Dana Lewis

How To Talk To Your Doctor About Your Enzyme (PERT) Dosing If You Have Exocrine Pancreatic Insufficiency (EPI or PEI or PI)

by Dana Lewis

In exocrine pancreatic insufficiency (EPI/PEI/PI), people are responsible for self-dosing their medication every time they eat something.

Doctors prescribe a starting dose, but a person with EPI determines each and every time they eat or drink something how many enzyme pills (of pancreatic enzyme replacement therapy, known as PERT) to take. Doctors often prescribe a low starting dose, and people have to try experimenting with multiple pills of the small size, and eventually work with their doctors to change their prescription to get a bigger pill size (so they can take fewer pills per meal) and the correct number of pills per day to match their needs.

For example, often people are prescribed one 10,000 unit pill per meal. The 10,000 units represents the amount of lipase (to help digest fat). There are also two other enzymes (protease, for protein digestion, and amylase, for carbohydrate digestion). They may be prescribed 1 pill per meal, which means 10,000 units of lipase per meal. But most dosing guidelines recommend starting at a dose of 40,000-50,000 units of lipase per meal (and people often need more), so it wouldn’t be surprising that someone prescribed one 10,000 pill per meal would need 4-5 pills of the 10,000 size pill PER MEAL, and times three meals per day (let alone any snacks), to get acceptable GI outcomes.

Mathematically, this means the initial prescription wouldn’t last long. The initial prescription for 1 pill per meal, with 3 meals a day, means 3 pills per day. 3 pills per day across a 30 day month is 90 pills. But when the pills per meal increase, that means the prescription won’t cover the entire month.

In fact, it would last a lot less than a month; closer to one week!

Showing that based on the number of pills and 3 meals per day, an intitial RX of 10,000 size pills may last more like a week rather than a full 30 days when the doctor is unaware of prescribing guidlines that typically suggest 40,000-50,000 per meal is needed as the starting meal dose.

Let’s repeat: with a too-small prescription pill size (e.g. 10,000 starting dose size) and count (e.g. 3 pills per day to cover 1 per meal) and with a person with EPI titrating themselves up to the starting dose guidelines in all of the medical literature, they would run out of their prescription WITHIN ONE WEEK. 

So. If you have EPI, you need to be prepared to adjust your dosing yourself; but you also need to be ready to reach out to your doctor and talk about your need for more enzymes and a changed prescription.

PERT (enzymes) come in different sizes, so one option is to ask for a bigger pill size and/or a different amount (count) per meal/day. Depending on the brand and the number of pills you need per meal, it could be simply going up to a bigger pill size. For example, if you need 3 pills of the 10,000 PERT size, you could move to a 36,000 pill size and take one per meal. If you find yourself taking 5 pills of the 10,000 PERT size, that might mean 2 pills of the 25,000 size. (Brands differ slightly, e.g. one might be 24,000 instead of 25,000, so the math may work out slightly differently depending on which brand you’re taking.)

Don’t be surprised if you need to do this within a week or two of starting PERT. In fact, based on the math above, especially if you’re on a much lower dose than starting guidelines (e.g. 40,000-50,000 units of lipase per meal), you should expect within a few days to need an updated prescription to make sure that you don’t run out of PERT.

If you do find yourself running out of PERT before you can get your prescription updated, there is an alternative you can consider: either substituting or adding on over the counter enzymes. The downsides include the fact that insurance doesn’t cover them so you would be paying out of pocket; plus there are no studies with these so you can’t (shouldn’t) rely on these as full 1:1 substitutes for prescription PERT without careful personal testing that you can do so. That being said, there is anecdotal evidence (from me, as well as hundreds of other people I’ve seen in community groups) that it is possible to use OTC enzymes if you can’t afford or can’t get a PERT prescription; or if you need to “top off”/supplement/add to your PERT because your prescription won’t last a full month and you can’t get a hold of your doctor or they won’t update your prescription.

For me, I generally evaluate the units of lipase (e.g. this kind is 17,000 units of lipase per pill) but then factor in for the lack of reliability for OTC and really treat it like it contains 13-15,000 units of lipase when choosing to take it. Similarly for another lipase-only OTC option (that has ~6,000 units per pill), I assume it acts like it only has ~5,000 units. Unlike insulin, there is little downside to taking a little too much of enzymes; but there is a LOT of downside to not taking enough, so my personal approach is that if in doubt, or on the fence, to round up (especially with OTC pills, which cost somewhere between $0.08/pill (lipase-only) to $0.34/pill (for the larger and multiple enzyme pill)).

So how do you talk to your doctor about needing more PERT?

It helps if you bring data and evidence to the conversation, especially if your doctor thinks by default that you don’t need more than what they initially prescribed. You can bring your personal data (more on that below and how to collect and present that), but you can also cite relevant medical literature to show if your dose is below standard starting guidelines.

Below I’ve shared a series of citations that show that the typical starting dose for people with EPI should be around 40,000-50,000 units of lipase per meal.

Important note that this is the STARTING DOSE SIZE, and most of these recommend further increasing of dose to 2-3 times this amount as needed. Depending on the starting dose size, you can see the chart I built below that illustrates with examples exactly how much this means one might need to increase to. Not everyone will need the upper end of the numbers, but if a doctor starts someone on 10,000 and doesn’t want to get them up to 40,000 (the lower end of starting doses) or go beyond 40,000 because it’s the starting dose, I’ve found this chart useful to show that numerically the range is a lot larger than we might assume.

Example of Titrating According to Common Dose Guidelines, Before Adding PPI

Examples of PERT starting doses of 25,000, 40,000, and 50,000 (plus half that for snacks) and what the dose would be if increased according to guidelines to 2x and 3x, plus the sum of the total daily dose needed at those levels.

Here are some citations that back up my point about 40,000-50,000 units of lipase being the typically recommended starting dose, including across different conditions (e.g. regardless of whether you have EPI + any of (chronic pancreatitis, diabetes, celiac, etc)).

