Understanding the Difference Between Open Source and DIY in Diabetes

There’s been a lot of excitement (yay!) about the results of the CREATE trial being published in NEJM, followed by the presentation of the continuation results at EASD. This has generated a lot of blog posts, news articles, and discussion about what was studied and what the implications are.

One area that I’ve noticed is frequently misunderstood is how “open source” and “DIY” are different.

Open source means that the source code is openly available to view. There are different licenses with open source; most allow you to also take and reuse and modify the code however you like. Some “copy-left” licenses commercial entities to open-source any software they build using such code. Most companies can and do use open source code, too, although in healthcare most algorithms and other code related to FDA-regulated activity is proprietary. Most open source licenses allow free individual use.

For example, OpenAPS is open source. You can find the core code of the algorithm here, hosted on Github, and read every line of code. You can take it, copy it, use it as-is or modify it however you like, because the MIT license we put on the code says you can!

As an individual, you can choose to use the open source code to “DIY” (do-it-yourself) an automated insulin delivery system. You’re DIY-ing, meaning you’re building it yourself rather than buying it or a service from a company.

In other words, you can DIY with open source. But open source and DIY are not the same thing!

Open source can and is usually is used commercially in most industries. In healthcare and in diabetes specifically, there are only a few examples of this. For OpenAPS, as you can read in our plain language reference design, we wanted companies to use our code as well as individuals (who would DIY with it). There’s at least one commercial company now using ideas from the OpenAPS codebase and our safety design as a safety layer against their ML algorithm, to make sure that the insulin dosing decisions are checked against our safety design. How cool!

However, they’re a company, and they have wrapped up their combination of proprietary software and the open source software they have implemented, gotten a CE mark (European equivalent of FDA approval), and commercialized and sold their AID product to people with diabetes in Europe. So, those customers/users/people with diabetes are benefitting from open source, although they are not DIY-ing their AID.

Outside of healthcare, open source is used far more pervasively. Have you ever used Zoom? Zoom uses open source; you then use Zoom, although not in a DIY way. Same with Firefox, the browser. Ever heard of Adobe? They use open source. Facebook. Google. IBM. Intel. LinkedIn. Microsoft. Netflix. Oracle. Samsung. Twitter. Nearly every product or service you use is built with, depends on, or contains open source components. Often times open source is more commonly used by companies to then provide products to users – but not always.

So, to more easily understand how to talk about open source vs DIY:

  • The CREATE trial used a version of open source software and algorithm (the OpenAPS algorithm inside a modified version of the AndroidAPS application) in the study.
  • The study was NOT on “DIY” automated insulin delivery; the AID system was handed/provided to participants in the study. There was no DIY component in the study, although the same software is used both in the study and in the real world community by those who do DIY it. Instead, the point of the trial was to study the safety and efficacy of this version of open source AID.
  • Open source is not the same as DIY.
  • OpenAPS is open source and can be used by anyone – companies that want to commercialize, or individuals who want to DIY. For more information about our vision for this, check out the OpenAPS plain language reference design.
Venn diagram showing a small overlap between a bigger open source circle and a smaller DIY circle. An arrow points to the overlapping section, along with text of "OpenAPS". Below it text reads: "OpenAPS is open source and can be used DIY. DIY in diabetes often uses open source, but not always. Not all open source is used DIY."

Continuation Results On 48 Weeks of Use Of Open Source Automated Insulin Delivery From the CREATE Trial: Safety And Efficacy Data

In addition to the primary endpoint results from the CREATE trial, which you can read more about in detail here or as published in the New England Journal of Medicine, there was also a continuation phase study of the CREATE trial. This meant that all participants from the CREATE trial, including those who were randomized to the automated insulin delivery (AID) arm and those who were randomized to sensor-augmented insulin pump therapy (SAPT, which means just a pump and CGM, no algorithm), had the option to continue for another 24 weeks using the open source AID system.

These results were presented by Dr. Mercedes J. Burnside at #EASD2022, and I’ve summarized her presentation and the results below on behalf of the CREATE study team.

What is the “continuation phase”?

The CREATE trial was a multi-site, open-labeled, randomized, parallel-group, 24-week superiority trial evaluating the efficacy and safety of an open-source AID system using the OpenAPS algorithm in a modified version of AndroidAPS. Our study found that across children and adults, the percentage of time that the glucose level was in the target range of 3.9-10mmol/L [70-180mg/dL] was 14 percentage points higher among those who used the open-source AID system (95% confidence interval [CI], 9.2 to 18.8; P<0.001) compared to those who used sensor augmented pump therapy; a difference that corresponds to 3 hours 21 minutes more time spent in target range per day. The system did not contribute to any additional hypoglycemia. Glycemic improvements were evident within the first week and were maintained over the 24-week trial. This illustrates that all people with T1D, irrespective of their level of engagement with diabetes self-care and/or previous glycemic outcomes, stand to benefit from AID. This initial study concluded that open-source AID using the OpenAPS algorithm within a modified version of AndroidAPS, a widely used open-source AID solution, is efficacious and safe. These results were from the first 24-week phase when the two groups were randomized into SAPT and AID, accordingly.

The second 24-week phase is known as the “continuation phase” of the study.

There were 52 participants who were randomized into the SAPT group that chose to continue in the study and used AID for the 24 week continuation phase. We refer to those as the “SAPT-AID” group. There were 42 participants initially randomized into AID who continued to use AID for another 24 weeks (the AID-AID group).

One slight change to the continuation phase was that those in the SAPT-AID used a different insulin pump than the one used in the primary phase of the study (and 18/42 AID-AID participants also switched to this different pump during the continuation phase), but it was a similar Bluetooth-enabled pump that was interoperable with the AID system (app/algorithm) and CGM used in the primary outcome phase.

All 42 participants in AID-AID completed the continuation phase; 6 participants (out of 52) in the SAPT-AID group withdrew. One withdrew from infusion site issues; three with pump issues; and two who preferred SAPT.

What are the results from the continuation phase?

In the continuation phase, those in the SAPT-AID group saw a change in time in range (TIR) from 55±16% to 69±11% during the continuation phase when they used AID. In the SAPT-AID group, the percentage of participants who were able to achieve the target goals of TIR > 70% and time below range (TBR) <4% increased from 11% of participants during SAPT use to 49% during the 24 week AID use in the continuation phase. Like in the primary phase for AID-AID participants; the SAPT-AID participants saw the greatest treatment effect overnight with a TIR difference of 20.37% (95% CI, 17.68 to 23.07; p <0.001), and 9.21% during the day (95% CI, 7.44 to 10.98; p <0.001) during the continuation phase with open source AID.

Those in the AID-AID group, meaning those who continued for a second 24 week period using AID, saw similar TIR outcomes. Prior to AID use at the start of the study, TIR for that group was 61±14% and increased to 71±12% at the end of the primary outcome phase; after the next 6 months of the continuation phase, TIR was maintained at 70±12%. In this AID-AID group, the percentage of participants achieving target goals of TIR >70% and TBR <4% was 52% of participants in the first 6 months of AID use and 45% during the continuation phase. Similarly to the primary outcomes phase, in the continuation phase there was also no treatment effect by age interaction (p=0.39).

The TIR outcomes between both groups (SAPT-AID and AID-AID) were very similar after each group had used AID for 24 weeks (SAPT-AID group using AID for 24 weeks during the continuation phase and AID-AID using AID for 24 weeks during the initial RCT phase).. The adjusted difference in TIR between these groups was 1% (95% CI, -4 to 6; p=-0.67). There were no glycemic outcome differences between those using the two different study pumps (n=69, which was the SAPT-AID user group and 18 AID-AID participants who switched for continuation; and n=25, from the AID-AID group who elected to continue on the pump they used in the primary outcomes phase).

In the initial primary results (first 24 weeks of trial comparing the AID group to the SAPT group), there was a 14 percentage point difference between the groups. In the continuation phase, all used AID and the adjusted mean difference in TIR between AID and the initial SAPT results was a similar 12.10 percentage points (95% CI, p<0.001, SD 8.40).

Similar to the primary phase, there was no DKA or severe hypoglycemia. Long-term use (over 48 weeks, representing 69 person-years) did not detect any rare severe adverse events.

CREATE results from the full 48 weeks on open source AID with both SAPT (control) and AID (intervention) groups plotted on the graph.

Conclusion of the continuation study from the CREATE trial

In conclusion, the continuation study from the CREATE trial found that open-source AID using the OpenAPS algorithm within a modified version of AndroidAPS is efficacious and safe with various hardware (pumps), and demonstrates sustained glycaemic improvements without additional safety concerns.

Key points to takeaway:

  • Over 48 weeks total of the study (6 months or 24 weeks in the primary phase; 6 months/24 weeks in the continuation phase), there were 64 person-years of use of open source AID in the study, compared to 59 person-years of use of sensor-augmented pump therapy.
  • A variety of pump hardware options were used in the primary phase of the study among the SAPT group, due to hardware (pump) availability limitations. Different pumps were also used in the SAPT-AID group during the AID continuation phase, compared to the pumps available in the AID-AID group throughout both phases of trial. (Also, 18/42 of AID-AID participants chose to switch to the other pump type during the continuation phase).
  • The similar TIR results (14 percentage points difference in primary and 12 percentage points difference in continuation phase between AID and SAPT groups) shows durability of the open source AID and algorithm used, regardless of pump hardware.
  • The SAPT-AID group achieved similar TIR results at the end of their first 6 months of use of AID when compared to the AID-AID group at both their initial 6 months use and their total 12 months/48 weeks of use at the end of the continuation phase.
  • The safety data showed no DKA or severe hypoglycemia in either the primary phase or the continuation phases.
  • Glycemic improvements from this version of open source AID (the OpenAPS algorithm in a modified version of AndroidAPS) are not only immediate but also sustained, and do not increase safety concerns.
CREATE Trial Continuation Results were presented at #EASD2022 on 48 weeks of use of open source AID

Reasons to “DIY” or Self-Organize Your Own Solo Ultramarathon or Ultra Run

I’ve now run two ultramarathons (both happened to be 50k races, with a race report for the second race here), and was planning my third ultrarace. I had my eye on the 50 mile (50M) version of the 50k I ran last year. It’s on a course I adore – a 6 foot wide crushed gravel trail that’s slightly uphill (about 1,000 feet) for the first 30 miles and then downhill at 2% grade for the remaining 20 miles. It happens to be close to home (hour and a half drive to the start), which helps for logistics.

I started training for the 50M weeks after my 50k this year, including talking my husband into taking me out to run some of the segments along the first 25 miles of the course. I’ve done the back half of the course several times through training and racing the 50k, and I wanted to check out each of the earlier segments to get a sense of what trail bathrooms existed on the course, make notes about milestones to watch for at various distances, etc.

After the first training run out there, when I started talking goal paces to get through the first and main cutoff at mile 30 (cutoffs got progressively easier from there, and even walking very slowly you could finish if you wanted to), my husband started to suggest that I should just run the course some other time on my own, so I didn’t have to worry about the cutoffs. I told him I didn’t want to do that. The cutoffs are a good incentive to help me push myself, and it’s worth the stress it causes in order to try to perform my best. (My target pace would get me through a comfortable 15 minutes before cutoff, and I could dial up the effort if needed to achieve cutoff). However, he suggested it another time and pointed out that even when running an organized race, I tend to run self-supported, so I don’t really don’t benefit as much from running in a race. I protested and talked again about the camaraderie of running when everyone else did, the fact that there were aid stations, the excellent search and rescue support, the t-shirt, the medal, the pictures! Then out loud I realized that I would be running at the back of the pack that I would miss the pictures at 25 miles because the photographer heads to the finish before I would get there. And they stop finish line pictures 3 hours before the end of the race. (Why, I don’t know!) And so I’d miss those photos too. And last year, I didn’t partake in the 50k staffed aid stations because I couldn’t eat any of their food and didn’t want any extra COVID exposure. Instead, my husband crewed me and refilled my hydration at two points on the course. The un-staffed aid stations didn’t have the plethora of supplies promised, and one race report from someone near the front of the pack said they were low on water! So it was a good thing I didn’t rely on the aid stations. I didn’t wear the tshirt last year, because it wasn’t a tech tee. Medals aren’t that exciting. So…why was I running the organized race?

My only remaining reasons were good search and rescue (still true) and the motivation of signing up for and committing to running on that date. It’s a commitment device. And my husband then smashed that reason, too, by reminding me that the only commitment device I typically need is a spreadsheet. If I decide I’m going to work toward a goal, I do. Signing up doesn’t make a difference.

And to be fair, he crews me whether it’s an organized race or not! So to him, it makes no difference whether I’m running an organized race or a self-organized long ultra.

And so I decided to give it some thought. Where would I run, if I could run anywhere in an hour’s distance from home? Do the same 50 mile course? Was that course worth it? Or was there somewhere closer to home where I could run that would be easier for my husband to crew?

He suggested running on our “home” trails, which is a network of hundreds of miles of paved trail that’s a short walk away. I immediately scoffed, then took the suggestion seriously. If I ran “from home”, he could crew from home and either drive out or e-bike out or walk out to bring me supplies along my route. If the park trail bathrooms ended up getting locked, I could always use the bathroom at home (although not ideal in terms of motivating myself to move quickly and get back out on the trail). I’d have a bigger variety of fueling options, since he could microwave and bring me out more options than if it had to be shelf-stable.

The list of benefits of potentially doing my own DIY or self-organized ultra grew.

(And then, I broke my toe. Argh. This further solidified my willingness to do a DIY ultra, because I could train up until when I was ready, and then run my distance, without having to choose between a non-refundable signup and not running or risking injury from running before I was ready.)

Eventually, my plans evolved (in part due to my broken toe). I was originally going to DIY a 50M or 100k (62M) over Labor Day weekend, recover, then re-train up and run a DIY 100 mile (100M) in late October or early November. When I broke my toe, I decided to scratch the “test” 50M/100k and just train and run the 100M, since that was my ultimate goal distance for the year.

Here are the pros of running a DIY ultra or a “self-organized” ultra, rather than an organized race with other people:

  • For me specifically, I have better trail options and route options. I can run a 95% flat course on paved, wide, safe trails through my local community.
  • These are so local that they are only a few minutes walk from my door.
  • The location means it’s easy for Scott to reach me at any point. He can walk out and bring me water and fuel and any needed supplies when I complete a loop every 4 or so hours. If needed, he could also e-bike out to bring me anything I need if I ran out or had a more urgent need for supplies. He can also drive out and access the course every half mile or mile for most of my planned route.

    This also means I have more fuel options that I can prepare and have for Scott to bring out. This is awesome because I can have him warm up ¼ of a ham and cheese quesadilla, or a corn dog, or sweet potato tots, or any other fuel options that I wouldn’t be able to use if I had to rely on pre-packed shelf stable options for a 30 hour race.

