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One Year of Pancreatic Enzyme Replacement Therapy for Exocrine Pancreatic Insufficiency (EPI or PEI)

by Dana Lewis

I’ve had exocrine pancreatic insufficiency (EPI or PEI) for a full year now and have been taking pancreatic enzyme replacement therapy (PERT) ever since diagnosis.

I’ve written about what EPI is, what it’s like to go on PERT, and a variety of other posts (such as how I ultimately taught myself to titrate and adjust my dosing of PERT based on what I am eating) in the last year – you can see all my EPI posts listed at DIYPS.org/EPI. I also wrote recently about estimating the costs of PERT for a year, in which I had tallied up the number of PERT pills I had taken so far in the year. Since I’ve now hit the one year mark, I wanted to revisit that math.

In 365 days of pancreatic enzyme replacement therapy, I have consumed (at least) 3,277 pills.

That’s an average of 8.98 pills per day!

As I previously wrote, the number of pills is in part because I’m trying to lower the total costs (to everyone involved in paying for it) of my PERT by taking a mix of prescription PERT and OTC enzymes to try to balance effective dosing, cost, and the number of pills I swallow. I take one pill with my standard breakfast, so the remaining ~8 average pills are usually split between lunch, dinner, and/or a snack if I have one. (This is also influenced by my ultrarunning where I typically take ~2 pills every 30 minutes with my snacks/fuel for running, so long training days of 4 hours would involve 8 or more pills just for running fuel; obviously longer runs would involve even more, which drives the pills/day average higher.) If I wanted to reduce the total number of pills, I could by driving up the cost by using bigger, prescription PERT pills in lieu of some of the OTC options. However, most of the time, 3-4 pills per meal mixed between prescription and OTC is doable for me. I typically would choose to round up more PERT and reduce OTC pill count when I’m less certain about the macronutrient content of the meal or I want more confidence in better outcomes.

Speaking of better outcomes – is PERT effective?

For me, yes!

Overall, I feel so much better. Most of the time, I hardly ever have ANY symptoms (such as gas, bloating, or feeling icky) let alone my more extreme symptoms of “disrupting” my GI system. In the year of taking PERT, 78% of the time I had no disruption or any noticeable symptoms.

The average length of time between days with noticeable symptoms was 5.37 days.

And, if you look at the second half of the year, this increased quite a bit: 88% of the time I had no noticeable symptoms and the streak length of days between symptom days increased to 6.81 average days! The max streak is now 28 days (and counting)!

Showing the increasing length of streaks of consecutive days where I did not have any GI symptoms. The trend line shows a steady increase in the length of these streaks throughout the year.

That’s approaching a full month without any GI symptoms (woohoo) of any kind, and means less than 1 or 2 instances of symptoms per month for me in the last several months. That’s probably better than average for most people, even people without known GI conditions, and getting a lot closer back to my personal level of “normal”.

And obviously, this is continuing to increase over time as I improve my PERT dosing strategy.

This is pretty meaningful to think about.

PERT made a difference overall straight away, but I was also starting with very small portions of food and a very restricted diet. (This is because before I realized I had EPI I had done all kinds of behavioral gymnastics to try to eliminate foods like onion, garlic, and other foods that seemed to cause issues). So first I figured out PERT successfully for what I was eating; then carefully expanded my portion sizes back to typical quantities of food; then slowly expanded my diet to cover all the foods I used to eat before I started having all my GI problems.

It very much felt like I had three phases this year:

  • Phase 1: Use PERT to cover small quantities of small varieties of food. Figure out what foods I could eat that could “fit” into one PERT pill.
  • Phase 2: Start to figure out what quantities of food I wanted to eat, and get the PERT to match the food.
  • Phase 3: Finish expanding out my food choices to cover everything I was eating before and tackling all my “firsts” with PERT.

You can see this evolution in my diet, too, when you look at the relative changes in the amount of fat and protein I have eaten over the course of the year. (The one big obvious outlier on the graph in October is my 82 mile ultramarathon where I ate every 30 minutes for 25 hours!) There’s been a slight increase in my fat consumption over the course of the year, and protein consumption has stayed relatively flat as I’ve been making a very conscious effort to eat enough protein to fuel my ultrarunning endeavors throughout the year.

You can then see the relationship with increased number of pills (albeit pills with different amounts of lipase) over the course of the year, relative to the fat and protein consumed.

Displaying lines showing the relative amounts of fat and protein consumed throughout the year, plus the number of enzyme pills per day throughout 2022.

(Note that the pills per day is using a hidden right axis, whereas the fat and protein share the same left axis numbers, also not shown)

For anyone who is new (just diagnosed or recently diagnosed within a few weeks or months) to EPI, here’s what I would hope you take away:

  1. PERT works, but it needs to match what you are eating. Come up with a strategy (here’s mine – you can use it!) to adjust your dosing to match what you are eating. What you eat changes, and so should your PERT dosing.
  2. Things will improve over time, and you will get more effective at matching your dosing to what you are eating. You should be able to have more and more “streaks” of days without symptoms, or with reduced symptoms. However, this may take a few months, because you’ll likely also be – at the same time – re-expanding your variety of foods that you’re eating. The combination of eating more and different foods AND tweaking your dosing can make it take a little bit longer to figure it all out.
  3. If you’re not seeing success, talk with your doctor. There are different sizes of PERT pills – if you’re struggling to take X number of pills, you may be able to take fewer pills of a bigger size. There are different brands of PERT – so if one isn’t working for you (after you match your dosing to how much fat and protein is in each meal), you can switch and try another brand. There are also OTC options, which you can use to “top off” your prescription PERT or substitute, but you need to have an effective strategy for adjusting your dose that you can translate to your OTCs to be sure that they’re working.
One year of pancreatic enzyme replacement therapy for EPI by Dana M. Lewis

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(PS – you can find my previous posts about EPI at DIYPS.org/EPI – and make sure you check out PERT Pilot, the first iOS app for Exocrine Pancreatic Insufficiency!)

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You can also contribute to a research study and help us learn more about EPI/PEI – take this anonymous survey to share your experiences with EPI-related symptoms!

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Looking Back Through 2022 (What You May Have Missed)

by Dana Lewis

I ended up writing a post last year recapping 2021, in part because I felt like I did hardly anything – which wasn’t true. In part, that was based on my body having a number of things going on that I didn’t know at the time. I figured those out in 2022 which made 2022 hard and also provided me with a sense of accomplishment as I tackled some of these new challenges.

For 2022, I have a very different feeling looking back on the entire year, which makes me so happy because it was night and day (different) compared to this time last year.

One major example? Exocrine Pancreatic Insufficiency.

I started taking enzymes (pancreatic enzyme replacement therapy, known as PERT) in early January. And they clearly worked, hooray!

I quickly realized that like insulin, PERT dosing needed to be based on the contents of my meals. I figured out how to effectively titrate for each meal and within a month or two was reliably dosing effectively with everything I was eating and drinking. And, I was writing and sharing my knowledge with others – you can see many of the posts I wrote collected at DIYPS.org/EPI.

I also designed and built an open source web calculator to help others figure out their ratios of lipase and fat and protease and protein to help them improve their dosing.

I even published a peer-reviewed journal article about EPI – submitted within 4 months of confirming that I had it! You can read that paper here with an analysis of glucose data from both before and after starting PERT. It’s a really neat example that I hope will pave the way for answering many questions we all have about how particular medications possibly affect glucose levels (instead of simply being warned that they “may cause hypoglycemia or hyperglycemia” which is vague and unhelpful.)

I also had my eyes opened to having another chronic disease that has very, very expensive medication with no generic medication option available (and OTCs may or may not work well). Here’s some of the math I did on the cost of living with EPI and diabetes (and celiac and Graves) for a year, in case you missed it.

Another other challenge+success was running (again), but with a 6 week forced break (ha) because I massively broke a toe in July 2022.

That was physically painful and frustrating for delaying my ultramarathon training.

I had been successfully figuring out how to run and fuel with enzymes for EPI; I even built a DIY macronutrient tracker and shared a template so others can use it. I ran a 50k with a river crossing in early June and was on track to target my 100 mile run in early fall.

However with the broken toe, I took the time off needed and carefully built back up, put a lot of planning into it, and made my attempt in late October instead.

I succeeded in running ~82 miles in ~25 hours, all in one go!

I am immensely proud of that run for so many reasons, some of which are general pride at the accomplishment and others are specific, including:

  • Doing something I didn’t think I could do which is running all day and all night without stopping
  • Doing this as a solo or “DIY” self-organized ultra
  • Eating every 30 minutes like clockwork, consuming enzymes (more than 92 pills!), which means 50 snacks consumed. No GI issues, either, which is remarkable even for an ultrarunner without EPI!
  • Generally figuring out all the plans and logistics needed to be able to handle such a run, especially when dealing with type 1 diabetes, celiac, EPI, and Graves
  • Not causing any injuries, and in fact recovering remarkably fast which shows how effective my training and ‘race’ strategy were.

On top of this all, I achieved my biggest-ever running year, with more than 1,333 miles run this year. This is 300+ more than my previous best from last year which was the first time I crossed 1,000 miles in a year.

Professionally, I did quite a lot of miscellaneous writing, research, and other activities.

I spent a lot of time doing research. I also peer reviewed more than 24 papers for academic journals. I was asked to join an editorial board for a journal. I served on 2 grant review committees/programs.

I also wrote a lot.

*by ton, I mean way more than the past couple of years combined. Some of that has been due to getting some energy back once I’ve fixed missing enzyme and mis-adjusted hormone levels in my body! I’m up to 40+ blog posts this year.

And personally, the punches felt like they kept coming, because this year we also found out that I have Graves’ disease, taking my chronic disease count up to 4. Argh. (T1D, celiac, EPI, and now Graves’, for those curious about my list.)

My experience with Graves’ has included symptoms of subclinical hyperthyroidism (although my T3 and T4 are in range), and I have chosen to try thyroid medication in order to manage the really bothersome Graves’-related eye symptoms. That’s been an ongoing process and the symptoms of this have been up and down a number of times as I went on medication, reduced medication levels, etc.

What I’ve learned from my experience with both EPI and Graves’ in the same year is that there are some huge gaps in medical knowledge around how these things actually work and how to use real-world data (whether patient-recorded data or wearable-tracked data) to help with diagnosis, treatment (including medication titration), etc. So the upside to this is I have quite a few new projects and articles coming to fruition to help tackle some of the gaps that I fell into or spotted this year.

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And that’s why I’m feeling optimistic, and like I accomplished quite a bit more in 2022 than in 2021. Some of it is the satisfaction of knowing the core two reasons why the previous year felt so physically bad; hopefully no more unsolved mysteries or additional chronic diseases will pop up in the next few years. Yet some of it is also the satisfaction of solving problems and creating solutions that I’m uniquely poised, due to my past experiences and skillsets, to solve. That feels good, and it feels good as always to get to channel my experiences and expertise to try to create solutions with words or code or research to help other people.

How To Dose Pancreatic Enzyme Replacement Therapy (PERT) By What You Are Eating – And A Free Web Calculator To Calculate Enzyme Dosing

by Dana Lewis

PS – check out PERT Pilot, the first iOS app for Exocrine Pancreatic Insufficiency! It’s an iOS app that allows you to record as many meals as you want, the PERT dosing and outcomes, to help you visualize and review more of your PERT dosing data!

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I’ve had exocrine pancreatic insufficiency (known as EPI or PEI) for a year now. I have had type 1 diabetes for 20+ years and am experienced in adjusting my medication (previously insulin) in response to everything that I eat or drink.

With EPI, though, most people are given a static prescription, such as one saying “take 3 pills with each meal”.

Well, what if every meal is not the same size?

Let’s think about a couple of hypothetical meals.

Meal A: Baked chicken, sweet potato, and broccoli. This meal likely results in ~31 grams of carbohydrates; 7 grams of fat; and ~30 grams of protein.

How would you dose for this meal? Most people do what they are told and dose based on the fat content of the meal. If they typically take 3 pills, they may take all 3 pills or take fewer pills if this is less fat than their typical meal.

Many people post in EPI social media groups post about restaurant dinners that sound like this complaining about side effects they experience with this type of meal. The commonly mentioned theory is that maybe the chicken is cooked in oil. However, the entire meal is so low in fat compared to other meals that it is unlikely to be the fat content causing symptoms if the typical meal dose of PERT is used, even if the chicken is cooked in oil.

Let’s discuss another meal.

Meal B: A bowl of chili topped with cheddar cheese and a piece of cornbread.

This meal results in ~45 grams of carbs; ~30 grams of fat; and ~42 grams of protein.

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The fat content between these two meals is quite a bit different (7 grams of fat versus 30 grams of fat). Yet, again, most people are told simply to dose by the amount of fat, so someone might take a lower dose for the chicken meal because it has so little fat relative to other meals.

This could result in symptoms, though. The pancreas actually produces THREE kinds of enzymes. That’s why pancreatic enzyme replacement therapy medicine, called pancrelipase as a common name, has THREE types of enzymes: lipase, to help digest fat; protease, to help digest protein; and amylase, to help digest carbohydrates. A typical PERT pill has different amounts of these three enzymes, although it is usually described by the size/quantity of lipase it has – yet the other enzymes still play an important role in digestion.

I’ve observed that it’s pretty common for people to completely ignore the protein in what they’re eating. But as I mentioned, that seems to be the most obvious thing to try dosing for if “low fat” meals are causing issues. (It could also be sensitivity to carbohydrates, but the above example meal is fairly low carbohydrate.) My personal experience has also been that I am sensitive to fat and protein, and dose my meals based on these macronutrients, but other than eating fruit on an empty stomach (when I would add PERT/enzyme, despite the zero fat and protein in it), I don’t need to dose based on carbohydrates.