  • Shandro et al, 2020, the median starting dose of 50,000 units per lipase “is an appropriate starting dose”, also citing UEG 2017 guidelines.
  • Forsmark et al, 2020, defined appropriate dose of PERT as >=120,000 units of lipase per day (e.g. 40,000 units of lipase per meal).
  • Whitcomb et al, 2022, in a joint American Gastroenterology Association and PancreasFest symposium paper, concur on 40,000 units as a starting dose and that “This dose should be titrated up as needed to reduce steatorrhea or gastrointestinal symptoms of maldigestion “
  • 2021 UK guidelines for EPI management suggest 50,000 units as the starting dose and emphasize that “all guidelines endorse dose escalation if the initial dose is not effective”

There are also many guidelines and research specific for EPI and different co-conditions supporting the ballpark of 40-50,000 units of lipase starting dose:

It is also worth noting that these guidelines also point out that after titrating 2-3x above the starting dose, PPI (proton pump inhibitors, to suppress acid) should be added if gastrointestinal symptoms are still not resolved. Anecdotally, it seems a lot of doctors are not aware that PPIs should be added if 3x the starting dose is not effective, so make sure to bring this up as well.

How to Share Your Personal PERT Data To Show How Much You Need

In addition to pointing out the guidelines (based on the above), it’s useful to share your data to show what you’ve been taking (dosing) and how it’s been working. I’ve written a lot about how you can do this manually, but I also recently created an iOS based app to make it easier to track what you’re eating, what you’re dosing in terms of PERT/enzymes, and what the outcome is. This app, PERT Pilot, is free to use, and it also enables you to visualize on a graph the relationship between what you’re eating and dosing.

PERT Pilot lets you track how many grams of fat each pill of your current prescription has been used for, so you can see with red and green coloring the relationship between meals that you’ve had symptoms after (in red) vs. when you recorded no symptoms (green). If you have a “convergence zone” of green and red in the same area, that may help you decide to change your ratio (e.g. dose more) around that amount, until you can comfortably and repeatedly get green results (no symptoms when you eat).

How you might use this to talk to your doctor

You can take a screenshot of your PERT Pilot graph and share it with your doctor to show them how many grams of fat your prescription size (e.g. pill size) effectively “covers” for you, and how many meals that you’ve tested it with.

Meals based on the ratio of fat:lipase and protein:protease mapped with color coded dots where green means no symptoms, orange means not sure if symptoms, and red means symptoms occurred and the dose likely didn't work at that ratio.For example, I was initially prescribed an enzyme dose that was one pill per meal (and no snacks), so I had 3 pills per day. But I quickly found myself needing two pills per meal, based on what I was typically eating. I summarized my data to my doctor, saying that I found one pill typically covered up to ~30 grams of fat per meal, but most of my meals were >30 grams of fat, so that I wanted to update my prescription to have an average of 2 pills per meal of this prescription size. I also wanted to be able to eat snacks, so I asked for 2 pills per meal, 1 per snack, which meant that my prescription increased to 8 pills per day (of the same size), to cover 2 pills x 3 meals a day (=6) plus up to 2 snacks (=2). I also had weeks of data to show that my average meal was >30 grams of fat to confirm that I need more than the amount of lipase I was originally prescribed. My doctor was happy to increase my prescription as a result, and this is what I’ve been using successfully for over a year ever since.

So in summary, the data that would be useful to share is:

  • How much one pill ‘covers’ (which is where the PERT Pilot graph can be used)
  • How many pills per meal you’ve been taking and how big your meals typically are
  • Whether you are struggling with the number of pills per meal: if so, ask whether there’s a larger pill size in your current brand that you could increase to, in order to reduce the number of pills per meal (and/or snack) you need to take every time

If you are told that you shouldn’t need “that much”, remember the above section and have those resources ready to discuss that the starting dose is often 40,000-50,000 per meal and that the guidelines say to titrate up to 3x that before adding PPI. Therefore, it would be expected for some people to need upwards of 600,000 units of lipase per day (50,000 starting dose, increased 3x per meal and half of the dose used per snack). Depending on what people eat, this could be even higher (because not everyone eats the same size meal and snack and many of us adjust dose based on what we eat).

Also, it is worth noting that the dosing guidelines never mention the elastase levels or severity of EPI: so PERT prescriptions should not be based on whether you have “moderate” or “severe” EPI and what your elastase level is (e.g. whether it’s 45 or 102 or 146 or even 200, right on the line of EPI – all of those elastase levels would still get the same starting dose of PERT, based on the clinical guidelines for EPI).

It is common and you are not alone if you’ve not been giving the starting dose of PERT that the guidelines recommend.

There are numerous studies showing most people with EPI are initially underdosed/underprescribed PERT. For example, in 2020 Forsmark et al reported that only 8.5% of people with chronic pancreatitis and EPI received an adequate prescription for PERT: and only 5.5% of people with pancreatic cancer and EPI received an adequate prescription dose of PERT. Other studies in chronic pancreatitis and EPI from 2014, 2016, and 2020 report that undertreatment often occurs in EPI and CP; and I’ve found studies in other conditions as well showing undertreatment compared to guidelines, although it’s most studied in CP and cancer (which is true of all types of EPI-related research, despite the prevalence in many other conditions like diabetes, celiac, etc.).

You may need to advocate for yourself, but know that you’re not alone. Again, feel free to comment or email privately (Dana@OpenAPS.org) if you need help finding research for another co-condition and EPI that I haven’t mentioned here.

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PS – if you haven’t seen it, I have other posts about EPI at DIYPS.org/EPI

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

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How I Built An AI Meal Estimation App – AI Meal Estimates in “PERT Pilot” and Announcing A New App “Carb Pilot”

by Dana Lewis

As I have been working on adding additional features to PERT Pilot, the app I built (now available on the App Store for iOS!) for people like me who are living with exocrine pancreatic insufficiency, I’ve been thinking about all the things that have been challenging with managing pancreatic enzyme replacement therapy (PERT). One of those things was estimating the macronutrients – meaning grams of fat and protein and carb – in what I was eating.