    (Note that even if I did an organized race, I most likely still wouldn’t benefit from aid station food. In part, because I have celiac and have to have everything gluten free. I also have to watch cross contamination, so a bowl of any kind of food that’s not individually packaged is something that’s likely contaminated by gluten. COVID has helped reduce this but not completely. Plus, I have diabetes so I need to be roughly aware of the amount of carbs I’m eating to decide whether or not to dose insulin for them, given what is happening to my blood sugar at the time. And, I have exocrine pancreatic insufficiency (EPI) which means I have to dose enzymes for everything I eat. Grazing is hard with EPI; it’s easier to dose and eat the amount that matches my enzymes, so pre-packaged snacks that I know the carb and fat and protein count means I know what insulin I need and what enzymes I need for each set of “fuel”. Guessing carb counts or enzyme counts in the middle of the night while running long distance is likely not going to be very effective or fun. So as a result of all that – pre-planned food is the way to go for me. Related, you can read about my approach for tracking fuel on the go with a spreadsheet and pre-planned fuel library here.)

  • There is regular public bathroom access along my chosen route.
  • I’ve designed out and back laps and loops that have me coming back by my start (remember, only a few minutes walk from home) and that make it so I am passing the bathrooms multiple times on a regular basis in case I need them.

    These laps and loops also make for mentally smaller chunks to tackle. Instead of 100 miles, I’ve got a ~24 mile out and back, a 13 mile loop, a 16 mile out and back, a repeat of the 13 mile loop, repeating again the 16 mile out and back followed by the 13 mile loop one more time, and then a quick 5 mile total out and back (so 2.5 out and back). These are also all routes I know well, so mentally finding waypoints to focus on and know how far I’ve gone are a huge benefit for mentally breaking down the distance into something my brain and body “know”.

  • There are no cutoffs or pace requirements. If I slow down to a 20 minute mile (or slower)…well hey, it’s faster than I was walking with my hands-free knee crutch a few months ago! (I rocked anywhere from a 45 minute mile to a 25 minute mile).

    There’s no pressure to go faster, which means I won’t have pressure to push my effort, especially at the start. Hopefully, that means I can maintain an “easy”, even effort throughout and maybe cause less stress to my body’s hormone systems than I would otherwise.

    The only pressure I have will be the pressure I put on myself to finish (eventually), which could be 26 hours or could be 30 hours or could be 36 hours or even slower… basically I have to finish before my husband gives up on coming out to refuel me!

  • And, once I finish, it’ll be ‘fast’ to get home, shower, refuel, and be done. This is in comparison to a race where I’d have an hour+ drive to get home. I’ll need to walk home which might actually take me much longer than that after I’ve ambulated for 100 miles…but it should hopefully be shorter than an hour!
  • Finally, the major benefit is flexibility. I can set my race date for a weekend when I’ve trained enough to do it. I can move it around a week or two based on the weather (if it’s too cold or too rainy). I can even decide to move it to the spring (although I’d really love to do it this year).

Here are some of the cons of running a DIY ultra or a “self-organized” ultra, rather than an organized race with other people:

  • Theoretically, it would be easier to stop because I am so close to home. I haven’t committed money or drive time or dragged my husband to far away places to wait for me to finish my run. (However, I’m pretty stubborn so in my case I think this is less of an issue than it might be for others?)
  • Yet, out and back loops and the route I’ve chosen could get monotonous. I chose these loops and the route because I know the distance and almost every tenth mile of the route super well. The first 6 miles of all the laps/loops are the same, so I’ll run those same 6 miles repeated 7 times over the course of the run.
  • I won’t have the camaraderie and knowledge that other people are out here tackling the same distance. I’m a back of the pack runner (and celebrate being places from last the way most people celebrate places from first!) and often don’t see anyone running after the start…yet there’s comfort in knowing I’m one of dozens or hundreds out here covering the same course on the same day with the same goal. I do think I’ll miss this part.
  • There is no one to cheer for me. There’s no aid station volunteers, fellow runners, or anyone (other than my amazing husband who will crew me) to cheer for me and encourage me and tell me I’m moving well.
  • There’s no medal (not a big deal), t-shirt (not a big deal), or official finishing time (also not a big deal for me).
  • There’s no cutoffs or pace requirements to motivate me to keep pushing when things get hard.

All in all, the benefits pretty clearly outweigh the downsides – for me. Again, I’m a back of the pack super slow runner (in fact, I typically run 30 seconds and walk 60 seconds throughout my whole race consistently) who can’t eat aid station food (because celiac/EPI makes it complicated) coming off of a broken toe injury (which messed up my training and racing plans), so my pros/cons lean pretty heavily toward making a DIY/self-organized solo ultra run an obvious choice. Others might have different pro/con list based on the above variables and their situations, but hopefully this helps someone else think through some of the ways they might decide between organized and un-organized ultramarathon efforts!

Reasons to "DIY" or self-organize your own ultramarathon run

What is in my running pack for running ultramarathons or training for a marathon

After three years of using a multi-purpose activity backpack as my running pack, the strap connector broke, and I had to find and re-stock a new running pack. I use a running pack for when I’m doing long runs for marathon or ultramarathon training.  I ended up pulling everything out of my old backpack and evaluating whether I still wanted to carry it on every long run. For the most part, everything got moved over to the new pack. There were a few cases where I had excessive duplicates (more on that below and why) where I ended up reducing the quantity. But everything else made the list for what I carry with me on long runs every single time.

  1. Hydration – via a camelbak or other bladder with a hose (example). I prefer straight water in my hydration pack and to separately manage electrolytes and fuel separately. The bonus of just having water is it’s easier to clean the hydration pack after each run!Tips: put ice cubes in your bladder and fill it with cold water. Cold water is awesome for long, hot runs in the sun. Also, my old hydration pack had an insulated compartment that kept the ice water cold for hours. My new running vest does not, and in fact has holes in the back for air flow that also means the heat from my back melts my ice pretty fast. To work around this in the new vest is to slide the filled hydration bladder into a padded mailing envelope that’s open at the top. It’s not quite as insulated as true insulation, but it protects the bladder from some of the heat coming off of your back and it probably stays cool 60% instead of 20% as long as before, which is a huge improvement.

    Extra tip: use a Qtip or similar to clean out the mouthpiece of your hose every few runs!

  2. Diabetes backups  – this means things like a backup insulin pump site. On long unsupported runs, it can also mean my blood glucose meter. (I wear a CGM so I don’t always take a meter along on runs unless it’s in an unsupported area where I don’t have easy crew access or support within a few miles). I’ve had several runs where my pump site has stopped working or ripped out, so having a backup pump site is just as necessary as having bandaids.The other source of backups is extra low carbs, e.g. sugar in case my blood sugar goes low. I usually keep a stash of carbs in my shorts pocket, but I also keep extra in my backpack in case I run through everything in my pocket. This is in addition to regular food/fuel for ultrafueling, it has to be faster-acting glucose/sugar that can more quickly fix a dropping or already-low blood sugar level.

    (This is one of the places I mentioned where I had excessive duplicates. I have continued to add extra to my backup stashes, and ended up with well over 100+ grams of “backup” carbs just in case. I ended up cutting down the total amount of carbs to closer to ~50 grams instead.)

    You can read some more about my strategy for running with diabetes here.

  3. Baggie with extra socks – I always carry a pair of extra socks, although I’ve never needed them in a normal training long run, I did end up using them in my 50k that involved crossing a river up to my knees five times
  4. Bandaids – Just like hiking, but I carry bandaids in case of bleeding cuts or scratches or worse, blisters on my heels, feet, or toes. I carry some that are blister-style and some regular style, smaller ones and larger ones, all the way up to large multi-inch squares that can cover the backs of my heels if I don’t already have them covered.More recently, I also started carrying small squares and strips of kinesiology tape for the same purpose. I originally did kinesio tape strips in case my knee needed some extra support, but I’ve found the kinesio tape also works well to cover my toes or backs of my heels in lieu of bandaids for blister prevention. For fixing blisters, I have to dry my feet really well or the kinesio tape doesn’t stay well or easily rubs off; so I tend to cover the toes that blister frequently as well as my heels prior to my runs so they’re less likely to generate blisters and require fixing mid-runs. I get a large roll of kinesiology tape (example) and cut it into smaller pieces as needed for all of these uses cases.

    I also keep at least one mini individual packet of antibiotic ointment (example) in the baggie as well.

  5. Lubrication – I carry a lubrication stick (Squirrel Nut Butter, because it works for me and is easy to reapply) to making sure between my thighs and other areas don’t chafe. When I sweat a lot, I often have to reapply every few hours to my thighs. While this can also be accomplished by carrying dabs of vaseline or your preferred lubrication in a baggie, the SNB stick is lightweight and I don’t mind carrying it so it’s easy to reapply and the hassle doesn’t prevent me from wanting to prevent chafing.
  6. Stuff to fix GI problems – it’s common to have GI issues when running, but I also had a two-year stretch of known GI issues that ultimately turned out to be undiscovered exocrine pancreatic insufficiency. During this time, I always carried individual Immodium and GasX in case I needed them.
  7. Electrolyte pills – I prefer to measure and track electrolytes separate from my hydration, so I use electrolyte pills (example) that I swallow on a scheduled basis to keep my electrolyte levels topped off. I’ve tried chew kinds (but they make me burp), so I stick with a baggie full of electrolyte pills. I bring extra just in case I drop some, but I generally eyeball and count out to make sure I have enough for each super long run.
  8. Any medication you need during the run – For me, that includes enzymes for fuel because I have exocrine pancreatic insufficiency and I need enzymes to help me digest any of my fuel. I have expensive, larger dose prescription pills that I usually use for meals, but it would make running even more expensive if I had to use a $9 pill every 30 minutes for a fuel snack. Luckily, there are over the counter versions of enzyme pills (more about that here) that are single-enzyme or multi-enzyme, that are more in the ballpark of $0.35 per pill, and I have a baggie of both kinds that I use to cover each snack.
  9. Fuel or snacks – A lot of ultra runners use gels, but I have been experimenting with ‘real’ foods. Basically, anything that’s around ~20g of carbs and less than ~10g of fat and 5-10g of protein that I like to eat. So far, that list includes chili Cheese Fritos, yogurt covered pretzels, peanut butter pretzel nuggets, beef sticks, Honey Stinger Stroopwaffles (the gluten free kinds – beware that only some of their flavors are GF!), mini date or fruit bars, fruit snacks, sweet potato tots, ¼ of a ham and cheese quesadilla, ¼ of a PBJ sandwich, a waffle, mini PayDay bars…. Noting that all of these are gluten free versions or are naturally gluten free, because I have celiac disease. I do a lot of work in advance to test these snacks carefully on training runs before I commit to using them repeatedly throughout longer runs so I know my body likes them during runs as well as other times. I only take the fresh/hot snacks (sweet potato tots, quesadilla etc) and eat those at the start or when my husband re-fills my pack for me mid-run, so I don’t have to worry about them spoiling. Everything else is shelf stable so when I pack a few more than I need per run and leave some in my pack, they’re not an issue to sit there for weeks until I manage to eat them in my rotation of snacks on a future run.
  10. Miscellaneous other supplies – car keys, house keys, hand sanitizer, a mask for going into trail bathrooms, and a battery and cord for charging my phone.

Phew. That’s a lot of stuff. And yes, it does end up being more supplies and more weight than most people carry. But…I use pretty much everything in my pack every few runs. Stuff happens: pump sites fall out, blisters happen, chafing happens, GI stuff happens..and I’ve found that training and running with a little extra weight in my pack is worth having the proper supplies when I need them, rather than having to end runs early due to lack of preparation or minor supplies that would enable me to keep running.

Every time I go out for a run, I add the requisite amount of snacks, enzymes, electrolyte pills, and hydration for the run. Any time I come back from a run and I have depleted a supply off of the above list – such as using my backup pump site – I immediately go and refill that supply so I don’t have to remember to refill it prior to the next run. Keeping the above supplies topped off and ready to go always in my backpack means they’re always there when I need them, and the peace of mind of knowing how I can handle and that I can handle these situations while running is priceless.

Note: previously I was using a backpack, because it was $30 and for my running it was good enough. However, when the strap broke, I looked to buy the same backpack again and it was $60. It was fine for $30 but if I was going to double the cost, I decided to research alternative running packs and vests. Vests seem to be more common in ultrarunners, so I looked for those, although they’re a lot more expensive (often $125-200). I was disappointed with how small of a volume some of them held, or they were just ugly. I liked the look of a purple one I found that came with a 1.5L bladder….but ugh. I fit a 3L bladder in my previous backpack and typically fill it 2-2.5L full as a baseline, and all the way up for a longer (6h+) unsupported run. I decided to risk getting this vest even though it was smaller and try putting my larger 3L capacity bladder in the new vest. (Luckily it was on sale for $90 at the time  which made it a little less annoying to buy compared to a $150 one.) The bladder does fit, but it sticks out the top and hits the back of my neck if it’s all the way full (3L). So for the most part, I’m filling the 3L capacity bladder about 2L full (and as noted in this post earlier, putting it inside an insulated envelope to help retain the cold for longer), and that works for me.

One thing I do like a lot from my new running vest is the front pockets. My old backpack I had to partially take off and twist around me in order to get snacks out. With two large front pockets, I can fit several hours of fuel in there so there is no twisting involved to get my fuel out, which is helping with my goal to fuel every 30 minutes. I do wish there was a separate smaller pouch – my old backpack had a small old school flip phone size “cell phone” pocket that I used to keep my baggies of enzymes and electrolytes in. Right now, I just have those baggies floating around the top of those pockets and it’s fairly easily to grab and pull out the right baggie, but I’m toying with adding some kind of small strap-on holster/pouch to the shoulder just for enzymes so I don’t have to worry as much about them jostling out when my pockets are completely full of snacks. But otherwise, these front pockets are overall a nice improvement.

A purple running vest on the left; supplies described in blog post in the middle laid out on the ground, and my old purple backpack used for running on the right.
A cat in mid air jumping over the purple runing vest in the left of the picture; another cat sitting to the right of the old purple backpack used for running.
Outtake! Mint jumping over my new running vest and running supplies while Mo looks on from the right next to my old running backpack.
A cat sitting on and sniffing the new smells of a new, purple running vest
Mint helpfully inspected my new running vest as soon as I set it on the ground.

2022 Strawberry Fields Forever Ultramarathon Race Report Recap

I recently ran my second-ever 50k ultramarathon. This is my attempt to provide a race recap or “race report”, which in part is to help people in the future considering this race and this course. (I couldn’t find a lot of race reports investigating this race!)

It’s also an effort to provide an example of how I executed fueling, enzyme dosing (because I have exocrine pancreatic insufficiency, known as EPI), and blood sugar management (because I have type 1 diabetes), because there’s also not a lot of practical guidance or examples of how people do this. A lot of it is individual, and what works for me won’t necessarily work for anyone, but if anything hopefully it will help other people feel not alone as they work to figure out what works for them!

Context of my running and training in preparation

I wrote quite a bit in this previous post about my training last year for a marathon and my first 50k. Basically, I’m slow, and I also choose to run/walk for my training and racing. This year I’ve been doing 30:60 intervals, meaning I run 30 seconds and walk 60 seconds.

Due to a combination of improved training (and having a year of training last year), as well as now having recognized I was not getting sufficient pancreatic enzymes so that I was not digesting and using the food I was eating effectively, this year has been going really well. I ended up training as far as a practice 50k about 5 weeks out from my race. I did several more mid- to high-20 mile runs as well. I also did a next-day run following my long runs, starting around 3-4 miles and eventually increasing to 8 miles the day after my 50k. The goal of these next-day runs was to practice running on tired legs.