But I do need to dose for BOTH fat AND protein in what I’m eating. And I have a theory that a lot of other people with EPI do, too.

So how do you do this?

How do you dose for meals of different sizes, and take into account both fat and protein for these varying meals?

First, you need to figure out what dosing “works” for you and begin to estimate some “ratios” that you can use.

Most people begin experimenting and find a quantity of food that they can eat with the dose that they typically take. This meal size is going to vary person to person; it’ll also vary based on what it is in the meal they’re eating (such as chicken vs chili, from the above examples).

Once you find a dose that “works” and try it out a few times on the same meal, you can use this to determine what your ratios/dosing should be.

How?

Let’s use two examples with different dose sizes and types of PERT.

(PS – did you know there are 6 FDA-approved PERT brands in the US? Sometimes one works for someone where a different brand does not. If you’re struggling with the first type of PERT you’ve been prescribed, and you’ve already ruled out that you’re dosing correctly (see below), make sure to talk to your doctor and ask about trying a different brand.)

First, let’s calculate the ratios of lipase needed per gram of fat.

Let’s say the meal that “works” with your typical dose is 30 grams of fat. If 30 grams of fat is fine on your current dose, I would eat another meal with a slightly higher amount of fat (such as 35 or 40 grams of fat). When you get to an amount that “doesn’t work” – meaning you get symptoms – then you go back to the dose that does “work” to use in the math.

If the meal that “worked” was 30 grams of fat I would do the following math for each of these two examples:

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Example A: You need 1 pill of Zenpep 25,000 to cover this meal

Example B: You need 3 pills of Creon 36,000 to cover this meal

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Example A: 1 pill of Zenpep 25,000 is 1 multiplied by 25,000, or 25,000 units of lipase. Take that (25,000) and divide it by the grams of fat in the meal that works (30 grams). This would be 25,000/30 = 833. This means you need 833 units of lipase to “cover” 1 gram of fat. You can round up to ~1000 units of lipase to make it easier; your ratio would be 1000 units of lipase for every 1 gram of fat.

Example B: 3 pills of Creon 36,000 is 3 multiplied by 36,000, which is 108,000 units of lipase. Take that number (108,000) and divide it by the grams of fat in the meal that works (30 grams). This would be 108,000/30 = 3,600. This means you need 3,600 units of lipase to “cover” 1 gram of fat.

The next time you wanted to eat a meal, you would look at the grams of fat in a meal.

Let’s say you’re going to eat two bowls of chili and two pieces of cornbread. Let’s assume that is about 64 grams of fat. (Two bowls of chili and two cornbread is 30×2=60, plus a bit of butter for the cornbread so we’re calling it 64 grams of fat).

Example A: Take the meal and multiply it by your ratio. 64 (grams of fat) x 1,000 (how many units of lipase you need to cover 1 grant of fat) = 64,000. A Zenpep 25,000 has 25,000 lipase. Since you need 64,000 (units of lipase needed to cover the meal), you would divide it by your pill/dose size of 25,000. 64,000 divided by 25,000 is 2.56. That means for these ratios and a prescription of Zenpep 25,000 pill size, you need *3* Zenpep 25,000 to cover a meal of 64g of fat. (Remember, you can’t cut a PERT, so you have to round up to the next pill size.)

Example B: Take the meal and multiply it by your ratio. 64 (grams of fat) times 3,600 (how many units of lipase you need to cover 1 grant of fat) = 230,400. A Creon 36,000 has 36,000 lipase. Since you need 230,400 units of lipase to cover the meal, you would divide it by your pill/dose size of 36,000. 230,400 divided by 36,000 is 6.4. This means you need *7* Creon 36,000 to cover a meal of 64g of fat. (Again, you can’t cut a PERT, so you have to round up to 7 from 6.4.)

Another way to think about this and make it easier in the future is to determine how much one pill “covers”.

Example A: A Zenpep 25,000 “covers” 25 grams of fat if my ratio is 1000 units of lipase for every gram of fat (25,000/1000=25).

So if a meal is under 25g of fat? 1 pill. A meal under 50g (25×2)? 2 pills. 75g (25×3)? 3 pills. And so on. Once you know what a pill “covers”, it’s a little easier; you can simply assess whether a meal is above/below your pill size of 1 (25g), 2 (50g), 3 (75g) etc.

Example B: A Creon 36,000 “covers” 10 grams of fat if my ratio is 3,600 units of lipase for every gram of fat (36,000/3600=10).

So if a meal is under 10 grams of fat? 1 pill. 20 grams of fat is 2 pills (10×2); 30 grams of fat is 3 pills (10×3); etc.

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When people with EPI share experiences online, they often describe their dose size (such as 1 x 25,000 or 3 x 36,000 like examples A and B above) for most meals, but the meal size and composition is rarely discussed.

Personally, I can eat pretty widely varying amounts of fat in each meal on a day to day basis.

That’s why, instead of a flat dosing that works for everything (because I would be taking a LOT of pills at every meal if I was trying to take enough to cover my highest fat meals every time), I have found it to be more effective to estimate each meal to determine my meal dosing.

Remember that meal estimates aren’t very precise. If you use a nutrition panel on a box serving, the serving size can vary a bit. Restaurants (especially chains) have nutrition information, but the serving size can vary. So recognize that if you are calculating or estimating 59 grams of fat and that means either 2 vs 3 pills or 6 vs 7 pills, that you should use your judgment on whether you want to round up to the next pill number – or not.

Let’s put the hypothetical meals side by side and compare dosing with examples A and B from above:

Example of how much PERT is needed for two different meals based on dose ratios from Examples A and B

Using the previous meal examples with either 7 or 30 grams of fat:

  • With Example A (ratio of 25g of fat for every 1 pill, or 1000 units of lipase to cover 1 gram of fat), we would need 1 pill for the chicken meal and 2 for the chili meal. Why? The chili is >25 grams of fat which means we need to round up to 2 pills.
  • With Example B (ratio of 10 grams of fat for every 1 pill or 3600 units of lipase to cover 1 gram of fat), we would need 1 pill to cover the chicken (because it’s less than 10 grams of fat) and 3 – or more – pills for the chili. Why “or more”? Well, something like chili is likely to be imprecisely counted – and if you’re like me, you’d want a bit of extra cheese, so chances are I would round up to a 4th pill here to take in the imprecision of the measurements of the ingredients.

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PERT Dosing for Protein

Wait, didn’t you say something about protein?

Yes, I did. Fat isn’t the only determinant in this math!

I do the same type of math with grams of protein and units of protease. (Remember, PERT has all 3 types of enzymes, even though it is labeled by the amount of lipase. You can look online or on the bottle label to see how much protease is in your PERT.)

For our examples, Zenpep 25,000 contains 85,000 units of protease. Creon 36,000 contains 114,000 units of protease.

For the meal that ‘worked’ of 30 grams of fat, we also want to know the protein that worked. For easy math, let’s also say 30 grams of protein is in this meal.

Following the same math as before:

Example A (Zenpep 25,000): 30 grams of protein divided by 1×85,000 units of protease is ~2,833 units of protease to every 1 gram of protein. Again, I like to think about how much 1 pill “covers” protein-wise. In this case, 1 Zenpep 25,000 “covers” 30 grams of protein.

Example B (Creon 36,000): 30 grams of protein divided into 3 x 114,000 units of protease is 11,400 units of protease per gram of protein. Again, I like to think about how much 1 pill “covers” protein-wise as well. In this case, 1 Creon 36,000 “covers” 10 grams of protein.

Here’s how many pills are needed for protein:

Example of how much PERT is needed for two different meals based on dose ratios from Examples A and B, showing both protein and fat quantities

  • With Example A (ratio of 30g of protein for every 1 pill), we would need 1 pill for the chicken meal and 2 for the chili meal. Why? The chili is 42, which is greater than (30×1) grams of protein which means we need to round up to 2 pills.
  • With Example B (ratio of 10 grams of protein for every 1 pill), we would need 3 or more pills to cover the chicken. Why 3 or more? Again, it’s on the top edge of what 3 pills would cover, so I’d be likely to round up to 4 pills here. For the chili, 5 pills are needed (42 is more than 4 x 10 and is less than 5 x 10).

So how do you decide the number of pills to take for these meals? Let’s go back to our two example meals and compare the amount needed, pill-wise, for both fat and protein for each meal and each example.

Example of how much PERT is needed for two different meals based on dose ratios from Examples A and B and comparing the number of pills for fat and protein

When the pill numbers MATCH (e.g. the same number needed for fat and protein), which is the case for both examples with Zenpep 25,000, it’s easy: take that number of pills total! For Zenpep 25,000, I would take 1 pill for the Chicken (1 fat | 1 protein); and I would take 2 pills for the Chili (2 fat | 2 protein). Remember that PERT pills contain all three enzymes, so the fat and protein are sufficiently *each* covered by the quantities of lipase and protease in this pill type.

When the pill numbers are DIFFERENT between your fat and protein estimates, you use the LARGER number of pills. For Creon 36,000, with the chicken meal the protein quantity is much larger than the fat quantity; I would in this case dose 4 total pills (1 fat | 4 protein), which would then cover the protein in this meal and would also sufficiently cover the amount of fat in this meal. For the chili meal, it is closer: I estimated needing 4 pills for fat and 5 for protein; in this case, I would take 5 total pills which would then successfully cover the protein and the fat in the meal.

If you find the math challenging to do, don’t worry: once you determine your ratios and figure out how much one pill “covers”, it gets a lot easier.

And I made a few tools to help you!

Check out this free enzyme calculator which does the math to determine the ratios on exactly how much one pill “covers” for your successful meal.

(The calculator is for entering one meal at a time, and doesn’t save them, but if you’d like AI to estimate what is in your meal and help you log and save multiple meals, check out PERT Pilot if you have an iPhone.)

Here’s what it looks like using the two examples above:

Example of Part 1 of the EPI Enzyme Calculator using Zenpep 25,000, where 1 pill covers 30 grams of fat and 30 grams of protein. Example of Part 1 of the EPI Enzyme Calculator using Creon 36,000, where 3 pills covers 30 grams of fat and 30 grams of protein.

You can input your meal that “works”, what your dose is that “works” (the number of pills and pill type), and it will share what your ratios are and what one pill “covers”.

You can also use the second part of the calculator to estimate the amount you need for a future meal! Say it’s coming up on a holiday and you’re going to eat a much larger meal than you normally do.

You can input into the calculator that you’ll be eating 90 grams of fat and 75 grams of protein.

Here’s the example with our dose from Example A (Zenpep 25,000):

Example of Part 2 of the EPI Enzyme Calculator using Zenpep 25,000, with a future larger meal of 90 grams of fat and 75 grams of protein.

Here’s the example large meal with our dose from Example B (Creon 36,000):

Example of Part 2 of the EPI Enzyme Calculator using Creon 36,000, with a future larger meal of 90 grams of fat and 75 grams of protein.

You can also hit the button to expand the calculations to see the math it is doing, and how it compares between the fat and protein pill estimates to see what “drives” the total number of pills needed.

You can also hit the button to expand the calculations to see the math it is doing, and how it compares between the fat and protein pill estimates to see what “drives” the total number of pills needed, with the calculation view expanded to show all the details

You can even download a PDF with this math to have on hand. Here’s what the PDF download looks like for Example B (Creon 36,000):

Example of a PDF print view of the same data from previous screenshots with a Creon 36000 example

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Switching dose sizes or PERT brand types

This calculator can also be useful if you were originally prescribed a smaller quantity of PERT (e.g. Creon 3000 or Zenpep 3000) and you find yourself taking many numbers of these pills (6 or more) to cover a small meal for you, let alone more pills for a larger meal.

You can input this into the calculator and get your ratios; then in the second part, identify a different pill size, to see how many numbers of pills you’d take on a different dose.

Example switching from one size of PERT pill to another size

You can also use it to help you understand how much you might need if you are switching between brands. Let’s say you were prescribed Zenpep 25,000 and you need to try Creon, either because you don’t think Zenpep works well for you or your insurance is more willing to cover the Creon brand.

You would use the top part of the calculator with your current brand and size (e.g. Zenpep 25,000 of which you take 6 for a standard meal of 30 grams of fat and 30 grams of protein) and then input the new brand and size and the same size meal (e.g. Creon 36,000 and another 30 grams of fat and 30 grams of protein meal) to see that you’d likely need 5 Creon 36,000 to match the 6 Zenpep 25,000 you were taking for a standard size (30 gram of fat and 30 gram of protein) meal.

Example of using the calculator to estimate the different number of pills for a different brand and size of PERT pill

Note: I’m not suggesting 30 grams of fat and protein at each meal is “standard” or the “right” size of the meal – I picked arbitrary numbers here to illustrate these examples, so make sure to include the meal that your PERT dosing successfully covers for YOU!

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As a reminder, I’m not a doctor – I’m a person living with EPI. None of this is medical advice. I use this math and this calculator for my own personal use and share it in case it’s helpful to others. If you have questions, please do talk to your doctor. If you’re still experiencing symptoms with your enzyme dosing, you definitely should talk with your doctor. Your prescription size might need updating compared to what you were originally prescribed.

Also, please note that the calculator is open source; you can find the code here, and I welcome contributions (pull requests) and suggestions! You can leave feedback on Github or share feedback in this form. For example, if you’re using a different type of enzyme not listed in the calculator (currently 2/6 of the US FDA-approved versions are listed), please let me know and I can work to add the relevant list.

