA decided that the CGM should not show data, and instead show an error message/symbol, to help prevent anyone from making incorrect treatment decisions based off of confusing or misleading data.  That’s good enough most of the time.  As mentioned above, there are edge cases when seeing the raw is helpful, but most of the time, I’m happy with the filtered data.

But to me, there’s a difference between using raw or DIY-calibrated data for edge cases, vs. using them all the time. I’ve seen several cases in just the past few days with a newer “DIY CGM app”, which uses its own calibration algorithm for processing the unfiltered CGM readings.  These people have reported the app displaying normal BGs (say, 90 mg/dL), while they found themselves in the 40’s (rather low). It’s not clear whether that is due to the app’s calibration algorithm, something the user did in testing and calibrating, or if it’s just a bad sensor, and since most of them are not using the official receiver/app in parallel, that’s difficult to figure out.  But regardless, it’s happened enough times across numerous people for me to be concerned about a DIY CGM app being used as the primary source of CGM data. There are limitations to using company-built apps or physical devices for CGMs, but in the case where people can afford it, for safety I think it is important to at least use the approved and vetted receiver/app in parallel, to provide a backup and baseline level of alerting and alarming. The FDA & the companies have worked to create something that can be reliable for alarming when your BG is actually low (say <55 mg/dl) and alerting a human that something is going on. This is important regardless of whether people are looping or not, but it’s perhaps even more important when people are looping, since that data is driving insulin dosing decisions. Additionally, the company-created devices have been designed to deal with miscalibrations that aren’t in line with what the data from the receiver is showing, and have safety measures in place to “reject” calibrations and request new ones when necessary. Sure: there are times where that’s frustrating, but those features truly are “there for safety”, and are important for avoiding the rare but potentially serious outcomes that could be caused by incorrect CGM readings. Since safety is what we prioritize and design around in DIY closed looping, I hope people will consider that ,and prioritize safety first when choosing what to use as their primary data source.

Tl;dr – YDMV. I currently use G4 with two receivers, for the reasons described above. I think it’s important to prioritize safety over convenience most of the time, and understand the limitations of the solution that you choose (DIY or commercial). But everyone’s different, and their situation, preferences, etc. may drive different decision making. And did I mention YDMV?

Vitamin D and insulin sensitivity

tl;dr – for me, Vitamin D hugely influences insulin sensitivity.

After the flu, I continued to be sick. We did the usual song and dance many people do around “hey, do you have pneumonia?”. Which, luckily, I didn’t, but I was still pretty sick and my after visit summary sheet said bronchitis. Also, my average BGs were going up, which was weird. After all, when I had the flu, I had spectacular BGs throughout. So I was pretty concerned when my time in range started dropping and my average BG started rising.

In diabetes, there are a lot of things that influence BGs. It can be a bad pump site; a bad bottle of insulin; stress; sickness; etc etc. that causes out of range BGs. Most of these are helped by having a DIY closed loop like OpenAPS. So, when your BGs start to rise above (your) normal and stay there, it’s indicative of something else going on. And because I was sick, that’s what I thought it was. But as I continued to gradually heal, I noticed something else: not only were my BG averages continuing to rise (not normal), but I also was needing a lot more insulin. Like, 20-30u more per day than usual. And that wasn’t just one day, it was 4 days of that much insulin being required. Yikes. That’s not normal, either.

So, I was thinking that I was hitting the Fiasp plateau, which made me really sad. I’ve been using Fiasp for many months now with good results. (For those of you who haven’t been tuned into the diabetes community online, while many people like Fiasp because it’s slightly faster, many people also have experienced issues with it, ranging from pump sites dying much faster than on other insulins; having issues with prolonged high BGs where “insulin acts like water”, etc.) But, I was prepared mentally to accept the plateau as the likely cause. I debated with Scott whether I should switch back to my other insulin for 2-3 sites and reservoirs to give my body a break, and try again. But I was still sick – so maybe I should wait until I was not clearing gunk out of my lungs. Or I was also pretty convinced that it was correlated with my absolute ZERO level of activity. (I had some rising BG averages briefly over Christmas where I was fearing the plateau, but turns out it was related to my inactivity, and getting more than zero steps a day resolved that.) I knew I would be moving around more the next week as I gradually felt better, so it should hopefully self-resolve. But making changes in diabetes sometimes feels like chicken and egg, with really complicated chickens and eggs – there’s a lot of variables and it’s hard to pin down a single variable that’s causing the root of the problem.