Overall, I think this training was very effective for me. My training runs were easy paced, and I always felt like I could run more after I was done. I recovered well, and the next-day runs weren’t painful and I did not have to truncate or skip any of those planned runs. (Previous years, running always felt hard and I didn’t know what it was like to recover “well” until this year.) My paces also increased to about a minute/mile faster than last year’s easy pace. Again, that’s probably a combination of increased running overall and better digestion and recovery.

Last year I chose to run a marathon and then do a 50k while I was “trained up” for my marathon. This year, I wanted to do a 50k as a fitness assessment on the path to a 50 mile race this fall. I looked for local-ish 50k options that did not have much elevation, and found the Strawberry Fields Forever Ultra.

Why I chose this race, and the basics about this race

The Strawberry Fields Forever Ultra met most of my goal criteria, including that it was around the time that I wanted to run a 50k, so that I had almost 6 months to train and also before it got to be too hot and risked being during wildfire smoke season. (Sadly, that’s a season that now overlaps significantly with the summers here.) It’s local-ish, meaning we could drive to it, although we did spend the night before the race in the area just to save some stress the morning of the race. The race nicely started at 9am, and we drove home in the evening after the race.

The race is on a 10k (6.2 miles) looped course in North Bonneville, Washington, and hosted a 10k event (1 lap), a 50k event (5 laps), and also had 100k (10 laps) or (almost) 100 miles (16 laps). It does have a little bit of elevation – or “little” by ultramarathon standards. The site and all reports describe one hill and net 200 feet of elevation gain and loss. I didn’t love the idea of a 200 foot hill, but thought I could make do. It also describes the course as “grass and dirt” trails. You’ll see a map later where I’ve described some key points on the course, and it’s also worth noting that this course is very “crew-able”. Most people hang out at the start/finish, since it’s “just” a 10k loop and people are looping through pretty frequently. However, if you want to, either for moral or practical support, crew could walk over to various points, or my husband brought his e-bike and biked around between points on the course very easily using a mix of the other trails and actual roads nearby.

The course is well marked. Any turn had a white sign with a black arrow on it and also white arrows drawn on the ground, and there were dozens of little red/pink fluorescent flags marking the course. Any time there was a fork in the path, these flags (usually 2-3 for emphasis, which was excellent for tired brains) would guide you to the correct direction.

The nice thing about this race is it includes the 100 mile option and that has a course limit of 30 hours, which means all the other distances also have this course limit of 30 hours. That’s fantastic when a lot of 50k or 50 mile (or 100k, which is 62 miles) courses might have 12 hour or similar tighter course limits. If you wanted to have a nice long opportunity to cover the distance, with the ability to stop and rest (or nap/sleep), this is a great option for that.

With the 50k, I was aiming to match or ideally beat my time from my first 50k, recognizing that this course is harder given the terrain and hill. However, I think my fitness is higher, so beating that time even with the elevation gain seemed reasonable.

Special conditions and challenges of the 2022 Strawberry Fields Forever Ultramarathon

It’s worth noting that in 2021 there was a record abnormal heat wave due to a “heat dome” that made it 100+ degrees (F) during the race. Yikes. I read about that and I am not willing to run a race when I have not trained for that type of heat (or any heat), so I actually waited until the week before the race to officially sign up after I saw the forecast for the race. The forecast originally was 80 F, then bounced around mid 60s to mid 70s, all of which seemed doable. I wouldn’t mind some rain during the race, either, as rainy 50s and 60s is what I’ve been training in for months.

But just to make things interesting, for the 2022 event the Pacific Northwest got an “atmospheric river” that dumped inches of rain on Thursday..and Friday. Gulp. Scott and I drove down to spend the night Friday night before the race, and it was dumping hard rain. I began to worry about the mud that would be on the course before we even started the race. However, the rain finished overnight and we woke up to everything being wet, but not actively raining. It was actually fairly warm (60s), so even if it drizzled during the race it wouldn’t be chilly.

During the start of the race, the race director said we would get wet and joked (I thought) about practicing our backstroke. Then the race started, and we took off.

My race recap / race report the 2022 Strawberry Fields Forever Ultramarathon

I’ve included a picture below that I was sent a month or so before the race when I asked for a course map, and a second picture because I also asked for the elevation profile. I’ve marked with letters (A-I) points on the course that I’ll describe below for reference, and we ran counterclockwise this year so the elevation map I’ve marked with matching letters where “A” is on the right and “I” is on the left, matching how I experienced the course.

The course is slightly different in the start/finish area, but otherwise is 95% matching what we actually ran, so I didn’t bother grabbing my actual course map from my run since this one was handy and a lot cleaner than my Runkeeper-derived map of the race.

Annotated course map with points A-I
StrawberryFieldsForever-Ultra-Elevation-Profile

My Runkeeper elevation profile of the 50k (5 repeated laps) looked like this:
Runkeeper elevation profile of 5 loops on the Strawberry Fields Forever 50k course

I’ll describe my first experience through the course (Lap 1) in more detail, then a couple of thoughts about the experiences of the subsequent laps, in part to describe fueling and other choices I made.

Lap 1:

We left the start by running across the soccer field and getting on a paved path that hooked around the ballfield and then headed out a gate and up The Hill. This was the one hill I thought was on the course. I ran a little bit and passed a few people who walked on a shallower slope, then I also converted to a walk for the rest of the hill. It was the most crowded race start I’ve done, because there were so many people (150 across the 10k, 50k, 100k, and 100 miler) and such a short distance between the start and this hill. The Hill, as I thought of it, is point A on the course map.

Luckily, heading up the hill there are gorgeous purple wildflowers along the path and mountain views. At the top of the hill there are some benches at the point where we took a left turn and headed down the hill, going down the same elevation in about half a mile so it was longer than the uphill section. This downhill slope (B) was very runnable and gravel covered, whereas going up the hill was more dirt and mud.

At the bottom of the hill, there was a hairpin turn and we turned and headed back up the hill, although not all the way up, and more along a plateau in the side of the hill. The “plateau” is point C on the map. I thought it would be runnable once I got back up the initial hill, but it was mud pit after mud pit, and I would have two steps of running in between mud pits to carefully walk through. It was really frustrating. I ended up texting to my parents and Scott that it was about 1.7 miles of mud (from the uphill, and the plateau) before I got to some gravel that was more easily runnable. Woohoo for gravel! This was a nice, short downhill slope (D) before we flattened out and switched back to dirt and more mud pits.

This was the E area, although it did feel more runnable than the plateau because there were longer stretches between muddy sections.

Eventually, we saw the river and came out from the trail into a parking lot and then jogged over onto the trail that parallels the river for a while. This trail that I thought of as “River Road” (starting around point F) is just mowed grass and is between a sharp bluff drop with opening where people would be down at the river fishing, and in some cases we were running *underneath* fishing lines from the parking spots down to the river! There were a few people who would be walking back and forth from cars to the river, but in general they were all very courteous and there was no obstruction of the trail. Despite the mowed grass aspect of the trail, this stretch physically and psychologically felt easier because there were no mud pits for 90% of it. Near the end there were a few muddy areas right about the point we hopped back over into the road to connect up a gravel road for a short spurt.

This year, the race actually put a bonus aid station out here. I didn’t partake, but they had a tent up with two volunteers who were cheerful and kind to passing runners, and it looked like they had giant things of gatorade or water, bottled water, and some sugared soda. They probably had other stuff, but that’s just what I saw when passing.

After that short gravel road bit, we turned back onto a dirt trail that led us to the river. Not the big river we had been running next to, but the place where the Columbia River overflowed the trail and we had to cross it. This is what the race director meant by practicing our backstroke.

You can see a video in this tweet of how deep and far across you had to get in this river crossing (around point G, but hopefully in future years this isn’t a point of interest on the map!!)

Coming out of the river, my feet were like blocks of ice. I cheered up at the thought that I had finished the wet feet portion of the course and I’d dry off before I looped back around and hit the muddy hill and plateau again. But, sadly, just around the next curve, came a mud POND. Not a pit, a pond.

Again, ankle deep water and mud, not just once but in three different ponds all within 30 seconds or so of each other. It was really frustrating, and obviously you can’t run through them, so it slowed you down.

Then finally after the river crossing and the mud ponds, we hooked a right into a nice, forest trail that we spent about a mile and a half in (point H). It had a few muddy spots like you would normally expect to get muddy on a trail, but it wasn’t ankle deep or water filled or anything else. It was a nice relief!

Then we turned out of the forest and crossed a road and headed up one more (tiny, but it felt annoying despite how small it looks on the elevation profile) hill (point I), ran down the other side of that slope, stepped across another mud pond onto a pleasingly gravel path, and took the gravel path about .3 miles back all the way to complete the first full lap.

Phew.

I actually made pretty good time the first loop despite not knowing about all the mud or river crossing challenges. I was pleased with my time which was on track with my plan. Scott took my pack about .1 miles before I entered the start/finish area and brought it back to me refilled as I exited the start/finish area.

Lap 2:

The second lap was pretty similar. The Hill (A) felt remarkably harder after having experienced the first loop. I did try to run more of the downhill (B) as I recognized I’d make up some time from the walking climb as well as knowing I couldn’t run up the plateau or some of the mud pits along the plateau (C) as well as I had expected. I also decided running in the mud pits didn’t work, and went with the safer approach of stepping through them and then running 2 steps in between. I was a little slower this time, but still a reasonable pace for my goals.

The rest of the loop was roughly the same as the first, the mud was obnoxious, the river crossing freezing, the mud obnoxious again, and relief at running through the forest.

Scott met me at the end of the river road and biked along the short gravel section with me and went ahead so he could park his bike and take video of my second river crossing, which is the video above. I was thrilled to have video of that, because the static pictures of the river crossing didn’t feel like it did the depth and breadth of the water justice!

At the end of lap 2, Scott grabbed my pack again at the end of the loop and said he’d figured out where to meet me to give it back to me after the hill…if I wanted that. Yes, please! The bottom of the hill where you hairpin turn to go back up the plateau is the 1 mile marker point, so that means I ran the first mile of the third lap without my pack, and not having the weight of my full pack (almost 3L of water and lots of snacks and supplies: more on that pack below) was really helpful for my third time up the hill. He met me as planned at the bottom of the downhill (B) and I took my pack back which made a much nicer start to lap 3.

Lap 3:

Lap 3 for some reason I came out of the river crossing and the mud ponds feeling like I got extra mud in my right shoe. It felt gritty around the right side of my right food, and I was worried about having been running for so many hours with soaked feet. I decided to stop at a bench in the forest section and swap for dry socks. In retrospect, I wish I had stopped somewhere else, because I got swarmed by these moth/gnat/mosquito things that looked gross (dozens on my leg within a minute of sitting there) that I couldn’t brush off effectively while I was trying to remove my gaiters, untie my shoes, take my shoes off, peel my socks and bandaids and lambs wool off, put lubrication back on my toes, put more lambs wool on my toes, put the socks and shoes back on, and re-do my gaiters. Sadly, it took me 6 minutes despite me moving as fast as I could to do all of those things (this was a high/weirdly designed bench in a shack that looked like a bus stop in the middle of the woods, so it wasn’t the best way to sit, but I thought it was better than sitting on the ground).

(The bugs didn’t hurt me at the time, but two days later my dozens of bites all over my leg are red and swollen, though thankfully they only itch when they have something chafing against them.)

Anyway, I stood up and took off again and was frustrated knowing that it had taken 6 minutes and basically eaten the margin of time I had against my previous 50k time. I saw Scott about a quarter of a mile later, and I saw him right as I realized I had also somewhere lost my baggie of electrolyte pills. Argh! I didn’t have back up for those (although I had given Scott backups of everything else), so that spiked my stress levels as I was due for some electrolytes and wasn’t sure how I’d do with 3 or so more hours without them.

I gave Scott my pack and tasked him with checking my brother-in-law’s setup to see if he had spare electrolytes, while he was refilling my pack to give me in lap 4.

Lap 4:

I was pretty grumpy given the sock timing and the electrolyte mishap as I headed into lap 4. The hill still sucked, but I told myself “only one more hill after this!” and that thought cheered me up.

Scott had found two electrolyte options from my brother-in-law and brought those to me at the end of mile 1 (again, bottom of B slope) with my pack. He found two chewable and two swallow pills, so I had options for electrolytes. I chewed the first electrolyte tab as I headed up the plateau, and again talked myself through the mud pits with “only one more time through the mud pits after this!”.

I also tried overall to bounce back from the last of mile 4 where I let myself get frustrated, and try to take more advantage of the runnable parts of the course. I ran downhill (B) more than the previous laps, mostly ignoring the audio cues of my 30:60 intervals and probably running more like 45:30 or so. Similarly, the downhill gravel after the mud pits (D) I ran most of without paying attention to the audio run cues.

Scott this time also met me at the start of the river road section, and I gave him my pack again and asked him to take some things out that he had put in. He put in a bag with two pairs of replacement socks instead of just one pair of socks, and also put in an extra beef stick even though I didn’t ask for it. I asked him to remove it, and he did, but explained he had put it in just in case he didn’t find the electrolytes because it had 375g of sodium. (Sodium is primarily the electrolyte I am sensitive to and care most about). So this was actually a smart thing, although because I haven’t practiced eating larger amounts of protein and experienced enzyme dosing for it on the run, I would be pretty nervous about eating it in a race, so that made me a bit unnecessarily grumpy. Overall though, it was great to see him extra times on the course at this point, and I don’t know if he noticed how grumpy I was, but if he did he ignored it and I cheered up again knowing I only had “one more” of everything after this lap!

The other thing that helped was he biked my pack down the road to just before the river crossing, so I ran the river road section like I did lap 3 and 4 on the hill, without a pack. This gave me more energy and I found myself adding 5-10 seconds to the start of my run intervals to extend them.

The 4th river crossing was no less obnoxious and cold, but this time it and the mud ponds didn’t seem to embed grit inside my shoes, so I knew I would finish with the same pair of socks and not need another change to finish the race.

Lap 5:

I was so glad I was only running the 50k so that I only had 5 laps to do!

For the last lap, I was determined to finish strong. I thought I had a chance of making up a tiny bit of the sock change time that I had lost. I walked up the hill, but again ran more than my scheduled intervals downhill, grabbed my bag from Scott, picked my way across the mud pits for the final time (woohoo!), ran the downhill and ran a little long and more efficiently on the single track to the river road.

Scott took my pack again at the river road, and I swapped my intervals to be 30:45, since I was already running closer to that and I knew I only had 3.5 or so miles to go. I took my pack back at the end of river road and did my last-ever ice cold river crossing and mud pond extravaganza. After I left the last mud pond and turned into the forest, I switched my intervals to 30:30. I managed to keep my 30:30 intervals and stayed pretty quick – my last mile and a half was the fastest of the entire race!

I came into the finish line strong, as I had hoped to finish. Woohoo!

Overall strengths and positives from the race

Overall, running-wise I performed fairly well. I had a strong first lap and decent second lap, and I got more efficient on the laps as I went, staying focused and taking advantage of the more runnable parts of the course. I finished strong, with 30:45 intervals for over a mile and 30:30 intervals for over a mile to the finish.