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PS – You can find my other posts about EPI at DIYPS.org/EPI, and you can also check out PERT Pilot, the first iOS app for Exocrine Pancreatic Insufficiency! It’s an iOS app that allows you to record as many meals as you want, the PERT dosing and outcomes, to help you visualize and review more of your PERT dosing data!

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You can also contribute to a research study and help us learn more about EPI/PEI – take this anonymous survey to share your experiences with EPI-related symptoms!

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More Tools To Help Diabetes Researchers and Other Researchers

by Dana Lewis

A few years ago I made a big deal about a tool I had created, converting someone’s web tool into a command line tool to be able to take complex json data and convert it to csv. Years later, I (and thousands of others, it’s been downloaded 1600+ times!) am still using this tool because there’s nothing better that I’ve found when you have data that you don’t know the data structure for or the data structure varies across files.

I ended up creating a repository on Github to store it with details on running it, and have expanded it over the last (almost) six years as I and others have added additional tools. For example, it’s where Arsalan, one of my frequent collaborators, and I store open source code from some of our recent papers.

Recently, I added two more small scripts. This was motivated to help researchers who have been successfully using the OpenAPS Data Commons and want to update their dataset with a later version of the data. Chances are, they have cleaned and worked with a previous version of the dataset, and instead of having to re-clean all of the data all over again, this set of scripts should help narrow down what the “new” data is that needs to be pulled out, cleaned, and appended to a previously cleaned dataset.

You can check out the full tool repository here (it has several other scripts in addition to the ones mentioned above). The latest are two python scripts that checks the content of an existing folder and lists out the memberID and filenames for each. This is useful to run on an existing, already-cleaned dataset to see what you currently have. It can also be run on the latest/newest/bigger dataset available. Then, the second script can be run to compare the memberIDs and file names in the newer/biggest/larger dataset against the previously cleaned/smaller/older dataset. Those that “match” already exist in the version of the dataset they have; they don’t need to be pulled again. The others don’t exist in the current dataset, and can be popped into a script to pull out just those data files to then be cleaned and appended to the existing dataset.

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As a heads up specifically for those working with the OpenAPS Data Commons, it is best practice to name/describe the version of the dataset via the size. For example, you might be working with the n=88 or n=122 version of the dataset. If you used the above method, you would then describe it along the lines of taking and cleaning the n=122 version; selecting new files available from the n=183 version and appending them to the n=122 version; and the resulting dataset is n=(122+number of new files used).

Folks who access the n=183 version of the dataset and haven’t previously used a smaller version of the dataset can reference using the n=183 and clarifying how many files they ended up using, e.g. describing that they followed X method to clean the data starting from the n=183 version and their resulting dataset is n=166, for example.

It is important to clarify which version and size of the dataset is being used.

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PS – this method works on other data file types, too! You’d change the variable/column header names in the script to update this for other cases.

Adding Lines On A Google Sheets Chart To Indicate Today’s Date And Other Dates

by Dana Lewis

Filed under more micro hacks that I’ve been doing lately (see this script I wrote to flag embedded social media content so that I could switch it to an image instead), I have been building time series charts to track various things.

One thing I was doing was exporting the finished chart to an image, then manually adding a line to mark dates of interest on the chart.

Then I realized that I could insert lines automatically to reflect dates, without having to manually add it to the exported image.

How?

First, I added another column to my sheet. I created a value in that column on the date of interest (my date is in the adjacent column). For this particular chart, I had made the data points I was tracking by date as “1”, so to show a different size line I made the date of interest 1.2. I changed the min and max values to be 0.7 and 1.2, which means that the “1”s showed up in the middle of the graph and my “date” markers went the full height of the graph.

Here’s how the source data looks in my sheet:

Example of a spreadsheet with 4 columns. The first two columns have 1s as values to indicate tracking; the second column has a single 1.20 value shown next to a relevant date; the fourth column is a list of dates

Then, I expanded my chart to include the new line as a data source, and my chart then looked something like this:

Example of a generated chart with a date line displayed on top of the tracked data.

Because I am simply tracking the presence of things, I’ve hidden the left horizontal axis, because the value is not a meaningful data point and just an artifact of the numbers I’ve chosen to visualize the data on particular days. (Again, what’s displayed has a min of 0.7 and max of 1.2, so the blue and green lines have 1 values whereas the purple line I’m using to indicate a major date is a value of 1.2)

That’s a fixed date, though. I want to track data over time and be able to have the graph automatically update without me having to constantly expand the series of data the chart includes. I’d rather include a month or two of empty data in advance, and have today’s date flagged.

But that’s not a default feature, so how could I make this work? With a similar trick of graphing the date, but using a feature of Google Sheets where you can enter “=TODAY()” and have the cell fill with today’s value. It automatically updates, so it can therefore shift along my graph as long as I’ve gotten a sufficiently large selection of data past today’s date.

I struggled with having a single cell value selected, though, so I ended up creating another column. In this column, I had it check for what today’s date was (TODAY()) and compare it against the date in my existing date column. If the date matched today’s date, then it would display a 1.2 value. If it didn’t match, it would leave the cell blank. The full formula for this was:

=IF(TODAY()=D3,1.2, )

This checked if my date column (column D for me; make sure to update with the column letter that matches where your dates live) had today’s date and marked it if so.

It worked! Here’s how it looks – I’ve made the today’s date marker a different color (bright orange) than my other dates of interest (purple):

Example chart with the relevant date line shown and later, a date line (in a different color) distinguishing today's date. This chart will auto-update based on the method described in the full text of the blog post

This orange line will keep shifting to today’s date, so I can quickly glance at this chart and not have to be updating the data selection of the chart as often.

Troubleshooting tips:

I ran into a couple of errors. First, I had used quotes around the 1.2 value in my formula, which entered it as text so it wouldn’t graph the line on my chart. Removing the “” in the formula (correctly written above) changed it back to number formatting so it would graph. Also, I had selected a smaller portion of data for this chart, but then I grabbed the entire today’s date column, so the today’s-date line was incorrectly graphed at the far right of the graph rather than on today’s date. That was because of the size of data mismatch; I had something like A334-C360,G3:G360. Instead, I had to make sure the today’s-date checking column matched the size of the other data selection, meaning A334-C360,G334-360 (notice how the first G number is now updated to match the A starting number). So, if you see your value graphed in an unexpected place, check for that.

Other tricks

PS – I actually am getting my “1” values based on data from another tracking spreadsheet. I use a formula to check for the presence of cell values on another tab where I am simply marking with an ‘x’ or various other simple markers. I use another IF checking formula to see if the cell matching the date in the other tab has a value, and if so, printing that 1 value I illustrated in my source data.

The formula I use for that is:

=IF(OTHER-TAB-NAME!E3=””,,1)

It checks to see if the cell (E3) in the other tab for the same date row has a value. If so, it marks a 1 down and otherwise leaves it blank. That way I can create these rows of values for graphing and additional elements, like the today’s-date row, in another sheet without getting in the way of my actual tracking sheet.

Costs, Price and Calculations for Living With Diabetes and Exocrine Pancreatic Insufficiency and Celiac and Graves

by Dana Lewis

Living with diabetes is expensive. However, the cost and price goes beyond the cost of insulin, which you may have heard about lately. In addition to insulin, you need tools and supplies to inject the insulin (e.g. syringes, insulin pens, or an insulin pump). Depending on those methods, you need additional supplies (e.g. pen needles for insulin pens, reservoirs and infusion sets for insulin pumps). You also need blood glucose monitoring supplies, whether that is meter and up to a dozen glucose test strips a day and/or a continuous glucose monitor which is made up of a disposable sensor and a reusable transmitter.

All those costs add up on a daily basis for people living with diabetes, even if you have health insurance.

Understanding the costs of living with chronic illness with health insurance in the US

Every year in the US we have “open enrollment” time when we opt-in or enroll into our choice of health insurance plan for the following year. I am lucky and have access to insurance through my husband’s employer, who covers part of the cost for him and me (as a spouse). We have a high-deductible (HSA-qualified) health plan, so our deductible (the amount we must pay before insurance begins to pay for a portion of the costs) is usually around $1,500-$2,500 USD for me. After that, I might pay either a fixed copay ($10 or $25 or similar) for a doctor’s visit, or a percentage (10% or 20%) while the insurance covers the rest of the cost. Then there is a fixed “out of pocket (OOP) max” cost for the year, which might be something like $3,000 USD total. Sometimes the OOP max is pretty close to the deductible, because we typically choose the ‘high deductible’ plan (with no monthly cost for the insurance plan) over a plan where we have a lower deductible but pay a monthly premium for the insurance.

That’s a very rough summary of how I see my health insurance. Everyone has different health insurers (the company providing the insurance) and different plans (the costs will be different based on whether it’s through a different employer or if it’s an individual plan).

So the costs to people with diabetes can vary quite a bit in the US, depending on whether you have insurance: there is variation in the monthly cost of the plan, the amount of the deductible, and the amount of the out of pocket max.

In order to choose my plan for the following year, I look at the total cost for the year of my health supplies and health care, then look at the plans. Usually, the high deductible plan “feels” more expensive because I might have to reach $2,500 before insurance kicks in; however, the out of pocket cap may only be $500 beyond that, so that I’m going to pay a maximum of $3,000 for the year in insurance-covered costs*. There are other types of plans that are lower deductible, such as insurance kicking in after a $250 deductible. That sounds better, right? Well, those plans come with a monthly cost (premium) of $250. So you need to factor that in ($250×12=$3,000) alongside the deductible and any costs up to the out of pocket max ($2,500). From this, you’d pay the $3,000 total yearly premium plus up to $2,500 OOP, or $5,500. Thus, even though it has a lower deductible and OOP, you’re in total paying much more ($5,500 vs $3,000) if you’re someone like me.

Why? Because I have >$3,000 of health supply costs every year.

This is why every few years (mostly after I forget what I learned the last time), I do the math on how much my supply costs to see if I’m still making the most cost-effective choices for me with my insurance plans.

I wanted to share this math methodology below, also because this year I have new variables, which are two new chronic diseases (exocrine pancreatic insufficiency and Graves) that add additional costs and healthcare needs and require me to want to re-check my math.

* Clarifying that previously and most years I pay out of pocket for minor, relatively low-cost health supplies like vitamins or tape to cover my CGM that I buy and do not get through insurance coverage, so my total costs are usually over that OOP max, but likely not by more than a few hundred dollars.

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Note: Do not attempt to use this as an absolute cost of diabetes for anyone else. These numbers are based on my use cases in terms of volume of insulin, insurance coverage, etc. Ditto for trying to use the costs for EPI. Where relevant below, I provide rough estimates of my methodology so that another individual with diabetes or EPI/PEI could use similar methods to calculate their own rough costs, if they wished. However, this cannot be used to determine any average cost to people with diabetes more broadly, so don’t excerpt or cite this in those ways. This is purely n=1 math with conclusions that are unique to this n=1 (aka me) but with methods that can be extended for others.

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I’ll cover my estimates for costs of diabetes, celiac, exocrine pancreatic insufficiency (EPI or PEI), and Graves’ disease below. This doesn’t account for visits (e.g. doctor’s appointments), lab tests, or other health costs such as x-rays for breaking bones, because those vary quite a bit year to year and aren’t guaranteed fixed costs. But the supplies I need for diabetes, EPI, etc are fixed costs, which I use to anchor my math. Given that they end up well above my OOP max, the then-variable amount of other costs (doctor’s appointments, lab work, etc) is minor in comparison and irrelevant regardless of how much it varies year to year.

The costs (for me) of daily living with diabetes

(You read the caveat note above, right? This is my math based on my volume of insulin, food intake, personal insulin sensitivity, etc. Lots of variables, all unique to me.)

To calculate the yearly costs of living with diabetes, I make a list of my diabetes supplies.

Primarily for me, those are:

  • Insulin
  • CGM sensors
  • CGM transmitter
  • Pump sites
  • Reservoirs

(Not included: meter/test strips or the cost of a pump or the cost of any hardware I’m using for my open source automated insulin delivery. I’ve not bought a new in-warranty pump in years, and that alone takes care of the OOP max on my insurance plan if I were to buy a pump that year. Anyway, the above list is really my recurring regular costs, but if you were purchasing a pump or on a subscription plan for a pump, you’d calculate that in as well).

First, I calculate the daily cost of insulin. I take the cost of a vial of my insulin and divide it by 1,000, because that’s how many units a vial of insulin has. Then I multiply that by the average number of units I use per day to get the cost per day of insulin, which for me is $4.36. (The yearly cost of insulin would be $1,592.)

Then, I calculate my CGM sensors. I take the total cost for a 3 month order of sensors and divide by the number of sensors; then divide by 10 days (because a sensor lasts about 10 days) to get the cost per day of a CGM sensor: about $11 per day. But, you also have to add in the cost of the re-usable transmitter. Again, factor the cost of a transmitter over the number of days it covers; for me it’s about $2 per day. In total, the cost per day of CGM is about $13 and the yearly cost of CGM is roughly $4,765.

Next is pump sites and reservoirs. You need both to go with your insulin pump: the pump site is the catheter site into your body and the tubing (this cumulatively gets replaced every few days), and the reservoir is disposable and is filled with insulin. The cost per day of pump sites and reservoirs is about $6 ($4.67 for a pump site and $1.17 for a reservoir) and the yearly cost of pump sites and reservoirs is $2,129.

If you add up these supplies (pump sites and reservoirs, CGM sensor and transmitter, insulin), the daily cost of diabetes for me is about $23. The yearly cost of diabetes for me is $8,486.

