diabetes

How Medical Research Literature Evolves Over Time Like A Game of Telephone

by Dana Lewis

Have you ever searched for or through medical research on a specific topic, only to find different studies saying seemingly contradictory things? Or you find something that doesn’t seem to make sense?

You may experience this, whether you’re a doctor, a researcher, or a patient.

I have found it helpful to consider that medical literature is like a game of telephone, where a fact or statement is passed from one research paper to another, which means that sometimes it is slowly (or quickly!) changing along the way. Sometimes this means an error has been introduced, or replicated.

A Game of Telephone in Research Citations

Imagine a research study from 2016 that makes a statement based on the best available data at the time. Over the next few years, other papers cite that original study, repeating the statement. Some authors might slightly rephrase it, adding their own interpretations. By 2019, newer research has emerged that contradicts the original statement. Some researchers start citing this new, corrected information, while others continue citing the outdated statement because they either haven’t updated their knowledge or are relying on older sources, especially because they see other papers pointing to these older sources and find it easiest to point to them, too. It’s not necessarily made clear that this outdated statement is now known to be incorrect. Sometimes that becomes obvious in the literature and field of study, and sometimes it’s not made explicit that the prior statement is ‘incorrect’. (And if it is incorrect, it doesn’t become known as incorrect until later – at the time it’s made, it’s considered to be correct.) 

By 2022, both the correct and incorrect statements appear in the literature. Eventually, a majority of researchers transition to citing the updated, accurate information—but the outdated statement never fully disappears. A handful of papers continue to reference the original incorrect fact, whether due to oversight, habit (of using older sources and repeating citations for simple statements), or a reluctance to accept new findings.

The gif below illustrates this concept, showing how incorrect and correct statements coexist over time. It also highlights how researchers may rely on citations from previous papers without always checking whether the original information was correct in the first place.

Animated gif illustrating how citations branch off and even if new statements are introduced to the literature, the previous statement can continue to appear over time.

This is not necessarily a criticism of researchers/authors of research publications (of which I am one!), but an acknowledgement of the situation that results from these processes. Once you’ve written a paper and cited a basic fact (let’s imagine you wrote this paper in 2017 and cite the 2016 paper and fact), it’s easy to keep using this citation over time. Imagine it’s 2023 and you’re writing a paper on the same topic area, it’s very easy to drop the same citation from 2016  in for the same basic fact, and you may not think to consider updating the citation or check if the fact is still the fact.

Why This Matters

Over time, a once-accepted “fact” may be corrected or revised, but older statements can still linger in the literature, continuing to influence new research. Understanding how this process works can help you critically evaluate medical research and recognize when a widely accepted statement might actually be outdated—or even incorrect.

If you’re looking into a medical topic, it’s important to pay attention not just to what different studies say, but also when they were published and how their key claims have evolved over time. If you notice a shift in the literature—where newer papers cite a different fact than older ones—it may indicate that scientific understanding has changed.

One useful strategy is to notice how frequently a particular statement appears in the literature over time.

Whenever I have a new diagnosis or a new topic to research on one of my chronic diseases, I find myself doing this.

I go and read a lot of abstracts and research papers about the topic; I generally observe patterns in terms of key things that everyone says, which establishes what the generally understood “facts” are, and also notice what is missing. (Usually, the question I’m asking is not addressed in the literature! But that’s another topic…)

I pay attention to the dates, observing when something is said in papers in the 1990s and whether it’s still being repeated in the 2020s era papers, or if/how it’s changed. In my head, I’m updating “this is what is generally known” and “this doesn’t seem to be answered in the literature (yet)” and “this is something that has changed over time” lists.

Re-Evaluating the Original ‘Fact’

In some cases, it turns out the original statement was never correct to begin with. This can happen when early research is based on small sample sizes, incomplete data, or incorrect assumptions. Sometimes that statement was correct, in context, but taken out of context immediately and this out of context use was never corrected. 

For example, a widely cited statement in medical literature once claimed that chronic pancreatitis is the most common cause of exocrine pancreatic insufficiency (EPI). This claim was repeated across numerous papers, reinforcing it as accepted knowledge. However, a closer examination of population data shows that while chronic pancreatitis is a known co-condition of EPI, it is far less common than diabetes—a condition that affects a much larger population and is also strongly associated with EPI. Despite this, many papers still repeat the outdated claim without checking the original data behind it.

(For a deeper dive into this example, you can read my previous post here. But TL;DR: even 80% of .03% is a smaller number than 10% of 10% of the overall population…so it is not plausible that CP is the biggest cause of EPI/PEI.)

Stay Curious

This realization can be really frustrating, because if you’re trying to do primary research to help you understand a topic or question, how do you know what the truth is? This is peer-reviewed research, but what this shows us is that the process of peer-review and publishing in a journal is not infallible. There can be errors. The process for updating errors can be messy, and it can be hard to clean up the literature over time. This makes it hard for us humans – whether in the role of patient or researcher or clinician – to sort things out.

But beyond a ‘woe is me, this is hard’ moment of frustration, I do find that this perspective of literature as a process of telephone makes me a better reader of the literature and forces me to think more critically about what I’m reading, and take papers in context of the broader landscape of literature and evolving knowledge base. It helps remove the strength I would otherwise be prone to assigning any one paper (and any one ‘fact’ or finding from a single paper), and encourages me to calibrate this against the broader knowledge base and the timeline of this knowledge base.

