safety

A Crouton In Your Salad (Or COVID In The Air)

by Dana Lewis

Look, I get it: you don’t care about a crouton in your salad.

If you don’t like croutons, you simply pick them out of your salad and nudge them to the side of your plate. No harm done.

But for me, a crouton in my salad IS harm done. Even if I were (or the restaurant were) to pick off the croutons, the harm is done. There are specks and crumbs of gluten remaining in my food, and since I have celiac disease, my body is going to overreact to microscopic flecks of gluten and cause damage to my intestines and actively block absorbing the nutrients in the other food that I’m eating.

You might scoff at this concept, but one of the reasons celiac is so risky is because there are both the short term effects (days of abdominal pain, for example) and the long-term risk of causing holes in my intestine and drastically increasing the risk of stomach cancer, if I were to continue consuming gluten.

Some people with celiac aren’t symptomatic, meaning, they could eat the specks (or heck, chunks) of gluten and not feel what I feel.

When I eat specks of gluten? Bad news bears. Literally. It feels like bears clawing at my insides for hours, then days of abdominal soreness, headaches, and feeling unwell. That’s from a SPECK of gluten. I have a strong symptomatic response, so that makes it easier – perhaps – for me than for those with celiac without symptomatic response to choose to be very, very careful and avoiding cross-contamination in my food, and lower my long-term risk of things like stomach cancer that is linked to celiac long-term.

But knowing what I know about how my brain works and the rest of what I’m dealing with, I can imagine the alternative that if I was asymptomatic but lucky enough to discover that I did have celiac disease (through routine screening), I would probably still go to 99% of the same lengths that I do now to avoid gluten and cross-contamination of gluten, because of the long-term risks being so high.

I also don’t have celiac in a silo. I also have type 1 diabetes, which raises my risk of other things…and now I also have exocrine pancreatic insufficiency (EPI) which means every meal I am fighting to supply the right amount of enzymes to successfully digest my food, too. Oh, and now I also have Graves’ disease, so while my thyroid levels are nicely in range and always have been, I’m fighting battles with invisible ghosts in my body (thyroid-related antibodies) that are causing intermittent swelling of my eyelids and messing with my heart rate to tell me that there’s something going on in my body that I have no direct control over.

My plate is already full. (Or my dance card is already full, if you prefer that analogy). I don’t want, and can’t mentally envision right now, handling another thing. I work really hard every day to keep myself in good health. That involves managing my glucose levels and insulin delivery (for Type 1 diabetes), taking my thyroid-related medication that might be helping bring my antibody levels down and monitoring for symptoms to better provided feedback to the 6-week loop of data I get from blood testing to decide how we should be treating my Graves’, to thinking about EVERY SINGLE THING I put in my mouth so that I can take the right amount of enzymes for it, to making sure EVERY SINGLE THING I put in my mouth is gluten-free and is safe from cross-contamination.

Every meal. Every snack. Every drink. Every day.

Probably for the rest of my life: I can’t stop thinking about or doing those things.

Perhaps, then, if you could imagine being in this situation (and I’m so glad most of you are not!), you can imagine that I work really hard to make things easier and better for myself. Both with the plate that I’ve been given, but also in doing my best to lower the risk of more things being added to my already over-loaded plate.

(Preface for this next section: this is about ME not about YOU.)

COVID is one such example. I have worked very hard to avoid COVID, and I am still working very hard to avoid COVID. Like celiac and EPI, if I were to get COVID or other viral illnesses (like the flu), there is the risk of feeling very bad for a short period of time (e.g. 5-7 days). (I’m vaccinated, so the risk of short-term illness being severe (e.g. hospitalization, death) is lowered, and is probably at the same risk as being hospitalized for flu. Even when vaccinated for flu, I’ve been sick enough to almost be hospitalized, which is also why I don’t discount this risk, albeit recognizing it is lower with vaccination).

But like celiac and EPI, if I were to get COVID etc, that increases health risks for the long-term. This is true of most viral illnesses. And when you have an autoimmune condition which indicates your body is a super-star at overreacting to things (which causes other autoimmune conditions), you can imagine that poking the bear is going to make the bear (over)react, whether it is in the short-term or long-term.

It’s not so much if, but when, I would get handed my FIFTH chronic condition if I do get COVID. I went from two (type 1 diabetes and celiac) to four (adding EPI and Graves’) within the course of the same year. This is without having COVID. Given the data showing the increased risk in the long-term of developing many other conditions following COVID, even in people who don’t have superstar overreactive immune systems, it is easy to draw a dotted line to predict the future post-COVID infection to imagine it is not if, but when, my fifth thing would develop and get added to my plate.

So this is why I choose to do things differently than perhaps you do. I mask in indoor spaces. I am currently still choosing to avoid indoor dining. I don’t mind if you choose to do differently; I similarly don’t begrudge you eating croutons. But just like I wouldn’t expect you to pelt me with croutons and yell at me for not eating croutons when you can, I also prefer people not to propel possibly-infectious air at me at short-range when I am unmasked, which is why I prefer to be masked in indoor public spaces. The air is lava (or crouton dust) to me in terms of COVID.

Again, the point here is not to convince you to act any differently than you are acting. You do you! Eat your croutons, do what you like in regard to breathing the air however you like.

But like most folks are 100% fantastic about respecting that I’m not going to eat flecks of croutons, I wish folks would be more understanding of all the background situations behind my (and others’) choices regarding masking or avoiding indoor dining. What I do is not hurting someone else, whether it is not eating croutons or choosing to be masked in an indoor space.

Why would someone want to force me to eat a crouton, knowing it would cause immense harm in the short-term and contribute to long-term damage to my body and increase the risk of life-ending harm?