Also, I didn’t quit after experiencing the river crossing and the mud ponds and the mud pits of the first lap. This wasn’t an “A” race for me or my first time at the distance, so it would’ve been really easy to quit. I probably didn’t in part because we did pay to spend the night before and drove all that way, and I didn’t want to have “wasted” Scott’s time by quitting, when I was very capable of continuing and wasn’t injured. But I’m proud of mostly the way I handled the challenges of the course, and for how I readjusted from the mental low and frustration after realizing how long my sock change took in lap 3. I’m also pleased that I didn’t get injured, given the terrain (mud, river crossing, and uneven grass to run on for most of the course). I’m also pleased and amazed I didn’t hurt my feet, cause major blisters, or have anything really happen to them after hours of wet, muddy, never-drying-off feet.

The huge positive was my fueling, electrolytes, and blood glucose management.

I started taking my electrolyte pills that have 200+mg of sodium at about 45 minutes into the race, on schedule. My snack choices also have 100-150mg of sodium, which allowed me to not take electrolyte pills as often as I would otherwise need to (or on a hotter day with more sweat – it was a damp, mid-60s day but I didn’t sweat as much as I usually do). But even with losing my electrolytes, I used two chewable 100mg sodium electrolytes instead and otherwise ended up with sufficient electrolytes. Even with ideal electrolyte supplementation, I’m very sensitive to sodium losses and am a salty sweater, and I have a distinct feeling when my electrolytes are insufficient, so not having that feeling during after the race was a big positive for me.

So was my fueling overall. The race started at 9am, and I woke up at 6am to eat my usual pre-race breakfast (a handful of pecans, plus my enzyme supplementation) so that it would both digest effectively and also be done hitting my blood sugar by the time the race started. My BGs were flat 120s or 130s when I started, which is how I like them. I took my first snack about an hour and 10 minutes into the race, which is about 15g carb (10g fat, 2g protein) of chili cheese flavored Fritos. For this, I didn’t dose any insulin as I was in range, and I took one lipase-only enzyme (which covers about 8g of fat for me) and one multi-enzyme (that covers about 6g of fat and probably over a dozen grams of protein). My second snack was an hour later, when I had a gluten free salted caramel Honey Stinger stroopwaffle (21g carb, 6 fat, 1 protein). For the stroopwaffle I ended up only taking a lipase-only pill to cover the fat, even though there’s 1g of protein. For me, I seem to be ok (or have no symptoms) from 2-3g of uncovered fat and 1-2g of uncovered protein. Anything more than that I like to dose enzymes for, although it depends on the situation. Throughout the day, I always did 1 lipase-only and 1 multi-enzyme for the Fritos, and 1 lipase-only for the stroopwaffle, and that seemed to work fine for me. I think I did a 0.3u (less than a third of the total insulin I would normally need) bolus for my stroopwaffle because I was around 150 mg/dL at the time, having risen following my un-covered Frito snack, and I thought I would need a tiny bit of insulin. This was perfect, and I came back down and flattened out. An hour and 20 minutes after that, I did another round of Fritos. An hour or so after that, a second stroopwaffle – but this time I didn’t dose any insulin for it as my BG was on a downward slope. An hour later, more Fritos. A little bit after that, I did my one single sugar-only correction (an 8g carb Airhead mini) as I was still sliding down toward 90 mg/dL, and while that’s nowhere near low, I thought my Fritos might hit a little late and I wanted to be sure I didn’t experience the feeling of a low. This was during the latter half of loop 4 when I was starting to increase my intensity, so I also knew I’d likely burn a little more glucose and it would balance out – and it did! I did one last round of Fritos during lap 5.
CGM graph during 50k ultramarathon

This all worked perfectly. I had 100% time in range between 90 and 150 mg/dL, even with 102g of “real food” carbs (15g x 4 servings of Fritos, 21g x 2 waffles), and one 8g Airhead mini, so in total I had 110g grams of carbs across ~7+ hours. This perfectly matched my needs with my run/walk moderate efforts.

BG  and carb intake plotted along CGM graph during 50k ultramarathon

I also nailed the enzymes, as during the race I didn’t have any GI-related symptoms and after the race and the next day (which is the ultimate verdict for me with EPI), no symptoms.

So it seems like my practice and testing with low carbs, Fritos, and waffles worked out well! I had a few other snacks in my pack (yogurt-covered pretzels, peanut butter pretzel nuggets), but I never thought of wanting them or wanting something different. I did plan to try to do 2 snacks per hour, but I ended up doing about 1 per hour. I probably could have tolerated more, but I wasn’t hungry, my BGs were great, and so although it wasn’t quite according to my original plan I think this was ideal for me and my effort level on race day.

The final thing I think went well was deciding on the fly after loop 2 to have Scott take my pack until after the hill (so I ran the up/downhill mile without it), and then for additional stretches along river road in laps 4 and 5. I had my pocket of my shorts packed with dozens of Airheads and mints, so I was fine in terms of blood sugar management and definitely didn’t need things for a mile at a time. I’m usually concerned about staying hydrated and having water whenever I want to sip, plus for swallowing electrolytes and enzyme pills to go with my snacks, but I think on this course with the number of points Scott could meet me (after B, at F all through G, and from I to the finish), I could have gotten away with not having my pack the whole time; having WAY less water in the pack (I definitely didn’t need to haul 3L the whole time, that was for when I might not see Scott every 2-3 laps) and only one of each snack at a time.

Areas for improvement from my race

I trained primarily on gravel or paved trails and roads, but despite the “easy” elevation profile and terrain, this was essentially my first trail ultra. I coped really well with the terrain, but the cognitive burden of all the challenges (Mud pits! River crossing! Mud ponds!) added up. I’d probably do a little more trail running and hills (although I did some) in the final weeks before the race to help condition my brain a little more.

I’ll also continue to practice fueling so I can eat more regularly than every hour to an hour and a half, even though this was the most I’ve ever eaten during a run, I did well with the quantities, and my enzyme and BG management were also A+. But I didn’t eat as much as I planned for, and I think that might’ve helped with the cognitive fatigue, too, by at least 5-10%.

I also now have the experience of a “stop” during a race, in this case to swap my socks. I’ve only run one ultra and never stopped before to do gear changes, so that experience probably was sufficient prep for future stops, although I do want to be mentally stronger/less frustrated by unanticipated problem solving stops.

Specific to this course, as mentioned above, I could’ve gotten away with less supplies – food and water – in my pack. I actually ran a Ragnar relay race with a group of fellow T1s a few years back where I finished my run segment and…no one was there to meet me. They went for Starbucks and took too long to get there, so I had to stand in the finishing chute waiting for 10-15 minutes until someone showed up to start the next run leg. Oh, and that happened in two of the three legs I ran that day. Ooof. Standing there tired, hot, with nothing to eat or drink, likely added to my already life-with-type-1-diabetes-driven-experiences of always carrying more than enough stuff. But I could’ve gotten away very comfortably with carrying 1L of water and one set of each type of snacks at a time, given that Scott could meet me at 1 mile (end of B), start (F) and end of river road (before G), and at the finish, so I would never have been more than 2-2.5 miles without a refill, and honestly he could’ve gotten to every spot on the trail barring the river crossing bit to meet me if I was really in need of something. Less weight would’ve made it easier to push a little harder along the way. Basically, I carried gear like I was running a solo 30 mile effort at a time, which was safe but not necessary given the course. If I re-ran this race, I’d feel a lot more comfortable with minimal supplies.

Surprises from my race

I crossed the finish line, stopped to get my medal, then was waiting for my brother-in-law to finish another lap (he ran the 100k: 62 miles) before Scott and I left. I sat down for 30 minutes and then walked to the car, but despite sitting for a while, I was not as stiff and sore as I expected. And getting home after a 3.5 hour car ride…again I was shocked at how minimally stiff I was walking into the house. The next morning? More surprises at how little stiff and sore I was. By day 3, I felt like I had run a normal week the week prior. So in general, I think this is reinforcement that I trained really well for the distance and my long runs up to 50k and the short to medium next day runs also likely helped. I physically recovered well, which is again part training but also probably better fueling during the race, and of course now digesting everything that I ate during and after the race with enzyme supplementation for EPI!

However, the interesting (almost negative, but mostly interesting) thing for me has been what I perceived to be adrenal-type fatigue or stress hormone fatigue. I think it’s because I was unused to focusing on challenging trail conditions for so many hours, compared to running the same length of hours on “easy” paved or gravel trails. I actually didn’t listen to an audiobook, music, or podcast for about half of the race, because I was so stimulated by the course itself. What I feel is adrenal fatigue isn’t just being physically or mentally tired but something different that I haven’t experienced before. I’m listening to my body and resting a lot, and I waited until day 4 to do my first easy, slow run with much longer walk intervals (30s run, 90s walk instead of my usual 30:60). Day 1 and 2 had a lot of fatigue and I didn’t feel like doing much, Day 3 had notable improvement on fatigue and my legs and body physically felt back to normal for me. Day 4 I ran slowly, Day 5 I stuck with walking and felt more fatigue but no physical issues, Day 6 again I chose to walk because I didn’t feel like my energy had fully returned. I’ll probably stick with easy, longer walk interval runs for the next week or two with fewer days running until I feel like my fatigue is gone.

General thoughts about ultramarathon training and effective ultra race preparation

I think preparation makes a difference in ultramarathon running. Or maybe that’s just my personality? But a lot of my goal for this race was to learn what I could about the course and the race setup, imagine and plan for the experience I wanted, plan for problem solving (blisters, fuel, enzymes, BGs, etc), and be ready and able to adapt while being aware that I’d likely be tired and mentally fatigued. Generally, any preparation I could do in terms of deciding and making plans, preparing supplies, etc would be beneficial.

Some of the preparation included making lists in the weeks prior about the supplies I’d need in my pack, what Scott should have to refill my pack, what I’d need the night and morning before since we would not be at home, and after-race supplies for the 3.5h drive home.

From the lists, the week before the race I began grouping things. I had my running pack filled and ready to go. I packed my race outfit in a gallon bag, a full set of backup clothes in another gallon bag and labeled them, along with a separate post-run outfit and flip flops for the drive home. I also included a washcloth for wiping sweat or mud off after the run, and I certainly ended up needing that! I packed an extra pair of shoes and about 4 extra pairs of socks. I also had separate baggies with bandaids of different sizes, pre-cut strips of kinesio tape for my leg and smaller patches for blisters, extra squirrel nut butter sticks for anti-chafing purposes, as well as extra lambs wool (that I lay across the top of my toes to prevent socks from rubbing when they get wet from sweat or…river crossings, plus I can use it for padding between my toes or other blister-developing spots). I had sunscreen, bug spray, sungless, rain hat, and my sunny-weather running visor that wicks away sweat. I had low BG carbs for me to put in my pockets, a backup bag for Scott to refill, and a backup to the backup. The same for my fuel stash: my backpack was packed, I packed a small baggie for Scott as well as a larger bag with 5-7 of everything I thought I might want, and also an emergency backup baggie of enzymes.

*The only thing I didn’t have was a backup baggie of electrolyte pills. Next time, I’ll add this to my list and treat them like enzymes to make sure I have a separate backup stash.

I even made a list and gave it to Scott that mapped out where key things were for during and after the race. I don’t think he had to use it, because he was only digging through the snack bag for waffles and Fritos, but I did that so I didn’t have to remember where I had put my extra socks or my spare bandaids, etc. He basically had a map of what was in each larger bag. All of this was to reduce the decision and communication because I knew I’d have decision fatigue.

This also went for post-race planning. I told Scott to encourage me to change clothes, and it was worth the energy to change so I didn’t sit in cold, wet clothes for the long drive home. I pre-made a gluten free ham and cheese quesadilla (take two tortillas, fill with shredded cheese and slices of ham, microwave, cut into quarters, stick in baggies, mark with fat/protein/carb counts, and refrigerate) so we could warm that up in the car (this is what I use) so I had something to eat on the way home that wasn’t more Fritos or waffles. I didn’t end up wanting it, but I also brought a can of beef stew with carrots and potatoes, that I generally like as a post-race or post-run meal, and a plastic container and a spoon so I could warm up the stew if I wanted it. Again, all of this pre-planned and put on the list weeks prior to the race so I didn’t forget things like the container or the spoon.

The other thing I think about a lot is practicing everything I want to do for a race during a training run. People talk about eating the same foods, wearing the same clothes, etc. I think for those of us with type 1 diabetes (or celiac, EPI, or anything else), it’s even more important. With T1D, it’s so helpful to have the experience adjusting to changing BG levels and knowing what to do when you’re dropping or low and having a snack, vs in range and having a fueling snack, or high and having a fueling snack. I had 100% TIR during this run, but I didn’t have that during all of my training runs. Sometimes I’d plateau around 180 mg/dL and be over-cautious and not bring my BGs down effectively; other times I’d overshoot and cause a drop that required extra carbs to prevent or minimize a low. Lots of practice went into making this 100% TIR day happen, and some of it was probably a bit of luck mixed in with all the practice!

But generally, practice makes it a lot easier to know what to do on the fly during a race when you’re tired, stressed, and maybe crossing an icy cold river that wasn’t supposed to be part of your course experience. All that helps you make the best possible decisions in the weirdest of situations. That’s the best you can hope for with ultrarunning!

Findings from the world’s first RCT on open source AID (the CREATE trial) presented at #ADA2022

September 7, 2022 UPDATEI’m thrilled to share that the paper with the primary outcomes from the CREATE trial is now published. You can find it on the journal site here, or view an author copy here. You can also see a Twitter thread here, if you are interested in sharing the study with your networks.

Example citation:

Burnside, M; Lewis, D; Crocket, H; et al. Open-Source Automated Insulin Delivery in Type 1 Diabetes. N Engl J Med 2022;387:869-81. DOI:10.1056/NEJMoa2203913


(You can also see a previous Twitter thread here summarizing the study results, if you are interested in sharing the study with your networks.)

TLDR: The CREATE Trial was a multi-site, open-labeled, randomized, parallel-group, 24-week superiority trial evaluating the efficacy and safety of an open-source AID system using the OpenAPS algorithm in a modified version of AndroidAPS. Our study found that across children and adults, the percentage of time that the glucose level was in the target range of 3.9-10mmol/L [70-180mg/dL] was 14 percentage points higher among those who used the open-source AID system (95% confidence interval [CI], 9.2 to 18.8; P<0.001) compared to those who used sensor augmented pump therapy; a difference that corresponds to 3 hours 21 minutes more time spent in target range per day. The system did not contribute to any additional hypoglycemia. Glycemic improvements were evident within the first week and were maintained over the 24-week trial. This illustrates that all people with T1D, irrespective of their level of engagement with diabetes self-care and/or previous glycemic outcomes, stand to benefit from AID. This study concluded that open-source AID using the OpenAPS algorithm within a modified version of AndroidAPS, a widely used open-source AID solution, is efficacious and safe.

The backstory on this study

We developed the first open source AID in late 2014 and shared it with the world as OpenAPS in February 2015. It went from n=1 to (n=1)*2 and up from there. Over time, there were requests for data to help answer the question “how do you know it works (for anybody else)?”. This led to the first survey in the OpenAPS community (published here), followed by additional retrospective studies such as this one analyzing data donated by the community,  prospective studies, and even an in silico study of the algorithm. Thousands of users chose open source AID, first because there was no commercial AID, and later because open source AID such as the OpenAPS algorithm was more advanced or had interoperability features or other benefits such as quality of life improvements that they could not find in commercial AID (or because they were still restricted from being able to access or afford commercial AID options). The pile of evidence kept growing, and each study has shown safety and efficacy matching or surpassing commercial AID systems (such as in this study), yet still, there was always the “but there’s no RCT showing safety!” response.