I have 20+ years practice on estimating carbs, but when I was diagnosed with EPI, estimating fat and protein was challenging! I figured out methods that worked for me, but part of my PERT Pilot work has included re-thinking some of my assumptions about what is “fine” and what would be a lot better if I could improve things. And honestly, food estimation is still one of those things I wanted to improve! Not so much the accuracy (for me, after a year+ of practice I feel as though I have the hang of it), but the BURDEN of work it takes to develop those estimates. It’s a lot of work and part of the reason it feels hard to titrate PERT every single time I want to eat something.

So I thought to myself, wouldn’t it be nice if we could use AI tools to get back quick estimates of fat, protein, and carbs automatically in the app? Then we could edit them or otherwise use those estimates.

And so after getting the initial version of PERT Pilot approved and in the App Store for users to start using, I submitted another update – this time with meal estimation! It’s now been live for over a week.

Here’s how it works:

  • Give your meal a short title (which is not used by the AI but is used at a glance by us humans to see the meal in your list of saved meals).
  • Write a simple description of what you’re planning to eat. It can be short (e.g. “hot dogs”) or with a bit more detail (e.g. “two hot dogs with gluten free buns and lots of shredded cheddar cheese”). A little more detail will get you a somewhat more accurate estimates.
  • Hit submit, and then review the generated list of estimated counts. You can edit them if you think they’re not quite right, and then save them.

Here’s a preview of the feature as a video. I also asked friends for examples of what they’d serve if they had friends or family coming over to dinner – check out the meal descriptions and the counts the app generated for them. (This is exactly how I have been using the app when traveling and eating takeout or eating at someone’s house.)

Showing screenshots of PERT Pilot with the meal description input and the output of the estimated macronutrient counts for grams of fat, protein, and carb Showing more screenshots of PERT Pilot with the meal description input and the output of the estimated macronutrient counts for grams of fat, protein, and carb Showing even more screenshots of PERT Pilot with the meal description input and the output of the estimated macronutrient counts for grams of fat, protein, and carb

The original intent of this was to aid people with EPI (PEI/PI) in estimating what they’re eating so they can better match the needed enzyme dosing to it. But I realized…there’s probably a lot of other people who might like a meal estimation app, too. Particularly those of us who are using carb counts to dose insulin several times a day!

I pulled the AI meal estimation idea out into a second, separate app called Carb Pilot, which is also now available on the App Store.

Carb Pilot is designed to make carb counting easier and to save a bunch of clicks for getting an estimate for what you’re eating.

The Carb Pilot logo, which has pieces of fruit on the letters of the word "Carb". Pilot is written in italic script in purple font.

What does Carb Pilot do?

  • Like PERT Pilot, Carb Pilot has the AI meal estimation feature. You can click the button, type your meal description (and a meal title) and get back AI-generated estimates.
  • You can also use voice entry and quickly, verbally describe your meal.
  • You can also enter/save a meal manually, if you know what the counts are, or want to make your own estimates.

Carb Pilot integrates with HealthKit, so if you want, you can enable that and save any/all of your macronutrients there. HealthKit is a great tool for then porting your data to other apps where you might want to see this data along with, say, your favorite diabetes app that contains CGM/glucose data (or for any other reason/combination).

Speaking of “any/all”, Carb Pilot is designed to be different from other food tracking apps.

As a person with diabetes, historically I *just* wanted carb counts. I didn’t want to have to sift through a zillion other numbers when I just needed ONE piece of information. If that’s true for you – whether it’s carbs, protein, calories, or fat – during onboarding you can choose which of these macronutrients you want to display.

Just want to see carbs? That’s the default, and then in the saved meals you’ll ONLY see the carb info! If you change your mind, you can always change this in the Settings menu, and then the additional macronutrients will be displayed again.

Carb Pilot enables you to toggle the display of different nutrients. This shows what it looks like if only carbs are displaying or what happens if you ask the app to display all nutrients for each recorded food item.

It’s been really fun to build out Carb Pilot. Scott has been my tester for it, and interestingly, he’s turned into a super user of Carb Pilot because, in his words, “it’s so easy to use” and to generate macronutrient estimates for what he’s eating. (His use case isn’t for dosing medicine but matching what he’s eating against his energy expenditure for how much exercise/activity he’s been doing.) He’s been using it and giving me feedback and feature requests – I ended up building the voice-entry feature much more quickly than I expected because he was very interested in using it, which has been great! He also requested the ability to display meals in reverse chronological order and to be able to copy a previous meal to repeat it on another day (swipe on a meal and you can copy the description if you want to tweak and use it again, or simply repeat the meal as-is). We also discovered that it supports multiple languages as input for the AI meal estimation feature. How? Well, we were eating outside at a restaurant in Sweden and Scott copied and pasted the entree description from the menu – in Swedish – into Carb Pilot. It returned the counts for the meal, exactly as if he had entered them in English (our default language)!

I’m pointing this out because if you give Carb Pilot a try and have an idea for a feature/wish you could change the app in some way, I would LOVE for you to email me and tell me about it. I have a few other improvements I’m already planning to add but I’d love to make this as useful to as many people who would find this type of app helpful.

Why (was) there a subscription for ongoing AI use?

For both PERT Pilot and Carb Pilot, there is a cost (expense) to using the AI meal estimation. I have to pay OpenAI (which hosts the AI I’m using for the app) to use the AI for each meal estimation, and I have to host a web server to communicate between the app and the AI, which also costs a bit for every time we send a meal estimation request from the app. That’s why I decided to make Carb Pilot free to download and try. I originally played with $1.99 a month for unlimited AI meal estimations, but temporarily have turned that off to see what that does to the server load and cost, so right now it’s free to use the AI features as well.

TLDR:

– PERT Pilot has been updated to include the new meal estimation feature!

– People without EPI can use Carb Pilot for carb, protein, fat, and/or calorie tracking (of just one or any selection of those) tracking, also using the new AI meal estimation features!

You can find PERT Pilot here or Carb Pilot here on the App Store.

PERT Pilot – the first iOS app for Exocrine Pancreatic Insufficiency (EPI or PEI) and Pancreatic Enzyme Replacement Therapy (PERT)

by Dana Lewis

Introducing PERT Pilot, the first iOS app designed for people with exocrine pancreatic insufficiency (EPI / PEI) and the only iOS app for specifically recording pancreatic enzyme replacement therapy (PERT) dosing!