This is the direction in which I wish we could shift thinking about individual behaviors. Me wearing a mask is like me not eating croutons. Also, I don’t usually ask people to not eat croutons, but many of my friends and family will be happy to agree to eat at a 100% gluten free place if that’s the best option, because it doesn’t harm them not to eat gluten on occasion. Sometimes we do eat at a place that serves gluten, and they eat their croutons without thinking about it. I’m fine with that, too, as long as I am not asked or put at risk of having my mouth be stuffed with crouton dust. That’s how, maybe, I wish people would think about masking. Even if you don’t typically wear masks because you don’t feel you need to, you might choose to occasionally mask indoors when you’re around others who are masking to protect themselves. Like eating at a gluten free restaurant with your friends on occasion, it probably won’t be a big deal for you. You get plenty of gluten at other times. Then you can go back to eating your usual dietary choices (croutons all day, not masking).

COVID is interesting because it is something that potentially impacts all of us, which is why I think maybe the dynamics are changed. Someone might say “oh sure, I wouldn’t throw croutons at you or yell at you for choosing not to eat gluten”. But some people might also think they have the right to judge me regarding my choices around showing up somewhere masked, because they are ‘in the same situation’ and are choosing differently than I.

But my point is: this is not the same situation, the risks to me are not the same, which is why I may choose differently.

TLDR – I guess the point is, what looks like the ‘same’ situation on the outside is not the same for everyone; these differences influence our individual choices and needs; and I wish this is the way more people saw things.

A Crouton In Your Salad (or COVID in the air) by Dana M. Lewis on DIYPS.org

CGM for primary care doctors: a new article in the BMJ

by Dana Lewis

I was honored last year to be asked to write an article about the basics of continuous glucose monitoring (CGM) for primary care providers by the BMJ, which was released today online.

This, like most of my academic literature article writing, was an unpaid gig. So why did I do it?

Well, most people with diabetes are treated primarily by primary care providers (“GPs” or “PCPs” or “family doctors”, etc). It’s somewhat rare for most people with diabetes to see an endocrinologist! It also varies regionally, even within the same country. And, primary care providers obviously treat a lot of widely varying conditions, from acute to chronic, so they may not have time or energy to stay up to date on all treatment options for all conditions.

This therefore felt like a great opportunity to contribute some information about CGM, an incredibly useful piece of technology for anyone with diabetes who wants it, specifically written and targeted for primary care providers who may not have the exposure to CGM technology that endocrinology providers have had over the years. And, like most things, the technology (thankfully) has changed quite a bit. Accuracy, ease of use, cost, and many other factors have changed dramatically in the last almost two decades since CGMs were introduced on the market!

I sought out two fellow experts in CGM and diabetes technology to co-author the article with me. I asked Ben Wheeler, an excellent pediatric endocrinologist who has done quite a bit of research on “intermittently scanned” CGMs (isCGM); and Tamara Oser, who is the director of the Primary Care Diabetes Lab (and a parent and a spouse of people living with diabetes) and worked to facilitate uptake of CGM in primary care settings.

I’m also appreciative that a parent and teen with newly diagnosed diabetes and new experiences with CGM both reviewed this article when it was drafted and shared their perspective to it; as well as appreciative of valuable input from a friend with many years of experience with diabetes who has used 8 (!) different CGM systems.

We are starting to see a shift in adoption and coverage of CGM, thankfully. Historically, people with diabetes haven’t always had insurance cover CGM. Even if insurance does cover CGM, sometimes we have to fight an uphill battle every year to re-prove that we (still) have diabetes and that we still need CGM. Sometimes good outcomes from using CGM disqualifies us from the next year’s coverage of CGM (in which case we have to appeal our cases for coverage). It’s frustrating! That’s why it’s so nice to see increasing guidelines, recommendations, and even country-specific guidelines encouraging funding and coverage of CGM for people with all types of diabetes. The biggest latest news – as of yesterday (March 2, 2023) – was that in the U.S., Medicare will now be covering CGM for people with type 2 diabetes on insulin. This is a huge group of people who previously didn’t have CGM coverage before!

So here it is, just out today online (March 3, 2023), and projected to be in the March 25, 2023 print edition of the BMJ: an article on continuous glucose monitoring (CGM) for primary providers. I’m hoping it helps pave the way for more providers to feel comfortable prescribing CGM for more people with diabetes; increased their knowledge in working with people with diabetes who have CGM prescribed from other providers; and also reduce unconscious and conscious bias against people with diabetes being offered this important, life-changing and life-saving technology.

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P.S. – if you can’t access the article from the link above, as a reminder I always store an accessible author copy of my research articles at DIYPS.org/research!

Ultramarathon Races Are Exclusionary

by Dana Lewis

Recently, I’ve been thinking about the feeling I have that ultrarunning races (ultramarathons) are exclusionary.

Running is theoretically very accessible: you go out and do it. No special equipment or clothes needed. Same for ultrarunning: go run a distance longer than a marathon (26.2 miles or ~42 kilometers). You don’t even have to do it in an organized “race”, as many of us run DIY or solo ultramarathons for training or in lieu of races (like I did for my 82 miler). Run 26.3 miles? Technically you’re an ultrarunner (although it’s more common for a 50k/31 mile race to be the first distance most people consider ‘ultra’).

For many people, though, an organized ‘race’ or event is important for a number of reasons. It provides a commitment device and a firm and hard deadline for which to train. It might be the only safe way to achieve a distance, with aid stations and volunteers to support achieving the endeavor, if they don’t have family or friends able to crew runs otherwise or lack safe places to run these distances. It also provides motivation and camaraderie of setting out to achieve the same goal as a group of other people at the same time. And of course, it provides competition – not only with one’s self to achieve their best that day, but also against other people.

Most of us, though, statistically aren’t racing in an ultramarathon for a podium place or top-whatever finish.