After Martin de Bock saw me present about OpenAPS and open source AID at ADA Scientific Sessions in 2018, we literally spent an evening at the dinner table drawing the OpenAPS algorithm on a napkin at the table to illustrate how OpenAPS works in fine grained detail (as much as one can do on napkin drawings!) and dreamed up the idea of an RCT in New Zealand to study the open source AID system so many were using. We sought and were granted funding by New Zealand’s Health Research Council, published our protocol, and commenced the study.

This is my high level summary of the study and some significant aspects of it.

Study Design:

This study was a 24-week, multi-centre randomized controlled trial in children (7–15 years) and adults (16–70 years) with type 1 diabetes comparing open-source AID (using the OpenAPS algorithm within a version of AndroidAPS implemented in a smartphone with the DANA-i™ insulin pump and Dexcom G6® CGM), to sensor augmented pump therapy. The primary outcome was change in the percent of time in target sensor glucose range (3.9-10mmol/L [70-180mg/dL]) from run-in to the last two weeks of the randomized controlled trial.

  • This is a LONG study, designed to look for rare adverse events.
  • This study used the OpenAPS algorithm within a modified version of AndroidAPS, meaning the learning objectives were adapted for the purpose of the study. Participants spent at least 72 hours in “predictive low glucose suspend mode” (known as PLGM), which corrects for hypoglycemia but not hyperglycemia, before proceeding to the next stage of closed loop which also then corrected for hyperglycemia.
  • The full feature set of OpenAPS and AndroidAPS, including “supermicroboluses” (SMB) were able to be used by participants throughout the study.

Results:

Ninety-seven participants (48 children and 49 adults) were randomized.

Among adults, mean time in range (±SD) at study end was 74.5±11.9% using AID (Δ+ 9.6±11.8% from run-in; P<0.001) with 68% achieving a time in range of >70%.

Among children, mean time in range at study end was 67.5±11.5% (Δ+ 9.9±14.9% from run-in; P<0.001) with 50% achieving a time in range of >70%.

Mean time in range at study end for the control arm was 56.5±14.2% and 52.5±17.5% for adults and children respectively, with no improvement from run-in. No severe hypoglycemic or DKA events occurred in either arm. Two participants (one adult and one child) withdrew from AID due to frustrations with hardware issues.

  • The pump used in the study initially had an issue with the battery, and there were lots of pumps that needed refurbishment at the start of the study.
  • Aside from these pump issues, and standard pump site/cannula issues throughout the study (that are not unique to AID), there were no adverse events reported related to the algorithm or automated insulin delivery.
  • Only two participants withdrew from AID, due to frustration with pump hardware.
  • No severe hypoglycemia or DKA events occurred in either study arm!
  • In fact, use of open source AID improved time in range without causing additional hypoglycemia, which has long been a concern of critics of open source (and all types of) AID.
  • Time spent in ‘level 1’ and ‘level 2’ hyperglycemia was significantly lower in the AID group as well compared to the control group.

In the primary analysis, the mean (±SD) percentage of time that the glucose level was in the target range (3.9 – 10mmol/L [70-180mg/dL]) increased from 61.2±12.3% during run-in to 71.2±12.1% during the final 2-weeks of the trial in the AID group and decreased from 57.7±14.3% to 54±16% in the control group, with a mean adjusted difference (AID minus control at end of study) of 14.0 percentage points (95% confidence interval [CI], 9.2 to 18.8; P<0.001). No age interaction was detected, which suggests that adults and children benefited from AID similarly.

  • The CREATE study found that across children and adults, the percentage of time that the glucose level was in the target range of 3.9-10mmol/L [70-180mg/dL] was 14.0 percentage points higher among those who used the open-source AID system compared to those who used sensor augmented pump therapy.
  • This difference reflects 3 hours 21 minutes more time spent in target range per day!
  • For children AID users, they spent 3 hours 1 minute more time in target range daily (95% CI, 1h 22m to 4h 41m).
  • For adult AID users, they spent 3 hours 41 minutes more time in target range daily (95% CI, 2h 4m to 5h 18m).
  • Glycemic improvements were evident within the first week and were maintained over the 24-week trial. Meaning: things got better quickly and stayed so through the entire 24-week time period of the trial!
  • AID was most effective at night.
Difference between control and AID arms overall, and during day and night separately, of TIR for overall, adults, and kids

One thing I think is worth making note of is that one criticism of previous studies with open source AID is regarding the self-selection effect. There is the theory that people do better with open source AID because of self-selection and self-motivation. However, the CREATE study recruited a diverse cohort of participants, and the study findings (as described above) match all previous reports of safety and efficacy outcomes from previous studies. The CREATE study also found that the greatest improvements in TIR were seen in participants with lowest TIR at baseline. This means one major finding of the CREATE study is that all people with T1D, irrespective of their level of engagement with diabetes self-care and/or previous glycemic outcomes, stand to benefit from AID.

This therefore means there should be NO gatekeeping by healthcare providers or the healthcare system to restrict AID technology from people with insulin-requiring diabetes, regardless of their outcomes or experiences with previous diabetes treatment modalities.

There is also no age effect observed in the trail, meaning that the results of the CREATE Trial demonstrated that open-source AID is safe and effective in children and adults with type 1 diabetes. If someone wants to use open source AID, they would likely benefit, regardless of age or past diabetes experiences. If they don’t want to use open source AID or commercial AID…they don’t have to! But the choice should 100% be theirs.

In summary:

  • The CREATE trial was the first RCT to look at open source AID, after years of interest in such a study to complement the dozens of other studies evaluating open source AID.
  • The conclusion of the CREATE trial is that open-source AID using the OpenAPS algorithm within a version of AndroidAPS, a widely used open-source AID solution, appears safe and effective.
  • The CREATE trial found that across children and adults, the percentage of time that the glucose level was in the target range of 3.9-10mmol/L [70-180mg/dL] was 14.0 percentage points higher among those who used the open-source AID system compared to those who used sensor augmented pump therapy; a difference that reflects 3 hours 21 minutes more time spent in target range per day.
  • The study recruited a diverse cohort, yet still produced glycemic outcomes consistent with existing open-source AID literature, and that compare favorably to commercially available AID systems. Therefore, the CREATE Trial indicates that a range of people with type 1 diabetes might benefit from open-source AID solutions.

Huge thanks to each and every participant and their families for their contributions to this study! And ditto, big thanks to the amazing, multidisciplinary CREATE study team for their work on this study.


September 7, 2022 UPDATE – I’m thrilled to share that the paper with the primary outcomes from the CREATE trial is now published. You can find it on the journal site here, or like all of the research I contribute to, access an author copy on my research paper.

Example citation:

Burnside, M; Lewis, D; Crocket, H; et al. Open-Source Automated Insulin Delivery in Type 1 Diabetes. N Engl J Med 2022;387:869-81. DOI:10.1056/NE/Moa2203913

Note that the continuation phase study results are slated to be presented this fall at another conference!

Findings from the RCT on open source AID, the CREATE Trial, presented at #ADA2022

Everything I did wrong (but did anyway) training for a marathon after a broken ankle and marathon running with type 1 diabetes

This is another one of those posts for a niche audience. If you found this post, you’re likely looking for information about:

  • Running after a broken ankle (or are coming from my “tips for returning to weight bearing” and looking for an update from me, two years after my trimalleolar ankle fracture)
  • Running with the “Galloway method”, also known as run-walk or run/walk methods for marathon or similar long distances – but with information about run-walking for slow runners.
  • Running a marathon with type 1 diabetes, or running an ultra with type 1 diabetes
  • Running a marathon and training for a marathon and going without fuel or less fuel
    *Update: also running an ultramarathon with the same methods (less fuel than typical)!

There’s a bit of all of this in the post! (But TLDR – I ran my marathon (finally), successfully, despite having a previously broken ankle. And despite running it with type 1 diabetes, I had no issues managing my blood sugars during even the longest training runs, even with significantly less fuel than is typically used by marathon runners. I also ran a 50k ultra using the same methods!)

running a marathon after a broken ankle and with type 1 diabetes

First up, some context that explains why I chose run-walking as my method of running a marathon (as that also influences fueling choices) and what it is like to be a slow marathon runner (6 hour marathon ish). I broke my ankle in January 2019 and began running very tiny amounts (literally down the block to start) in summer 2019. I progressed, doing a short run interval followed by a walk interval, increasing the total numbers of intervals, and then slowly progressing to extend the length (distance and/or time) of the running intervals. In early fall 2019, I was attempting a couch-to-5k type program where I would extend my running intervals even longer, but I still had subsequent injuries (a very stubborn big toe joint, then intermetatarsal bursitis in TWO spots (argh)) that made this not work well. Eventually, I went back to running 30 seconds and walking 30 seconds, then keeping those “short” intervals and extending my run. I focused on time at first: going from 5 to 10 to 15 to 20 etc minutes, rather than focusing on distance. Once I built up to about 30 minutes of run-walking (30:30, meaning running 30 seconds and walking 30 seconds), I switched to adding a quarter or half mile each time depending on how I was feeling. But doing 30:30 seemed to work really well for me in terms of the physical impact to my feet, even with long miles, and also mentally, so I stuck with it. (You can go read about the Galloway run-walk-run method for more about run-walking; most people build up to running more, say 5 minutes or 8 minutes followed by a minute of walking, or maybe run 1 mile and then walk for a minute, or walk through the aid stations, but I found that 30:30 is what I liked and stuck with it or 60:30 as my longest intervals.)

This worked so well for me that I did not think about my right ankle a single time during or after my marathon! It took days to even remember that I had previously broken my ankle and it could’ve been problematic or weaker than my other ankle during my marathon. It took a long time to get to this point – I never thought I’d be forgetting even for a few days about my broken ankle! But two years later, I did.)

When COVID-19 struck, and as someone who paid attention early (beginning late January 2020), I knew my marathon would not be taking place in July 2020 and would be postponed until 2021. So I focused on keeping my feet healthy and building up a running “base” of trying to stay healthy feet-wise running twice a week into fall 2020, which worked fairly well. At the start of 2021, I bumped up to three runs a week consistently, and eventually began making one run every other a week longer. My schedule looked something like this:

Monday – 3 miles  Wednesday – 3 miles   Friday – 3 miles

Monday – 4 miles  Wednesday – 3 miles   Friday – 3 miles

Monday – 5 miles  Wednesday – 3 miles   Friday – 3 miles

Monday – 6 miles  Wednesday – 3 miles   Friday – 3 miles

Monday – (back to) 3 miles  Wednesday – 3 miles   Friday – 3 miles

Monday – 8 miles  Wednesday – 3 miles   Friday – 3 miles

Monday – (back to) 3  miles  Wednesday – 5 miles   Friday – 4 miles

Monday – 10 miles  Wednesday – 3 miles   Friday – 3 miles

Note that these runs I refer to were all technically run-walks, where I ran 30 seconds and walked 30 seconds (aka 30:30) until I covered the miles. I was running slow and easy, focusing on keeping my heart rate below its maximum and not worrying about speed, so between that and run-walking I was often doing 15m30s miles. Yes, I’m slow. This all enabled me to build up to safely be able to run 3 runs weekly at first, and then eventually progressed to adding a fourth run. When I added a fourth run, I was very conservative and started with only 1 mile for two weeks in a row, then 2 miles, then up to 3 miles. Eventually, later in my training, I had some of my other runs in the week be a bit longer (4-5 miles) in addition to my “long” run.

But, because I’m so slow, this means it takes a lot of time to run my long runs. If you estimate a 15-minute mile for easy math, that means an 8 mile “long” run would take at least 2 hours. With marathon training (and my goal to train up to multiple 22-24 mile runs before the marathon), that took A LOT of time. And, because of my broken ankle and intermetatarsal experiences from 2019, I was very cautious and conservative about taking care of my feet during training. So instead of following the usual progression of long runs increasing 2-3 weeks in a row, followed by a “cutback” long week, after I hit two hours of long running (essentially 8 miles, for me), I started doing long runs every other week. The other week was a “cutback” long run, which was usually 8 miles, 10 miles (for several weeks), up to eventually 12-14. In terms of “time on feet”, this meant 2-3 hours “cutback” long runs, which according to many people is the max you should be running for marathon training. That doesn’t quite work for slow runners such as myself where you might be doing a 6-hour marathon or 7-hour marathon or thereabouts. (The standard advice also maybe doesn’t apply when you are doing run-walking for your marathon training.)

I had ~6 months to build up to my marathon (from January to the end of July), so I had time to do this, which gave me a buffer in my overall training schedule in case of scheduling conflicts (which happened twice) and in case of injury (which thankfully didn’t happen). I ended up scheduling training long runs all the way to full marathon distance (26ish miles), because I wanted to practice my fueling (especially important for type 1 diabetes marathon runners, which I’ll talk about next) as well as get my feet used to that many hours of run-walking. I did my long runs without care for speed, so some of them were closer to 16-minute mile averages, some were around 15-minute mile averages for the entire run, and the day I ran the full marathon course for training I ended up doing 16+ minute miles and felt fabulous at the end.

I ended up doing a few “faster” “shorter” long runs (on my cutback weeks), where I would do a half marathon-ish distance on the actual marathon course (a public trail), and try to go faster than my super slow long run pace. I had several successful runs where I was at or near marathon pace (which for me would be around 13m30s). So yes, you can train slow and run fast for a marathon, even without much speed work, and even if you are doing a run-walk method, and even if you’re as slow as I am. Running ~15-minute miles took forever but kept my feet and body healthy and happy through marathon training, and I was still able to achieve my sub-6 hour marathon goal (running 13:41 average pace for 26.2+ miles) on race day.

Now let’s talk about fueling, and in particular fueling for people with type 1 diabetes and for people wondering if the internet is right about what fueling requirements are for marathon runners.

I previously wrote (for a T1D audience) about running when fasted, because then you don’t have to deal with insulin on board at the start of a run. That’s one approach, and another approach is to have a smaller meal or snack with fewer carbs before the run, and time your run so that you don’t need to bolus or inject for that meal before you start your run. That’s what I chose for most of my marathon training, especially for longer runs.

On a typical non-running day, I would eat breakfast (½ cup pecans, ¼ cup cranberries, and a few sticks of cheese), my OpenAPS rig would take care of insulin dosing (or I could bolus for it myself), and my BGs would be well managed. However, that would mean I had a lot of insulin on board (IOB) if I tried to run within an hour of that. So instead, during marathon training, I ended up experimenting with eating a smaller amount of pecans (¼ cup) and no cranberries, not bolusing or letting OpenAPS bolus, and running an hour later. I had a small BG rise from the protein (e.g. would go from 100 mg/dL flat overnight to 120-130 mg/dL), and then running would balance out the rest of it.