Give that $8,486 is well over the out of pocket max cost of $3,000, you can see why that for diabetes alone there is reason to pick the high deductible plan and pay a max of $3,000 for these supplies out of pocket.

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The daily and yearly costs of living with celiac disease

But I don’t just have type 1 diabetes, so the above are not my only health supply costs.

I also have celiac disease. The treatment is a 100% gluten free diet, and eating gluten free is notoriously more expensive than the standard cost of food, whether that is groceries or eating out.

However, the cost of gluten free food isn’t covered by health insurance, so that doesn’t go in my cost calculation toward pricing the best insurance plan. Yet, it does go into my “how much does it cost every day from my health conditions” mental calculation.

I recently looked at a blog post that summarized the cost of gluten free groceries by state compared to low/medium/high grocery costs for the average person. By extrapolating my state’s numbers from a high-cost grocery budget, plus adding $5 each for eating out twice a week (typically gluten free food has at least a $2-3 surcharge in addition to being at higher cost restaurants, plus the fact that I can’t go eat at most drive-throughs, which is why I use $5/meal to offset the combined cost of the actual surcharge plus my actual options being more expensive).

I ended up estimating about a $3 daily average higher cost of being gluten free, or $1,100 per year cost of eating gluten free for celiac.

That’s probably an underestimate for me, but to give a ballpark, that’s another $1,000 or more I’m paying out of pocket in addition to healthcare costs through insurance.

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The daily and yearly cost of living with exocrine pancreatic insufficiency and the daily and yearly cost of pancreatic enzyme replacement therapy

I spent a pleasant (so to speak) dozen or so years when “all” I had to pay for was diabetes supplies and gluten free food. However, in 2022, I was diagnosed with exocrine pancreatic insufficiency (and more recently also Graves’ disease, more on that cost below) and because I have spent ~20 years paying for diabetes, I wasn’t super surprised at the costs of EPI/PEI. However, most people get extreme sticker shock (so to speak) when they learn about the costs of pancreatic enzyme replacement therapy (PERT).

In summary, since most people don’t know about it: exocrine pancreatic insufficiency occurs for a variety of reasons, but is highly correlated with all types of diabetes, celiac, and other pancreatic conditions. When you have EPI, you need to take enzymes every time you eat food to help your body digest fat, protein, and carbohydrates, because in EPI your pancreas is not producing enough enzymes to successfully break down the food on its own. (Read a lot more about EPI here.)

Like diabetes, where different people may use very different amounts of insulin, in EPI people may need very different amounts of enzymes. This, like insulin, can be influenced by their body’s makeup, and also by the composition of what they are eating.

I use PERT (pancreatic enzyme replacement therapy) to also describe the prescription enzyme pills used for EPI. There are 6 different brands approved by the FDA in the US. They also come in different sizes; e.g. Brand A has 3,000, 6,000, 12,000, 24,000, 36,000 size pills. Those size refer to the units of lipase. Brand B has 3,000, 5,000, 10,000, 15,000, 20,000, 25,000, 40,000. Brands C, D, E and F have similar variety of sizes. The point is that when people compare amounts of enzymes you need to take into account 1) how many pills are they taking and 2) how much lipase (and protease and amylase) each of those pills are.

There is no generic for PERT. PERT is made from ground up pig pancreas. It’s expensive.

There are over the counter (OTC) enzymes made from alternative (plant etc) sources. However, there are ZERO studies looking at safety and efficacy of them. They typically contain much less lipase per pill; for example, one OTC brand pill contains 4,000 units of lipase per pill, or another contains 17,500 units of lipase per pill.

You also need to factor in the reliability of these non-approved pills. The quality of production can vary drastically. I had one bottle of OTC pills that was fine; then the next bottle of OTC pills I started to find empty capsules and eventually dumped them all out of the bottle and actually used a colander to filter out all of the enzyme powder from the broken capsules. There were more than 30 dud pill capsules that I found in that batch; in a bottle of 250 that means around 12% of them were unusable. That makes the reliability of the other ones suspect as well.

A pile of powder in the sink next to a colander where a bunch of pills sit. The colander was used to filter out the loose powder. On the right of the image is a baggie with empty pill capsules, illustrating where this loose powder came from. This shows the unreliability of over the counter (OTC) enzymes.

If the reliability of these pills even making it to you without breaking can be sketchy, then you need to assume that the counts of how much lipase (and protease and amylase) may not be precisely what the label is reporting. Again, there have been no tests for efficacy of these pills, so anyone with EPI or PEI needs to use these carefully and be aware of these limitations.

This unreliability isn’t necessarily true of all brands, however, or all types of OTC enzymes. That was a common brand of pancrelipase (aka contains lipase, protease, and amylase). I’ve had more success with the reliability of a lipase-only pill that contains about 6,000 units of lipase. However, it’s more expensive per pill (and doesn’t contain any of the other enzymes). I’ve used it to “top off” a meal with my prescription PERT when my meal contains a little bit more fat than what one PERT pill would “cover” on its own.

This combination of OTC and prescription PERT is where the math starts to get complicated for determining the daily cost and yearly cost of pancreatic enzyme replacement therapy.

Let’s say that I take 6-8 prescription PERT pills every day to cover what I eat. It varies because I don’t always eat the same type or amount of food; I adjust based on what I am eating.

The cost with my insurance and a 90 day supply is $8.34 for one PERT pill.

Depending on whether I am eating less fat and protein on a particular day and only need 6 PERT, the cost per day of enzymes for EPI might be $50.04, whereas if I eat a little more and need 8 PERT, the cost per day of enzymes for EPI could be up to $66.72.

The costs per year of PERT for EPI then would range from $18,000 (~6 per day) to $24,000 (~8 per day).

Please let that sink in.

Eighteen to twenty four thousand dollars to be able to successfully digest my food for a single year, not taking into account the cost of food itself or anything else.

(See why people new to EPI get sticker shock?!)

Even though I’m used to ‘high’ healthcare costs (see above estimates of $8,000 or more per year of diabetes costs), this is a lot of money. Knowing every time that I eat it “costs” at least one $8.34 pill is stressful. Eating a bigger portion of food and needing two or three pills? It really takes a mental toll in addition to a financial cost to think about your meal costing $25.02 (for 3 pills) on top of the cost of the food itself.

This is why OTC pills are interesting, because they are drastically differently priced. The 4,000 unit of lipase multi-enzyme pill that I described costs $0.09 per pill, which is about $0.02 per 1000 units of lipase. Compared to my prescription PERT which is $0.33 per 1000 units of lipase, it’s a lot cheaper.

But again, check out those pictures above of the 4,000 units of lipase OTC pills. Can you rely on those?

Not in the same way you can with the prescription PERT.

In the course of taking 1,254 prescription PERT pills this year (so far), I have not had a single issue with one of those pills. So in part the high cost is to ensure the safety and efficacy. Compare that to 12% (or more) of the OTC pills being complete duds (empty pill capsules that have emptied their powder into the bottle) and some % of unreliability even with a not-broken capsule.

Therefore it’s not feasible to me to completely replace prescription PERT with OTC pills, although it’s tempting purely on price.

I previously wrote at a high level about the cost calculations of PERT, but given my desire to look at the annual cost for estimating my insurance plan (plus many more months of data), I went deeper into the math.

I need to take anywhere from 2-6 OTC pills (depending on the brand and size) to “match” the size of one PERT. I found a new type (to me) of OTC pills that are more units of lipase (so I need 2 to match one PERT) instead of the two other kinds (which took either 4 or 6 to match one PERT), which would enable me to cut down on the number of pills swallowed.

The number of pills swallowed matters.

So far (as of mid-November, after starting PERT in early January), I have swallowed at least 1,254 prescription PERT enzyme pills. I don’t have as much precision of numbers on my OTC pills because I don’t always log them (there’s probably a few dozen I haven’t written down, but I probably have logged 95% of them in my enzyme tracking spreadsheet that I use to help calculate the amount needed for each meal/snack and also to look at trends.), but it’s about 2,100 OTC enzyme pills swallowed.

This means cumulatively this year (which is not over), I have swallowed over 3,300 enzyme pills. That’s about 10 enzyme pills swallowed every day!

That’s a lot of swallowing.

That’s why switching to a brand that is more units of lipase per pill, where 2 of these new OTC kind matches one PERT instead of 4-6, is also significant. While it is also slightly cheaper than the combination of the two I was using previously (a lipase-only and a multi-enzyme version), it is fewer pills to achieve the same amount.

If I had taken prescription PERT instead of the OTCs, it would have saved me over 1,600 pills to swallow so far this year.

You might be thinking: take the prescription PERT! Don’t worry about the OTC pills! OMG that’s a lot of pills.

(OMG, it *is* a lot of pills: I think that as well now that I’m adding up all of these numbers.)

Thankfully, so far I am not having issues with swallowing these pills. As I get older, that might change and be a bigger factor in determining my strategy for how I dose enzymes; but right now, that’s not the biggest factor. Instead, I’m looking at efficacy (getting the right amount of enzymes to match my food), the cost (in terms of price), and then optimizing and reducing the total number of pills if I can. But the price is such a big variable that it is playing the largest role in determining my strategy.

How should we collectively pay for this?

You see, I don’t have EPI in a vacuum.

As I described at the top of the post, I already have $8,000+ of yearly diabetes costs. The $18,000 (or $24,000 or more) yearly enzyme costs are a lot. Cumulatively, just these two alone mean my supply costs are $26-32,000 (or more), excluding other healthcare costs. Thankfully, I do have insurance to cover costs after I hit my out of pocket max, but the bigger question is: who should be paying for this?

If my insurer pays more, then the employer pays more, which means employees get worse coverage on our pooled insurance plan. Premiums go up and/or the plans cover less, and the out of pocket costs to everyone goes up.

So while it is tempting to try to “stuff” all of my supply needs into insurance-covered supplies, in order to reduce my personal out of pocket costs in the short run, that raises costs for everyone in the long run.

This year, for all of those (remember I estimated 2,100 OTC pills swallowed to date) OTC pills I bought, it cost me $515. Out of pocket. Not billed through insurance; they know nothing about it.

It feels like a lot of money. However, if you calculate how many PERT it replaced and the cost per PERT pill, I saved $4,036 by swallowing 1,652 extra pills.

Is paying $500 to save everyone else $4000 worth it?

I think so.

Again, the “price” question gets interesting.

The raw costs of yearly supplies I don’t pay completely; remember with health insurance I am capped at $3,000 out of pocket for supplies I get through insurance. However, again, it’s worth considering that additional costs do not cost me but they cost the insurer, and therefore the employer and our pool of people in this insurance plan and influences future costs for everyone on insurance. So if I can afford (although I don’t like it) $500-ish out of pocket and save everyone $4,000 – that’s worth doing.

Although, I think I can improve on that math for next year.

I was taking the two OTC kinds that I had mentioned: one that was lipase-only and very reliable, but $0.28/pill or $0.04 per 1000 units of lipase (and contains ~6000 units of lipase). The less reliable multi-enzyme pill was cheaper ($.09) per pill but only contains 4000 units of lipase, and was $.02 per 1000 units of lipase. That doesn’t factor in the duds and the way I had to increase the number of pills to account for the lack of faith I had in the 4000 units of lipase always being 4000 units of lipase.

The new OTC pill I mentioned above is $0.39 per pill, which is fairly equivalent price to a combined lipase-only and multi-enzyme pill. In fact, I often would take 1+1 for snacks that had a few grams of protein and more than a few grams of lipase. So one new pill will cover 17,000 units of lipase (instead of 10,000, made up of 6000+4000) at a similar cost: $0.39 instead of $0.36 (for the two combined). And, it also has a LOT more protease per pill, too. It has >2x the amount of protease as the multi-enzyme OTC pill, and is very similar to the amount of protease in my prescription PERT! I’ve mostly discussed the math by units of lipase, but I also dose based on how much protein I’m eating (thus, protease to cover protein the way lipase covers fat digestion), so this is also a benefit. As a result, two of the new OTC pill now more than match 1 PERT on lipase, double the protease to 1 PERT, and is only two swallows instead of the 4-6 swallows needed with the previous combination of OTCs.

I have only tested for a few days, but so far this new OTC is working fairly well as a substitute for my previous two OTC kinds.

Given the unreliability of OTCs, even with different brands that are more reliable than the above picture, I still want to consume one prescription PERT to “anchor” my main meals. I can then “top off” with some of the new OTC pills, which is lower price than more PERT but has the tradeoff cost of slightly less reliability compared to PERT.

So with 3 main meals, that means at least 3 PERT per day ($8.34 per pill) at $25.02 per day in prescription PERT costs and $9,132 per year in prescription PERT costs. Then to cover the additional 3-5 PERT pills I would otherwise need, assuming 2 of the new OTC covers 1 PERT pills, that is 6-10 OTC pills.

Combined, 3 PERT + 6 OTC pills or 3 PERT + 10 OTC pills would be $27.36 or $28.92 per day, or $9,986 or $10,556 per year.

Still quite a bit of money, but compared to 6-8 PERT per day (yearly cost $18,264 to $24,352), it saves somewhere between $7,708 per year (comparing 6 PERT to 3 PERT + 6 OTC pills per day) all the way up to $14,366 per year (comparing 8 PERT to 3 PERT +10 OTC pills per day).

And coming back to number of pills swallowed, 6 PERT per day would be 2,190 swallows per year; 8 PERT pills per day is 2,920 swallows per year; 3 PERT + 6 OTC is 9 pills per day which is 3,285 swallows per year; and 3 PERT + 10 OTC is 13 swallows per day which is 4,745 swallows per year.