So why do the rules work to exclude so many people from participating in ultramarathons?

I’m talking about rules like those often found listed in the 200 mile ultramarathon race descriptions and rule handbooks that say that aid cannot be administered outside of the aid station. Crew may not hand anything to racers outside of the aid station:

  • Cowboy 200, runner manual last updated 8/16/22: “Crew is only allowed to assist runners at FULL/MANNED aid stations. No exceptions. Crew cannot give anything to or take anything from runners anywhere except at manned aid stations.”
  • Bigfoot 200, 2022 runner manual: “Pacers are not allowed to mule (carry items) for their runner. Pacers may not give their runner any aid, food or water unless it is an emergency situation, in which case the runner may be disqualified. Pacers are for safety, not for giving aid or gaining an advantage over fellow participants.” and “Crew may not meet their runner between aid”
  • Tahoe 200, 2022 runner manual: A full disqualification may be given if “Contacts crew anywhere between aid stations; Has crew leave items left for the runner anywhere along the course; Takes outside aid between aid stations”
  • Moab 240, 2022 runner manual – same as above Tahoe 2022
  • Cocodona 250, accessed January 2023: “Crew may not meet their runner at any point on the course other than designated crew access aid stations. Runners will be automatically disqualified for receiving aid from crew outside of crew access aid stations.”

It’s a thing in 100 miles races, too.

  • Western States 100, 2023 participant guide: “Runners may not accept aid or assistance from their crew or other spectators in between crew-accessible aid stations.” and “Pacers may not carry water, food, flashlights, shoes, clothing, or other supplies for their runner or provide any other type of mechanical or physical assistance to their runner on the course.”
  • Hardrock 100, 2022 guide: “No stashing of supplies along the course and no accepting aid except within 400 yards of a designated aid station.” and “Pacers may not carry water, food, flashlights, shoes, clothing, or other supplies for their runner or provide any other type of mechanical or physical assistance to their runner on the course.”

Why is this a problem?

Well, say that an ultrarunner has type 1 diabetes and uses an insulin pump and the insulin pump breaks. (Battery dies; the pump itself smashes against a rock and breaks the screen; or like in my 82 miler last year, the water busts the button panel and it is no longer operable.) If you have a backup pump and a crew member, in a non-race setting they’d simply bike or run or drive out to you (whatever was feasible and safe for them) and hand you the pump. You’d replace it, and continue on your way.

But according to the ‘rules’ of these ultramarathon ‘races’, you’d be immediately disqualified and stopped from continuing the ultramarathon. In order to not be disqualified, you’d have to wait until you got to the aid station to swap to a backup insulin pump. Sure, you’d likely have a back up insulin delivery method (syringe or insulin pen), but those are stop gaps and not a strategy to get you to the end of the race, most likely. Knowing those rules, it incentivizes non-optimal decision making of participants to choose to continue for miles (in some cases, could be hours to the next crew-accessible aid station), all the while racking up high blood sugar and low insulin levels that can be really, really, physically unpleasant and further put ultrarunners at risk of physical injury due to the altered state of unnaturally high blood sugar levels.

My guess is these rules are there to limit cheating and a non-fair playing field for those competing for podium. (In some cases, it might be to limit traffic on narrow parts of trail, etc. so for safety reasons, but for the most part the reasons cited seem to be about ‘a fair playing field’.)

But you know what? It’s already an unfair playing field between them and people with diabetes: because those runners without diabetes have a fully functioning insulin production system inbuilt to their body! People with diabetes are already at a disadvantage. Allowing someone to switch to their backup insulin pump outside of an aid station isn’t an unfair advantage or “cheating”, nor does it even “level the playing field” with the other runners.

Instead, the ability to get medical supplies for a chronic disease outside of an aid station reduces medical and physical injury risk to the participant.

Maybe you think I’m being dramatic about the rules of these races and feeling excluded from participating. Because in fact, I do feel excluded. I know things can happen and there’s no point in paying hundreds or thousands of dollars to participate in an event where if I need to switch medical equipment mid-race and outside of an aid station, that I’ll be disqualified and receive an automatic DNF (did not finish) on my race record.

Further, there are other races with even more stringent rules that point blank exclude people with diabetes from participating at all in their races.

Yes, really.

In 2021, UTMB (one of the world’s top ultrarunning race series) announced a new medical policy (based on the Quartz Program) that forbids use of any substance on the WADA (World Anti-Doping Agency) Prohibited List that would require a TUE (therapeutic use exemption) within 7 days prior to competition or during competition.

Guess what’s on the WADA Prohibited List? Insulin.

So if you use insulin and are an athlete in another sport, you get a TUE approved and you’re allowed to participate in your sport despite using insulin for insulin-requiring diabetes.

But as a person with diabetes, you’re banned from participating in UTMB’s races! People with insulin-requiring diabetes can’t go 7 days prior to an event without insulin, nor can we go the entire race (hello, 105 miles takes a long time) without insulin. So this means we cannot participate.

This is dumb and outright exclusionary. There’s other people with healthcare conditions who are now outright banned from participating in UTMB races, too. The same exclusionary ‘health’ “program” has also been used by the Golden Trail Running Series.

This makes ultrarunning exclusionary for people with most chronic illnesses.

Think I’m being dramatic again? Check out this quote from an interview with the organizer of the health ‘program’ that UTMB used to generate this list of requirements:

“Whether the athlete is under the influence of drugs or sick, our role consists of protecting them and therefore stop them from starting the race.”

They outright say they’re trying to stop athletes from starting the race, under the guise of policing what is healthy and safe for trail and ultrarunning. It doesn’t allow for individual evaluation.

Point blank: I’m excluded, and so are many other people with chronic illnesses, despite the fact that we are likely in better health than many other prospective participants of the race, regardless of chronic illness.