*Available to download for FREE on the iOS App Store *
The PERT Pilot logo - PERT is in all caps and bold purple font, the word "Pilot" is in a script font in black placed below PERT.

After originally developing GI symptoms, then working through the long journey to diagnosis with exocrine pancreatic insufficiency (known as EPI or PEI), I’ve had to come up methods to figure out the right dosing of PERT for my EPI. I realized that the methods that I’ve made work for me – logging what I was eating in a spreadsheet and using it to determine the ratios I needed to use to dose my pancreatic enzyme replacement therapy (PERT) – weren’t methods that other people were as comfortable using. I have been thinking about this for the last year or more, and in my pursuit for wanting to encourage others to improve their outcomes with EPI (and realize that it IS possible to get to few symptoms, based on increasing/titrating the enzymes we take based on what we eat), I wrote a very long blog post explaining these methods and also sharing a free web-based calculator to help others to calculate their ratios.

But, that still isn’t the most user-friendly way to enable people to do this.

What else could I do, though? I wasn’t sure.

More recently, though, I have been experimenting with various projects and using ‘large language model’ (LLM) tools like GPT-4 to work on various projects. And a few weeks ago I realized that maybe I could *try* to build an iOS app version of my idea. I wanted something to help people log what they are eating, record their PERT dosing, and more easily see the relationship in what they are eating and what enzymes they are dosing. This would enable them to use that information to more easily adjust what they are dosing for future meals if they’re not (yet) satisfied with their outcomes.

And thus, PERT Pilot was born!

Screenshots from the PERT Pilot app which show the home screen, the calculator where you enter what PERT you're taking and a typical meal, plus the resulting ratios screen that show you the relationship between what you ate and how many enzymes you dosed.

What does PERT Pilot do?

PERT Pilot is designed to help people living with Exocrine Pancreatic Insufficiency (EPI or PEI) more easily deal with pancreatic enzyme replacement therapy (PERT). Aka, “taking enzymes”.

The PERT Pilot calculator enables you log the PERT that you are taking along with a meal, how many pills you take for it, and whether this dosing seems to work for you or not.

PERT Pilot then shows you the relationship between how much PERT you have been taking and what you are eating, supporting you as you fine-tune your enzyme intake.

PERT Pilot also enables you to share what’s working – and what might not be working – with your healthcare provider. PERT Pilot not only lists every meal you’ve entered, but also has a visual graph so you can see each meal and how much fat and protein from each meal were dosed by one pill – and it’s color coded by the outcome you assigned that meal! Green means you said that meal’s dosing “worked”; orange means you were “unsure”, and red matches the meals you said “didn’t work” for that level of dosing.

You can press on any meal and edit it, and you can swipe to delete a meal.

PERT Pilot also has is an education section so you can learn more about EPI and why you need PERT, and how this approach to ratios may help you more effectively dose your PERT in the future.

Why use PERT Pilot if you have EPI or PEI or PI?

PERT Pilot is the first and only specific app for those of us living with EPI (PEI or PI). People who use the approach in PERT Pilot of adapting their PERT dosing to what they are eating for each meal or snack often report fewer symptoms. PERT Pilot was designed and built by someone with exocrine pancreatic insufficiency, just like you!

With PERT Pilot you can:

  • Log your meals and PERT dosing. No other app specifically is designed for PERT dosing.
  • Edit or adjust your meal entry at any time – including if you wake up the next morning and realize your last dose from the day before ‘didn’t work’.
  • Review your dosing and see all of your meals, dosing, and outcomes – including a visual graph that shows you, for each meal, what one pill ‘covered’ so you can see where there are clusters of dosing that worked and if there are any clear patterns in what didn’t work for you.
  • You can also export your data, as a PDF list of all meals or a CSV file (which you can open in tools like Excel or other spreadsheet tools) if you want to analyze your data elsewhere!
  • Your data is your data, period. No one has access to your dosing data, meal data, or outcome data, and nothing you enter into PERT Pilot leaves your device – unless you decide to export your data. (See more in the PERT Pilot Privacy Policy.)

Note: this app was not funded by nor has any relationship to any pharmaceutical or medical-related companies. It’s simply built by a person with EPI for other people with EPI.

Here is a quick demonstration of PERT Pilot in action:

An animated gif of PERT Pilot in action

You can share your feedback about PERT Pilot:

Feel free to email me (Dana+PERTPilot@OpenAPS.org) any time.

I’d love to hear what works or is helpful, but also if something in the app isn’t yet working as expected.

Or, if you use another approved brand of PERT that’s not currently listed, let me know and I can add it in.

And, you can share your feature requests! I’m planning to build more features soon (see below).

What’s coming next for PERT Pilot:

I’m not done improving the functionality! I plan to add an AI meal estimation feature (UPDATE: now available!), so if you don’t know what’s in what you’re eating at a restaurant or someone else’s home cooked meal you can simply enter a description of the meal and have macronutrient estimates generated for you to use or modify.

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Download PERT Pilot today! It’s free to download, so go ahead and download it and check it out! If you find it useful, please also leave a rating or review on the App Store to help other people find it in the future. You can also share it via social media, and give people a link to download it: https://bit.ly/PERT-Pilot-iOS

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

How I Use LLMs like ChatGPT And Tips For Getting Started

by Dana Lewis

You’ve probably heard about new AI (artificial intelligence) tools like ChatGPT, Bard, Midjourney, DALL-E and others. But, what are they good for?

Last fall I started experimenting with them. I looked at AI art tools and found them to be challenging, at the time, for one of my purposes, which was creating characters and illustrating a storyline with consistent characters for some of my children’s books. I also tested GPT-3 (meaning version 3.0 of GPT). It wasn’t that great, to be honest. But later, GPT-3.5 was released, along with the ChatGPT chat interface to it, which WAS a big improvement for a lot of my use cases. (And now, GPT-4 is out and is an even bigger improvement, although it costs more to use. More on the cost differences below)

So what am I using these AI tools for? And how might YOU use some of these AI tools? And what are the limitations? This is what I’ve learned:

  1. The most frequent way I use these AI tools is for getting started on a project, especially those related to writing.

You know the feeling of staring at a blank page and not knowing where to start? Maybe it’s the blank page of a cold email; the blank page of an essay or paper you need to write; the blank page of the outline for a presentation. Starting is hard!