That can also be hard to deal with personally as a researcher/author, especially someone who tends to work in the gaps, establishing new findings and facts and introducing them to the literature. Some of my work also involves correcting errors in the literature, which I find from my outsider/patient perspective to be obvious because I’ve been able to use fresh eyes and evaluate at a systematic review level/high level view, without being as much in the weeds. That means my work, to disseminate new or corrected knowledge, is even more challenging. It’s also challenging personally as a patient, when I “just” want answers and for everything to already be studied, vetted, published, and widely known by everyone (including me and my clinician team).

But it’s usually not, and that’s just something I – and we – have to deal with. I’m curious as to whether we will eventually develop tools with AI to address this. Perhaps a mini systematic review tool that scrapes the literature and includes an analysis of how things have changed over time. This is done in systematic review or narrative reviews of the literature, when you read those types of papers, but those papers are based on researcher interests (and time and funding), and I often have so many questions that don’t have systematic reviews/narrative reviews covering them. Some I turn into papers myself (such as my paper on systematically reviewing the dosing guidelines and research on pancreatic enzyme replacement therapy for people with exocrine pancreatic insufficiency, known as EPI or PEI, or a systematic review on the prevalence of EPI in the general population or a systematic review on the prevalence of EPI in people with diabetes (Type 1 and Type 2)), but sometimes it’s just a personal question and it would be great to have a tool to help facilitate the process of seeing how information has changed over time. Maybe someone will eventually build that tool, or it’ll go on my list of things I might want to build, and I’ll build it myself like I have done with other types of research tools in the past, both without and with AI assistance. We’ll see!

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TL;DR: be cognizant of the fact that medical literature changes over time, and keep this in mind when reading a single paper. Sometimes there are competing “facts” or beliefs or statements in the literature, and sometimes you can identify how it evolves over time, so that you can better assess the accuracy of research findings and avoid relying on outdated or incorrect information.

Whether you’re a researcher, a clinician, or a patient doing research for yourself, this awareness can help you better navigate the scientific literature.

A screenshot from the animated gif showing how citation strings happen in the literature, branching off over time but often still resulting in a repetition of a fact that is later considered to be incorrect, thus both the correct and incorrect fact occur in the literature at the same time.

Assessing the Impact of Diabetes on Gastrointestinal Symptom Severity in Exocrine Pancreatic Insufficiency (EPI/PEI): A Diabetes Subgroup Analysis of EPI/PEI-SS Scores – Poster at #ADA2024

by Dana Lewis

Last year, I recognized that there was a need to improve the documentation of symptoms of exocrine pancreatic insufficiency (known as EPI or PEI). There is no standardized way to discuss symptoms with doctors, and this influences whether or not people get the right amount of enzymes (pancreatic enzyme replacement therapy; PERT) to treat EPI and eliminate symptoms completely. It can be done, but like insulin, it requires matching PERT to the amount of food you’re consuming. I also began observing that EPI is underscreened and underdiagnosed, whether that’s in the general population or in people with diabetes. I thought that if we could create a list of common EPI symptoms and a standardized scale to rate them, this might help address some of these challenges.

I developed this scale to address these needs. It is called the “Exocrine Pancreatic Insufficiency Symptom Score” or “EPI/PEI-SS” for short.

I had a handful of people with and without EPI help me test the scale last year, and then I opened up a survey to the entire world and asked people to share their experiences with GI-related symptoms. I specifically sought people with EPI diagnoses as well as people who don’t have EPI, so that we could compare the symptom burden and experiences to people without EPI. (Thank you to everyone who contributed their data to this survey!)

After the first three weeks, I started analyzing the first set of data. While doing that, I realized that (both because of my network of people with diabetes and because I also posted in at least one diabetes-specific group), I had a large sub-group of people with diabetes who had contributed to the survey, and I was able to do a full subgroup analyses to assess whether having diabetes seemed to correlate with a different symptom experience of EPI or not.

Here’s what I found, and what my poster is about (you can view my poster as a PDF here), presented at ADA Scientific Sessions 2024 (#ADA2024):

1985-LB at #ADA2024, “Assessing the Impact of Diabetes on Gastrointestinal Symptom Severity in Exocrine Pancreatic Insufficiency (EPI/PEI): A Diabetes Subgroup Analysis of EPI/PEI-SS Scores”

Exocrine pancreatic insufficiency has a high symptom burden and is present in as many as 3 of 10 people with diabetes. (See my systematic review from last year here). To help improve conversations about symptoms of EPI, which can then be used to improve screening, diagnosis, and treatment success with EPI, I created the Exocrine Pancreatic Insufficiency Symptom Score (EPI/PEI-SS), which consists of 15 individual symptoms that people separately rate the frequency (0-5) and severity (0-3) for which they experience those symptoms, if at all. The frequency and severity get multiplied for an individual symptom score (0-15 possible) and these get added up for a total EPI/PEI-SS score (0-225 possible, because 15 symptoms times 15 possible points per symptom is 225).

I conducted a real-world study of the EPI/PEI-SS in the general population to assess the gastrointestinal symptom burden in individuals with (n=155) and without (n=169) EPI. Because there was a large cohort of PWD within these groups, I separately analyzed them to evaluate whether diabetes contributes to a difference in EPI/PEI-SS score.

Methods:

I calculated EPI/PEI-SS scores for all survey participants. Previously, I had analyzed the differences of people with and without EPI overall. For this sub-analysis, I analyzed and compared between PWD (n=118 total), with EPI (T1D: n=14; T2D: n=20) or without EPI (T1D: n=78; T2D: n=6), and people without diabetes (n=206 total) with and without EPI.