Personally, I think having a chronic illness, as hard as it makes ultrarunning, makes me better prepared and a better ultrarunner: I am very experienced with listening to my body and adjusting to challenging situations and dealing with physical and medical adversity. I do ultramarathons in part because they are hard and challenging. They’re hard and challenging for everyone! That’s why so few (relatively speaking) people run ultramarathons. If it was easy, everyone would have done it.

But no one should be prevented from entering a race because of living with a chronic illness.

If you’re willing to put in the training and cover the miles and plan what you need to do in order to achieve this with your medical devices and life-critical medications? You should do so. You should not be discouraged from taking the best possible care of your body before, during, and after an ultramarathon. That is what these policies do at best: at worst they exclude you outright from entering the race.

Race directors and race organizers, your ultramarathon policies are exclusionary. You should fix them.

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Fellow ultrarunners, I encourage you to ask race directors to update their policies, too.

How?

Take a leaf out of Tunnel Hill 100’s book. They say (bold emphasis mine):

“USATF SPECIAL NOTICE: No American, or World Record, including age group records, will be recognized for any athlete who:

1) receives aid outside of a designated Aid Station area, OR

2) uses a pacer who is not entered in the race. These rules fall under the “unfair advantage” rules.

NOTE: Don’t worry about these rules if you aren’t going to set any records other than your own personal records.“

This is how it should be done: make it clear what rules apply to elite/pro runners (aka podium/top 10/whatever places get rank or $$$) and which ones do NOT apply to the rest of us.

Don’t make people with chronic diseases pay yet another time tax to have to contact the race director and (in the US) ask for an accommodation under the Americans with Disabilities Act. Or point out, if declined, that it’s illegal to exclude people with disabilities (which includes people with most chronic diseases). We do enough work and already pay a lot of “time tax” for acquiring health supplies and managing our chronic diseases; don’t put MORE hoops in front of us to be able to participate and run.

That’s not equitable, nor fun, and it’s yet another barrier to keep more people out of running these races and events.

Functional Self-Tracking is The Only Self-Tracking I Do

by Dana Lewis

“I could never do that,” you say.

And I’ve heard it before.

Eating gluten free for the rest of your life, because you were diagnosed with celiac disease? Heard that response (I could never do that) for going on 14 years.

Inject yourself with insulin or fingerstick test your blood glucose 14 times a day? Wear an insulin pump on your body 24/7/365? Wear a CGM on your body 24/7/365?

Yeah, I’ve heard you can’t do that, either. (For 20 years and counting.) Which means I and the other people living with the situations that necessitate these behaviors are…doing this for fun?

We’re not.

More recently, I’ve heard this type of comment come up about tracking what I’m eating, and in particular, tracking what I’m eating when I’m running. I definitely don’t do that for fun.

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I have a 20+ year strong history of hating tracking things, actually. When I was diagnosed with type 1 diabetes, I was given a physical log book and asked to write down my blood glucose numbers.

“Why?” I asked. They’re stored in the meter.

The answer was because supposedly the medical team was going to review them.

And they did.

And it was useless.

“Why were you high on February 22, 2003?”

Whether we were asking this question in March of 2003 or January of 2023 (almost 20 years later), the answer would be the same: I have no idea.

BG data, by itself, is like a single data point for a pilot. It’s useless without the contextual stream of data as well as other metrics (in the diabetes case, things like what was eaten, what activity happened, what my schedule was before this point, and all insulin dosed potentially in the last 12-24h).

So you wouldn’t be surprised to find out that I stopped tracking. I didn’t stop testing my blood glucose levels – in fact, I tested upwards of 14 times a day when I was in high school, because the real-time information was helpful. Retrospectively? Nope.

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I didn’t start “tracking” things again (for diabetes) until late 2013, when we realized that I could get my CGM data off the device and into the laptop beside my bed, dragging the CGM data into a CSV file in Dropbox and sending it to the cloud so an app called “Pushover” would make a louder and different alarm on my phone to wake me up to overnight hypoglycemia. The only reason I added any manual “tracking” to this system was because we realized we could create an algorithm to USE the information I gave it (about what I was eating and the insulin I was taking) combined with the real-time CGM data to usefully predict glucose levels in the future. Predictions meant we could make *predictive* alarms, instead of solely having *reactive* alarms, which is what the status quo in diabetes has been for decades.

So sure, I started tracking what I was eating and dosing, but not really. I was hitting buttons to enter this information into the system because it was useful, again, in real time. I didn’t bother doing much with the data retrospectively. I did occasional do things like reflect on my changes in sensitivity after I got the norovirus, for example, but again this was mostly looking in awe at how the real-time functionality of autosensitivity, an algorithm feature we designed to adjust to real-time changes in sensitivity to insulin, dealt throughout the course of being sick.

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At the beginning of 2020, my life changed. Not because of the pandemic (although also because of that), but because I began to have serious, very bothersome GI symptoms that dragged on throughout 2020 and 2021. I’ve written here about my experiences in eventually self-diagnosing (and confirming) that I have exocrine pancreatic insufficiency, and began taking pancreatic enzyme replacement therapy in January 2022.

What I haven’t yet done, though, is explain all my failed attempts at tracking things in 2020 and 2021. Or, not failed attempts, but where I started and stopped and why those tracking attempts weren’t useful.

Once I realized I had GI symptoms that weren’t going away, I tried writing down everything I ate. I tried writing in a list on my phone in spring of 2020. I couldn’t see any patterns. So I stopped.

A few months later, in summer of 2020, I tried again, this time using a digital spreadsheet so I could enter data from my phone or my computer. Again, after a few days, I still couldn’t see any patterns. So I stopped.

I made a third attempt to try to look at ingredients, rather than categories of food or individual food items. I came up with a short list of potential contenders, but repeated testing of consuming those ingredients didn’t do me any good. I stopped, again.