Even for this blog post, I had a list of bulleted notes of things I wanted to remember to include. But I wasn’t sure how I wanted to start the blog post or incorporate them. I stuck the notes in ChatGPT and asked it to expand the notes.

What did it do? It wrote a few paragraph summary. Which isn’t what I wanted, so I asked it again to use the notes and this time “expand each bullet into a few sentences, rather than summarizing”. With these clear directions, it did, and I was able to look at this content and decide what I wanted to edit, include, or remove.

Sometimes I’m stuck on a particular writing task, and I use ChatGPT to break it down. In addition to kick-starting any type of writing overall, I’ve asked it to:

  • Take an outline of notes and summarize them into an introduction; limitations section; discussion section; conclusion; one paragraph summary; etc.
  • Take a bullet point list of notes and write full, complete sentences.
  • Take a long list of notes I’ve written about data I’ve extracted from a systematic review I was working on, and ask it about recurring themes or outlier concepts. Especially when I had 20 pages (!) of hand-written notes in bullets with some loose organization by section, I could feed in chunks of content and get help getting the big picture from that 20 pages of content I had created. It can highlight themes in the data based on the written narratives around the data.

A lot of times, the best thing it does is it prompts my brain to say “that’s not correct! It should be talking about…” and I’m able to more easily write the content that was in the back of my brain all along. I probably use 5% of what it’s written, and more frequently use it as a springboard for my writing. That might be unique to how I’m using it, though, and other simple use cases such as writing an email to someone or other simplistic content tasks may mean you can keep 90% or more of the content to use.

2. It can also help analyze data (caution alert!) if you understand how the tools work.

Huge learning moment here: these tools are called LLMs (large language models). They are trained on large amounts of language. They’re essentially designed so that, based on all of those words (language) it’s taken in previously, to predict content that “sounds” like what would come after a given prompt. So if you ask it to write a song or a haiku, it “knows” what a song or a haiku “looks” like, and can generate words to match those patterns.

It’s essentially a PATTERN MATCHER on WORDS. Yeah, I’m yelling in all caps here because this is the biggest confusion I see. ChatGPT or most of these LLMs don’t have access to the internet; they’re not looking up in a search engine for an answer. If you ask it a question about a person, it’s going to give you an answer (because it knows what this type of answer “sounds” like), but depending on the amount of information it “remembers”, some may be accurate and some may be 100% made up.

Why am I explaining this? Remember the above section where I highlighted how it can start to sense themes in the data? It’s not answering solely based on the raw data; it’s not doing analysis of the data, but mostly of the words surrounding the data. For example, you can paste in data (from a spreadsheet) and ask it questions. I did that once, pasting in some data from a pivot table and asking it the same question I had asked myself in analyzing the data. It gave me the same sense of the data that I had based on my own analysis, then pointed out it was only qualitative analysis and that I should also do quantitative statistical analysis. So I asked it if it could do quantitative statistical analysis. It said yes, it could, and spit out some numbers and described the methods of quantitative statistical analysis.

But here’s the thing: those numbers were completely made up!

It can’t actually use (in its current design) the methods it was describing verbally, and instead made up numbers that ‘sounded’ right.

So I asked it to describe how to do that statistical method in Google Sheets. It provided the formula and instructions; I did that analysis myself; and confirmed that the numbers it had given me were 100% made up.

The takeaway here is: it outright said it could do a thing (quantitative statistical analysis) that it can’t do. It’s like a human in some regards: some humans will lie or fudge and make stuff up when you talk to them. It’s helpful to be aware and query whether someone has relevant expertise, what their motivations are, etc. in determining whether or not to use their advice/input on something. The same should go for these AI tools! Knowing this is an LLM and it’s going to pattern match on language helps you pinpoint when it’s going to be prone to making stuff up. Humans are especially likely to make something up that sounds plausible in situations where they’re “expected” to know the answer. LLMs are in that situation all the time: sometimes they actually do know an answer, sometimes they have a good guess, and sometimes they’re just pattern matching and coming up with something that sounds plausible.

In short:

  • LLM’s can expand general concepts and write language about what is generally well known based on its training data.
  • Try to ask it a particular fact, though, and it’s probably going to make stuff up, whether that’s about a person or a concept – you need to fact check it elsewhere.
  • It can’t do math!

But what it can do is teach you or show you how to do the math, the coding, or whatever thing you wish it would do for you. And this gets into one of my favorite use cases for it.

3. You can get an LLM to teach you how to use new tools, solve problems, and lower the barrier to entry (and friction) on using new tools, languages, and software.

One of the first things I did was ask ChatGPT to help me write a script. In fact, that’s what I did to expedite the process of finding tweets where I had used an image in order to get a screenshot to embed on my blog, rather than embedding the tweet.

It’s now so easy to generate code for scripts, regardless of which language you have previous experience with. I used to write all of my code as bash scripts, because that’s the format I was most familiar with. But ChatGPT likes to do things as Python scripts, so I asked it simple questions like “how do I call a python script from the command line” after I asked it to write a script and it generated a python script. Sure, you could search in a search engine or Stack Overflow for similar questions and get the same information. But one nice thing is that if you have it generate a script and then ask it step by step how to run a script, it gives you step by step instructions in context of what you were doing. So instead of saying “to run a script, type `python script.py’”, using placeholder names, it’ll say “to run the script, use ‘python actual-name-of-the-script-it-built-you.py’ “ and you can click the button to copy that, paste it in, and hit enter. It saves a lot of time for figuring out how to take placeholder information (which you would get from a traditional search engine result or Stack Overflow, where people are fond of things like saying FOOBAR and you have no idea if that means something or is meant to be a placeholder). Careful observers will notice that the latest scripts I’ve added to my Open Humans Data Tools repository (which is packed with a bunch of scripts to help work with big datasets!) are now in Python rather than bash; such as when I was adding new scripts for fellow researchers looking to check for updates in big datasets (such as the OpenAPS Data Commons). This is because I used GPT to help with those scripts!