That is 1,095 more swallows per year (3PERT+6 OTC vs 6 PERT) or 1,825 more swallows per year (3 PERT + 10 OTC vs 8 PERT).

Given that I estimated I swallowed ~10 enzyme pills per day this year so far, the estimated range of 9-13 swallows with the combination of PERT and OTC pills (either 3 PERT + (6 or 10) OTC) for next year seems reasonable.

Again, in future this might change if I begin to have issues swallowing for whatever reason, but in my current state it seems doable.

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The daily and annual costs of thyroid treatment for Graves’ Disease

No, we’re still not done yet with annual health cost math. I also developed Graves’ disease with subclinical hyperthyroidism this year, putting me to a grand total of 4 chronic health conditions.

Luckily, though, the 4th time was the charm and I finally have a cheap(er) one!

My thyroid med DOES have a generic. It’s cheap: $11.75 for 3 months of a once-daily pill! Woohoo! That means $0.13 per day cost of thyroid treatment and $48 per year cost of thyroid treatment.

(Isn’t it nice to have cheap, easy math about at least one of 4 things? I think so!)

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Adding up all the costs of diabetes, celiac disease, exocrine pancreatic insufficiency and Graves’ Disease

High five if you’ve read this entire post; and no problem if you skimmed the sections you didn’t care about.

Adding it all up, my personal costs are:

  • Diabetes: $23.25 per day; $8,486 per year
  • Celiac: $3 per day; $1,100 per year (all out of pocket)
  • Exocrine Pancreatic Insufficiency:
    • Anywhere from $50.04 up to $66.72 per day with just prescription PERT pills; $18,265 (6 per day) to $24,353 (8 per day) per year
    • With a mix of prescription and OTC pills, $27.36 to $28.92 per day; $9,986 to $10,556 per year.
    • Of this, the out of pocket cost for me would be $2.34 to $3.90 per day; or $854 up to $1,424 per year.
  • Thyroid/Graves: $0.13 per day; $48 per year

Total yearly cost:

  • $27,893 (where EPI costs are 6 prescription PERT per day); 2,190 swallows
  • $33,982 (where EPI costs are 8 prescription PERT per day); 2,920 swallows
  • $19,615 (where EPI costs are 3 prescription PERT and 6 OTC per day); 3,285 swallows
  • $20,185 (where EPI costs are 3 prescription PERT and 9 OTC per day); 4,745 swallows

* My out of pocket costs per year are $854-$1424 for EPI when using OTCs to supplement prescription PERT and an estimated $1,100 for celiac-related gluten free food costs. 

** Daily cost-wise, that means $76.42, $93.10, $53.74, or $55.30 daily costs respectively.

*** The swallow “cost” is 1,095-1,825 more swallows per year to get the lower price cost of enzymes by combining prescription and OTC.

Combining these out of pocket costs with my $3,000 out of pocket max on my insurance plan, I can expect that I will therefore pay around $4,900 to $5,600 next year in health supply costs, plus another few hundred for things like tape or vitamins etc. that aren’t major expenses.

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TLDR: 

  • Diabetes is expensive, and it’s not just insulin.
    • Insulin is roughly 19% of my daily cost of diabetes supplies. CGM is currently 56% of my diabetes supply costs.
  • EPI is super expensive.
    • OTC pills can supplement prescription PERT but have reliability issues.
    • However, combined with prescription PERT it can help drastically cut the price of EPI.
    • The cost of this price reduction is significantly more pills to swallow on a daily basis, and adds an additional out of pocket cost that insurance doesn’t cover.
    • However in my case; I am privileged enough to afford this cost and choose this over increasing everyone in my insurance plan’s costs.
  • Celiac is expensive and mostly an out of pocket cost.
  • Thyroid is not as expensive to manage with daily medication. Yay for one of four being reasonably priced!

REMEMBER to not use these numbers or math out of context and apply them to any other person; this is based on my usage of insulin, enzymes, etc as well as my insurance plan’s costs.

Yearly costs, prices, and calculations of living with 4 chronic diseases (type 1 diabetes, celiac, Graves, and exocrine pancreatic insufficiency)

What It Feels Like To Take Thyroid Medication

by Dana Lewis

I’ve been taking thyroid medication for a few months now. It surprised me how quickly I saw some symptom resolution. As I wrote previously, I started taking thyroid medication and planned to get more lab work at the 8 week mark.

The theory is that thyroid medication influences the production of new thyroid hormones but not the stored thyroid hormones; thus, since it takes around 6 weeks for you to replace your stores of thyroid hormones, you usually get blood work no sooner than 6 weeks after making a change to thyroid medication.

I had noted, though, that some of my symptoms included changes in my heart rate (HR). This was both my overnight resting HR and how my HR felt during the day. I had hypothesized:

Given I have a clear impact to my heart rate, I’m hypothesizing that I might see changes to the trend in my heart rate data sooner than 6 weeks – 2 months, so that’ll be interesting to track!

This turned out to be an accurate prediction!

My provider had suggested starting me on a low dose of “antithyroid” medication. Guidelines typically suggest 10-20mg per day, with plans to titrate (adjust) the dose based on how things are going. However, in my case, I have subclinical hyperthyroidism – not actual hyperthyroidism – which means my thyroid levels themselves (T3 and T4) were in range. What was out of range for me was my thyroid stimulating hormone (TSH), which was below range, and my thyroid antibodies, all of which were above range. (If you want to read about my decision making and my situation with Graves’ disease with eye symptoms and subclinical hyperthyroidism, read my previous post for more details.)

I ended up being prescribed a 5mg dose. Thinking about it, given my T3 and T4 were well within range, that made sense. I started taking it in early August.

What it felt like to start taking antithyroid medication for the first time:

For context, my primary most bothersome symptoms were eye symptoms (eyelid swelling, sometimes getting a red patchy dry area outside the outer corner of my eye, eye pressure that made me not want to wear my contacts); increased resting overnight HR and higher HR during periods of rest during the day; and possibly mood and energy impacts.

  • Within a week (!) of starting the antithyroid medication, my overnight HR began lowering. This can be influenced by other factors like exercise etc., but it was also accompanied by fewer days with higher heart rate while I was sitting and relaxing! I definitely felt a noticeable improvement within a week of my heart rate-related symptoms. 
  • My eyelid swelling went away toward the end of the first week. Then after 3 or so days, it came back again for a few days, then went away for 12 days. It came back for several days, went away for another 6 days. Came back, then…nothing! I went weeks without eyelid swelling and none of the other eye-related symptoms that typically ebbed and flowed alongside the eyelid swelling. HOORAY!
  • It’s unclear how much my mood and energy were directly effected by the wonky thyroid antibody levels compared to being a correlation with the symptoms themselves. (I was also resuming ultramarathon training during this time period, following the recovery of my broken toe.) However, I definitely was feeling more energetic and less grumpy, as noticed by my husband as well.

What is interesting to me is that my symptoms were changed within a week. They often talk in the medical literature about not knowing exactly how the thyroid medication works. In my case, it’s worth noting again for context that I had subclinical hyperthyroidism (in range T3 and T4 but below range TSH) and Graves’ disease (several thyroid antibodies well above range) with correlated eye symptoms. The theory is that the eye symptoms are influenced by the thyroid antibody levels, not the thyroid levels (T3 and T4) themselves. So although the thyroid medication influences the production of new thyroid hormones and it takes 6 weeks to replace your store of thyroid hormones; my working hypothesis is that the symptoms driven by TSH and thyroid antibodies are influenced by the production of those (rather than the stores) and that is why I see a change to my symptoms within a week or so of starting thyroid medication.

I went for repeat lab work at 8 weeks, and I was pretty confident that I would have improved antibody and TSH levels. I wasn’t sure if my T3 and T4 would drop below range or not. The lab work came back in and… I was right! TSH was back to normal range (HOORAY), T3 and T4 were slightly lower than the previous numbers but still nicely in the middle of the range. Yay! However, my TSI (thyroid stimulating immunoglobulin) was still well above range, and slightly higher than last time. Boo, that was disappointing, because there are some studies (example) showing that out of range TSI can be a predictor for those with Graves’ disease for the need to continue antithyroid medication in the future.

Animated gif showing changes to various thyroid labs two days and 8 weeks after annual lab work. T3 and T4 remain in range, TSH returns from below to in range, TSI remains above range; TRAb, TgAB, and TPO were above range but not re-tested at 8 weeks.

As I wrote in my last post:

I am managing my expectations that managing my thyroid antibody and hormone levels will be an ongoing thing that I get to do along with managing insulin and blood sugars and managing pancreatic enzymes. We’ll see!

The TSI was a pointer that although I had reduced all of my symptoms (hooray) and my T3 and T4 were within range, I would probably need ongoing medication to keep things in range.

However, as a result of the lab work, my provider suggested dropping down to 2.5mg dose, to see if that would manage my thyroid successfully without pushing me over to hypothyroidism (low T3 and T4) levels, which can be a risk of taking too much antithyroid medication. He suggested switching to 2.5mg, and repeating lab work in 3 months or if I felt unwell.

I agreed that it was worth trying, but I was a little nervous about reducing my dose, because my T3 and T4 were still well within the middle of normal. And, I had an upcoming very long ultramarathon. Given that with the start of thyroid medication I saw symptoms change within a week, and I was two weeks out from my ultra, I decided to wait until after the ultramarathon so I could more easily monitor and assess any symptoms separately from the taper and ultra experience.

Recovery from my ultramarathon was going surprisingly well, enough so that I felt ready to switch the medication levels pretty soon after my ultra. I started taking the 2.5mg dose (by cutting the 5mg dose in half, as I had some remaining and it was easier than ordering a changed prescription to 2.5mg).

I carefully watched and saw some slight changes to my HR within the first week. But, I was also recovering from an ultramarathon, and that can also influence HR. Again, I was looking at both the overnight resting HR and noting any periods of time during the day where I was resting when my HR was high (for me). I had two days where it did feel high during the day, but the following days I didn’t observe it again, so I chalked that up to maybe being related to ultramarathon recovery.

But a little over a week and my right eye started feeling gunky. I had just been to the eye doctor for my annual exam and all was well and my eye didn’t look red or irritated. I didn’t think much of it. But a few days after that, I had rubbed my right eyelid and realized it felt poofy. I felt my left eyelid in comparison, and the right was definitely swollen in comparison. Looking in the mirror, I could see the swollen eyelid pushing down the corner of my right eye. Just like it had done before I started thyroid medications. Ugh. So eye symptoms were back. A few days later, I also woke up feeling like my eyes hurt and they needed lubrication (eye drops) as soon as I opened my eyes. That, too, had been a hallmark of my eye symptoms from last October onward.

The plan had been to wait until 3 months after this medication change to repeat labs. I’m going to try to wait until the 6-8 week mark again, so we can see what the 2.5mg does to my T3 and T4 levels alongside my TSH. But, my prediction for this next round of lab work is that T3 and T4 will go up (maybe back to the higher end but likely still within range; although the possibility to fully go above range), and that my TSH will have dropped back down below range, because the symptom pattern I am starting to have mimics the symptom pattern I had for months prior to starting the 5mg thyroid medication.

Why only wait 6-8 weeks, when my provider suggested 3 months?

These symptoms are bothersome. The eyelid swelling thankfully subsided somewhat after 4 days (after the point where it got noticeable enough for my husband to also see it compressing my outer corner of my eye, which means anyone would be able to visibly see it), but I’m watching it to see if it returns with a cyclical pattern the way it went away previously, expecting it to likely return to constant every day eye swelling. Since it influences my vision slightly (because the eyelid is pushed down by the swelling), that impacts my quality of life enough to take action sooner. If it gets really bad, I might discuss with my provider and get labs even sooner, but I’m going to try to tough it out to 6-8 weeks to get a full picture of data of how the 2.5mg impacted all of my levels and also see what pattern of symptoms return when, because it will be interesting to compare the symptom levels at 5mg (essentially all gone within 1-2 weeks) and at 2.5mg compared to my original, pre-thyroid medication symptom levels and patterns.

But depending on those labs, I predict that I will return to taking the 5mg dose, and hopefully my symptoms will go away completely and stay away. Then it’ll be a future decision on if/when to try titrating down again; possibly guided by the TSI level, since the TSI was still above range when we had switched me to 2.5mg (despite the change in TSH back to range).

The good news is, though, that in future I should be able to use the 1-2 weeks of symptom data to determine whether a change in dose is working for me or not, instead of having to wait a full 6-8 weeks, because my symptoms seem to be driven by the TSH and antibody levels, rather than out of range T3 and T4 levels (because they were and are still in the middle of the goal range).

I also discussed this with my eye doctor. You’ll note from my previous post that I was very concerned about the eye impacts and symptoms, so I had asked my eye doctor if she’s still comfortable treating me (she is), and we talked about what things would cause me to get a referral to a specialist. So far my symptoms don’t seem on track for that; it would be my eyes protruding from the socket and having pressure that would possibly need surgery. Disappointingly, she confirmed that there’s really no treatment for the symptoms since they’re caused by the antibody levels. There’s no anti-swelling stuff to put on my eyelid to help. Instead, the goal is to manage the antibody levels so they don’t cause the symptoms. (Which is everything I’m talking about doing above, including likely returning to the 5mg dose given that my eye symptoms resumed on the 2.5mg dose).