When I first went to the GI doctor in fall of 2020, one of the questions he asked was whether there was any pattern between my symptoms and what I was eating. “No,” I breathed out in a frustrated sigh. “I can’t find any patterns in what I’m eating and the symptoms.”

So we didn’t go down that rabbit hole.

At the start of 2021, though, I was sick and tired (of being sick and tired with GI symptoms for going on a year) and tried again. I decided that some of my “worst” symptoms happened after I consumed onions, so I tried removing obvious sources of onion from my diet. That evolved to onion and garlic, but I realized almost everything I ate also had onion powder or garlic powder, so I tried avoiding those. It helped, some. That then led me to research more, learn about the categorization of FODMAPs, and try a low-FODMAP diet in mid/fall 2021. That helped some.

Then I found out I actually had exocrine pancreatic insufficiency and it all made sense: what my symptoms were, why they were happening, and why the numerous previous tracking attempts were not successful.

You wouldn’t think I’d start tracking again, but I did. Although this time, finally, was different.

When I realized I had EPI, I learned that my body was no longer producing enough digestive enzymes to help my body digest fat, protein, and carbs. Because I’m a person with type 1 diabetes and have been correlating my insulin doses to my carbohydrate consumption for 20+ years, it seemed logical to me to track the amount of fat and protein in what I was eating, track my enzyme (PERT) dosing, and see if there were any correlations that indicated my doses needed to be more or less.

My spreadsheet involved recording the outcome of the previous day’s symptoms, and I had a section for entering multiple things that I ate throughout the day and the number of enzymes. I wrote a short description of my meal (“butter chicken” or “frozen pizza” or “chicken nuggets and veggies”), the estimate of fat and protein counts for the meal, and the number of enzymes I took for that meal. I had columns on the left that added up the total amount of fat and protein for the day, and the total number of enzymes.

It became very apparent to me – within two days – that the dose of the enzymes relative to the quantity of fat and protein I was eating mattered. I used this information to titrate (adjust) my enzyme dose and better match the enzymes to the amount of fat or protein I was eating. It was successful.

I kept writing down what I was eating, though.

In part, because it became a quick reference library to find the “counts” of a previous meal that I was duplicating, without having to re-do the burdensome math of adding up all the ingredients and counting them out for a typical portion size.

It also helped me see that within the first month, I was definitely improving, but not all the way – in terms of fully reducing and eliminating all of my symptoms. So I continued to use it to titrate my enzyme doses.

Then it helped me carefully work my way through re-adding food items and ingredients that I had been avoiding (like onions, apples, and pears) and proving to my brain that those were the result of enzyme insufficiency, not food intolerances. Once I had a working system for determining how to dose enzymes, it became a lot easier to see when I had slight symptoms from slightly getting my dosing wrong or majorly mis-estimating the fat and protein in what I was eating.

It provided me with a feedback loop that doesn’t really exist in EPI and GI conditions, and it was a daily, informative, real-time feedback loop.

As I reached the end of my first year of dosing with PERT, though, I was still using my spreadsheet. It surprised me, actually. Did I need to be using it? Not all the time. But the biggest reason I kept using it relates to how I often eat. I often look at an ‘entree’ for protein and then ‘build’ the rest of my meal around that, to help make sure I’m getting enough protein to fuel my ultrarunning endeavors. So I pick my entree/main thing I’m eating and put it in my spreadsheet under the fat and protein columns (=17 g of fat, =20 g of protein), for example, then decide what I’m going to eat to go with it. Say I add a bag of cheddar popcorn, so that becomes (=17+9 g of fat) and (=20+2 g of protein), and when I hit enter, those cells now tell me it’s 26 g of fat and 22 g of protein for the meal, which tells my brain (and I also tell the spreadsheet) that I’ll take 1 PERT pill for that. So I use the spreadsheet functionally to “build” what I’m eating and calculate the total grams of protein and fat; which helps me ‘calculate’ how much PERT to take (based on my previous titration efforts I know I can do up to 30g of fat and protein each in one PERT pill of the size of my prescription)

Example in my spreadsheet showing a meal and the in-progress data entry of entering the formula to add up two meal items' worth of fat and protein

Essentially, this has become a real-time calculator to add up the numbers every time I eat. Sure, I could do this in my head, but I’m usually multitasking and deciding what I want to eat and writing it down, doing something else, doing yet something else, then going to make my food and eat it. This helps me remember, between the time I decided – sometimes minutes, sometimes hours in advance of when I start eating and need to actually take the enzymes – what the counts are and what the PERT dosing needs to be.

I have done some neat retrospective analysis, of course – last year I had estimated that I took thousands of PERT pills (more on that here). I was able to do that not because it’s “fun” to track every pill that I swallow, but because I had, as a result of functional self-tracking of what I was eating to determine my PERT dosing for everything I ate, had a record of 99% of the enzyme pills that I took last year.

I do have some things that I’m no longer entering in my spreadsheet, which is why it’s only 99% of what I eat. There are some things like a quick snack where I grab it and the OTC enzymes to match without thought, and swallow the pills and eat the snack and don’t write it down. That maybe happens once a week. Generally, though, if I’m eating multiple things (like for a meal), then it’s incredibly useful in that moment to use my spreadsheet to add up all the counts to get my dosing right. If I don’t do that, my dosing is often off, and even a little bit “off” can cause uncomfortable and annoying symptoms the rest of the day, overnight, and into the next morning.

So, I have quite the incentive to use this spreadsheet to make sure that I get my dosing right. It’s functional: not for the perceived “fun” of writing things down.