I also looked at sub-groups within the non-EPI cohorts and broke them into two groups to see whether other GI conditions contributed to a higher EPI/PEI-SS score and whether we could distinguish EPI from other GI and non-GI conditions.

Results:

People with EPI have a much higher symptom burden than people without EPI. This can be assessed by looking at the statistically significant higher mean EPI/PEI-SS score as well as the average number of symptoms; the average severity score of individual symptoms; and the average frequency score of individual symptoms.

This remains true irrespective of diabetes. In other words, diabetes does not appear to influence any of these metrics.

People with diabetes with EPI had statistically significant higher mean EPI/PEI-SS scores (102.62 out of 225, SD: 52.46) than did people with diabetes without EPI (33.64, SD: 30.38), irrespective of presence of other GI conditions (all group comparisons p<0.001). As you can see below, that is the same pattern we see in people without diabetes. And the stats confirm what you can see: there is no significant difference overall or in any of the subgroups between people with and without diabetes.

Box plot showing EPI/PEI-SS scores for people with and without diabetes, and with and without EPI or other GI conditions. The scores are higher in people with EPI regardless of whether they have diabetes. The plot makes it clear that the scores are distinct between the groups with and without EPI, even when the people without EPI have other GI conditions. This suggests the EPI/PEI-SS can be useful in distinguishing between EPI and other conditions that may cause GI symptoms, and that the EPI/PEI-SS could be a useful screening tool to help identify people who need screening for EPI.

T1D and T2D subgroups were similar
(but because the T2D cohort is small, I did not break them out separately in this graph).

For example, people with diabetes with EPI had an average of 12.59 (out of 15) symptoms, with an average frequency score of 3.06 and average severity score of 1.79, and an average individual symptom score of 5.48. This is a pretty clear contrast to people with diabetes without EPI who had had an average of 7.36 symptoms, with an average frequency score of 1.4 and average severity score of 0.8, and an average individual symptom score of 1.12. All comparisons are statistically significant (p<0.001).

A table comparing the average number of symptoms, frequency, severity, and individual symptom scores between people with diabetes with and without exocrine pancreatic insufficiency (EPI). People with EPI have more symptoms and higher frequency and severity than without EPI: regardless of diabetes.

Conclusion 

  • EPI has a high symptom burden, irrespective of diabetes.
  • High scores using the EPI/PEI-SS among people with diabetes can distinguish between EPI and other GI conditions.
  • The EPI/PEI-SS should be further studied as a possible screening method for EPI and assessed as a tool to aid people with EPI in tracking changes to EPI symptoms over time based on PERT titration.

What does this mean if you are a healthcare provider? What actionable information does this give you?

If you’re a healthcare provider, you should be aware that people with diabetes may be more likely to have EPI – rather than celiac or gastroparesis (source) – if they mention having GI symptoms. This means you should incorporate fecal elastase screening into your care plans to help further evaluate GI-related symptoms.

If you want to further improve your pre-test probability of the elastase testing, you can use the EPI/PEI-SS with your patients to assess the severity and frequency of their GI-related symptoms. I will explain the cutoff and AUC numbers we calculated, but first understand the caveat that these were calculated in the initial real-world study that included people with EPI who are already treating with PERT; thus these numbers might change a little when we repeat this study and evaluate it in people with untreated EPI. (However, I actually predict the mean score to go up in an undiagnosed population, because scores should go down with treatment.) But that different population study may change these exact cutoff and sensitivity specificity numbers, which is why I’m giving this caveat. That being said: the AUC was 0.85 which means a higher EPI/PEI-SS is pretty good for differentiating between EPI and not having EPI. (In the diabetes sub-population specifically, I calculated a suggested cutoff of 59 (out of 225) with a sensitivity of 0.81 and specificity of 0.75. This means we estimate that if people are bringing up GI symptoms to you and you have them take the EPI/PEI-SS and their score is greater than or equal to 59, you would expect that out of 100 people that 81 with EPI would be identified (and 75 of 100 people without EPI would also correctly be identified via scores lower than 59). That doesn’t mean that people with EPI can’t have a lower score; or that people with a higher score do have EPI; but it does mean that the chances of having fecal elastase <=200 ug/g is a lot more likely in those with higher EPI/PEI-SS scores.

In addition to the cutoff score, there is a notable difference in people with diabetes and EPI compared to people with diabetes without EPI in their top individual symptom scores (representing symptom burden based on frequency and severity). For example, the top 3 symptoms of those with EPI and diabetes include avoiding certain food/groups; urgent bowel movements; and avoiding eating large meals. People without EPI and diabetes also score “Avoid certain food/groups” as their top score, but the score is markedly different: the mean score of 8.94 for people with EPI as compared to 3.49 for people without EPI. In fact, the mean score on the lowest individual symptom is higher for people with EPI than the highest individual symptom score for people without EPI.

QR code for EPI/PEI-SS - takes you to https://bit.ly/EPI-PEI-SS-WebHow do you have people take the EPI/PEI-SS? You can pull this link up (https://bit.ly/EPI-PEI-SS-Web), give this link to them and ask them to take it on their phone, or save this QR code and give it to them to take later. The link (and the QR code) go to a free web-based version of the EPI/PEI-SS that will calculate the total EPI/PEI-SS score, and you can use it for shared decision making processes about whether this person would benefit from a fecal elastase test or other follow up screening for EPI. Note that the EPI/PEI-SS does not collect any identifiable information and is fully anonymous.

(Bonus: people who use this tool can opt to contribute their anonymized symptom and score data for an ongoing observational study.)