One other topic came up in our discussion – vitamin D. Scott asked me, “when was the last time you saw the sun?”. Which, because I’d been sick for weeks, and traveled for a week before that, AND because we live in Seattle and it’s winter, meant I couldn’t remember the last time I had seen the sun directly on my skin. (That sounds depressing, doesn’t it? Sheesh.)

So, I decided I would not switch back to the previous insulin I was using, and I would give it some time before I tried that, and I would focus on taking my vitamin D (because I hadn’t been taking it) and also trying to get at least SOME activity every day. I took vitamin D that night, went to bed, and….

…woke up with perfect BGs. But I didn’t hold my breath, because I was having ok nights but rough days that required the extra 30 units of insulin. But by the end of the day, I still had picture-perfect BGs (my “normal”), and I was back to using my typical average amount of insulin. PHEW. Day 2 also yielded great BG levels (for me, regardless of sickness) and around average level of insulin needed for the day time. Double phew. Day 3 is also going as expected BG and total insulin usage wise.

You might find yourself thinking, “how can it be as simple as Vitamin D? There’s probably something else going on.” I would think that – except for I have enough data to know that, when I’m vitamin D deficient, getting some vitamin D (either via pill or via natural form from sunlight) can pack a punch for insulin sensitivity. In 2014, Scott and I went out in February even when it was cold to sit in a park and get some sunshine. After about an hour of sitting and doing nothing, with no extra insulin on board, WHOOOSH. I went mega-low. I’ve had several other experiences where after being likely vitamin D deficient, and then spending an hour or so in sunlight, WHOOSH. And same for when there was no sunlight, but I took my vitamin D supplements after a while of not taking them. And no, they’re not mixed with cinnamon 😉 (That’s a diabetes joke, cinnamon does not cure diabetes. Nothing cures type 1 diabetes.)

So tl;dr – my insulin sensitivity is influenced by vitamin D, and I’ll be trying to do a better job to take my vitamin D regularly in the winters from now on!

Making changes in diabetes is hard by DanaMLewis

Women in open source make a difference

I was incredibly honored to find out that I had been nominated for the 2018 Women in Open Source award (and even more blown away to learn that I am one of the finalists). I wasn’t familiar with the award, and when I looked it up to learn more about it, the finalist list for the last few years gives me some serious imposter syndrome! Aside from that, there were a few things that caught my eye – and one of them was a citation from a study that found that only 11% of people contributing in open source are women.

To me, this number both makes sense, and doesn’t.

Why it makes sense (to me): open source can be hard on women.

I’ve been doing things in open source since 2014, falling into it because of DIYPS and because of getting to know people like Ben who are passionate open source advocates. Because I was helped by open source work, it was a key driver for my own passion behind making our work with OpenAPS open source, and is why I’m currently working on developing a series of open source tools to help researchers working with diabetes data. I don’t know that I would have done anything open source had I not found the perfect series of projects that led me there.

While there are many great people in the diabetes open source community, in the middle of 2014 I wrote this blog post about being female and being discounted. It was a hard post to write. But I felt it was important, because one of things both Scott and I noticed is a lot of the attitudes behind this seemed to be subconscious: directing technical questions about our project to Scott only; refusing to direct any substantial questions to me even after Scott specifically would redirect questions to me, etc. The only way I saw to (begin to) deal with the problem was to address it head on.

And, for me, things have improved with time. But it hasn’t gone away, and it still requires active addressing about once a month or so. And yes – these are (relatively) minor problems compared to what some women experience in open source, or in tech. But it’s some of the most common, frustrating friction that can easily drive women away when they get tired of experiencing stuff like that. And when they go away, it’s a loss for everyone.

Why this number doesn’t make sense (to me): women contribute incredible value to open source, and are high-volume contributors, especially if you look beyond the narrow definition applied to open source coding.