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It’s the same thing that happens when I run long runs. I need to fuel my runs, and fuel (food) means enzymes. Figuring out how many enzymes to dose as I’m running 6, 9, or 25 hours into a run gets increasingly harder. I found that what works for me is having a pre-built list of the fuel options; and a spreadsheet where I quickly on my phone open it and tap a drop down list to mark what I’m eating, and it pulls in the counts from the library and tells me how many enzymes to take for that fuel (which I’ve already pre-calculated).

It’s useful in real-time for helping me dose the right amount of enzymes for the fuel that I need and am taking every 30 minutes throughout my run. It’s also useful for helping me stay on top of my goal amounts of calories and sodium to make sure I’m fueling enough of the right things (for running in general), which is something that can be hard to do the longer I run. (More about this method and a template for anyone who wants to track similarly here.)

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The TL;DR point of this is: I don’t track things for fun. I track things if and when they’re functionally useful, and primarily that is in real-time medical decision making.

These methods may not make sense to you, and don’t have to.

It may not be a method that works for you, or you may not have the situation that I’m in (T1D, Graves, celiac, and EPI – fun!) that necessitates these, or you may not have the goals that I have (ultrarunning). That’s ok!

But don’t say that you “couldn’t” do something. You ‘couldn’t’ track what you consumed when you ran or you ‘couldn’t’ write down what you were eating or you ‘couldn’t’ take that many pills or you ‘couldn’t’ inject insulin or…

You could, if you needed to, and if you decided it was the way that you could and would be able to achieve your goals.

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 tool 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.

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!

We Have Changed the Standards of Care for People With Diabetes

by Dana Lewis

We’ve helped change the standard of care for people with diabetes, with open source automated insulin delivery.

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I get citation alerts sometimes when my previous research papers or articles are cited. For the last few years, I get notifications when new consensus guidelines or research comes out that reference or include mention of open source automated insulin delivery (AID). At this time of year, the ADA Standards of Care is released for the following year, and I find out usually via these citation alerts.

Why?

This year, in 2023, there’s a section on open source automated insulin delivery!

A screenshot of the 2023 ADA Standards of Care section under Diabetes Technology (7) that lists DIY closed looping, meaning open source automated insulin delivery

But did you know, that’s not really new? Here’s what the 2022 version said:

A screenshot of the 2022 ADA Standards of Care section under Diabetes Technology (7) that lists DIY closed looping, meaning open source automated insulin delivery

And 2021 also included…

A screenshot of the 2021 ADA Standards of Care section under Diabetes Technology (7) that lists DIY closed looping, meaning open source automated insulin delivery

And 2020? Yup, it was there, too.

A screenshot of the 2020 ADA Standards of Care section under Diabetes Technology (7) that lists DIY closed looping, meaning open source automated insulin delivery

All the way back to 2019!

A screenshot of the 2019 ADA Standards of Care under Diabetes Technology (7) that lists DIY closed looping, meaning open source automated insulin delivery

If you read them in chronological order, you can see quite a shift.

In 2019, it was a single sentence noting their existence under a sub-heading of “Future Systems” under AID. In 2020, the content graduated to a full paragraph at the end of the AID section (that year just called “sensor-augmented pumps”). In 2021, it was the same paragraph under the AID section heading. 2022 was the year it graduated to having its own heading calling it out, with a specific evidence based recommendation! 2023 is basically the same as 2022.

So what does it say?

It points out patients are using open source AID (which they highlight as do-it-yourself closed loop systems). It sort of incorrectly suggests healthcare professionals can’t prescribe these systems (they can, actually – providers can prescribe all kinds of things that are off-label – there’s just not much point of a “prescription” unless it’s needed for a person’s elementary school (or similar) who has a policy to only support “prescribed” devices).

And then, most importantly, it points out that regardless, healthcare providers should assist in diabetes management and support patient choice to ensure the safety of people with diabetes. YAY!

“…it is crucial to keep people with diabetes safe if they are using these methods for automated insulin delivery. Part of this entails ensuring people have a backup plan in case of pump failure. Additionally, in most DIY systems, insulin doses are adjusted based on the pump settings for basal rates, carbohydrate ratios, correction doses, and insulin activity. Therefore, these settings can be evaluated and modified based on the individual’s insulin requirements.”

You’ll notice they call out having a backup plan in case of pump failure.

Well, yeah.

That should be true of *any* AID system or standalone insulin pump. This highlights that the needs of people using open source AID in terms of healthcare support are not that different from people choosing other types of diabetes therapies and technologies.

It is really meaningful that they are specifically calling out supporting people living with diabetes. Regardless of technology choices, people with diabetes should be supported by their healthcare providers. Full stop. This is highlighted and increasingly emphasized, thanks to the movement of individuals using open source automated insulin delivery. But the benefits of this is not limited to those of us using open source automated insulin delivery; this spills over and expands to people using different types of BG meters, CGM, insulin pumps, insulin pens, syringes, etc.

No matter their choice of tools or technologies, people with diabetes SHOULD be supported in THEIR choices. Not choices limited by healthcare providers, who might only suggest specific tools that they (healthcare providers) have been trained on or are familiar with – but the choices of the patient.

In future years, I expect the ADA Standard of Care for 2024 and beyond to evolve, in respect to the section on open source automated insulin delivery.

The evidence grading should increase from “E” (which stands for “Expert consensus or clinical experience”), because there is now a full randomized control trial in the New England Journal of Medicine on open source automated insulin delivery, in addition to the continuation results (24 weeks following the RCT; 48 full weeks of data) accepted for publication (presented at EASD 2022), and a myriad of other studies ranging from retrospective to prospective trials. The evidence is out there, so I expect that this evidence grading and the text of the recommendation text will evolve accordingly to catch up to the evidence that exists. (The standards of care are based on literature available up to the middle of the previous year; much of the things I’ve cited above came out in later 2022, so it matches the methodology to not be included until the following year; these newest articles should be scooped up by searches up to July 2023 for the 2024 edition.)