—

In summary, I think it is worth noting for anyone with Graves’ disease (whether or not they have subclinical or actual hyperthyroidism) that it is possible to see symptom changes within a week or two of starting or changing your thyroid medication. I can’t find anything in the literature tracking symptom resolution on anything shorter than a 6 week time period, but maybe in the future someone will design a study to capture some of the real-world data and/or run a prospective study to capture this data and see how prevalent this is for symptoms to resolve on a much shorter time frame, for those of us whose symptoms are driven not by thyroid levels themselves (T3 and T4) but for the TSH and TSI and other thyroid antibodies (TPO etc).

If you do start thyroid medication, it’s worth logging your symptoms as soon as  possible, ideally before you start your medication, or if it’s too late for that, start logging them afterward. You can then use that as a comparison in the future for if you reduce, increase, or are directed to stop taking your medication, so you can see changes in the length of time it takes to develop or reduce symptoms and whether the patterns of symptoms change over time.

What it feels like to take thyroid medication

Convening The Center Paper Describing Our Methods and The Two-Spectrum Framework For Assessing Patient Experience

by Dana Lewis

I’m excited to share another paper is out that has been in the works for a while. This paper describes the methods we used to design the Convening The Center project, and an artifact we ended up creating in the process that we think will be helpful to people with lived experience and traditional researchers and others who want to partner with patients!

As a quick recap, John Harlow and I (Dana Lewis) collaborated to create Convening The Center (CTC) to bring people (known as “patients” and “carers”, or people with lived experience based on health and healthcare experiences) together, solely to allow them to connect and convene about what they care about. There was no agenda! It’s a bit hard to design an agenda-less meeting, and we put a lot of thought into it. We ended up converting from an in-person gathering in 2020 to a digital experience due to the COVID-19 pandemic, which also required a lot of design in order to achieve a digital space that allowed virtual strangers to feel comfortable connecting and discussing their experiences and perspectives.

One theme that came up throughout the first individual round of discussions (Phase 1) was that there was a spectrum of participation; some people participate and contribute as individuals to other projects and organizations, whereas others choose to or find themselves in situations that necessitate creating something new. I also saw there were different levels, from individual to community or system-level creation and contributions.

Thus, the Two-Spectrum Framework for Assessing Patient Experience was created, and we used it to “see” where our 25 participants from CTC fell, based on our Phase 1 discussions, and this helped us group people in Phase 2 (alongside scheduling availability) for smaller group discussions.

Figure 1 from our paper, illustrating the Two-Spectrum Framework for Assessing Patient Experience. It shows a horizontal spectrum with "contributing" on the left and "creating" on the right. The vertical axis has "level 1 - individual" at the bottom; "level 2 - community" in the center, and "level 3 - systems" at the top. Light blue boxes, 25 in total, are arranged across this spectrum to illustrate where CTC participants are.
Figure 1 from our paper, illustrating the Two-Spectrum Framework for Assessing Patient Experience

It was really helpful for thinking about how patients (people with lived experience) do things; not just the labels we are given by others. And so I decided we should try to write it up as a paper so that others could use it as well!

An animated gif showing an individual first on the continuum from contributing to creating; then the various locations on the vertical spectrum (indivdiual to community to systems) where they might be.
An illustrated gif I use to articulate how individuals might see themselves on the Two-Spectrum Framework for Assessing Patient Experience.

As of today, our paper is now out and is open access: “From Individuals to Systems and Contributions to Creations: Novel Framework for Mapping the Efforts of Individuals by Convening The Center of Health and Health Care”.

I encourage you to read it, and in particular the “Principal Findings” section of the discussion that talks more about the Two-Spectrum Framework for Assessing Patient Experience. Notably, “Rather than making claims about what patients “are,” this framework describes what patients “do,” the often-unseen work of patients, and, importantly, how they do this work “, and the implications of this.

We hope you find something in this paper useful, and we’re excited to see how this framework might be further used in the future!

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Huge thanks to our advisors, Liz Salmi and Alicia Staley, who not only advised throughout the project but also co-authored this paper with us. And of course, ongoing respect, admiration, and appreciation to the 25 participants of Convening The Center, as well as our artist collaborator, Rebeka Ryvola who’s beautiful work is represented in this paper!

What Do You See When You See (Or Think Of) Diabetes?

by Dana Lewis

What do you see when you see (or think of) diabetes?

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In my house, I see small piles of low treatments (for hypoglycemia) in every place that I hang out. On my desk next to my computer. In my bedside table. On the counter next to the door where I grab them before heading out for a run or a walk. On the edge of the bathtub in my shower, because low blood sugars happen everywhere.

Sometimes, one of my nephews spots them in a translucent pocket on my shorts. His brain sees candy at first, not a medical treatment. Which is fine – he’s young. He’s learning that for Aunt Dana, they’re not “candy” or a “treat” – they’re a medical treatment.

All of the nieces and nephews have learned or are learning that Aunt Dana has “robot parts”, which is how they see my pump clipped to my pocket or waist band or the hard lump (CGM sensor) they feel or see on my arm.

—

What I hope people see, though, is that diabetes is not a death sentence. Thanks to improvements in insulin, insulin delivery, and blood glucose measuring, it’s no longer visibly tied to possible complications of diabetes, like amputations, kidney dialysis, or loss of vision. That is what I saw when I was diagnosed with diabetes in 2002, and what was presented to me.

I hope instead that people see people with diabetes like me living our lives, running 82 mile ultramarathons (for those of us who wish to do that), experiencing pregnancy (for those who wish to do that), achieving our career goals, living life in whatever ways we want to live our lives. Just like everyone else.

—

It’s worth noting that when typing this, autocorrect in my first sentence suggested “treat” instead of “treatment”.

That’s how computers “see” diabetes, too, with sugar and carbs equivalent with diabetes. Despite the fact that medical research shows that diabetes is a complicated combination of genetics, immune system shenanigans (my words), and numerous other factors not in a person’s control, humans haven’t gotten that message. People are still stigmatized and joked about.

So computers learn that. And that’s what they see.

When I was testing Stable Diffusion (an open source AI tool for generating images) recently, I learned about a site “Lexica” that shows you what other people have generated with similar key words. I thought it would be interesting to get ideas for better images to visualize concepts in posts about diabetes, so I searched diabetes.

A screenshot of search results in Lexica for the term "diabetes". Primarily it is images of people portrayed as very overweight and many images of a lot of food.

I should’ve known better. Humans say and think “diabetes” in response to seeing pictures of carbohydrates, so that’s what computers learn.

AI doesn’t know any better because humans haven’t taught themselves any better.

Sadly, “insulin pump” as a key word is disheartening in a different way.

A screenshot of image results from Lexica for the term "insulin pump", which mostly shows a mix of devices that look like blood glucose meters or pulse oximeters.

There are so few existing visuals and images of people with insulin pumps that the visual images generated by AI are a mix of weird hybrid old school computer components and blood glucose monitors or other medical devices.

“Hypoglycemia” mostly generates cartoons in foreign languages or made up languages that I’m guessing are jokes by people without diabetes about having low blood sugar and using it as an excuse for various things. “Hyperglycemia” brings a mix of the hypoglycemia-style cartoons and the diabetes-style images of carbs and how the AI thinks people with diabetes all look.

I’ve noticed this with AI-writing tools, too. AI is good at completing your sentence or writing a few sentences based on well known concepts and topics that already exist today. It’s not yet good at helping you write content about new concepts or building on existing content.

It’s trained on the content of today and the past, which means all of the biases, stereotypes, and stigmatizing content that aren’t good today are also extrapolated into our future with AI.

I don’t have all the answers or solutions (I wish I did), but I want to flag this as a problem. We can’t expect AI to do better trained on what we have and do today, because what we do today (stigmatize, stereotype, and harm people living with chronic diseases) is not ok and not good enough.

We need to change today and train AI with different inputs in order to get different outputs.

That starts with us changing our behavior today. As I wrote a few days ago, please speak up when you see chronic diseases being used as a “joke” and when we see people being stereotyped or when we see racism occurring.

It’s hard, it’s uncomfortable – both to speak up, and to be corrected.

I’ve been corrected before, on verbal patterns and phrases I learned from society that I didn’t realize were harmful and stigmatizing to other people.

I’m working on learning to say “I’m sorry, you’re right, and let me learn from this” and trying to do better in the future, living up to my statement that I’m going to learn from that moment.

It can absolutely be done. It desperately needs to be done, by all of us.

We can course-correct, whether it’s in a one on one conversation, something we see in a small social network in social media, or even in a large room at a conference.

I still remember and appreciate greatly when I flagged that a diabetes joke was made at a conference on stage over four years ago. Upon hearing the joke, I noted that half the room laughed; and that it wasn’t ok. So I spoke up on Twitter, because I was live tweeting from the conference. I didn’t think much would come from it. But it did. Amazingly, it did.

John Wilbanks saw my tweet, realized it wasn’t ok, and instead of tweeting support or agreement (which also would have been great), took an amazing, colossally huge and unexpected step. He literally got up from his seat, went to the microphone, and interrupted the panel that had moved on to other topics. He called out the fact that diabetes was used as a joke a few minutes prior and that it wasn’t ok.

He put on a master class for how to speak up and how to use his power to intervene.

It was incredibly powerful because although the “joke” had gone over most people’s heads and they didn’t think it was a big deal, he brought attention to the fact that it had happened, was hurtful and harmful, and created a moment for reflection for the entire room of hundreds of people.

We need more of this.

When someone flags that they are being stereotyped, stigmatized, being discriminated against – we need to speak up. We need to support them.

It matters not just for today (although it matters incredibly much for today, too) but also for the future.

AI (artificial intelligence) learns from what we teach it, much like our children learn from what we teach and show them. I don’t have kids, but I know what I do and how I behave matters to my nieces and nephews and how they see the future.

We need to understand that AI is learning from what we are doing today, and what we do today matters. It should be enough to want to not be racist, discriminating, stereotyping, and harmful to other people today. But it’s not enough.

The loudest voices are often the ones establishing “normal” for our culture, our children, and the AI systems that may be running much of the world before our children graduate college. We need to speak up to help shape the conversation today, because  what we are doing today is teaching our children, our technology, and is what we’ll get in the future, ten-fold.

And I want the future to look different and be better, for all of us.

What do you see when you think of diabetes? And what are we teaching our children and our technology?

What It Feels Like To Run 100 Miles Or Similar Long Ultramarathons

by Dana Lewis

Sometime in the last year, I decided I wanted to run 100 miles. In part, because I wanted to tackle the complex challenge and problem-solving that is even figuring out how to do it.

My situation as an ultrarunner is slightly atypical: I have type 1 diabetes and need to closely manage insulin levels and glucose levels while running; I have celiac disease so I can only eat 100% gluten free things; and I have exocrine pancreatic insufficiency (EPI) so I need to swallow enzymes with everything that I eat, including when I run. It’s a logistical cornucopia of challenges…which is in part why I wanted to do it. It wouldn’t be half as rewarding if it were easy? Or something like that.

But mainly, I wanted to prove to myself that I can do hard things, even things that most people think I can’t do. No, I can’t produce my own insulin, but I can locomote for 100 miles at one time despite this and the other challenges I have to deal with along the way.

Plus, there’s the “normal” ultrarunning challenges of fueling, hydrating, managing electrolytes, keeping your feet from becoming a ball of blisters, etc.

Ultrarunning is a sport where it generally doesn’t matter how fast you go, and the farther the distance the more of an equalizer it is. I’m a slow runner, and I had trained at an easy slow pace that I planned to run during my race (self-organized). Not having the pressure of time cutoffs would help. I was also curious whether running so slow at the start would possibly help me maintain a more even pace split across the entire run, and whether I could ultimately achieve a reasonable time by keeping consistent slow paces, compared to many I’ve read about who go a bit too fast at the start and end up with wildly different paces at the end. Everyone hurts running an ultra no matter how much you run or walk or both and no matter how fast or slow you go, but I was hoping that more consistent pacing and effort would minimize how terrible everything felt if I could pull that off.

Background

I trained, ran a 50k in June, and resumed training and worked back up to 24 mile long runs and all was going well, until I massively broke a toe and had 6 weeks off. Then I resumed training and re-built back up to running 29 miles, ending around midnight for night-run training. At that point, I had one more long run scheduled (32-ish miles), but decided I would rather skip the last long run and push my 100 mile run up a few weeks to try to beat the impending rainy season that Seattle would eventually get.

The joke was on me. We had 6+ weeks of terrible air quality, which peaked into a two-day stretch of downright “hazardous” (ugh) air quality the two days before my run. Air quality was finally improving overnight before and the morning of my run, thanks in part to the most rain we had gotten in 128 days. Woohoo! So I got to add some wet and cold running challenges to my list of problem-solving that I’d tackle during my run.

Overall, though, my training had gone well, and I had spent enough time planning and prepping that I felt relatively confident. Mostly, confident that no matter how well or long I trained, it was going to hurt. All over. For what felt like forever, and then I still wouldn’t be anywhere near done. And confident that I had planned and prepped to the best of my ability, and that I could figure out how to tackle whatever situations I faced as they came.

How I felt before the race

Aside from having cabin fever from being inside (AQI was too hazardous to go out even with a mask), I felt fairly good in terms of running fitness. I had been tapering, my legs felt fresh, I was fueling and hydrating and everything felt fine. Unfortunately, though, while I managed to escape many taper niggles, I experienced a round of ovulation pain that I don’t get every month but was lucky enough to get this month, for the 3 days prior to my race. (I’m not sure why, but in the last few years after never experiencing ovulation pain, I have started to get ovulation pain similar to period pain and cramps and general icky feelings. My doctor isn’t concerned about it, but it’s unfun, and in this case poorly timed.) So I was a bit grumpy about going into my race in a less-than-perfect state, even though “perfect” state is an ideal and usually there is something wrong, whether it’s a taper niggle or something else.