Every where I turn, I see women participating in open source. I see Kate Farnsworth and Christine Deltrap, two incredible individuals who have made watchfaces used by thousands of families to remote monitor their children’s blood sugars. I see Katie DiSimone, who has written hundreds of lines of documentation, and answers hundreds of technical troubleshooting questions across several channels. I see Mad Price Ball, who leads the Open Humans Foundation with open source work (*and* is an amazing mentor to women like me, who have non-traditional development backgrounds). I see Karen Sandler, a fierce advocate for making software open source, who herself is a finalist for the WOS award, too!

I also see a lot of my own contributions in open source, especially in the early days when Scott was the one doing most of the committing to Github for the tools we were building. Those were part of why I was told I was discounted in 2014, because my work didn’t “count”. Today when someone goes and looks at Github, if they look at the wrong toolkit (or just one, for example), it gets said that “Dana didn’t do anything on OpenAPS”. (Heh).

So I know there are also other women out there whose work is being overlooked when counting who’s doing open source. However, this type of work is absolutely crucial to open source projects, and these contributors drive an incredible amount of value. I’m glad the Red Hat Women in Open Source Awards site acknowledged this, and made this list:

  • Code and programming.
  • Quality assurance and bug triage.
  • Involvement in open hardware.
  • System administration and infrastructure.
  • Design, artwork, user experience, and marketing.
  • Documentation, tutorials, and other communications.
  • Translation and internationalization.
  • Open content.
  • Community advocacy and community management.
  • Intellectual property advocacy and legal reform.
  • Open source methodology.

The list was partially to help encourage people to nominate women; and also to help women to recognize all of the activities they do that’s open source. And it was helpful to me, too. Because of that list, instead of a handful of key examples of open source activity by women, I can instead name dozens of women. I bet you can, too. There’s so much incredible open source activity and value that happens in places outside of commit history, and if we want to recognize and acknowledge the work of everyone in open source communities, we should do a better job of acknowledging *all* of these types of activities and not just recognizing individuals (male or female) who have a traditional code-based commit history.

So if you’re reading this, it’s likely you’re a supporter of women in open source communities. Thank you for that! But I’d like to ask you to do two specific things.

1) Actively recognize the women working with you in open source. The internet can be a hard place to be, let alone work, when you are female. Help lift women up; recognize their work; and help them grow their skills.

2) Ok, this one is optional :) But if you’ve read all this way, you might consider clicking here and going to the Women in Open Source Awards site and voting for one the finalists in each category. It’s one vote per email address. Thanks!

Acknowledging all contributions in open source by DanaMLewis

Makers gonna make…a book about diabetes devices? Kids book written by @DanaMLewis

book inspirationLast year after Christmas, I was running around my parents’ backyard with my niece when she spotted my CGM sensor on my arm and asked what it was. I’m always struck when my niece and nephews have noticed my diabetes devices, and am interested to see what “new” humans think about and how they encounter things and what they mean. In this case, I explained the CGM and we went back to running around, but it stuck in my mind for a few days.

I also remember the excitement and attention any time a kids’ book has a character with diabetes in it, or a storyline of diabetes, because there’s just not much out there. I was diagnosed at 14, but I love seeing PWDs in the wild and like the idea of more diabetes inclusion in materials for all ages.

So, I wrote a kids book, with the goal of introducing the concept of diabetes devices and more broadly, how people are different in different ways. I talked my incredible artist aunt into illustrating this book. :)

This book is primarily for me and my niece and nephews, but I know there might be a few other people who like the idea, too (even as there may be a few people who sniff at the idea*). I investigated the publishing options and decided to go with self-publishing, which would allow for:

  • The cheapest copies for me as the author, to be able to give to my various family members who want them.
  • The ability to make it available to other people who want copies.
  • The ability to price said copies so it’s accessible and reasonable to order easily.
  • (It’s actually cheaper for you to order this on Amazon directly to your house, than it is for you to ask me for an author-priced copy and for me to go through the hoopla of getting it to ship.)
  • Every two copies purchased via Amazon yields an author-priced copy that I plan to donate to libraries, hospitals, etc. (If you’d like to sponsor 10+ books for a library system, feel free to ping me about the easiest way to do that.) I’m planning to use any “profits” from the book to pay for copies that I’m donating.