If you have feedback about whether the EPI/PEI-SS was helpful – or not – in your care of people with diabetes; or if you want to discuss collaborating on some prospective studies to evaluate EPI/PEI-SS in comparison to fecal elastase screening, please reach out anytime to Dana@OpenAPS.org. 

What does this mean if you are a patient (person with diabetes)? What actionable information does this give you?

If you don’t have GI symptoms that bother you, you don’t necessarily need to take action. (Just put a note in your brain that EPI is more likely than celiac or gastroparesis in people with diabetes so if you or a friend with diabetes have GI symptoms in the future, you can make sure you are assessed for EPI.) You can also choose to take the EPI/PEI-SS regardless, and also opt in to donate your data.

If you do have GI symptoms that are annoying, you may want to take the EPI/PEI-SS to help you evaluate the frequency and severity of your GI symptoms. You can take it for free and anonymously – no identifiable information is needed to access the tool. It will generate the EPI/PEI-SS score for you.

Based on the score, you may want to ask your doctor (which could be the doctor that treats your diabetes, or a primary/general care provider, or a gastroenterologist – whoever you seek routine care from or have an appointment from next) about your symptoms; share the EPI/PEI-SS score; and explain that you think you may warrant screening for EPI.

(You can also choose to contribute your anonymous symptom data to a research dataset, to help us improve the EPI/PEI-SS and help us figure out how to help improve screening and diagnosis and treatment of EPI. Remember, this tool will not ask you for any identifying information. This is 100% optional and you can opt out of doing so if you do not prefer to contribute to research, while still using the tool.)

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You can see a pre-print version of the diabetes sub-study here or pre-print of the general population data here.

If you’re looking for more personal experiences about living with EPI, check out DIYPS.org/EPI, and also for people with EPI looking to improve their dosing with pancreatic enzyme replacement therapy – you may want to check out PERT Pilot (a free iOS app to record enzyme dosing).

Researchers & clinicians, if you’re interested in collaborating on studies in EPI (in diabetes, or more broadly on EPI), whether specifically on EPI/PEI-SS or broader EPI topics, please reach out! My email is Dana@OpenAPS.org

Being a raccoon and living with chronic disease

by Dana Lewis

Being a raccoon loading a dishwasher is a really useful analogy for figuring out: what you want to spend a lot of effort and precision on, where you can lower your effort and precision and still obtain reasonable outcomes, or where you can allow someone else to step in and help you when you don’t care how as long as the job gets done.

Huh? Raccoons?!

A few years ago Scott and I spotted a meme/joke going around that in every relationship there is a person who loads the dishwasher precisely (usually “stacks the dishwasher like a Scandinavian architect”) and one who loads the dishwasher like a “raccoon on meth” or a “rabid raccoon” or similar.

Our relationship and personality with dishwasher loading isn’t as opposite on the spectrum as that analogy suggests. However, Scott has a strong preference for how the dishwasher should be loaded, along with a high level of precision in achieving it. I have a high level of precision, but very low preference for how it gets done. Thus, we have evolved our strategy where I put things in and he re-arranges them. If I put things in with a high amount of effort and a high level of precision? He would rearrange them ANYWAY. So there is no point in me also spending high levels of effort to apply a first style of precision when that work gets undone. It is more efficient for me to put things in, and then he re-organizes as he sees fit.

Thus, I’ve embraced being the ‘raccoon’ that loads the dishwasher in this house. (Not quite as dramatic as some!)

A ChatGPT-created illustration of a cute raccoon happily loading the dishwasher, which looks fine but not precisely loaded.This came to mind because he went on a work trip, and I stuck things in the dishwasher for 2 days, and jokingly texted him to “come home and do the dishes that the raccoon left”. He came home well after dinner that night, and the next day texted when he opened the dishwasher for the first time that he “opened the raccoon cage for the first time”. (LOL).

Over the years, we’ve found other household tasks and chores where one of us has strong preferences about the way things should be done and the other person has less strong preferences. Similarly, there are some things that feel high-effort (and not worth it) for one of us but not the other. Over time, we’ve sorted tasks so things that feel high-effort can be done by the person for which it doesn’t feel high-effort, and depending on the preference level determines ‘how’ it gets done. But usually, the person who does it (because it’s low-effort) gets to apply their preferences, unless it’s a really weak preference and the preference of the non-doer doesn’t require additional effort.

Here are some examples of tasks and how our effort/preference works out. You can look at this and see that Scott ends up doing the dishwasher organization (after I load it like a raccoon) before starting the dishwasher and also has stronger preferences about laundry than I do. On the flip side, I seem to find it easier with routines for staying on top of household supply management including buying/re-ordering and acquiring and putting those away where we have them ready to go, because they’re not on a clear scheduled cadence. Ditto for managing the cats’ health via flea/tick medication schedules, scheduling and taking them to the vet, signing them up for cat camp when we travel, coordinating with the human involved in their beloved cat camp, etc. We end up doing a mix of overall work, split between the two of us.

A four-quadrant grid. Across the top it says "Effort" with low effort on the left and high effort on the right. Along the side it says "preference" with weak preference on the bottom and strong preference at the top. The implication is you can have a mix of preference and how much work certain chores are. Usually the person in the top left quadrant for a particular chore - representing easy or lower effort anad stronger preference - ends up doing that chore. For me that's household supply ordering; managing cat vet appts, etc. where due to Scott's much stronger preference his include the dishwasher, laundry, etc.
Could each of us do those tasks? Sure, and sometimes we do. But we don’t have to each do all of them, all the time, and we generally have a split list of who does which type of things as the primary doer.