The thing I was most pleased about was my feet. My broken toe had healed well and hadn’t been giving me any issues. However, after I broke my toe it changed my foot strike or how my feet move in my shoes in a way that caused epic blisters and then I kept getting blisters on top of blisters for several runs. I finally figured out that I needed to try something different, stopped causing new blisters, and the existing blisters healed, peeled off, and went away. So my feet were in great shape, and despite being nervous about the effect of the rain on my feet during my 100 miles, I at least was starting from a “clean slate” with healthy, non-blistered feet.

The start

I set my alarm and woke up and checked air quality. The winds and the start of the rain had blown it absolutely clear, so I was able to head out without a mask for the first time in weeks! (Last time I ran with it for all 8 hours of my long run, which is annoying when you need to fuel every 30 min.)

I wasn’t even a mile in when I had my first problem. I started with a long sleeve shirt and my rain jacket, knowing I’d warm up and want to take it off soon after I started. As I removed my arms from my rain jacket (keeping it zipped around my waist) and shuffled my arms in and out of my running vest, I suddenly felt water hit my feet and looked down. Water was gushing out of my hydration hose! I grabbed it and stuck my finger over the end: the bite valve had flown off somehow while I was getting out of my jacket. Ugh.

Luckily, though, this is where all of my planning and reading of others’ experiences had come in handy. While this had never happened to me, I had read in someone’s blog that this had happened and it took them 20 minutes to find the valve. I had a bright waistlamp and it was getting increasingly lighter outside as the sun rose, so I hoped mine would be easier to spot. I figured it was stuck in my rain jacket sleeve so I worked to check my sleeve and vest for the valve. No go. I looked around and didn’t see it. I turned and walked back a bit, looking for it on and off the trail. No luck. I finally pulled out my phone and called Scott, while still holding my finger over the hydration hose to keep it from leaking out 3 liters of water. While I talked to him and told him I probably needed him to get dressed and bike out a replacement valved to me, I turned around and walked forward again one more time. Aha! Found it. It had flown way to the left side of the trail. I replaced it and breathed a sigh of relief. It had added only 4 minutes to my first mile time.

Well, I thought: that’s one way to keep my early paces slow! I hung up with Scott, and carried on.

The first lap I was very focused on making sure my socks and shoes were in good shape. I am pretty good at gutting it out if I have blisters or foot issues, but that’s not a good strategy when you’re going to cover 99 more miles. So 6 miles into my first lap, I stopped at a bench, took my socks off, and re-lubricated my feet. Later on the way back (this first lap was an out-and-back), I stopped at mile 16 and similarly sat on a rock to re-lubricate and add lamb’s wool to reduce rubbing on the side of my foot.

A picture of Dana Lewis running down the rainy paved trail, with resupply gear (dry shoes, water, fuel) in the foreground of the picture. She's wearing shorts, a rain jacket, and a rain hat. She is smiling and around 12 miles into her eventual 82 mile run).

Yet overall, lap 1 went well. It started raining after about 20 minutes so I ran with my rain hat and rain jacket on (I put it on after my bite valve escapades at mile 1), and intermittently put my hood over my hat and took it off when the rain picked up or lessened, respectively. But it pretty much rained the whole time. Scott met me as planned after my turnaround spot (about 12 miles in) and refilled my hydration pack and I re-packed my vest with snacks, enzymes, and electrolytes and carried on.

At the end of lap 1 (almost 24 miles), I physically felt pretty decent. I had been working to focus on the lap I was in and what I needed to do for the next lap. Nothing else. No thoughts of how many miles I would run or hours it would take. My watch had stopped itself in the rain and canceled the run (argh), so I wasn’t going to have a running total of time throughout the entire run like I wanted. But this might have been a feature, as it kept me from using my watch for that and I set a new lap/run each time I headed out so I could keep an eye on the segment pace, even though I had no idea what the overall pace time really was.

A paved trail picture taken from on the trail. Trees and a river are to the left; more trees line the trail to the right. It is very cloudy, the trail is visibly wet.I went slow the first lap (part of why I was feeling so strong), and I took my time in between laps. I pulled off my socks and shoes. I used hand sanitizer on them to draw some of the water out, then re-lubricated and added Desitin (to continue to help draw water out of my feet and aid in preventing blisters). Then I put on a fresh pair of toe socks and added more lamb’s wool in between key toes that typically are blister-prone. At this stage I had no blisters, and other than wet soggy feet was in good shape! Sitting for 10 minutes for my sock and foot care change chilled me, though, and I was happy to start moving again and warm back up.

The middle

I headed out on lap 2, which similarly went well. This was my “triangle” shaped loop/lap. The only issue I had this lap was that it was the only section of my route where the trail crossed 3 small intersections. Two had lights but one did not. At the intersection without a light, there were no cars so I continued running across the pedestrian crossing. As I stepped out I saw a car whipping around the corner with their head turned looking for cars in the opposite direction. Not sure if they would turn in time to see me, I slammed on my physical brakes. They did turn and see me and stopped in plenty of time, so I continued across the crossing and on the trail. However, that had tweaked my right ankle and it felt sore and weak. Argh. It felt better after a few more minutes, but it intermittently (once every hour or so) would feel weak and sore throughout the rest of my run as a result.

After lap 2, I again sat to remove my socks and shoes, dry my feet, put hand sanitizer on them, re-lubricate, etc. My feet were definitely wet and wrinkly, so I added even more Desitin to my feet. It wasn’t raining super hard but it was a constant hard drizzle that was soaking through to my socks and feet even though there weren’t many puddles (yet). This time, though, I used some reusable hot packs while I sat to change shoes, so I wasn’t as chilled when I left.

Lap 3 (back to an out-and-back route) also went well, and I was starting to realize that I was in surprisingly good physical shape. My feet were intermittently a little bit sore from pounding the ground for hours, but they weren’t constantly annoying like I’ve had on some training runs. I had long surpassed my longest running distance (previously 32 miles; at the end of lap 3 I would reach 52 miles) and longest ever running time. I did develop one or two small blisters, but they didn’t bother me. Usually, I build up huge blisters and they’re a constant annoyance. During my race, maybe thanks to the Desitin etc, I only noticed the blisters (which were fairly tiny) when they popped themselves. I had one on each foot pop and sting for a minute and then not bother me again, which was pleasant! Lap 3 was also when it got dark, so I’d headed out with my double waist lamp. I have two sets of two waist lamps that we strapped to each other; I turn one on and run it out (somewhere around ~3 hours) and then turn the belt around and turn the other lamp on. This lasts me the longest laps I have, even if I was going at walking speed. It’s plenty of light for the paved trail even on the darkest nights, but because it was raining it was cloudy and the city’s light pollution reflected off the clouds so that trail itself was easy to see! So while I only saw a few stars at the end of the night in between patches of cloud, for most of the night the night-running aspects were pretty easy. Dana sits on a bench at a picnic table in a public park. It is dark. She is wearing long rain pants, a rain jacket, and a rain hat and is bent over her bare feet, applying lubrication. It is dark and nighttime, so she has an extra waistlamp on the table illuminating her feet. Other ultrarunning supplies are strewn across the table.

Interestingly regarding my feet, after lap 3 they were still white and wrinkly a bit, but they were definitely drying out. They were much drier than they had been after lap 2, so the combination of hand sanitizer and Desitin was working. I was pleased, and again slathered with more lubricant and Desitin before putting on fresh socks and heading back out for lap 4, which would be a repeat of my “triangle” lap.

Physically, I was mostly ok. My feet weren’t hurting. I had expected my IT bands to get tight and bother my right knee and for my hips and back to start getting sore: my left knee did intermittently hurt some, but it was like a 3/10 annoyance and came and went. Stretching my hip flexors didn’t change the tightness of my IT band, but it was also the least amount of knee pain I’ve ever had when things got tight, so it was very manageable and I didn’t stress about it. It was hard to believe that with the completion of this lap (lap 4) that I’d have finished a 100k (62 miles) and added a few miles to it!

It seemed like the triangle loop wanted to keep things interesting, though. On Lap 4, after I had turned off into the section that has the intersections and the “triangle” part of the loop, my hydration hose made a gurgling noise. I felt the back of my hydration pack, which was rock solid with ice…but no water left. Oops, I thought. I was at mile 6 out of 13. If I kept going forward on my route, it would take me an estimated 4+ miles to get back to the next water fountain. Or I could call and wake up Scott, who had just fallen asleep for his first 2 hour nap overnight (it was around 1am by now), to bring me water, but that would take him 20-30 minutes before reaching me.

It mattered that I didn’t have water. Not just in terms of thirst and hydration, but I also needed water to be able to swallow my electrolyte pills (every 45 minutes) and my fuel (every 30 minutes when I ate a snack) and the digestive enzymes I absolutely require to digest my food since I have EPI. I definitely needed water so that my hydration, fueling, electrolytes, etc. wouldn’t suffer.

I could go back, but I hated to backtrack. It would be a mile back to the previous water fountain, although I wasn’t even sure it would be turned on and working. Mentally, though, I groaned at the thought of “turning around” and finishing the loop in reverse and trying to figure out how many miles I would cut off that loop and how many I’d have to added to my very last loop to make up for it.

Luckily, I realized a better idea. Because I was on the section of the triangle running alongside a road (hence the annoying intersection crossings), the intersections are where the road turned off into various parking lots. Across the road at one of the two intersections with lights was a gas station! I could see it glowing from a quarter of a mile away. I crossed my fingers hoping it would still be open, because I could go inside and buy a bottle of water to hold me over. It was open! I crossed the intersection and went in, grabbed a liter of water, bought it, went outside, and refilled my hydration bladder under the bright lights of the gas station.

A 1-liter wattle bottle held in a hand covered with a blue nitrile gloves.
I’m wearing nitrile gloves to help keep my hands drier and warmer given the cold, endless rain.

I was pretty proud of that solution, especially because it was ~1am and I had been running for 17 hours and was able to troubleshoot and solve that problem on the fly! Without sending it, I also drafted a text to send to Scott near the end of that loop when he’d be awake, to list out which foods and gear I wanted at the next refuel, and to specify what happened and how I solved it and request that I get more water and less ice for the next loop.

(Running out of water was on my list of things I planned for in all of my preparation, so while I had low expectations of my mental capacity as the miles piled up, that likely helped because I had mentally listed out where all the available water fountains were, so I could run my loop mentally forward and backward to figure out where the closest one was. In this case it was a mile behind me; going forward it would have been 4+ miles or more than an hour away. The gas station ended up being 15 minutes from where I realized I was out of water).

Finishing lap 4 was exciting, because I only had 3 laps left to go! I had one more out and back loop, and my father-in-law was driving down in the wee hours of the morning to run part of it with me to keep me company. We hadn’t planned on that all along, but he and Scott had been texting and working it out, so Scott just told me that was the plan and I was thrilled. I was a little bit tired overall, but more energetic than I thought.

The sock change before lap 5 was disappointing, though. After lap 3, my feet had been drying out a little bit. Now after lap 4 they were wet and soft again, like they were after lap 2. The rain had been more constant. I took the time (15-20 min) I needed to dry and treat them with hand sanitizer, lubricant, Desitin, replace fresh toe socks and lambs wool and dry shoes. They weren’t hurting, so I was hoping the light rain would taper off and my feet would dry out again.

The (beginning of the) end

I headed out on to lap 5, buoyed by the thought that I only had ~4 miles ‘til I had company. The rain picked up again (argh) and as my father-in-law met me on the trail with his headlamp and rain gear, he asked if it had been raining this much the whole time. No, I said, and pointed out that it had only been raining hard in 10-20 minute chunks and this one had been going since before I met him so it should lighten up soon. He commented on how energetic and chatty I was. “You’re pretty chatty,” he said, “for 5am!” (I am well-known in both our families for NOT being a morning person). I joked about how impressive it was for me being this chatty not only at 5am but also for it being 22 hours into my run!

Unfortunately, 3 miles into the section he ran with me, it went from annoying hard drizzle to an epic mega downpour. My shoes went from damp from constant hard drizzle to super soaked from top all the way down to the insoles squishing with every step. I was frustrated, because this much rain was also making it hard to use my phone. My phone had an alarm going off every 30 minutes to remind me to fuel; I needed to pull out my phone each time and turn off the very loud alarm (it was effective!) and then open up my spreadsheet and enter what I ate and what electrolytes I took. Then I also had to pull the baggie out of my vest pocket, select out the number of enzyme pills I needed with wet and cold gloved fingers, re-seal the baggie and put it back in my vest, and get out the fuel from the other pocket of my vest and eat it. Even tired, I was managing to fuel successfully and stay on top of my schedule. I was increasingly proud of this.

But the rain and the inability to use my phone when I wanted to was starting to irritate me, in part likely because I was trying not to stress about what the volume of water was doing to my feet. They weren’t actively hurting, but I knew this much water for this long of time could be dangerous and I needed to be careful. It was still downpouring when we reached the turnaround and headed back to his car. I dropped him off at his car and carried on. I was tired, soaked, cold, but physically in great shape otherwise in terms of legs, knees, hips, back etc all holding up and not feeling like i had run ~78+ miles at that point!

I had just eaten another snack and went to press buttons on my pump to give myself some insulin for the snack. It didn’t seem to work. I have a vibration pattern so I can use the pump without seeing it; but the “enter” button was not working. I had been concerned about the volume of water my pump was going to be exposed to and mentally prepared for that, but it was SO disheartening to suddenly feel the pattern of 6+ vibrations followed by an audio beep indicating an error state had been reached on the pump. I cursed to myself, out in the rain after 24 hours of running, knowing what I would find when I pulled my pump out from under my jacket. Sure enough, “button error”, because water had gotten under the buttons and to protect itself, the pump went into a “I won’t do anything” state. That meant that the insulin I needed for my latest snack wasn’t going to happen and any future insulin wasn’t going to happen.