It’s really easy now to go from an idea to a script. If you’re able to describe it logically, you can ask it to write a script, tell you how to run it, and help you debug it. Sometimes you can start by asking it a question, such as “Is it possible to do Y?” and it describes a method. You need to test the method or check for it elsewhere, but things like uploading a list of DOIs to Mendeley to save me hundreds of clicks? I didn’t realize Mendeley had an API or that I could write a script that would do that! ChatGPT helped me write the script, figure out how to create a developer account and app access information for Mendeley, and debug along the way so I ended up within an hour and a half of having a tool that easily saved me 3 hours on the very first project that I used it with.

I’m gushing about this because there’s probably a lot of ideas you have that you immediately throw out as being too hard, or you don’t know how to do it. It takes time, but I’m learning to remember to think “I should ask the LLM this” and ask it questions such as:

  • Is it possible to do X?
  • Write a script to do X.
  • I have X data. Pretend I am someone who doesn’t know how to use Y software and explain how I should do Z.

Another thing I’ve done frequently is ask it to help me quickly write a complex formula to use in a spreadsheet. Such as “write a formula that can be used in Google Sheets to take an average of the values in M3:M84 if they are greater than zero”.

It gives me the formula, and also describes it, and in some cases, gives alternative options.

Other things I’ve done with spreadsheets include:

  • Ask it to write a conditional formatting custom formula, then give me instructions for expanding the conditional formatting to apply to a certain cell range.
  • Asking it to check if a cell is filled with a particular value and then repeating the value in the new cell, in order to create new data series to use in particular charts and graphs I wanted to create from my data.
  • Help me transform my data so I could generate a box and whisker plot.
  • Ask it for other visuals that might be effective ways to illustrate and visualize the same dataset.
  • Explain the difference between two similar formulas (e.g. COUNT and COUNTA or when to use IF and IFS).

This has been incredibly helpful especially with some of my self-tracked datasets (particularly around thyroid-related symptom data) where I’m still trying to figure out the relationship between thyroid levels, thyroid antibody levels, and symptom data (and things like menstrual cycle timing). I’ve used it for creating the formulas and solutions I’ve talked about in projects such as the one where I created a “today” line that dynamically updates in a chart.

It’s also helped me get past the friction of setting up new tools. Case in point, Jupyter notebooks. I’ve used them in the web browser version before, but often had issues running the notebooks people gave me. I debugged and did all kinds of troubleshooting, but have not for years been able to get it successfully installed locally on (multiple of) my computers. I had finally given up on effectively using notebooks and definitely given up on running it locally on my machine.

However, I decided to see if I could get ChatGPT to coax me through the install process.

I told it:

“I have this table with data. Pretend I am someone who has never used R before. Tell me, step by step, how to use a Jupyter notebook to generate a box and whisker plot using this data”

(and I pasted my data that I had copied from a spreadsheet, then hit enter).

It outlined exactly what I needed to do, saying to install Jupyter Notebook locally if I hadn’t, gave me code to do that, installing the R kernel, told me how to do that, then how to start a notebook all the way down to what code to put in the notebook, the data transformed that I could copy/paste, and all the code that generated the plot.

However, remember I have never been able to successfully get Jupyter Notebooks running! For years! I was stuck on step 2, installing R. I said:

“Step 2, explain to me how I enter those commands in R? Do I do this in Terminal?”

It said “Oh apologies, no, you run those commands elsewhere, preferably in Rstudio. Here is how to download RStudio and run the commands”.

So, like humans often do, it glossed over a crucial step. But it went back and explained it to me and kept giving more detailed instructions and helping me debug various errors. After 5-6 more troubleshooting steps, it worked! And I was able to open Jupyter Notebooks locally and get it working!

All along, most of the tutorials I had been reading had skipped or glossed over that I needed to do something with R, and where that was. Probably because most people writing the tutorials are already data scientists who have worked with R and RStudio etc, so they didn’t know those dependencies were baked in! Using ChatGPT helped me be able to put in every error message or every place I got stuck, and it coached me through each spot (with no judgment or impatience). It was great!

I was then able to continue with the other steps of getting my data transformed, into the notebook, running the code, and generating my first ever box and whisker plot with R!

A box and whisker plot, illustrated simply to show that I used R and Jupyter finally successfully!

This is where I really saw the power of these tools, reducing the friction of trying something new (a tool, a piece of software, a new method, a new language, etc.) and helping you troubleshoot patiently step by step.

Does it sometimes skip steps or give you solutions that don’t work? Yes. But it’s still a LOT faster than manually debugging, trying to find someone to help, or spending hours in a search engine or Stack Overflow trying to translate generic code/advice/solutions into something that works on your setup. The beauty of these tools is you can simply paste in the error message and it goes “oh, sorry, try this to solve that error”.

Because the barrier to entry is so low (compared to before), I’ve also asked it to help me with other project ideas where I previously didn’t want to spend the time needed to learn new software and languages and all the nuances of getting from start to end of a project.

Such as, building an iOS app by myself.

I have a ton of projects where I want to temporarily track certain types of data for a short period of time. My fall back is usually a spreadsheet on my phone, but it’s not always easy to quickly enter data on a spreadsheet on your phone, even if you set up a template with a drop down menu like I’ve done in the past (for my DIY macronutrient tool, for example). For example, I want to see if there’s a correlation in my blood pressure at different times and patterns of inflammation in my eyelid and heart rate symptoms (which are symptoms, for me, of thyroid antibodies being out of range, due to Graves’ disease). That means I need to track my symptom data, but also now some blood pressure data. I want to be able to put these datasets together easily, which I can, but the hardest part (so to speak) is finding a way that I am willing to record my blood pressure data. I don’t want to use an existing BP tracking app, and I don’t want a connected BP monitor, and I don’t want to use Apple Health. (Yes, I’m picky!)