I’ve been working on it off and on for the past few months as my aunt illustrated it, and got to give a copy to my brother and niece as a total surprise to read when we were in Alabama this past weekend. So now that the cat is out of the bag, the book is available online! The book, “Carolyn’s Robot Relative” (that’s me!), is available on Amazon here (note that’s an Amazon affiliate link). (There’s also now a German-translated copy with the title, “Ist Carolyns Tante ein Roboter?” – see the German version on Amazon.de here!)

robot illustration @DanaMLewisI also *love* the robot illustration that my aunt made with the CGM as the main body of the robot.  I reached out to someone on Etsy who does custom “stuffies” – and it turns out, she has a diabetes connection, too! So, you can get a stuffed CGM robot if you or your kids like it, for $20. Here is the link to the listing on Etsy. (I don’t make any money from this; I paid $20 for my first one, but had worked with her on pricing so it would be reasonable for people to get if they liked it!)

CGM robot stuffy from Carolyn's Robot Relative by DanaMLewisCGM robot stuffy from Carolyn's Robot Relative by DanaMLewisThe stuffy with the book – it’s an awesome sized stuffy!

And because I have also been playing with code fabric on Spoonflower (see tweet thread here, or this blog post here) and know they do fabric as well as gift wrap…I uploaded the CGM robot there so I could turn it into wrapping paper, too. Here’s the link to see it on Spoonflower.

CGM robot giftwrap preview! available on Spoonflower as fabric, gift wrap/wrapping paper, or wallpaper

I learned a lot in the research process about self-publishing options and the route I took that I wanted to share here, especially for anyone who sniffs and goes troll on me about putting this out there.

*Tl;dr – self-publishing is easy, and if you don’t like my book, go make a better one yourself! :) The more books, the better!

Some background on the publishing process & how I made the book:

I chose self-publishing with CreateSpace on Amazon. They now have this new “Kindle Direct Publishing” (KDP) program that’s similar, but less tested than CreateSpace, and seems to be higher cost for author copies. I never figured out what the benefits are of that, and chose CS.

I generally Google’d a bunch of questions and ended up on the CS forums, too, and read up on different programs to use to create the book, etc.

My process:

  • I wrote the book test in Microsoft Word, then translated it into a Google spreadsheet so I could visualize the left/right layout of the flow of text, as well as start to identify where I had ideas about what images to use.
    Example_storyflow_spreadsheet_Dana_Lewis
  • My aunt began illustrating, and sending me pictures. Fun fact – all of the images in the book are put in via iPhone photos -> AirDrop -> my computer -> inserted! No fancy graphics. (Although I did open a few of the images in Preview and change the white balance, since each photo was taken in different lighting, in a weak attempt to balance the colors of the pictures side by side.)
  • I started dropping them into a Microsoft Word document. The one thing the CS forums warned about was making sure the images were high enough res. The images were…but later in the upload process, it complained about the DPI being low. I switched to Microsoft PowerPoint (doing the same thing I did in Word to create the custom page size to work with bleed, trim, etc.) and dropped the images in the same way, and PPT doesn’t compress the images and it was fine. Word was problematic. It didn’t take much time to switch back and forth, but if I did it again, I’d start with PPT because they generally seem to get that images need to be full sized.
  • (A workaround if you take screenshots and need to insert images – you can use Preview to go in and adjust the size and make it >300 DPI that CS prefers, before inserting the images into PPT).
  • I placed text boxes on top of the images.
  • Once done, I saved as a PDF, and then went to upload to CS. I uploaded and tweaked and viewed the Digital Proofreader tool about a dozen times the first day I did it, as I wanted to move text a tad up or down, and as I resolved the complaints about DPI not being great.
  • (You do the same process for the cover image, and CS is pretty good about telling you how to calculate your spine size for the number of pages in the book, and adding that in to the front/back cover size to calculate what you need. You can also get a sized template from them, and then use images and cover it up so it’s sized perfectly.)
  • Once you’re happy with what’s uploaded to the system, you submit to CS for review (takes 24 hours). You then get to review another digital proof, and a PDF version, and then get the chance to order a physical proof copy!

Tl;dr version 2 – it was actually super easy, even for someone who’s not a graphic designer, to do this. This was a great method to work with an illustrator with simple iPhone photos of awesome illustrations and turn them into a book. You could probably also scan and do all kinds of fancy stuff…but for a basic book, the basic process described above works great. It actually doesn’t take much time in terms of placing text or uploading and tweaking your file.

The hardest part was calculating the size of the pages and deciding on whether to do with bleed or without bleed.