Raccoons and burnout with chronic diseases

I have now lived with type 1 diabetes for almost 22 years. When I met Scott, I had been living with diabetes for 11 years. When he asked on one of our early dates what he could do to help, my answer was: “…nothing?” I’m an adult, and I’ve successfully managed my diabetes solo for decades.

Obviously, we ended up finding various ways for him to help, starting with iterating together on technological solutions for remote monitoring (DIYPS) to eventually closing the loop with an automated insulin delivery system (OpenAPS). But for the longest time, I still did all the physical tasks of ordering supplies, physically moving them around, opening them, managing them, etc. both at a 3-month-supply order level and also every 3 days with refilling reservoirs and changing pump sites and sensors.

Most of the time, these decades-long routines are literally routines and I do them without thought, the same way I put on my shoes before I leave the house. Yet when burnout is approaching – often from a combination of having five autoimmune diseases or having a lot of life going on while also juggling the ‘routine’ tasks that are voluminous – these can start to feel harder than they should.

Should, being the key word here.

Scott would offer to do something for me and I would say no, because I felt like I “should” do it because I normally can/am able to with minimal effort. However, the activation energy required (because of burnout or volume of other tasks) sometimes changes, and these minimal, low-effort tasks suddenly feel high-effort. Thus, it’s a good time to examine whether someone can – even in the short term and as a one-off – help.

It’s hard, though, to eradicate the “should”. I “should” be able to do X, I “should” be able to handle Y. But honestly? I should NOT have to deal with all the stuff and management of living with 5 autoimmune diseases and juggling them day in and day out. But I do have to deal with these and therefore do these things to stay in optimal health. “Should” is something that I catch myself thinking and now use that as a verbal flag to say “hey, just because I CAN do this usually doesn’t mean I HAVE to do it right now, and maybe it’s ok to take a break from always doing X and let Scott do X or help me with Y.”

Some of these “I should do it” tasks have actually become tasks that I’ve handed off long-term to Scott, because they’re super low effort for him but they’re mildly annoying for me because I have roughly 247 other tasks to deal with (no, I didn’t count them: that would make it 248).

For example, one time I asked him to open my shipment with 3 months worth of pump supplies, and unbox them so I could put them away. He also carried them into the room where we store supplies and put them where they belonged. Tiny, but huge! Only 246 tasks left on my list. Now, I order supplies, and he unboxes and puts them away and manages the inventory rotation: putting the oldest boxes on top (that I draw from first) and newer ones on bottom. This goes for pump supplies, CGM supplies, and anything else mail order like that.

A similar four quadrant chart with the same axes as the other graph, with effort on top (low left; high right) and execution preference (weak bottom, strong top). Similar to chores, we look at how our preferences and how much work it feels like, relative to each other, to decide if there are any tasks I can ask Scott to take on related to chronic disease management (like opening boxes and rotating stock of supplies being lower effort for him than me, due to my overall volume of tasks being higher)

This isn’t always as straightforward, but there are a lot of things I have been doing for 20+ years and thus find very low effort once the supplies are in my hand, like changing my pump site and CGM. So I do those. (If I was incapacitated, I have no doubt Scott could do those if needed.) But there’s other stuff that’s low effort and low preference like the opening of boxes and arranging of supplies that I don’t have to do and Scott is happy to take on to lower my task list of 247 things so that I only have about 240 things left to do for routine management.

Can I do them? Sure. Should I do them? Well, again, I can but that doesn’t mean I have to if there’s someone who is volunteering to help.

And sometimes that help is really useful in breaking down tasks that are USUALLY low effort – like changing a pump site – but become high effort for psychological reasons. Sometimes I’ll say out loud that I need to change my pump site, but I don’t want to. Some of that might be burnout, some of that is the mental energy it takes to figure out where to put the next pump site (and remembering the last couple of placements from previous sites, so I rotate them), combined with the physical activation energy to get up from wherever I am and go pull out the supplies to do it. In these cases, divide and conquer works! Scott often is more than happy to go and pull out a pump site and reservoir and place it where it’s convenient for me when I do get up to go do something else. For me, I often do pump site changes (putting a new one on, but I keep the old one on for a few extra hours in case the new one works) after my shower, so he’ll grab a pump site and reservoir and set it on the bathroom counter. Barrier removed. Then I don’t have to get up now and do it, but I also won’t forget to do it because it’s there in flow with my other tasks to do after my shower.

A gif showing a similar four quadrant graph (effort across top, execution preference along the side), showing a task going from the top left (low effort usually, strong preference for how it is done) moving to the right (high effort and still high preference), then showing it being split into two halves, one of which becomes a Scott task because it's lower effort sub-tasks and the remaining part is still high preference for me but has lowered the effort it takes.

There are a lot of chronic disease-related tasks like this that when I’m starting to feel burnout from the sheer number of tasks, I can look for (or sometimes Scott can spot) opportunities) to break a task into multiple steps and do them at different times, or to have someone do the task portions they can do, like getting out supplies. That then lowers the overall effort required to do that task, or lowers the activation energy depending on the task. A lot of these are simple-ish tasks, like opening something, getting something out and moving it across the house to a key action spot (like the bathroom counter for after a shower), or putting things away when they no longer need to be out. The latter is the raccoon-style approach. A lot of times I’ll have the activation energy to start and do a task, but not complete (like breaking down supply boxes for recycling). I’ll set them aside to do later, or Scott will spot this ‘raccoon’ stash of tasks and tackle it when he has time/energy, usually faster than me getting around to do it because he’s not burdened with 240 other tasks like that. (He does of course have a larger pile of tasks than without this, but the magnitude of his task list is a lot smaller, because 5 autoimmune diseases vs 0.)