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In the meantime, I wish more people with diabetes were aware of the Standards of Care and could use them in discussion with providers who may not be as happy with their choices. (That’s part of the reason I wrote this post!)

I also wish we patients didn’t have to be aware of this and don’t have to argue our cases for support of our choices from healthcare providers.

But hopefully over time, this paradigm of supporting patient choice will continue to grow in the culture of healthcare providers and truly become the standard of care for everyone, without any personal advocacy required.

Did you know? We helped change the standards of care for people living with diabetes. By Dana M. Lewis from DIYPS.org

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)

Regulatory Approval Is A Red Herring

by Dana Lewis

One of the most common questions I have been asked over the last 8 years is whether or not we are submitting OpenAPS to the FDA for regulatory approval.

This question is a big red herring.

Regulatory approval is often seen and discussed as the one path for authenticating and validating safety and efficacy.

It’s not the only way.

It’s only one way.

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As background, you need to understand what OpenAPS is. We took an already-approved insulin pump that I already had, a continuous glucose monitor (CGM) that I already had, and found a way to read data from those devices and also to use the already-built commands in the pump to send back instructions to automate insulin delivery via the decision-making algorithm that we created. The OpenAPS algorithm was the core innovation, along with the realization that this already-approved pump had those capabilities built in. We used various off the shelf hardware (mini-computers and radio communication boards) to interoperate with my already approved medical devices. There was novelty in how we put all the pieces together, though the innovation was the algorithm itself.

The caveat, though, is that although the pump I was using was regulatory-approved and on the market, which is how I already had it, it had later been recalled after researchers, the manufacturer, and the FDA realized that you could use the already-built commands in the pump’s infrastructure. So these pumps, while not causing harm to anyone and no cases of harm have ever been recorded, were no longer being sold. It wasn’t a big deal to the company; it was a voluntary recall, and people like me often chose to keep our pumps if we were not concerned about this potential risk.

We had figured out how to interoperate with these other devices. We could have taken our system to the FDA. But because we were using already-off-the-market pumps, there was no way the FDA would approve it. And at the time (circa 2014), there was no vision or pathway for interoperable devices, so they didn’t have the infrastructure to approve “just” an automated insulin delivery algorithm. (That changed many years later and they now have infrastructure for reviewing interoperable pumps, CGM, and algorithms which they call controllers).

The other relevant fact is that the FDA has jurisdiction based on the commerce clause in the US Constitution: Congress used its authority to authorize the FDA to regulate interstate commerce in food, drugs, and medical devices. So if you’re intending to be a commercial entity and sell products, you must submit for regulatory approval.

But if you’re not going to sell products…

This is the other aspect that many people don’t seem to understand. All roads do not lead to regulatory approval because not everyone wants to create a company and spend 5+ years dedicating all their time to it. That’s what we would have had to do in order to have a company to try to pursue regulatory approval.

And the key point is: given such a strict regulatory environment, we (speaking for Dana and Scott) did not want to commercialize anything. Therefore there was no point in submitting for regulatory approval. Regardless of whether or not the FDA was likely to approve given the situation at the time, we did not want to create a company, spend years of our life dealing with regulatory and compliance issues full time, and maybe eventually get permission to sell a thing (that we didn’t care about selling).

The aspect of regulatory approval is a red herring in the story of the understanding of OpenAPS and the impact it is having and could have.

Yes, we could have created a company. But then we would not have been able to spend the thousands of hours that we spent improving the system we made open source and helping thousands of individuals who were able to use the algorithm and subsequent systems with a variety of pumps, CGMs, and mobile devices as an open source automated insulin delivery system. We intentionally chose this path to not commercialize and thus not to pursue regulatory approval.

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As a result of our work (and others from the community), the ecosystem has now changed.

Time has also passed: it’s been 8 years since I first automated insulin delivery for myself!

The commercial players have brought multiple commercial AIDs to market now, too.

We created OpenAPS when there was NO commercial option at the time. Now there are a few commercial options.

But it is also an important note that I, and many thousands of other people, are still choosing to use open source AID systems.

Why?

This is another aspect of the red herring of regulatory approval.

Just because something is approved does not mean it’s available to order.

If it’s available to order (and not all countries have approved AID systems!), it doesn’t mean it’s accessible or affordable.

Insurance companies are still fighting against covering pumps and CGMs as standalone devices. New commercial AID systems are even more expensive, and the insurance companies are fighting against coverage for them, too. So just because someone wants an AID and has one approved in their country doesn’t mean that they will be able to access and/or afford it. Many people with diabetes struggle with the cost of insulin, or the cost of CGM and/or their insulin pump.

Sometimes providers refuse to prescribe devices, based on preconceived notions (and biases) about who might do “well” with new therapies based on past outcomes with different therapies.

For some, open source AID is still the most accessible and affordable option.

And in some places, it is still the ONLY option available to automate insulin delivery.

(And in most places, open source AID is still the most advanced, flexible, and customizable option.)

—

Understanding the many reasons why someone might choose to use open source automated insulin delivery folds back into the understanding of how someone chooses to use open source automated insulin delivery.

It is tied to the understanding that manual insulin delivery – where someone makes all the decisions themselves and injects or presses buttons manually to deliver insulin – is inherently risky.

Automated insulin delivery reduces risk compared to manual insulin delivery. While some new risk is introduced (as is true of any additional devices), the net risk reduction overall is significantly large compared to manual insulin delivery.

This net risk reduction is important to contextualize.

Without automated insulin delivery, people overdose or underdose on insulin multiple times a day, causing adverse effects and bad outcomes and decreasing their quality of life. Even when they’re doing everything right, this is inevitable because the timing of insulin is so challenging to manage alongside dozens of other variables that at every decision point play a role in influencing the glucose outcomes.