I generally would choose to target my blood sugar to 130 mg/dL at the start of long runs, because I prefer to have a little bit of buffer for if/when my blood sugar began to drop. I also figured out that if I wasn’t having IOB from breakfast, I did not need to reduce my insulin much in advance of the run, but do it during the duration of the run. Therefore, I would set a higher temporary target in my OpenAPS rig, and if I was doing things manually, I would set a temporary basal rate on my insulin pump to about ⅓ of my usual hourly rate for the duration of the run. That worked well because by the time the beginning of my run (30-45 minutes) brought my BG down a little bit from the start with the protein breakfast bump (up to 130 mg/dL or so), that’d also be when the reduced insulin effect would be noticeable, and I would generally stay flat instead of having a drop at the beginning or first hour of my run.

After my first hour or so, I just kept an eye periodically on my blood sugars. My rule of thumb was that if my BG drifted down below 120 mg/dL, I would eat a small amount of carbs. My carb of choice was an individually wrapped peppermint (I stuffed a bunch in my pocket for the run) that was 3-4g of carb. If I kept drifting down or hadn’t come back up to 120 mg/dL 10-15 minutes later, I would do another. Obviously, if I was dropping fast I would do more, but 75% of the time I only needed one peppermint (3-4g of carb) to pause a drift down. If you have a lot of insulin on board, it would take more carbs, but my method of not having IOB at the start of long runs worked well for me. Sometimes, I would run my entire long run with no carbs and no fuel (other than water, and eventually electrolyte pills). Part of this is likely due to the fact that I was run-walking at such low intensity (remember 15-ish minute miles), but part of this is also due to figuring out the right amount of insulin I needed for endurance running and making sure I didn’t have excess insulin on board. On my faster runs (my half marathon distance fast training runs, that were 2+ minutes/mile faster than my slow long runs) and my marathon itself, I ended up needing more carbs than a super slow run – but it ended up being about 30 grams of carbohydrate TOTAL.

Why am I emphasizing this?

Well, the internet says (and most coaches, training plans, etc) that you need 30g of carbs PER HOUR. And that you need to train your stomach to tolerate that many carbs, because your muscles and brain need it. And without that much fuel, you will ‘hit the wall’.

My hypothesis, which may be nuanced by having type 1 diabetes and wearing a CGM and being able to track my data closely and manage it not only by carbs but also titrating insulin levels (which someone without diabetes obviously can’t do), is that you don’t necessarily need that many carbs, even for endurance running or marathon running.

I’m wondering if there’s a correlation between people who max out their long runs around 16-20 miles and who then “hit the wall” around mile 20 of a marathon. Perhaps some of it is muscle fatigue because they haven’t trained for the distance and some of it is psychological of feeling the brain fatigue.

During my marathon, in which I ran 2+ min/mi faster than most of my training runs, I did not ever experience hypoglycemia, and I did not “hit the wall”. Everything hurt, but I didn’t “hit the wall” as most people talk about. Those might be related, or it might be influenced by the fact that I had done a 20, 22, 24, 26, and another 21 mile run as part of my training, so my legs were “used” to the 20+ mile distance?

So again – some of my decreased fueling needs may be because I was already reducing my insulin and balancing my blood sugars (really well), and if my blood sugar was low (hypoglycemia), I would’ve needed more carbs. Or you can argue my lower fueling needs are because I’m so slow (15-16 minute mile training runs, or a 13m40s marathon pace). But in any case, I wanted to point out that if the fueling advice you’re getting or reading online seems like it’s “too much” per hour, there are people who are successful in hitting their time goals and don’t hit the wall on lower fueling amounts, too. You don’t necessarily have to fuel for the sake of fueling.

Note that I am not doing “low carb” or “keto” or anything particular diet-wise (other than eating gluten-free, because I also have celiac disease) outside of my running fuel choices. This was a successful strategy for me, and I eat what might be considered a moderate carb diet outside of running fuel choices.

Ps – if you don’t fuel (carbs or other nutrients) during your runs, don’t forget about your electrolytes. I decided to keep drinking water out of a Camelbak in a running pack, rather than filling it with Gatorade or a similar electrolyte drink, but I’m pretty electrolyte sensitive so I needed to do something to replace them. I got electrolyte pills and would take them every 30 minutes or so on long training runs when it was hotter. Play around with timing on those: if you don’t sweat a lot or aren’t a salty sweater, you may not need as many as often. I ended up doing the bulk of my long runs on hot days, and I sweat a lot, so every 30 minutes was about right for me. On cooler runs, one per hour was sufficient for me. (I tried these chewable tabs in lemon-lime but didn’t like the salt feeling directly in my mouth; I ended up buying these to swallow instead: I didn’t have any digestion issues or side effects from them, and they successfully kept my electrolytes to manageable levels. The package says not to take more than 10 within a 24 hour period, but I ended up taking 12 for my longest training run and the marathon itself and suffered no ill effects. It’s probably set to max 10 because of the amount of salt compared to the typical daily amount needed..but obviously, if you’re doing endurance running you need more than the daily amount of salt you would need on a regular day. But I’m not a doctor and this isn’t medical advice, of course – I’m just telling you what I chose to do).

In terms of training, here’s everything the internet told me to do for marathon training and everything I did “wrong” according to the typical advice:

  • Your long run should be 20-30% of your overall weekly mileageWhat I did: Sometimes my long runs got up to 70% of my weekly mileage, because I was only running 3 and then 4 days a week, and not doing very long mid-week runs.
  • Have longer mid-week runs, and build those up in addition to your true long runWhat I did: I did build up to a few 5-6 mile mid-week runs, but I chose consistency of my 4 runs per week rather than overdoing it with mid-week medium runs
  • Run 5-6 days a weekWhat I did: Only run 4 times a week, because I wanted a rest day after each run, and wanted a rest day prior to my longest run. I ran Monday, Wednesday, Friday, then added Saturday short runs. Monday was my long run (because I have the benefit of a flexible schedule for work).
  • Get high mileage (start from a base of 30-40 miles a week and build up to 50-60 miles!)What I did: I started with a “base” of 10 miles a week with two runs that I was very proud of. I went to three runs a week, and then 4. My biggest running week during training was 40.55 miles, although they were all 20+ mile weeks (long or cutback weeks) after the first two months of training.
  • Do progressively longer long runs for two or three weeks in a row and then do one cutback week, then continue the progressionWhat I did: Because of the time on my feet cost of being a slower runner, I did an every-other-week long-run progression alternating with a shorter cutback week.
  • Long run, tempo run, speed work, etc. plus easy runs! All the things each week!What I did: a long run per week, then the rest of my runs were usually easy runs. I tried a handful of times to do some “speed” work, but I often time was trying to keep my feet from being injured and it felt like running faster caused my feet to be sore or have other niggles in my legs, so I didn’t do much of that, other than doing some “cutback” long runs (around half marathon distance, as well as my last 21-mile run) at close to marathon pace to get a feel for how it felt to run at that pace for longer.

TLDR, again:

I signed up for a marathon in fall 2018 planning to run it in July 2019 but was thwarted by a broken ankle in January 2019 and COVID-19(/20) for 2020, so I ultimately trained for and ran it in July 2021. I am a slow runner, and I was able to achieve my sub-6 hour marathon goal using run-walk and without causing additional injury to my feet. And, because of my “slow” or less intense running, I needed a lot less fuel than is typically recommended for marathoners, and still managed my blood glucose levels within my ideal target ranges despite 5, 6, and even 7 hours run on my feet. Yes, you can run marathons with type 1 diabetes. And yes, you can run any length endurance runs with type 1 diabetes! I also ran a 50k ultramarathon using the same methods.

Poster and presentation content from @DanaMLewis at #ADA2020 and #DData20

In previous years (see 2019 and 2018), I mentioned sharing content from ADA Scientific Sessions (this year it’s #ADA2020) with those not physically present at the conference. This year, NO ONE is present at the event, and we’re all virtual! Even more reason to share content from the conference. :)

I contributed to and co-authored two different posters at Scientific Sessions this year:

  • “Multi-Timescale Interactions of Glucose and Insulin in Type 1 Diabetes Reveal Benefits of Hybrid Closed Loop Systems“ (poster 99-LB) along with Azure Grant and Lance Kriegsfeld, PhD.
  • “Do-It-Yourself Artificial Pancreas Systems for Type 1 Diabetes Reduce Hyperglycemia Without Increasing Hypoglycemia” (poster 988-P in category 12-D Clinical Therapeutics/New Technology—Insulin Delivery Systems), alongside Jennifer Zabinsky, MD MEng, Haley Howell, MSHI, Alireza Ghezavati, MD, Andrew Nguyen, PhD, and Jenise Wong, MD PhD.

And, while not a poster at ADA, I also presented the “AID-IRL” study funded by DiabetesMine at #DData20, held in conjunction with Scientific Sessions. A summary of the study is also included in this post.

First up, the biological rhythms poster, “Multi-Timescale Interactions of Glucose and Insulin in Type 1 Diabetes Reveal Benefits of Hybrid Closed Loop Systems” (poster 99-LB). (Twitter thread summary of this poster here.)

Building off our work as detailed last year, Azure, Lance, and I have been exploring the biological rhythms in individuals living with type 1 diabetes. Why? It’s not been done before, and we now have the capabilities thanks to technology (pumps, CGM, and closed loops) to better understand how glucose and insulin dynamics may be similar or different than those without diabetes.

Background:

Mejean et al., 1988Blood glucose and insulin exhibit coupled biological rhythms at multiple timescales, including hours (ultradian, UR) and the day (circadian, CR) in individuals without diabetes. The presence and stability of these rhythms are associated with healthy glucose control in individuals without diabetes. (See right, adapted from Mejean et al., 1988).

However, biological rhythms in longitudinal (e.g., months to years) data sets of glucose and insulin outputs have not been mapped in a wide population of people with Type 1 Diabetes (PWT1D). It is not known how glucose and insulin rhythms compare between T1D and non-T1D individuals. It is also unknown if rhythms in T1D are affected by type of therapy, such as Sensor Augmented Pump (SAP) vs. Hybrid Closed Loop (HCL). As HCL systems permit feedback from a CGM to automatically adjust insulin delivery, we hypothesized that rhythmicity and glycemia would exhibit improvements in HCL users compared to SAP users. We describe longitudinal temporal structure in glucose and insulin delivery rate of individuals with T1D using SAP or HCL systems in comparison to glucose levels from a subset of individuals without diabetes.

Data collection and analysis:

We assessed stability and amplitude of normalized continuous glucose and insulin rate oscillations using the continuous wavelet transformation and wavelet coherence. Data came from 16 non-T1D individuals (CGM only, >2 weeks per individual) from the Quantified Self CGM dataset and 200 (n = 100 HCL, n = 100 SAP; >3 months per individual) individuals from the Tidepool Big Data Donation Project. Morlet wavelets were used for all analyses. Data were analyzed and plotted using Matlab 2020a and Python 3 in conjunction with in-house code for wavelet decomposition modified from the “Jlab” toolbox, from code developed by Dr. Tanya Leise (Leise 2013), and from the Wavelet Coherence toolkit by Dr. Xu Cui. Linear regression was used to generate correlations, and paired t-tests were used to compare AUC for wavelet and wavelet coherences by group (df=100). Stats used 1 point per individual per day.

Wavelets Assess Glucose and Insulin Rhythms and Interactions

Wavelet Coherence flow for glucose and insulin

Morlet wavelets (A) estimate rhythmic strength in glucose or insulin data at each minute in time (a combination of signal amplitude and oscillation stability) by assessing the fit of a wavelet stretched in window and in the x and y dimensions to a signal (B). The output (C) is a matrix of wavelet power, periodicity, and time (days). Transform of example HCL data illustrate the presence of predominantly circadian power in glucose, and predominantly 1-6 h ultradian power in insulin. Color map indicates wavelet power (synonymous with Y axis height). Wavelet coherence (D) enables assessment of rhythmic interactions between glucose and insulin; here, glucose and insulin rhythms are highly correlated at the 3-6 (ultradian) and 24 (circadian) hour timescales.

Results:

Hybrid Closed Loop Systems Reduce Hyperglycemia

Glucose distribution of SAP, HCL, and nonT1D
  • A) Proportional counts* of glucose distributions of all individuals with T1D using SAP (n=100) and HCL (n=100) systems. SAP system users exhibit a broader, right shifted distribution in comparison to individuals using HCL systems, indicating greater hyperglycemia (>7.8 mmol/L). Hypoglycemic events (<4mmol/L) comprised <5% of all data points for either T1D dataset.
  • B) Proportional counts* of non-T1D glucose distributions. Although limited in number, our dataset from people without diabetes exhibits a tighter blood glucose distribution, with the vast majority of values falling in euglycemic range (n=16 non-T1D individuals).
  • C) Median distributions for each dataset.
  • *Counts are scaled such that each individual contributes the same proportion of total data per bin.

HCL Improves Correlation of Glucose-Insulin Level & Rhythm

Glucose and Insulin rhythms in SAP and HCL

SAP users exhibit uncorrelated glucose and insulin levels (A) (r2 =3.3*10-5; p=0.341) and uncorrelated URs of glucose and insulin (B) (r2 =1.17*10-3; p=0.165). Glucose and its rhythms take a wide spectrum of values for each of the standard doses of insulin rates provided by the pump, leading to the striped appearance (B). By contrast, Hybrid Closed Loop users exhibit correlated glucose and insulin levels (C) (r2 =0.02; p=7.63*10-16), and correlated ultradian rhythms of glucose and insulin (D) (r2 =-0.13; p=5.22*10-38). Overlays (E,F).

HCL Results in Greater Coherence than SAP

Non-T1D individuals have highly coherent glucose and insulin at the circadian and ultradian timescales (see Mejean et al., 1988, Kern et al., 1996, Simon and Brandenberger 2002, Brandenberger et al., 1987), but these relationships had not previously been assessed long-term in T1D.

coherence between glucose and insulin in HCL and SAP, and glucose swings between SAP, HCL, and non-T1DA) Circadian (blue) and 3-6 hour ultradian (maroon) coherence of glucose and insulin in HCL (solid) and SAP (dotted) users. Transparent shading indicates standard deviation. Although both HCL and SAP individuals have lower coherence than would be expected in a non-T1D individual,  HCL CR and UR coherence are significantly greater than SAP CR and UR coherence (paired t-test p= 1.51*10-7 t=-5.77 and p= 5.01*10-14 t=-9.19, respectively). This brings HCL users’ glucose and insulin closer to the canonical non-T1D phenotype than SAP users’.

B) Additionally, the amplitude of HCL users’ glucose CRs and URs (solid) is closer (smaller) to that of non-T1D (dashed) individuals than are SAP glucose rhythms (dotted). SAP CR and UR amplitude is significantly higher than that of HCL or non-T1D (T-test,1,98, p= 47*10-17 and p= 5.95*10-20, respectively), but HCL CR amplitude is not significantly different from non-T1D CR amplitude (p=0.61).

Together, HCL users are more similar than SAP users to the canonical Non-T1D phenotype in A) rhythmic interaction between glucose and insulin and B) glucose rhythmic amplitude.

Conclusions and Future Directions

T1D and non-T1D individuals exhibit different relative stabilities of within-a-day rhythms and daily rhythms in blood glucose, and T1D glucose and insulin delivery rhythmic patterns differ by insulin delivery system.