Be a friend to your friend who needs to be a raccoon some of the time

I am VERY lucky to have met & fallen in love & married someone who is so incredibly able and willing to help. I recognize not everyone is in this situation. But there may be some ways our friends and family who don’t live with us can help, too. I had a really fantastic example of this lately where someone who isn’t Scott stepped up and made my raccoon-life instantly better before I even got to the stage of being a raccoon about it.

I have a bunch of things going on currently, and my doctor recommended that I have an MRI done. I haven’t had an MRI in years and the last one was pre-pandemic. Nowadays, I am still masking in any indoor spaces including healthcare appointments, and I plan to mask for my MRI. But my go-to n95 mask has metal in the nose bridge, which means I need to find a safe alternative for my upcoming MRI.

I was busy trying to schedule appointments and hadn’t gotten to the stage of figuring out what I would wear as an alternative for my MRI. But I mentioned to a friend that I was going to have an MRI and she asked what mask I was going to wear, because she knows that I mask for healthcare appointments. I told her I hadn’t figured it out yet but needed to eventually figure it out.

She instantly sprang into action. She looked up options for MRI-safe masks and asked a local friend who uses a CAN99 mask without wire whether the friend had a spare for me to try. She also ordered a sample pack of another n95 mask style that uses adhesive to stick to the face (and thus doesn’t have a metal nose bridge piece). She ordered these, collected the CAN99 from the local friend, and then told me when they’d be here, which was well over a week before I would need it for the MRI and offered to bring them by my house so I had them as soon as possible.

Meanwhile, I was gobsmacked with relief and appreciation because I would have been a hot mess of a raccoon trying to get around to sorting that out days or a week after she had sorted a variety of options for me to try. Instead, she predicted my raccoon-ness or otherwise was being a really amazing friend and stepping up to take something off my plate so I had one less thing to deal with.

Yay for helpers. In this case, she knew exactly what was needed. But a lot of times, we have friends or family who want to help but don’t know how to or aren’t equipped with the knowledge of what would be helpful. Thus, it’s useful – when you have energy – to think through how you could break apart tasks and what you could offer up or ask as a task for someone else to do that would lower the burden for you.

That might be virtual tasks or physical tasks:

  • It might be coming over and taking a bunch of supplies out of boxes (or medicine) and splitting them up and helping put them in piles or all the places those things need to go
  • It could be researching safe places for you to eat, if you have food allergies or restrictions or things like celiac
  • It could be helping divvy up food into individual portions or whatever re-sizing you need for whatever purpose
  • It could be researching and brainstorming and identifying some safe options for group activities, e.g. finding places with outdoor dining or cool places to walk and hike that suits everyone’s abilities and interests

Sometimes it’s the physical burden that it’s helpful to lift; sometimes it’s the mental energy burden that is helpful to lift; sometimes a temporary relief in all the things we feel like we have to do ourselves is more important than the task itself.

If you have a chronic disease, it’s ok to be a raccoon. There is no SHOULD.

Part of the reason I really like the raccoon analogy is because now instead of being annoyed at throwing things in the dishwasher, because whether I exert energy or not Scott is going to re-load it his way anyway, I put the dishes in without much precision and giggle about being a raccoon.

The same goes for chronic disease related-tasks. Even for tasks where Scott is not involved, but I’m starting to feel annoyed at something I need to do, I find ways to raccoon it a little bit. I change my pump site but leave the supplies on the counter because I don’t HAVE to put those away at the same moment. I usually do, but I don’t HAVE to. And so I raccoon it a bit and put the supplies away later, because it doesn’t hurt anyone or anything (including me) for those not to get put away at the same time. And that provides a little bit of comedic relief to me and lightens the task of changing my pump site.

It also helps me move away from the SHOULD weighing heavily in my brain. I should be able to get all my pump site stuff out, change it, and throw away and put away the supplies when done. It shouldn’t be hard. No one else has this challenge occasionally (or so my brain tells me).

But the burden isn’t about that task alone. It’s one task in the list of 247 things I’m doing every day to take care of myself. And sometimes, my list GROWS. January 18, my list was about 212 things I needed to do. Beginning January 19, my list jumped up to 230. Last week, it grew again. I have noticed this pattern that when my list of things to do grows, some of the existing “easy” tasks that I’ve done for 20 years suddenly feel hard. Because it is hard to split my energy across more tasks and more things to focus on; it takes time to adapt. And so being a raccoon for some of those tasks, for some of the time, provides a helpful steam-valve to output some of the challenges I’m juggling of dealing with all the tasks, because those tasks 100% don’t have to be done in the same way as I might do during “calm” static times where my task list hasn’t expanded suddenly.

And it doesn’t matter what anyone else does or what they care about. Thus, remove the should. You should be able to do this, sure – if you weren’t juggling 246 other things. But you do have 246 things and that blows apart the “should”.

Free yourself of the “should” wherever possible, and be a raccoon wherever it helps.

How to Exercise When Exercise Is Harder Than Your Normal

by Dana Lewis

I’ve been spending a lot of time thinking lately about how to optimize exercise and physical activity when your body doesn’t do what it’s supposed to do (or what you want it to do). We don’t always have control over our bodies; whereas we do, sometimes, have control over our actions and what we can try to do and how we do physical activity. A lot of my strategies for optimizing exercise and physical activity have actually been updating my mental models, and I think they might be useful to other people, too.