With open source automated insulin delivery, it is not a single point-in-time decision to use the system.

Every moment, every day, people are actively choosing to use their open source automated insulin delivery system because it is better than the alternative of managing diabetes manually without automated insulin delivery.

It is a conscious choice that people make every single day. They could otherwise choose to not use the automated components and “fall back” to manual diabetes care at any moment of the day or night if they so choose. But most don’t, because it is safer and the outcomes are better with automated insulin delivery.

Each individual’s actions to use open source AID on an ongoing basis are data points on the increased safety and efficacy.

—

However, this paradigm of patient-generated data and patient choice as data contributing toward safety and efficacy is new. There are not many, if any, other examples of patient-developed technology that does not go down the commercial path, so there are not a lot of comparisons for open source AID systems.

As a result, when there were questions about the safety and efficacy of the system (e.g., “how do you know it works for someone else other than you, Dana?”), we began to research as a community to address the questions. We published data at the world’s biggest scientific conference and were peer-reviewed by scientists and accepted to present a poster. We did so. We were cited in a piece in Nature as a result. We then were invited to submit a letter to the editor of a traditional diabetes journal to summarize our findings; we did so and were published.

I then waited for the rest of the research community to pick up this lead and build on the work…but they didn’t. I picked it up again and began facilitating research directly with the community, coordinating efforts to make anonymized pools of data for individuals with open source AID to submit their data to and for years have facilitated access to dozens of researchers to use this data for additional research. This has led to dozens of publications further documenting the efficacy of these solutions.

Yet still, there was concern around safety because the healthcare world didn’t know how to assess these patient-generated data points of choice to use this system because it was better than the alternative every single day.

So finally, as a direct result of presenting this community-based research again at the world’s largest diabetes scientific conference, we were able to collaborate and design a grant proposal that received grant funding from New Zealand’s Health Research Council (the equivalent of the NIH in the US) for a randomized control trial of the OpenAPS algorithm in an open source AID system.

An RCT is often seen as the gold standard in science, so the fact that we received funding for such a study alone was a big milestone.

And this year, in 2022, the RCT was completed and our findings were published in one of the world’s largest medical journals, the New England Journal of Medicine, establishing that the use of the OpenAPS algorithm in an open source AID was found to be safe and effective in children and adults.

No surprises here, though. I’ve been using this system for more than 8 years, and seeing thousands of others choose the OpenAPS algorithm on an ongoing, daily basis for similar reasons.

—

So today, it is possible that someone could take an open source AID system using the OpenAPS algorithm to the FDA for regulatory approval. It won’t likely be me, though.

Why not? The same reasons apply from 8 years ago: I am not a company, I don’t want to create a company to be able to sell things to end users. The path to regulatory approval primarily matters for those who want to sell commercial products to end users.

Also, regulatory approval (if someone got the OpenAPS algorithm in an open source AID or a different algorithm in an open source AID) does not mean it will be commercially available, even if it will be approved.

It requires a company that has pumps and CGMs it can sell alongside the AID system OR commercial partnerships ready to go that are able to sell all of the interoperable, approved components to interoperate with the AID system.

So regulatory approval of an AID system (algorithm/mobile controller design) without a commercial partnership plan ready to go is not very meaningful to people with diabetes in and of itself. It sounds cool, but will it actually do anything? In and of itself, no.

Thus, the red herring.

Might it be meaningful eventually? Yes, possibly, especially if we collectively have insurers to get over themselves and provide coverage for AID systems given that AID systems all massively improve short-term and long-term outcomes for people with diabetes.

But as I said earlier, regulatory approval does necessitate access nor affordability, so an approved system that’s not available and affordable to people is not a system that can be used by many.

We have a long way to go before commercial AID systems are widely accessible and affordable, let alone available in every single country for people with diabetes worldwide.

Therefore, regulatory approval is only one piece of this puzzle.

And it is not the only way to assess safety and efficacy.

—

The bigger picture this has shown me over the years is that while systems are created to reduce harm toward people – and this is valid and good – there have been tendencies to convert to the assumption that therefore the systems are the only way to achieve the goal of harm reduction or to assess safety and efficacy.

They aren’t the only way.

As explained above, FDA approval is one method of creating a rubber stamp as a shorthand for “is this considered to be safe and effective”.

That’s also legally necessary for companies to use if they want to sell products. For situations that aren’t selling products, it’s not the only way to assess safety and efficacy, which we have shown with OpenAPS.

With open source automated insulin delivery systems, individuals have access to every line of code and can test and choose for themselves, not just once, but every single day, whether they consider it to be safer and more effective for them than manual insulin dosing. Instead of blindly trusting a company, they get the choice to evaluate what they’re using in a different way – if they so choose.

—

So any questions around seeking regulatory approval are red herrings.

A different question might be: What’s the future of the OpenAPS algorithm?

The answer is written in our OpenAPS plain language reference design that we posted in February of 2015. We detailed our vision for individuals like us, researchers, and companies to be able to use it in the future.

And that’s how it’s being used today, by 1) people like me; and 2)  in research, to improve what we can learn about diabetes itself and improve AID; and 3) by companies, one of whom has already incorporated parts of our safety design as part of a safety layer in their ML-based AID system and has CE mark approval and is being sold and used by thousands of people in Europe.

It’s possible that someone will take it for regulatory approval; but that’s not necessary for the thousands of people already using it. That may or may not make it more available for thousands more (see earlier caveats about needing commercial partnerships to be able to interoperate with pumps and CGMs).

And regardless, it is still being used to change the world for thousands of people and help us learn and understand new things about the physiology of diabetes because of the way it was designed.

That’s how it’s been used and that’s the future of how it will continue to be used.

No rubber stamps required.

Regulatory Approval: A Red Herring

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?

—

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?