The other hardest part was keeping the topic of the book a secret from my mom for 10 months, because I thought she’d get a bigger kick out of being surprised with the book’s topic and contents when she had a finished copy in her hands. Sorry, Mom! Hopefully you thought it’s worth it. :)

front and back of "Carolyn's Robot Relative" by @DanaMLewis

More open innovation coming soon?

This is a big deal: JDRF just announced funding for companies to open up their device protocols, with an explicit mention of projects including OpenAPS.

This is something we’ve been asking companies for over many years, but even the most forward-thinking diabetes device companies are still limiting patients to read-only retrospective access to the patient’s own data. That’s a start, but it isn’t enough.  We need all device makers to take the next step toward full and open interoperability: participating in open-protocol development of pumps and AP systems. If funding from a major organization like JDRF is what will be needed to prioritize this, great: we’re really excited to see them doing so.

Many of us in the diabetes community have chosen to accept the risk of a flawed device, because of the net risk reduction -and quality of life improvements – that come from being able to DIY closed loop. But that doesn’t mean we’re 100% happy with that.

  • We shouldn’t have to bandaid our pumps – literally – with tape.
  • We shouldn’t have to buy them second hand.
  • We should be able to use in-warranty devices that aren’t physically broken.

In order to use our medical devices in the safest and most effective way possible, we need the ability to remotely and safely control our devices – and understand them – as we see fit.  That means the makers of the medical devices we rely on need to openly document the communications protocols their devices use, so that any informed patient, or any company or organization operating on their behalf, can safely interact with the device.

It’s a big deal for JDRF to put resources into helping companies figure out how to do this, and ease liability and regulatory concerns. Thanks to everyone who’s been a vocal advocate in the DIY community; in organizations like JDRF; and individuals advocating at the medical device companies as well.  And props to the FDA, who last month released official guidance encouraging device makers to “design their devices with interoperability as an objective” and “clearly specify the relevant functional, performance, and interface characteristics to the user.”

We all have the same goals – to make life better, and safer, for those of us living with type 1 diabetes. I’m excited to see more efforts like this that further align all of our activities toward these goals.

To the diabetes device companies: we’ve long said we are happy to help if you want to figure out how to do this. Hopefully, you already have ideas about how to do this smartly and safely. But if you need help, let us know – we’re happy to help, because #WeAreNotWaiting and neither should you.

 

How I change pump sites

Last year, I wrote about how I “pre-soak” CGM sensors for better first-day BGs. That’s something I started doing years ago whenever possible.

Similarly, in the last few years, I’ve also changed how I change my pump sites with similar goals of improved outcomes, whenever possible.

What I used to do (i.e. for 12+ years):

  • Pull out pump site
  • Take shower
  • Put in new pump site
  • If the pump site didn’t work, spend all night high, or the next hours high while I debated whether it was just “slow” or if I needed a second new site. Ugh.

What I decided to start doing and have done ever since (unless a site gets pulled out by accident):

  • On day 3 when I decide to change my pump site, I do not take my “old” pump site out before my shower.
  • After my shower, I leave in the old pump site and put the new pump site on. Which means I am wearing TWO pump sites.
  • Put the tubing on the new site etc. as expected. But because I have the old site on, if I start to see BGs creep up, I can do one of two things:
    • 1) Swap tubing back to old site, give a bolus or a prime on the old site, then switch tubing back to new site. (I do this if I think the new site is working but “slow”)
    • 2) Swap tubing back to old site, ditch the new site, and then insert a second “new” site (or wait until the next morning to do so when I feel like it)
  •  Otherwise, if BGs are fine, I pull the “old” site out once I confirm the new site is good to go.

Is this method perfect? Nope. Does it usually help a lot when I have a new site that is kinked or otherwise a dud? Yup.

To me, it’s worth keeping the old site on for a few (or even ~12) hours. I know many people may not like the idea of “wearing two sites”. But it’s not wearing two sites for 3 days. And if you find yourself having a lot of kinked sites – that’s why and when I switched over to this approach.

YDMV, always. But hope this (post-soaking?) of pump sites, like the idea of pre-soaking CGM sensors, is helpful to someone else.