But first, let me outline a couple of scenarios and how they differ so we have a shared framework for discussing some of the mental strategies for incorporating activity and exercise into life with chronic diseases like autoimmune diseases.

Let’s imagine you’re running and you come to a cliff.

  • In scenario A, there’s a bridge across to the other side at the same level. It’s no big deal to continue running across and continue on your way.
  • In scenario B, there’s no bridge, and you tumble off the cliff, but then you are able to (eventually) work your way back up to the other side at the same level as the person who could just stroll across the bridge.
  • In scenario C, there’s no bridge but the cliff isn’t as steep of a drop off; instead, it’s like a 2% railroad grade trail sloping away and down. You continue down it, but you end up well below the other side where a bridge would’ve connected, and there’s no way up to that level. The longer you go, the farther you are from that level.
  • In scenario D, there is a cliff that you fall off of, and you pick yourself up and keep going but it’s on that 2% railroad grade sloping away and down. Like scenario C, you end up well below – and even farther below – where you would have been if the bridge had been there.

Illustration of a runner crossing a bridge; running up a slope after the trail drops first then returns to the same height (B); running down a slope that takes them below the target height (C); and a combination of a sharp drop then slope down (D), as explained in more words throughout the blog post.

This is basically illustrative of the different types of situations you can find yourself in related to health status.

  • If all is well, you’re in scenario A: no bumps in the road, you just carry on.
  • Scenario B is like when you have a short-term injury or accident (like breaking your ankle or a toe) where you have a sudden drop in ability but you are able to build back up to the level you were at before. It may take longer and feel like a hard slog, but usually you can get there.
  • Scenario C is when you have a chronic disease (or are experiencing aging over time) where there’s small changes in the situation or in your ability. Because of these factors, you end up below where you maybe would like to be.
  • Scenario D is when there’s an acute situation that triggers or results in a significant, sudden drop followed by a chronic state that mimics the downward 2% small change slope that adds up significantly over time, meaning you are well below compared to where you would like to be.

My personal experiences and living in Scenario D

I have dealt with scenario B via a broken ankle and a broken toe in past years. Those stink. They’re hard. But they’re a different kind of hard than scenario C and scenario D, where I’ve found myself in the last few years and more acutely, I now am clearly operating in scenario D: I have had an acute drop-off in lung function and have autoimmune diseases that are affecting my ability to exercise, especially as compared to “before”. In fact, I keep having cycles of scenario D where my VO2 max drops off a cliff (losing a full point or more) within 2-3 days, then plateaus at the low level during the length of that round of symptoms, before maybe responding to my efforts to bring it back up. And it doesn’t always go back up or respond to exercise the way it used to do, “before”, because well, my lungs don’t work like they used to.

It’s been pretty frustrating. I want to keep building on the hard work I’ve put into my last 2-3 years of ultrarunning. Last year around this time, I ran a personal best 100k (62 miles) and beat my brother-in-law’s 100k time. I’m pretty proud of that because I’m pretty slow; but in ultras if you pace well and fuel well, you can beat faster runners. (As opposed to much shorter distances where speed matters more!).

This year, however, I can barely trek out – on the best day – for a 4 mile run. I had originally envisioned that, due to my fitness level and cumulative mileage build up, I would be able to train for and run a fast marathon (26.2 miles / ~42k) this spring, and that was supposed to be what I was training for. (Fast being “fast for me”.) But instead of running ~30-40 miles a week, I have been running 8-16 miles per week and have only clocked in half of the total mileage I had done by this point last year. Argh. I didn’t expect to do as much overall, but 210 instead of 420 miles by the beginning of April shows how different it’s been and how limited I have been. I’ve dropped the scheduled plan for marathon training – or any hopes of ultra training this year, unless something changes drastically in a positive way that I’m not expecting.

I finally realized that comparing my abilities to “before” is the crux of a lot of my angst. It is a little hard when you realize over time (scenario C) that you can’t do something that you think you should be able to. For example, me trying to run fast: it just has never worked the way training to run fast seems to work for other people. Eventually, in “before times”, I had settled into a strategy of running far, but doing so more slowly, and that’s turned out to be way more fun for me. But when you have an acute adjustment in ability that isn’t like scenario B (e.g. you can expect to regain strength/function/ability over time), it’s really hard to wrap your brain around. And comparisons to ‘before’ feel inevitable. They’re probably part of the grieving process in recognizing that things have changed. But at some point, it’s helpful to recognize and picture that you ARE in scenario D. This includes grappling with and accepting the fact that something has changed; and you likely do not have control over it.

I have updated my mental model with some strategies, to help me frame and recognize that on bad days, I don’t have to push myself (even if deep down I want to, because I want to rebuild/gain fitness to where I “should” be) – and that I should save that strategy for “good” days.

Here’s what I’ve landed on, for general strategy approach, which applies to whatever activity that I ultimately choose for the day:

Overlapping circles of good days and bad days, showing that regardless of which day it is, I still go out every day. Strategies for 'bad' days include lowering expectations; changing activities; pacing slower; taking breaks; turning around; and not comparing to 'before'. Good/better days can involve a slow start but speed up or add distance if it feels good, as long as I pace/do it in a way that doesn't overdo it such that I can't be active as desired any following day.
The other thing, in addition to comparing distance, time and pacing to “before” abilities, that I have struggled with, is not having a training plan or schedule. Because my ‘good’ days (where my lungs do not seem to limit my activity) are unpredictable, I can’t build a training schedule and build up mileage/ability the way I used to. Ultimately, I have had to land on a strategy that I don’t like but accept is the most feasible one for now (suggested by Scott): have a “checklist” of activities for my ‘good days’, and have a checklist of activities for my ‘bad days’. This has helped me separate my before-desire for running being my primary activity (and thinking about my running ‘schedule’ that I wish I could go back to), and instead be more realistic on the day-of about what activities are ideal for the type of day I’m actually dealing with.