I decided to ask ChatGPT to help me accomplish this. I told it:

“You’re an AI programming assistant. Help me write a basic iOS app using Swift UI. The goal is a simple blood pressure tracking app. I want the user interface to default to the data entry screen where there should be three boxes to take the systolic, diastolic blood pressure numbers and also the pulse. There should also be selection boxes to indicate whether the BP was taken sitting up or laying down. Also, enable the selection of a section of symptom check boxes that include “HR feeling” and “Eyes”. Once entered on this screen, the data should save to a google spreadsheet.” 

This is a completely custom, DIY, n of 1 app. I don’t care about it working for anyone else, I simply want to be able to enter my blood pressure, pulse, whether I’m sitting or laying down, and the two specific, unique to me symptoms I’m trying to analyze alongside the BP data.

And it helped me build this! It taught me how to set up a new SwiftUI project in XCode, gave me code for the user interface, how to set up an API with Google Sheets, write code to save the data to Sheets, and get the app to run.

(I am still debugging the connection to Google Sheets, so in the interim I changed my mind and had it create another screen to display the stored data then enable it to email me a CSV file, because it’s so easy to write scripts or formulas to take data from two sources and append it together!)

Is it fancy? No. Am I going to try to distribute it? No. It’s meeting a custom need to enable me to collect specific data super easily over a short period of time in a way that my previous tools did not enable.

Here’s a preview of my custom app running in a simulator phone:

Simulator iphone with a basic iOS app that intakes BP, pulse, buttons for indicating whether BP was taken sitting or laying down; and toggles for key symptoms (in my case HR feeling or eyes), and a purple save button.

I did this in a few hours, rather than taking days or weeks. And now, the barrier to entry to creating more custom iOS is reduced, because now I’m more comfortable working with XCode and the file structures and what it takes to build and deploy an app! Sure, again, I could have learned to do this in other ways, but the learning curve is drastically shortened and it takes away most of the ‘getting started’ friction.

That’s the theme across all of these projects:

  • Barriers to entry are lower and it’s easier to get started
  • It’s easier to try things, even if they flop
  • There’s a quicker learning curve on new tools, technologies and languages
  • You get customized support and troubleshooting without having to translate through as many generic placeholders

PS – speaking of iOS apps, based on building this one simple app I had the confidence to try building a really complex, novel app that has never existed in the world before! It’s for people with exocrine pancreatic insufficiency like me who want to log pancreatic enzyme replacement therapy (PERT) dosing and improve their outcomes – check out PERT Pilot and how I built it here.

4. Notes about what these tools cost

I found ChatGPT useful for writing projects in terms of getting started, even though the content wasn’t that great (on GPT-3.5, too). Then they came out with GPT-4 and made a ChatGPT Pro option for $20/month. I didn’t think it was worth it and resisted it. Then I finally decided to try it, because some of the more sophisticated use cases I wanted to use it for required a longer context window, and in addition to a better model it also gave you a longer context window. I paid the first $20 assuming I’d want to cancel it by the end of the month.

Nope.

The $20 has been worth it on every single project that I’ve used it for. I’ve easily saved 5x that on most projects in terms of reducing the energy needed to start a project, whether it was writing or developing code. It has saved 10x that in time cost recouped from debugging new code and tools.

GPT-4 does have caps, though, so even with the $20/month, you can only do 25 messages every 3 hours. I try to be cognizant of which projects I default to using GPT-3.5 on (unlimited) versus saving the more sophisticated projects for my GPT-4 quota.

For example, I saw a new tool someone had built called “AutoResearcher”, downloaded it, and tried to use it. I ran into a bug and pasted the error into GPT-3.5 and got help figuring out where the problem was. Then I decided I wanted to add a feature to output to a text file, and it helped me quickly edit the code to do that, and I PR’ed it back in and it was accepted (woohoo) and now everyone using that tool can use that feature. That was pretty simple and I was able to use GPT-3.5 for that. But sometimes, when I need a larger context window for a more sophisticated or content-heavy project, I start with GPT-4. When I run into the cap, it tells me when my next window opens up (3 hours after I started using it), and I usually have an hour or two until then. I can open a new chat on GPT-3.5 (without the same context) and try to do things there; switch to another project; or come back at the time it says to continue using GPT-4 on that context/setup.

Why the limit? Because it’s a more expensive model. So you have a tradeoff between paying more and having a limit on how much you can use it, because of the cost to the company.

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TLDR:

Most important note: LLMs don’t “think” or “know” things the way humans do. They output language they predict you want to see, based on its training and the inputs you give it. It’s like the autocomplete of a sentence in your email, but more words on a wider range of topics!

Also, the LLM can’t do math. But they can write code. Including code to do math.

(Some, but not all, LLMs have access to the internet to look up or incorporate facts; make sure you know which LLM you are using and whether it has this feature or not.)

Ways to get started:

    1. The most frequent way I use these AI tools is for getting started on a project, especially those related to writing.
      • Ask it to help you expand on notes; write summaries of existing content; or write sections of content based on instructions you give it
    2.  It can also help analyze data (caution alert!) if you understand the limitations of the LLM.
      • The most effective way to work with data is to have it tell you how to run things in analytical software, whether that’s how to use R or a spreadsheet or other software for data analysis. Remember the LLM can’t do math, but it can write code so you can then do the math!
    3.  You can get an LLM to teach you how to use new tools, solve problems, and lower the barrier to entry (and friction) on using new tools, languages, and software.
      • Build a new habit of asking it “Can I do X” or “Is it possible to do Y” and when it says it’s possible, give it a try! Tell it to give you step-by-step instructions. Tell it where you get stuck. Give it your error messages or where you get lost and have it coach you through the process. 

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What’s been your favorite way to use an LLM? I’d love to know other ways I should be using them, so please drop a comment with your favorite projects/ways of using them!

Personally, the latest project that I built with an LLM has been PERT Pilot!

How I use LLMs (like ChatGPT) and tips for getting started

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!

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.

How to Find the Slope of the Trend Line in A Graph With Google Sheets

by Dana Lewis

I’ve been using Google Sheets for tracking and illustrating data for a number of reasons, such as tracking macronutrient and enzyme consumption patterns to help me understand my experiences with exocrine pancreatic insufficiency (EPI). It took me a while to figure out there was an easy way to display slope, though, to quantify what the trendline was.