Why a non-academic (patient) publishes in academic journals

Today I was able to share that my Letter to the Editor was published in the Journal of Diabetes Science and Technology. It’s on why we need to set expectations to help patients successfully adopt hybrid closed loop/artificial pancreas/automated insulin delivery system technology. (You can read it via image copies in the first link.)

JDST_screenshot_LTE_expectationsI’ve published a few times in academic journals. Last year, Scott and I published another Letter to the Editor in JDST with the OpenAPS outcomes study we had presented at the 2016 ADA Scientific Sessions conference.

But, I’m sure people are wondering why I choose to do so – especially as I am 1) a patient and 2) a non-academic. (Although in case you missed it – I’m now the Principal Investigator on a grant-funded study!)

While there are many healthcare providers, researchers, industry employees, FDA staff, etc. who read blogs like this and are up to speed on the bleeding edge of diabetes technology… there are easily 10x the number that do not.

And if they don’t know about the existence of this world, they won’t know about the valuable lessons we’re learning and won’t be able to share those lessons and knowledge with other healthcare providers and the patients that they treat.

So, in my pursuit to find more ways to share knowledge from our community with the rest of the diabetes community, this is why we submit abstracts for posters and presentations to conferences like ADA’s Scientific Sessions. Our abstracts are evaluated just like the abstracts from traditional healthcare providers (as far as they can tell, I’m just another academic, albeit one with fewer credentials ;)), and I’m proud that they’re evaluated and deemed worthy of poster presentations alongside mainstream researchers. Ditto for our written publications, whether they be letters to the editor or other types of articles submitted to journals and publications.

We need to find more ways to share and distribute knowledge with the “traditional” medical and academic research world. And I’d love to do more – so please share ideas if you have them. And if you’re someone who bridges the gap to the traditional world, I appreciate your help sharing these types of articles and conversations with your colleagues.

What I wish CDEs (diabetes educators) and other HCPs knew about DIY and other diabetes tech (#OpenAPS or otherwise)

I had the awesome opportunity to present at #AADE17, the annual education meeting for the American Association of Diabetes Educators, this past weekend. My topic was about OpenAPS and DIY diabetes… which really translates to some broader things I want all educators and HCPs to know about patients and technology, whether it’s DIY or just unknown to them. Unfortunately AADE didn’t record or livestream my session, so I wanted to write up a summary of the content here.

(If you’re new to this blog/me/OpenAPS, you can also watch this June 2017 TEDX talk where I share some of the story of how I ended up with a DIY artificial pancreas and how the OpenAPS community came to be; or this older talk from OSCON 2016 as well. As always, if you’re curious to learn more about OpenAPS or wondering how to build your own DIY artificial pancreas, OpenAPS.org is the first place to learn more!)

Diabetes is hard. Even if you are privileged to have access to insulin, education, and technology – it can still be so incredibly hard to get it right. And even if you do everything “right”, the outcomes will still vary. And after all, the devices themselves are not perfect, and we still have diabetes.

The lack of varying alarms and the unchangeable volume is what led me to create DIYPS (my open loop and louder alarm system), and the same frustration with lack of data access and visualization led John Costik, Lane Desborough, Ben West, and so many others to explore creating other DIY tools, such as Nightscout. And thanks to social media, we all didn’t have to create in a vacuum: we can share code (this is what open source means) and insight through social media, and build upon each other’s work. As a result, these collaborations, sharing, and iterative development is how OpenAPS, the open source artificial pancreas system movement, was created.

I tweet and talk and share frequently about how great it is having #OpenAPS in my life. Norovirus? No problem. Changes in sensitivity due to exercise? Not the biggie it used to be.

However, this technology is by no means a cure. It still requires work on the part of the person with diabetes. We still have to:

  • Change pump sites
  • Change CGM sensors
  • Calibrate regularly
  • Deal with bonked pump sites and sensors that fall out

And also, given the speed of insulin, most people are still going to engage with the system for some kind of meal bolus or announcement. This is why it’s called “hybrid” closed loop technology. (However, depending on the sophistication of the technology, you start to get to be able to choose what you want to optimize for and the behaviors you want to choose to do less of, which is great.)

In some cases, we humans know more than the technology: such as when a meal is going to happen/is coming, and when exercise is going to happen. So it’s nice to be able to interoperate your devices and be able to use your phone, watch, computer, etc. to be able to tell the system what to do differently (i.e. set higher targets in the case of activity, or lower targets to achieve “eating soon” mode , or in the case of waking up).