Hybrid Closed Looping is Associated With:

  • Lower incidence of hyperglycemia
  • Greater correlation between glucose level and insulin delivery rate
  • Greater correlation between ultradian glucose and ultradian insulin delivery rhythms
  • Greater degree of circadian and ultradian coherence between glucose and insulin delivery rate than in SAP system use
  • Lower amplitude swings at the circadian and ultradian timescale

These preliminary results suggest that HCL recapitulates non-diabetes glucose-insulin dynamics to a greater degree than SAP. However, pump model, bolusing data, looping algorithms and insulin type likely all affect rhythmic structure and will need to be further differentiated. Future work will determine if stability of rhythmic structure is associated with greater time in range, which will help determine if bolstering of within-a-day and daily rhythmic structure is truly beneficial to PWT1D.
Acknowledgements:

Thanks to all of the individuals who donated their data as part of the Tidepool Big Data Donation Project, as well as the OpenAPS Data Commons, from which data is also being used in other areas of this study. This study is supported by JDRF (1-SRA-2019-821-S-B).

(You can download a full PDF copy of the poster here.)

Next is “Do-It-Yourself Artificial Pancreas Systems for Type 1 Diabetes Reduce Hyperglycemia Without Increasing Hypoglycemia” (poster 988-P in category 12-D Clinical Therapeutics/New Technology—Insulin Delivery Systems), which I co-authored alongside Jennifer Zabinsky, MD MEng, Haley Howell, MSHI, Alireza Ghezavati, MD, Andrew Nguyen, PhD, and Jenise Wong, MD PhD. There is a Twitter thread summarizing this poster here.

This was a retrospective double cohort study that evaluated data from the OpenAPS Data Commons (data ranged from 2017-2019) and compared it to conventional sensor-augmented pump (SAP) therapy from the Tidepool Big Data Donation Project.

Methods:

  • From the OpenAPS Data Commons, one month of CGM data (with more than 70% of the month spent using CGM), as long as they were >1 year of living with T1D, was used. People could be using any type of DIYAPS (OpenAPS, Loop, or AndroidAPS) and there were no age restrictions.
  • A random age-matched sample from the Tidepool Big Data Donation Project of people with type 1 diabetes with SAP was selected.
  • The primary outcome assessed was percent of CGM data <70 mg/dL.
  • The secondary outcomes assessed were # of hypoglycemic events per month (15 minutes or more <70 mg/dL); percent of time in range (70-180mg/dL); percent of time above range (>180mg/dL), mean CGM values, and coefficient of variation.
Methods_DIYAPSvsSAP_ADA2020_DanaMLewis

Demographics:

  • From Table 1, this shows the age of participants was not statistically different between the DIYAPS and SAP cohorts. Similarly, the age at T1D diagnosis or time since T1D diagnosis did not differ.
  • Table 2 shows the additional characteristics of the DIYAPS cohort, which included data shared by a parent/caregiver for their child with T1D. DIYAPS use was an average of 7 months, at the time of the month of CGM used for the study. The self-reported HbA1c in DIYAPS was 6.4%.
Demographics_DIYAPSvsSAP_ADA2020_DanaMLewis DIYAPS_Characteristics_DIYAPSvsSAP_ADA2020_DanaMLewis

Results:

  • Figure 1 shows the comparison in outcomes based on CGM data between the two groups. Asterisks (*) indicate statistical significance.
  • There was no statistically significant difference in % of CGM values below 70mg/dL between the groups in this data set sampled.
  • DIYAPS users had higher percent in target range and lower percent in hyperglycemic range, compared to the SAP users.
  • Table 3 shows the secondary outcomes.
  • There was no statistically significant difference in the average number of hypoglycemic events per month between the 2 groups.
  • The mean CGM glucose value was lower for the DIYAPS group, but the coefficient of variation did not differ between groups.
CGM_Comparison_DIYAPSvsSAP_ADA2020_DanaMLewis SecondaryOutcomes_DIYAPSvsSAP_ADA2020_DanaMLewis

Conclusions:

    • Users of DIYAPS (from this month of sampled data) had a comparable amount of hypoglycemia to those using SAP.
    • Mean CGM glucose and frequency of hyperglycemia were lower in the DIYAPS group.
    • Percent of CGM values in target range (70-180mg/dL) was significantly greater for DIYAPS users.
    • This shows a benefit in DIYAPS in reducing hyperglycemia without compromising a low occurrence of hypoglycemia. 
Conclusions_DIYAPSvsSAP_ADA2020_DanaMLewis

(You can download a PDF of the e-poster here.)

Finally, my presentation at this year’s D-Data conference (#DData20). The study I presented, called AID-IRL, was funded by Diabetes Mine. You can see a Twitter thread summarizing my AID-IRL presentation here.

AID-IRL-Aim-Methods_DanaMLewis

I did semi-structured phone interviews with 7 users of commercial AID systems in the last few months. The study was funded by DiabetesMine – both for my time in conducting the study, as well as funding for study participants. Study participants received $50 for their participation. I sought a mix of longer-time and newer AID users, using a mix of systems. Control-IQ (4) and 670G (2) users were interviewed; as well as (1) a CamAPS FX user since it was approved in the UK during the time of the study.

Based on the interviews, I coded their feedback for each of the different themes of the study depending on whether they saw improvements (or did not have issues); had no changes but were satisfied, or neutral experiences; or saw negative impact/experience. For each participant, I reviewed their experience and what they were happy with or frustrated by.

Here are some of the details for each participant.

AID-IRL-Participant1-DanaMLewisAID-IRL-Participant1-cont_DanaMLewis1 – A parent of a child using Control-IQ (off-label), with 30% increase in TIR with no increased hypoglycemia. They spend less time correcting than before; less time thinking about diabetes; and “get solid uninterrupted sleep for the first time since diagnosis”. They wish they had remote bolusing, more system information available in remote monitoring on phones. They miss using the system during the 2 hour CGM warmup, and found the system dealt well with growth spurt hormones but not as well with underestimated meals.

AID-IRL-Participant2-DanaMLewis AID-IRL-Participant2-cont-DanaMLewis2 – An adult male with T1D who previously used DIYAPS saw 5-10% decrease in TIR (but it’s on par with other participants’ TIR) with Control-IQ, and is very pleased by the all-in-one convenience of his commercial system.He misses autosensitivity (a short-term learning feature of how insulin needs may very from base settings) from DIYAPS and has stopped eating breakfast, since he found it couldn’t manage that well. He is doing more manual corrections than he was before.

AID-IRL-Participant5-DanaMLewis AID-IRL-Participant5-cont_DanaMLewis5 – An adult female with LADA started, stopped, and started using Control-IQ, getting the same TIR that she had before on Basal-IQ. It took artificially inflating settings to achieve these similar results. She likes peace of mind to sleep while the system prevents hypoglycemia. She is frustrated by ‘too high’ target; not having low prevention if she disables Control-IQ; and how much she had to inflate settings to achieve her outcomes. It’s hard to know how much insulin the system gives each hour (she still produces some of own insulin).

AID-IRL-Participant7-DanaMLewis AID-IRL-Participant7-cont-DanaMLewis7 – An adult female with T1D who frequently has to take steroids for other reasons, causing increased BGs. With Control-IQ, she sees 70% increase in TIR overall and increased TIR overnight, and found it does a ‘decent job keeping up’ with steroid-induced highs. She also wants to run ‘tighter’ and have an adjustable target, and does not ever run in sleep mode so that she can always get the bolus corrections that are more likely to bring her closer to target.

AID-IRL-Participant3-DanaMLewis AID-IRL-Participant3-cont-DanaMLewis3 – An adult male with T1D using 670G for 3 years didn’t observe any changes to A1c or TIR, but is pleased with his outcomes, especially with the ability to handle his activity levels by using the higher activity target.  He is frustrated by the CGM and is woken up 1-2x a week to calibrate overnight. He wishes he could still have low glucose suspend even if he’s kicked out of automode due to calibration issues. He also commented on post-meal highs and more manual interventions.

AID-IRL-Participant6-DanaMLewis AID-IRL-Participant6-contDanaMLewis6 – Another adult male user with 670G was originally diagnosed with T2 (now considered T1) with a very high total daily insulin use that was able to decrease significantly when switching to AID. He’s happy with increased TIR and less hypo, plus decreased TDD. Due to #COVID19, he did virtually training but would have preferred in-person. He has 4-5 alerts/day and is woken up every other night due to BG alarms or calibration. He does not like the time it takes to charge CGM transmitter, in addition to sensor warmup.

AID-IRL-Participant4-DanaMLewis AID-IRL-Participant4-contDanaMLewis4 – The last participant is an adult male with T1 who previously used DIYAPS but was able to test-drive the CamAPS FX. He saw no TIR change to DIYAPS (which pleased him) and thought the learning curve was easy – but he had to learn the system and let it learn him. He experienced ‘too much’ hypoglycemia (~7% <70mg/dL, 2x his previous), and found it challenging to not have visibility of IOB. He also found the in-app CGM alarms annoying. He noted the system may work better for people with regular routines.

You can see a summary of the participants’ experiences via this chart. Overall, most cited increased or same TIR. Some individuals saw reduced hypos, but a few saw increases. Post-meal highs were commonly mentioned.

AID-IRL-UniversalThemes2-DanaMLewis AID-IRL-UniversalThemes-DanaMLewis

Those newer to CGM have a noticeable learning curve and were more likely to comment on number of alarms and system alerts they saw. The 670G users were more likely to describe connection/troubleshooting issues and CGM calibration issues, both of which impacted sleep.

This view highlights those who more recently adopted AID systems. One noted their learning experience was ‘eased’ by “lurking” in the DIY community, and previously participating in an AID study. One felt the learning curve was high. Another struggled with CGM.

AID-IRL-NewAIDUsers-DanaMLewis

Both previous DIYAPS users who were using commercial AID systems referenced the convenience factor of commercial systems. One DIYAPS saw decreased TIR, and has also altered his behaviors accordingly, while the other saw no change to TIR but had increased hypo’s.

AID-IRL-PreviousDIYUsers-DanaMLewis

Companies building AID systems for PWDs should consider that the onboarding and learning curve may vary for individuals, especially those newer to CGM. Many want better displays of IOB and the ability to adjust targets. Remote bolusing and remote monitoring is highly desired by all, regardless of age. Post-prandial was frequently mentioned as the weak point in glycemic control of commercial AID systems. Even with ‘ideal’ TIR, many commercial users still are doing frequent manual corrections outside of mealtimes. This is an area of improvement for commercial AID to further reduce the burden of managing diabetes.

AID-IRL-FeedbackForCompanies-DanaMLewis

Note – all studies have their limitations. This was a small deep-dive study that is not necessarily representative, due to the design and small sample size. Timing of system availability influenced the ability to have new/longer time users.

AID-IRL-Limitations-DanaMLewis

Thank you to all of the participants of the study for sharing their feedback about their experiences with AID-IRL!

(You can download a PDF of my slides from the AID-IRL study here.)

Have questions about any of my posters or presentations? You can always reach me via email at Dana@OpenAPS.org.

Tips and tricks for real life and living with an ankle fracture

As I wrote in a previous post with much more detail (see here), I fell off a mountain and broke my ankle in three places, then managed to break a bone in my 5th toe on the other foot. This meant that my right ankle was in a hard cast for 6 weeks and I was 100% non-weight bearing…but this was challenging because the foot meant to be my stable base for crutching or knee scootering was often pretty wobbly and in a lot of pain.

This post is a follow up with more detailed tips and lessons learned of things that were helpful in living with a leg cast, as well as what the return to weight bearing was really like. I couldn’t find a lot of good information about the transition to weight bearing was really like, so this is my take on information I was looking for and would have appreciated before and during the weight bearing progression process. (And if you’re looking for diabetes-specific stuff, it’s in the last section!)
Tips_weight_bearing_DanaMLewis
Dealing with lack of energy and fatigue

First, it’s worth noting something major about a fractured bone, and *especially* true if it’s a big bone fracture like some of mine were: it takes a lot of healing, which means a lot of energy going to the healing and not much energy left for every day living. I was constantly exhausted – and surprised by this fatigue – pretty much throughout this process. It made sense in the early days (say weeks 1-2 after fracture), but was frustrating to me how little I had energy to do even in the 4-6 weeks after my fracture.

But, then it got worse. Returning to weight bearing took *even more* energy. For example, on the first day of partial weight bearing, I was tasked with putting 25 lbs of weight on my foot in the walking boot. First by placing my foot on the scale and getting reliable with being able to put the right amount of weight on the boot; then by standing and repeating with the scale; then taking a few steps (with the crutches taking the rest of my weight) and re-calibrating with the scale until I was confident in that weight. With weight bearing progression, you’re supposed to spend up to an hour a day working on this.

I took to heart what my ortho said about not progressing fast if you only do 5-10 minute chunks, so after the first day, I tried to always do 10-15 minute chunks at a minimum, with a longer chunk wherever possible as permitted by pain and my energy levels.

But the first few days were really, really tough. It was hard to switch to a new weight every two days – because this meant readjusting how I was stepping/walking, and how much weight and where I placed my crutches. I started with a blister on my right palm, which turned into a squished nerve that made my right hand go numb, and ultimately damaged some tendons in my right wrist, too. This made it painful to use the crutches or even drive my knee scooter when I wasn’t focusing on weight bearing. So I had a lot of pain and suffering in the WB progression process that probably contributed to how fatigued I was overall.

So one of my biggest pieces of advice for anyone with broken bones is to expect your energy to take a(nother) dip for the first few weeks after you start returning to weight-bearing (or return to normal activity outside your cast). It’s a *lot* of work to regain strength in atrophied muscles while still also doing the internal healing on the broken bones!

Tips to deal with so much fatigue as you return to weight bearing:

Some of the tips and things I figured out for being non-weight bearing and sitting around with a hard cast came in handy for the weight-bearing progression fatigue, too.

  • I got a shower bench (this is the one I got) so that it was easy to sit down on and swing my legs over into the shower/bathtub. Once I was out of my hard cast, I still can’t weight bear without the boot, so I still need a sitting shower/bath solution while I return to weight bearing. I also removed the back after a while, so it was easier to sit in either direction depending on preference (washing hair/not) without having to ask Scott to remove the back and re-attach it on the other side.
  • Speaking of showers, I put a toothbrush and toothpaste in the shower so I can also brush my teeth there while seated.
  • I still keep most of my toiletries in the bedside table (or you could have a caddy by the bedside) so I can brush my hair, take my contacts out or put them in, wipe my face (facewipes instead of having to stand at the sink to wash my face), etc. from the bed.
  • I am taking ibuprofen 4x a day, and I get tired of opening the bottle. So I dumped a pile of ibuprofen on my bedside table to make it easy to reach and remember to take first thing in the morning or at night. (There are no kids or pets in my household; keep safety in mind if you have kids etc in your household – this solution may not work for you).
  • The one time I tended to forget to proactively take my medication was mid-day, so I added a recurring calendar event to my calendar saying “take ibuprofen if you haven’t 2x a day” around 2pm, which would be the latest I would take my second round, even if I woke up later in the day and my first dose was later in the morning. This has helped me remember multiple times, especially on weekends or times when I’m away from my desk or bed where I would have the meds visible as a reminder.
  • Pre-mix protein powder (this is what I chose) into the beverage of choice in advance, and keep it in individual containers so it’s easy to get and take (and if I’m really tired, round tupperware containers that have measurement lines make it easy to measure liquid into, put the lid on to shake it up, and drink out of without having to find another cup). I had Scott do this several days in advance when he went on a trip, and we kept doing it in advance even after he got home.
  • I kept using my portable desk for working, taking video calls propped up in the bed with pillows behind me, and also laying the surface flat to eat meals from when I was too tired to get out of the bed.