Once you have a chart with your data, you can go into the “Customize” tab on the right and scroll down. Under “Series”, you can select which series you want, then scroll down and click “Trendline” to make the trendline appear. The customize menu then expands with trendline options.

Example of the default options for displaying a trendline

I had never noticed this before, but “Label” is set to default to “Custom”. This creates a label that defaults to “Trendline __YourSeriesName___”. In the example I’m showing here, I have series A labeled as “Var A”, so if I turn the Trendline on, it defaults to adding the “Custom” label of Trendline Var A.

But you can change this!

Click the dropdown where it says “Custom” and select “Use Equation”.

Example for trendline showing the label to 'use equation' option

Now it will show the label as the y=mx+b equation, so you can find out the slope (m) of your trendline.

In my example this means the slope of the Var A green line is 0.267.

You can modify this name, though, and get the best of both worlds. Click on the equation in the legend, and you will get an editable text box. I like to put the series name (e.g., Var A) in front of the equation so I can more easily see at a glance which series trend line it is explaining:

Example showing the custom text label after 'use equation' is selected to then edit and add back the series name along with the numeric formula

In my particular case, I want a quick glance of the slope, so I modify mine to read (Var A) 0.267 and (Var B) 0.061.

Example of trendline now showing the numeric equation and the series name for easier understanding of the graph

The only downside to this is the custom names will not automatically update. So if your brain can handle seeing the full mx+B equation, it might be better to leave it with the default equation as the trendline label name without modifying it at all, so it hopefully updates if you update the data on your graph. Otherwise, you’ll want to make a mental note to come back and update this manually by re-toggling the variable to equation and then editing it again to show the updated slope.

Two New Children’s Books – And How I Illustrated Them Without Being An Illustrator

by Dana Lewis

I wrote two new books! You can find “Cooper’s Crutches” and “Chloe’s Cookies” on Amazon in paperback and Kindle formats.

Two children's books lay on the carpet: Cooper's Crutches and Chloe's Cookies, both written by Dana M. Lewis

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One of these books I wrote years ago, about a month or so after I broke my ankle, inspired by the initial reactions from one of my nephews about me being on crutches. This new book is called Cooper’s Crutches.

I let it sit for several years, though, because I didn’t have illustrations for it. I’ve used a different illustrator or artist for each of my books so far.

A few weeks ago, though, I started thinking about experimenting with AI-driven illustrations for various projects, including wondering whether I could illustrate a children’s book or other projects with it.

The answer is: not yet. It’s hard to create a character who persists throughout image generation for enough scenes that can fit a two-dozen page storyline, although it would probably work for one or two images! (Especially if you managed to AI-illustrate a character that you could then place in various AI-illustrated scenes. The challenge is also having different poses for the same character, to illustrate a story.)

It then occurred to me to search around and I stumbled across a library of free, open source illustrations. Woohoo! Maybe those would work. Actually, I couldn’t even download that one due to a bug in their site, so I started searching (now that I knew to look for it) and found several other sets of illustrations. I even found a site called Blush that had a series of illustrations by various artists, and a web interface (GUI) that allowed you to modify images slightly then download them.

It’s like paper dolls, but digital – you can adjust the coloring of the hair, hair style, accessories, etc to modify the illustrated character.

I gave it a try, building some illustrations and downloading them. I then did some DIY-ing again in PowerPoint to modify them to help illustrate the full story in my children’s book. I printed a proof copy, but the versions I had downloaded for free were too low resolution and were fuzzy. However, the idea as a whole had worked great! I signed up for a free trial of the “Pro” version of Blush which enabled me to download both high-resolution PNG (image) files as well as SVG files.

Having SVG files theoretically would enable me to further modify and customize these, but as a non-illustrator even though I could load them in Figma and modify them, I still struggled to export them as high-enough resolution to work for printing in a book. I gave up and went back to DIY-ing the modifications in PowerPoint. They’re not perfect, but for the use case of my books (for a very small, niche audience), I doubt they care that they’re not perfect.

Here’s a selection of a few of the pages (not in order) in Cooper’s Crutches:

Excerpt images from Cooper's Crutches by Dana M. Lewis

At the same time that I started playing with these illustrations, I wondered whether I had any more ideas for books that I could illustrate at the same time with the same methods. I had had Cooper’s book written and waiting to illustrate; I now had a method to illustrate, but I wasn’t sure what story to illustrate.

But like all of my children’s books, inspiration again struck based on a situation and conversation I had with one of my nieces. She’s newly lactose intolerant and is taking lactase any time she has milk, like with milk and cookies for a bedtime snack. Lactase is an enzyme…and I’ve been taking enzymes of another sort this year, for exocrine pancreatic insufficiency.

Thus the next book, Chloe’s Cookies, was created!

Here’s a selection of a few of the pages (not in order) in the book:

Excerpt images from Chloe's Cookies, by Dana M. Lewis

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Both Cooper’s Crutches and Chloe’s Cookies are illustrated with illustrations from a variety of artists who make their work available on Blush, including: Veronica Iezzi; Susana Salas; Pau Barbaro; Ivan Mesaroš; Mariana Gonzalez Vega; Deivid Saenz; and Cezar Berje.

The neat thing about Blush is their license: you can use the illustrations in any way, including commercial products, and you can modify or combine it with other works (like I did, modifying the images and combining illustrations from various artists) however you like.

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I think I’ve likely maximized my use of Blush between these two books; unless other collections get uploaded in the future. But if you need a handful of illustrations that you can customize, definitely check it out!

And if you have ideas for other cool illustration libraries that I could use for future books, please let me know! (Or if you’re an artist who would like to contribute to one of my future books. :) )

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TLDR:

I have two new children’s books, and you can find “Cooper’s Crutches” and “Chloe’s Cookies” on Amazon in paperback and Kindle formats.

Illustrating Children's Books without being an illustrator, plus introducting two new children's books by Dana M. Lewis

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

by Dana Lewis

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

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

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

That’s an average of 8.98 pills per day!

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

Speaking of better outcomes – is PERT effective?

For me, yes!

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

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

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

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

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

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

This is pretty meaningful to think about.

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

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

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

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

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

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

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

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

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

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

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

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