I pulled out my phone and started a text to Scott, explaining that I had a button error and needed him to pull out my backup pump. I told him where it was, told him to put in a new battery and program it with the basal rate that I wanted. I then sent a text saying it was raining a lot and it would be easier if he called me if he needed to talk, because it was so hard to use my phone in the rain. He read the text so I knew he was awake, so I called him and talked to him while I trudged on and he was getting dressed and packing up my replacement pump and the gear I needed for lap 6. Then we hung up and I carried on, grumbling along the way and starting to feel the physical effects of not having enough insulin for the past hour or so.

A picture of a glucose graph from a CGM. The dots are flat in the first hour of the screenshot, then slowly and almost exactly lineary head up and to the right.

My blood glucose levels were rising, but I wasn’t worried about that. I knew once I had replacement insulin my blood sugars would come down nicely. I had prepared for this; there was a “high BG” baggie with supplies ready to go! But the combination of the 25+ hours of rain, the extra hard rain and cold temps from the last several hours, my feet starting to be bothered from the wet soaking, and then on top of it all the chemical feeling of not having insulin going in my body: it was a lot. I really focused on the physical state I was in, evaluating what I wanted to do. I knew that I could fix the cold state (switch to dry clothes; use hot packs) and my blood sugars (new replacement pump, take some inhalable insulin for a faster fix while the new pump insulin would be kicking in within an hour and fixed from there). But my feet were starting to bother me in a way that I wasn’t sure could be fixed with a 20 minute sock change.

Scott biked up to me right as I passed my favorite trail bathroom, the stalwart of my ultra, and had me turn around and head in there to be out of the rain. It was clean, big, had toilet paper, and was well lit and had the door open (wasn’t locked) all night long. I stepped inside the bathroom while Scott parked his bike by the building and whipped out the baggie with the replacement pump. I checked that no one else was in the women’s bathroom and he stepped inside, and impressively (to me) pulled out the baggie that held a garbage bag. I had packed it so I could more easily change clothes in public bathrooms by standing on it and placing my clothes on it so they wouldn’t be on the ground. He instead laid the garbage bag on top of the garbage can lid and set out my dry clothes, helped me out of my wet soaked rain jacket, hat, and shirts, and handed me my dry shirts followed by some hot packs. He gave me a giant one and told me to stuff it down my shirt, which I did. I took some inhalable insulin (which hits in about 15 minutes), then held the smaller hot packs in my hands while he was pulling out the bag with my replacement pump. I rewound and primed the pump with my existing reservoir and tubing, then reconnected it to my pump site and primed it. That problem (lack of insulin) was now solved, and I knew that my blood glucose would come back down to target over the next hour.

Next up, I could walk/run (or walk) the remaining 1.5 miles back to my normal turn around point, which was a table under a park awning that was relatively dry. I knew that I needed to be warmer and stay dry, and although I had dry clothes on now, I wasn’t sure that sitting outside even with hot packs while I tried to address my feet would warm me up. I told Scott that I wanted to go back to the house (thinking I’d walk the ~1.5 miles to the house). Then I could dry out my feet, get warm, and go back out if I wanted to continue. But I had a hunch I didn’t want to continue. My feet were feeling like they were getting to be in a not-good state from the level of water they had retained after 25 hours, despite all the excellent foot care.

I thought about it and realized that I was satisfied with running 82 miles. I was in otherwise decent physical shape and energy, I had been nailing my electrolytes and fueling and blood sugars the entire run. I had successfully run overnight; more than 24 hours; and by far (2.6x) the longest distance I had ever run. I could keep running to 100 miles (about 18 more miles), but no one cared if I did. I didn’t have to prove anything to anyone, including myself. I had planned, strategized, and executed above and beyond what I had thought was possible, both in terms of physical and mental performance. I had no major injuries, and I wanted to keep it that way. I knew I had the willpower and persistence to keep going; I was stubborn enough to do it; but as the last bit of icing on top of my ultramarathon cake, I wanted to have the mental strength to decide to stop where I was so I wouldn’t create a long-lasting injury in the last 18 miles from sheer stubbornness.

So I stopped. I told Scott I would decide for sure after I got home and dried off and warmed up, but that I was pretty sure this would be a stop and not just a pause. Rather than let me walk home in the rain, he insisted I stay in the warm dry bathroom while he biked home and got the car and brought it to the nearest trail entrance, which was about a quarter of a mile away (more good planning on my part!). Once he had gotten in the car and called me, I slowly walked out to meet him at the parking lot, reaching it right as he pulled in. The walk on my feet confirmed to me that they were done. They weren’t exceptionally blistered or injured, but I knew the cumulative water effect and soggy skin would likely lead to some damage if I continued on them. We headed home. I sat down and took off my socks and shoes and sure enough, my feet were wet, white, and very wrinkly and starting to crease. I took a hot shower then dried off, put hand sanitizer on my feet to help dry them out, and laid down with them sticking out of the covers to help them air out. Within a few hours, they had dried out, and showed me some blisters on the bottom of my right foot that were not really bad, but if I had kept going on them, the wet wrinkly tissue would’ve been very prone to more extreme damage. I reflected on the choice to stop and was still happy with my decision.

The 24 hours after I ran 82 miles

After my shower and laying down, I realized that I was (still) in great physical shape. Some parts of me were starting to stiffen up now that I had stopped, but they hadn’t bothered me at all during running. That was my hips that now hurt if I tried to lay on my side but not on my front or my back; and my thighs felt sore when I straightened and bent my legs. I had never even been tempted during my run to take pain meds because I was never overly sore and didn’t have any injuries.

(Note: you shouldn’t take NSAIDs during extreme events due to the risks of overworked kidneys having problems. I had packed Tylenol, which is acetaminophen, in case I needed it for pain management, but specifically did not pack any oral NSAIDs and warned Scott about offering me any. I did pack topical NSAID *gel* which is an extremely low quantity of NSAID compared to even one oral NSAID pill, and I used that once on my shoulder blades during the run. After my run, I waited several hours and made sure my kidneys were fine via hydration before I took any NSAID.)

It is very surprising to me that despite my longest training runs being almost a third of the distance I did, that I ended up in better physical shape at the end than I did during some training runs! This is probably in part due to going even slower (as planned) during my ultra, but I was really pleased. It might have also been due to the fact that I mentally trained for it to hurt really bad and to continue anyway. Again, lots of mental training and prep.

I ended up napping 2 hours after I got home and showered, and then was awake a few more hours and took another one hour nap. I ate several small meals throughout the day and stayed in bed to rest and not stress my feet further, then went to sleep at a normal bedtime and managed to sleep 9.5 hours through the night. Woohoo! I really wasn’t expecting that. I did wake up many times and find myself bending and flexing my knees or my ankles to help me roll over and could feel them being sore, but it wasn’t painful enough to fully wake me up or keep me from falling back to asleep within seconds, so it felt like a fully rested un-broken night of sleep.

The bottoms of my feet felt weird as they dried out, but progressively felt better and felt close to normal (normal meaning as normal as you are with a routine blister on the bottom of your forefoot) by the time I woke up the next morning (24 hours after ending my run). Everything that stiffened up in the first few hours after I stop has been gradually loosening up, so other than my forefeet still being sensitive with blisters, I’m walking around normally again.

The good, the bad, the ugly, and what I wish I had done differently

I had prepared for so much to go wrong, both those things in my control and things out of my control. And I think that’s why it actually didn’t hurt as much or go as wrong as it could have, despite all the variables in play. I nailed my pacing plan, energy levels, hydration levels, fueling intake, electrolyte intake, and enzyme intake.

I had estimated that I would need to take up to ~160 enzymes to cover my fueling. Remember that I stopped at ~25 hours (82 miles) instead of ~32 hours (100 miles) so I took less than that, but still a lot.

I consumed 50 (fifty!!!) snacks, one every 30 minutes, and swallowed multiple enzyme pills each time. I consumed at least 98 enzyme pills (!!!) in this 25 hour time period. I was concerned that my body wouldn’t be able to digest the pills or have some other issue with them, because I have never taken anywhere near this number of pills in a single day. But, it worked, and flawlessly: I had ZERO EPI-related issues and ZERO other gastrointestinal (GI) symptoms. GI symptoms are super common in ultras, even for people without things like EPI, so I’m incredibly thrilled with how well my planning and practicing paid off so I could execute my fueling plan and not have any issues.

My goal had been to take in ~250 calories per hour and ~500 mg of sodium per hour (from both the snacks every 30 min and electrolyte pills every 45 min). I use calories as my rolling metric because while most ultrarunners prioritize carbs, I’m running slower and likely more fat adapted than most people, and also need digestive enzymes no matter what I’m eating so taking small amounts of fat and protein are fine for me. Plus it makes for more interesting running snacks. So using calories as the global running metric of consumption rather than just carbs or fat etc. works for me. I nailed it, and across all 25 hours of my run I averaged 671 mg of sodium per hour and 279 calories per hour. I did have one hour where I somehow dropped low on sodium and felt it, and took an extra electrolyte pill to help catch up. It fixed the “low on sodium” feeling and I didn’t have any issues again. I had slightly more variability toward the end of the run, but that’s just due to the timing of when I logged it into my spreadsheet (due to the wet-phone issues I described earlier) and the auto-calculation on which hour it falls into; overall I still was maintaining the goal levels every hour.

A graph of calorie consumption, sodium consumption, and carb consumption per hour for all 25 hours of the 82 mile run.

(The purple dotted line is carbs, because I was curious about how that level fluctuated given that I didn’t prioritize my run snacks based on carbs at all. I generally seek <20 grams of carbs per snack but have a few that are closer to 30 grams; otherwise <10 or so grams of fat and however many grams of protein I don’t care).

How do I have all this data? I used my macronutrient spreadsheet as I went, selecting the snack I was going to eat from the drop-down list that then pre-populated the rest of the data in the sheet and updated a pivot table that summarized my rolling totals per hour. It was getting increasingly hard to use my phone in the mega downpour rain in the last few hours, which is why the timing of logging them was a little variable and the numbers look a little more bouncy each hour toward the end, but my consumption was still on time thanks to my every 30 minute phone alarms and so the logging was the only thing that varied and I was still above-goal overall although trending downward slightly.

This spreadsheet means I can also summarize my total consumption across 25 hours: I consumed an eye-popping 817 grams of carbs; 365 grams of fat; 136 grams of protein; 16,775 mg of sodium; and 6,979 total calories. That matched the 98+ enzyme pills (and 33 electrolyte pills, which are 210 mg of sodium each and reflected in the overall sodium counts), so I also swallowed >131 pills in the 25 hour time period running. Wow.

It’s common to end up in a calorie deficit due to the hours and miles that an ultra demand of your body, but my watch estimates I burned around 8,000+ calories (maybe an undercount since it stopped itself a few times), so I didn’t have as big of a deficit as I had originally predicted.

There were so many (50!) opportunities to mess up my digestion, and I didn’t mess up once. I’m really proud of that! I also had such a variety of snack types and textures that even though I was never really hungry, I ate my snacks like clock work and didn’t get major palate fatigue or get to the point that I wanted to stop chewing and needed to switch to my backup list of liquid fuel. The only time I slightly felt off was when I did a Snickers for one snack at the end of my lap and then my next snack was hot mashed potatoes – combined, that was 390 calories (one of my top two hours of calorie consumption) and felt like a little too much food, either because of the calories or the volume of mashed potatoes. It was only a minor annoyance, though, and the feeling passed within another 15 minutes and I didn’t have issues with any other combination of snacks. I did get tired of peanut butter pretzel nuggets, because they’re drier than many of my other snacks and took a lot of water to swallow. So I stopped choosing those in lieu of my other snacks and left those as emergency backups.

Looking back, I wish I could have done something differently about my feet, but I don’t think there’s anything else I could have done. I changed socks and into dry shoes at every single lap. I dried them and tried to draw out water with hand sanitizer and Desitin. I lubricated with Squirrel Nut Butter and Desitin, and overall came out with very few blisters compared to my typical shorter long runs (e.g. 25-30 miles). But we did get 0.72 inches of rain in that 24 hour period, and a lot of it was dumped onto my feet in the 4-7am time period. If I’d had a way of knowing 24 hours in advance exactly when the rain was going to let up with enough confidence to delay the run for a day, it turns out it would’ve been drier, but the forecast before I started running was for similar chances of rain all weekend. The laws of feet physics and the timing was just not good, and that was out of my control. I’ll keep researching other strategies for wet feet management, but I think I had done everything I could, did it well, and it just was what it was.

Overall, I can’t think of anything else I would have changed (other than my training, it would have been swell not to have broken my toe and been not weight bearing for 6 weeks!). Fueling, electrolytes, enzymes, blood sugars, pacing, mental game: flawless. I was even picking up the pace and still running and walking 30:90 second intervals, and I think I would have continued to pick up the pace and pushed it to the finish, estimating that I would have come in under 32 hours overall for 100 miles (around a 19 min/mi average pace overall, or a bit under that).

But I chose to stop at 82 miles, and being willing to do that was a huge mental PR, too.

So I’m pleased, proud, and thrilled to have run an 82 mile ultramarathon, and physically and mentally feel better than I would have predicted would be possible after 24 hours.

What it feels like to run (almost) a 100 mile ultramarathon, by Dana M. Lewis on DIYPS.org