But in a LOT of cases, it’s tiring for the human to have to think about all the things. Such as whether a pump site is slowly dying and causing apparent insulin resistant. Or such as when you’re more sensitive 12-24 hours after exercise. Or during menstrual cycles. Or when sick. Or during a growth spurt. Or during jet lag. Or during a trip where you can’t find anything to eat. Etc. It’s a lot for us PWD’s to track, and this is where computers come in handy. Things like autosensitivity in OpenAPS to automatically detect changes in sensitivity and adjust the variables for calculations automatically; and autotune, to track the data of what’s actually happening and make recommendations for changing your underlying pump settings (ISF, carb ratio, and basal rates).

And how has this technology been developed by patients? Iteratively, as we figure out what’s possible. It’s not about boiling the ocean; it’s about approaching problems bit by bit as we have new tools to solve them, or new people with energy to think about the problem in different ways. It’s like thinking about getting a car – you wouldn’t expect the manufacturer to sell bits and pieces of the car frame, and you don’t really expect medical device manufacturers to sell bits and pieces of a pump or other device. However, patients are closest to the REAL problems in living with diabetes. Instead of a “car”, they’re looking for solutions for getting from point A to point B. And so in the car analogy, that means starting with a skateboard, scooter, or bike – and ending up with a car is great, but the car is not the point.

So no, any piece of technology isn’t going to be a cure or solve all problems or work perfectly for everyone. But that is true whether it’s DIY or a commercial tool: one size certainly does not fit all. And patients are individuals with their own lives and their own challenges with diabetes, with different motivations around what aspects of life with diabetes feel like friction and what they feel equipped to tackle and solve.

So, here’s some of what’s on my list for what I’d like CDE’s and other HCP’s to know as a result of the proliferation of technology around diabetes:

  • Yes, DIY tech is often off label. But that’s ok – it just means it’s off label; it doesn’t prevent you from listening to why patients are using it, what we think it’s doing for us, and it doesn’t prevent you from asking questions, learning more, or still advising patients.
  • Don’t make us switch providers by refusing to discuss it or listen to it, just because it’s new/different/you don’t understand it. (By the way: we don’t expect you to understand all possible technology! You can’t be experts on everything, but that doesn’t mean shunning what you don’t know.)
  • You get to take advantage of the opportunity when someone brings something new into the office – it’s probably the first of many times you’ll see it, and the first patient is often on the bleeding edge and deeply engaged and understands what they’re using, and open to sharing what they’ve learned to help you, so you can also help other patients!
  • You also get to take advantage of the open source community. It’s open, not just for patients to use, but for companies, and for CDEs and other HCPs as well. There are dozens if not hundreds of active people on Twitter, Facebook, blogs, forums, and more who are happy to answer questions and help give perspective and insight into why/how/what things are.
  • Don’t forget – many of the DIY tools provide data and insight that currently don’t exist in any traditional and/or commercially and/or FDA-approved tool. Take autotune for example – there’s nothing else out there that we know of that will tune basal rates, ISF, and carb ratio for people with pumps. And the ability of tools like Nightscout reports to show data from a patient’s disparate devices is also incredibly helpful for healthcare providers and educators to use to help patients.

And one final point specific to hybrid closed loop technology: this technology is going to solve a lot of problems and frustrations. But, it may mean that patients will shift the prioritization of other quality of life factors like ease of use over older, traditionally learned diabetes behaviors. This means things like precise carb counting may go by the wayside for general meal size estimations, because the technology yields similar outcomes. Being aware of this will be important for when CDE’s are working with patients; knowing what the patterns of behaviors are and knowing where a patient has shifted their choices will be helpful for identifying what behaviors can be adapted to yield different outcomes.

I think the increase in technology (especially various types of closed loops, DIY and commercial) will yield MORE work for CDE’s and HCP’s, rather than less. This means it’s even more important for them to get up to speed on current and evolving technology – because it’s by no means going away. And the first wave of DIY’ers have a lot we can share and teach not just other patients, but also CDE’s. So again, many thanks to AADE for the opportunity to share some of this perspective at #AADE17, and thanks to everyone for the engagement during and after the session!