Other advice for the return to weight-bearing:

If you’re like me, you’ll switch back to weight-bearing accompanied by getting out of your hard cast and getting a walking boot of some sort. If you can, ask your ortho/doc in advance what kind of boot they’ll put you in. It’s often cheaper to get the boot yourself. Perfect example: my ortho didn’t tell me what kind of boot I would need, and I looked at various boots online and saw they ranged $50-100 on Amazon. At my appointment he asked if I brought a boot and since I didn’t, they’d provide one..and the paperwork I signed stated the price would be $427 (::choking::) if the insurance didn’t cover it. Insurance negotiated down to $152 for me to pay out of pocket for since I haven’t hit my deductible…which is still 2-3x more than retail cost. UGH. So, if you can, buy your walking boot via retail. (Same goes for purchasing a knee scooter (here’s the one I got) – it may be cheaper to buy it new through Amazon/elsewhere than getting a medical purchase that goes through insurance and/or trying to do a rental.)

  • You’ll also probably end up with a boot with lots of velcro straps. When you undo your boot, fold back the strap on itself so it doesn’t stick to the boot, another strap, your clothes, etc.
Other equipment that has come in handy:
  • Get multiple ankle braces. I had a slightly structured ankle brace with hard sides that made me feel safer the first few nights sleeping out of the cast, and it was often easier to go from the bed to the bathroom on my knee scooter or crutches with the ankle brace(s) instead of re-putting on my walking boot and taking it off again for a shower. (I transitioned to sleeping in a lighter ankle brace after a week or so, but still used the structured brace inside the waterproof cast bag for swimming laps to help protect my ankle.)
  • An ice pack with a strap to put around your ankle/broken joint. I had gotten this ice pack for my knee last fall, and strap it and another ice pack to my ankle to get full joint coverage.
  • Wide leg athletic pants…ideally ones that you can put on/off without having to take your boot off. (Women should note I found better athletic pants for this purpose in the men’s athletic section at Target..but be aware a lot of the modern men’s style have tapered legs so make sure to watch out for those and have enough width to get over your boot). Taking off the boot is exhausting with so many velcro straps, so any time I can get dressed or undressed without having to remove the boot if I am not otherwise removing the boot is a win.
  • Look online for your state’s rules for a temporary handicap parking pass, and take the paperwork to your first ortho appointment to get filled out. Also, make sure to note where the places are that you can drop off the paperwork in person (in Seattle it was not the same as the DMV offices!), or otherwise be aware of the time frame for mailing those in and receiving the pass. The handicap parking placard has been helpful for encouraging me to get out of the house more to go to the store or go to a restaurant when otherwise I’m too exhausted to do anything.
  • A new shiny notebook for writing down your daily activities and what you did. If you’re not a notebook type person, use an app or note on your phone. But despite being mostly digital, I liked having a small notebook by the bed to list my daily activities and check the box on them to emphasize the activities I was doing and the progress I was making. At the beginning, it was helpful for keeping track of all the new things I needed to do; in the middle, it was useful for emphasizing the progress I was making; and at the end it felt really good to see the light of the end of the tunnel of a few pages/days left toward being fully weight bearing.
Weightbearing_notebook_DanaMLewis

Other tips for getting used to a walking boot and transitioning to weight bearing:

  • Don’t be surprised if you have pain in new areas when you move from a hard cast to a walking boot. (Remember you’ll be moving your leg or limbs in different ways than they’ve been accustomed to).
  • My ortho told me the goal of weight bearing progression is to understand the difference between discomfort (lasts a few minutes) and pain (lasts a few hours). You’re likely going to be in discomfort when doing weight bearing progression – that’s normal. Pain (i.e. sharp pain) is not normal, and you should take a break or back down to a previous weight (follow your protocol) if you have it. I was lucky – the only few times I had pain was from trying to press down forcefully on the scale when seated, rather than standing on the scale and naturally letting my weight on my leg. I didn’t end up plateauing at any weight, and was able to follow my protocol of 25lb weight bearing added every 2 days and get to full weight bearing with no delays.
  • If you have a watch with a stopwatch feature, use it. It’s hard to keep track of actual time spent walking (especially at first when 90 seconds feels like 6 minutes) with just a normal watch/clock. You could also use your smartphone’s timer feature. But tracking the time and pausing when you pause or take a break helps make sure you’re accurately tracking toward your hour of walking.
  • The process wasn’t without discomfort – physical and emotional. Putting weight on my leg was scary, and every new weight day was hard as I dealt with the fear and processing of the discomfort, as well as learning how to step and walk and do my crutches in a new way yet again.
  • But what I learned is that the first 5 minutes of every new weight day ALWAYS sucked. Once I recognized this, I set the goal to always tough out a 15 minute session after I calibrated on the scale by walking slowly around my apartment. (I put my headphones in to listen to music while I did it). As long as there was only discomfort and not pain, I didn’t stop until after 15 minutes of slow walking with that weight and also re-calibrated on the scale during and after to make sure I was in the right ballpark.
  • I had to spend the first half hour or so working on my weight bearing by myself. I couldn’t talk on the phone or talk with Scott while I did it; it required a lot of concentration. (The only thing I could do is listen to music, because I’m used to running with music). So distractions did not help when I got started, but toward the end of the hour I could handle and appreciate distractions. Same for day 2 of a weight – having distractions or a task to do (e.g. walk from A to B, or walking while my nephew was on his scooter) helped pass the time and get me to complete my hour or more of weight-bearing work.
  • Be careful with your hands and wrists. Blisters are common, and I managed to both squish a nerve (which caused me to have a numb side of my hand and be unable to type for several days) and also pull or damage tendons on both sides of my wrists. I was torn between choosing to delay my weight bearing progression work, but also recognizing that the sooner I got to full weight bearing the sooner I could completely ditch my crutches and be done hurting my hands. So I chose to continue, but in some cases shortened my chunks of WB walking down to 15 minutes wherever possible to reduce the pain and pressure on my hands.
You’ll likely also be doing range of motion exercises. At first, it’s scary how jerky your motions may be and how little your muscles and tendons respond to your brain’s commands. One thing I did was take a video on day 1 showing me pointing and stretching my ankle, and doing my ABC’s with my foot. Then every week or so when I was feeling down and frustrated about how my ankle wasn’t fully mobile yet, I’d take another video and watch the old one to compare. I was able to see progress every few days in terms of being able to point my foot more, and wider motions for doing the ABC’s with my foot.
Also remember, once you’re weight bearing and working toward getting rid of your crutches, you can use things like strollers or grocery carts to help you balance (and also kill some of your weight bearing time!) without crutches. The practice will make it easier for re-learning your posture and gaining confidence in walking without crutches.

Don’t you usually talk about diabetes stuff on this blog? 😉

(If anyone finds this post in the future mainly for ankle fracture and weight bearing transition/progression tips, you can ignore this part!)

Diabetes-wise, I’ve had a pretty consistent experience as to what I articulated in the last post about actually breaking bones.

  • It was common for my first few days of progressive weight bearing to have a small pain/stress rise in my BGs. It wasn’t much, but 20-30 points was an obvious stress response as I did the first few 15 minutes of weight bearing practice. The following days didn’t see this, so my body was obviously getting used to the stress of weight bearing again.
  • However, on the flip side, the first week of weight bearing progression also caused several lows. The hour of walking was the equivalent of any new activity where I usually have several hours later delayed sensitivity to insulin out of nowhere, and my blood sugars “go whoosh” – dropping far more than they normally would. I had two nights in a row in the first week where I woke up 2-3 hours after I went to sleep and needed to eat some carbs. This normally happens maybe once every few months (if that) now as an OpenAPS user, so it was obviously associated with this new surge of physical activity and hard work that I was doing for the weight bearing.
  • Overall, while I was 100% non-weight bearing, I was eating slightly (but not much) lower carb and slightly less processed food than I usually do. But not always. One day I ended up having 205+ grams of carbs for me (quite a bit more than my average). However, thanks to #OpenAPS, I still managed to have a 100% in range day (80-150 mg/dL). Similarly on a travel day soon after, I ate a lot less (<50g carb) and also had a great day where OpenAPS took care of any surges and dips automatically – and more importantly, without any extra work and energy on my part. Having OpenAPS during the broken bone recovery has been a HUGE benefit, not only for keeping my BGs in range so much of the time for optimal healing, but also for significantly reducing the amount of work and cognitive burden it takes to stay alive with type 1 diabetes in general. I barely had energy to eat and do my hour of weight bearing each day, let alone anything else. Thankfully good BGs didn’t fall by the wayside, but without this tech it certainly would have.

And finally the pep talk I gave myself every day during weight bearing progression work:

This is short-term and necessary discomfort and suffering on the way to weight bearing. It sucks, but you can and will do it. You have to do it. If you need to take a break, take a break. If you need to do something else to get yourself pumped up and motivated to do your weight bearing, it’s ok to do that. But you’ll get there. Slowly, but surely. You’ve got this!

Proof that I did get there:

Best of luck and lots of support and encouragement to anyone who’s working their way to weight bearing after an injury, and many thanks to everyone who’s supported me and cheered me on virtually along the way!

2021 update – see this post about (finally) running the marathon that I had signed up for before I broke my ankle!

Missing metrics in diabetes measurement by @DanaMLewis

“May I ask what your A1c is?”

This is a polite, and seemingly innocuous question. However, it’s one of my least favorite questions taken at face value. Why?

Well, this question is often a proxy for some of the following questions:

  • How well are *you* doing with DIY closed loop technology?
  • How well could *I* possibly do with DIY closed loop technology?
  • What’s possible to achieve in real-world life with type 1 diabetes?

But if I answered this question directly with “X.x%”, it leaves out so much crucial information. Such as:

  • What my BG targets are
    • Because with DIY closed loop tech like OpenAPS, you can choose and set your own target.
    • (That’s also one of the reasons why the 2018 OpenAPS Outcomes Study is fascinating to me, because people usually set high, conservative targets to start and then gradually lower them as they get comfortable. However, we didn’t have a way to retrospectively sleuth out targets, so those are results are even with the amalgamation of people’s targets being at any point they wanted at any time.)
  • What type of lifestyle I live
    • I don’t consider myself to eat particularly “high” or “low” carb. (And don’t start at me about why you choose to eat X amount of carbs – you do you! and YDMV) Someone who *is* eating a lot higher or lower carb diet compared to mine, though, may have a different experience than me.
    • Someone who is not doing exercise or activity may also have a different experience then me with variability in BGs. Sometimes I’m super active, climbing mountains (and falling off of them..more detail about that here) and running marathons and swimming or scuba diving, and sometimes I’m not. That activity is not so much about “being healthy”, but a point about how exercise and activity can actually make it a lot harder to manage BGs, both due to the volatility of the activity on insulin sensitivity etc.; but also because of the factor of going on/off of insulin for a period of time (because my pump is not waterproof).
  • What settings I have enabled in OpenAPS
    • I use most of the advanced settings, such as “superMicroBoluses” (aka SMB – read more about how it works here); with a higher than default “maxSMBBasalMinutes”; and I also use all of the advanced exercise settings so that targets also nudge sensitivity in addition to autosensitivity picking up any changes after exercise and other sensitivity-change-inducing activities or events. I also get Pushover alerts to tell me if I need any carbs (and how many), if I’m dropping faster and expected to go below my target, even with zero temping all the way down.
  • What my behavioral choices are
    • Timing of insulin matters. As I learned almost 5 years ago (wow), the impact of insulin timing compared to food *really* matters. Some people still are able to do and manage well with “pre-bolusing”. I don’t (as explained there in the previous link). But “eating soon” mode does help a lot for managing post-meal spikes (see here a quick and easy visual for how to do “eating soon”). However, I don’t do “eating soon” regularly like I used to. In part, because I’m now on a slightly-faster insulin that peaks in 45 minutes. I still get better outcomes when I do an eating-soon, sure, but behaviorally it’s less necessary.
    • The other reason is because I’ve also switched to not bolusing for meals.
      • (The exceptions being if I’m not looping for some reason, such as I’m in the middle of switching CGM sensors and don’t have CGM data to loop off of.)

These settings and choices are all crucial information to understanding the X.x% of A1c.

Diabetes isn’t just the average blood glucose value. It’s not just the standard deviation or coefficient of variation or % time in range or how much BG fluctuates.

Diabetes impacts so much of our daily life and requires so much cognitive burden for us, and our loved ones. That’s part of the reasons I appreciate so much Sulka & his family being candid about how their A1C didn’t change, but the amount of work required to achieve it did (way fewer manual corrections). And ditto for Jason & the Wittmer family for sharing about the change in the number of school nurse visits before/after using OpenAPS. (See both of their stories in this post)

For me, my quality of life metric has always been first about sleep: can I sleep safely and with peace of mind at night? Yes. Then – how long can I safely sleep? (The answer: a lot. Yay!)  But over time, my metrics have also evolved to consider how I can cut down (like Sulka) on the amount of work it takes to achieve my ideal outcomes, and find a happy balance there.

As I mentioned in this podcast recently, other than changing my pump site (here’s how I change mine) and soaking and swapping my CGM sensors (psst – soak your sensor!), I usually only take a few diabetes-related actions a day. They’re usually on my watch, pressing a button to either enable a temp target or entering carbs when I sit down to eat.

That’s a huge reduction in physical work, as well as amount of time spent thinking/planning/doing diabetes-related things. And when life happens – because I get the flu or the norovirus or I fall off a mountain and break my ankle – I don’t worry about diabetes any more.

So when I’m asked about A1c, my answer is not a simple “X.x%”. (And not just for the reason I’m annoyed by how much judging and shaming goes on around A1c, although that influences it, too.) I usually remind people that I first started with an “open loop” for a year, and that dropped my A1c by X%. And then I closed the loop, which reduced my A1c further. And we made OpenAPS even better over the last four years, which reduced it further. And then I completely stopped bolusing! And got less lows…and kept the same A1c.

And then I ask them what they’d really like to know. :) If it’s a fellow person with diabetes or a loved one, we talk about what problems they might be having or what areas they’d like to improve or what behaviors they’d like to change, if any. That’s usually way more effective than hearing “X.x%” of an A1c, and them wondering silently how to get there or what to do differently if someone wants to change things. (Or for clinicians who ask me, it turns into a discussion about choices and behaviors and tradeoffs that patients may choose to make.)

Remember, your diabetes may (and will) vary (aka, YDMV). Your lifestyle, the phase of life you’re in, your priorities, your body and health, and your choices will ALL be different than mine. That’s not bad in any way: that’s just the way it is. The behaviors I choose and the work I’m willing to do (or not do) to achieve *my* goals (and what my goals are), will be different than what you choose for yours.

And that’s therefore why A1c is not “enough” to me as a metric and something that we should compare people on, even though A1c is the “same” for everyone: because the work, time spent, behavioral tradeoffs, and goals related to it will all vary.

Missing_metrics_@DanaMLewis