For example, on my worst days, I cannot run for 30 seconds without gasping for breath and any type of intensive activity (anything more than a really slow meandering walk or a few seconds of a really slow run) feels terrible. Walking feels yuck too but it’s tolerable when I go slow enough, even though my lungs still feel physically uncomfortable inside my rib cage. On medium bad days, I maybe can do a slow, easy, short run with 20 seconds run intervals; a walk; an easy super slow hike with lots of stopping; or an e-bike ride; or easy pace cross-country skiing (when it was winter). On good days? I can do anything! Which means I can hike more elevation at clippier paces (and I can actually push myself on pace) or run with some modicum of effort above a snail’s pace or run a snail’s pace that doesn’t hurt for 30 second intervals. Those are my favorite activities, so those are high on my list (depending on whether it’s the weekday or weekend) to try to do when I’m feeling good. On the bad days or less good days, I take whatever activity is available to me however I can get it.

Activity choice check list for really bad days (e.g. walk or easy e-bike) vs less bad days (slow, easy short run or very slow hike or easy ski) versus the better days where I can run, hike longer/faster, and ski any distance I want.
There are tons of activities so if you’re reading this, know that I’m making this list based on MY favorite types of activities (and the climate I live in). You should make your list of activities and sort them if it’s helpful, to know which ones bring joy even on the worst days and those are what you should prioritize figuring out how to do more of, as the days permit.

Some of this stuff maybe seems “duh” and super intuitive to a lot of people, especially if you’re not living in Scenario D. Hello to everyone in Scenario A! But, when you’ve been thrust off a metaphorical cliff into Scenario D, and there’s no way to do what you did “before”, figuring out how to pace and push yourself to regain what fitness you can OR preserve basic health functionality as long as you can…it’s all an experiment of balancing what amount of activity pushes you in a positive way and builds strength, fitness and health and balancing against going over the point where it causes short-term harm (to the point where it impedes your activity the following days) and/or long-term harm (e.g. further hurts your lungs or other body parts in a way that is either irreversible or hard to recover from).

The pep talk I wish I got that I’m giving to you now

Before I lived in Scenario D (lung stuff), I lived a lot in Scenario C: running with type 1 diabetes AND celiac AND Grave’s AND exocrine pancreatic insufficiency (which means I have to juggle glucose management while only eating gluten free and calculating and eating enzymes for any of that gluten free food I eat as fuel while running) was a lot to juggle, in of itself. I often thought about how much I was juggling while running along, while recognizing that a lot of that juggling was invisible to the outside. Which made me think and observe that even though I feel like every other runner was flying by me and not dealing with the exact same set of balls to juggle; some of those runners WERE probably juggling their own health stuff and limitations, too (or are parents juggling jobs and kid schedules and running, etc). Everyone’s got baggage that they’re carrying, of some sort, or are juggling things in a different way. So, juggling is hard. Kudos to everyone for getting out there for juggling with what they’ve got.

But especially now in Scenario D, it’s even more important to me that it’s not about being out there and running certain paces or hiking certain distances: it’s getting out there AT ALL which is the entire point. And I’ve made it my mission to try to compliment people for getting out there, when it feels like it’s appropriate to do so.

Last week, I was handed the perfect opportunity, and it turned out to be the best conversation I’ve had in a long time. A woman was coming uphill and commented that I had not forgotten my hiking poles like she had. I said yeah, they make a difference going downhill as well as up! She said something about huffing and puffing because she has asthma. DING DING: opportunity to celebrate her for being out there hiking uphill, even with asthma. (I pretty much said that and complimented her). She and Scott were trading comments about it being the beginning of hiking season and how they had forgotten their hiking poles and we told them we were making a list throughout the hike of everything else we had forgotten. They mentioned that they were 70 (wow!) and 75 (wow!) and so they didn’t think they needed walkie talkies because they would not separate on the trail (one of the things that we forgot to bring in case Scott mountain-goated-ahead of me on the trail at any point). We gave them our sincere compliments for being out there hiking (because, goals! I am aiming hard and working hard to get to the age of 70 and be able to hike like that!). She talked about it being hard because she has asthma and was struggling to breathe at first before she remembered to take her albuterol…and I pointed out that even if she was struggling and had to stop every few minutes, it didn’t matter: she was out there, she was hiking, and it doesn’t matter how long it takes! She thought that was the best thing to hear, but it was really what I try to tell myself because I love to hear it, too, which is celebrating going and not worrying about pace/slow/whatever. I told her I had a lung condition too (she’s the first stranger I’ve ever told) and she asked if I was stopping every 2 minutes and whether I had taken an inhaler. I explained most of my lung condition doesn’t respond to an inhaler but that yes, I too had to stop and catch my breath. But it was an awesome, gorgeous day and worth hiking in and that I was glad I had gone up. Ultimately, she said a lot of things that made it seem like my shared experience helped her – but in turn, seeing her and talking to her helped ME just as much, because it reminded me that yes, everyone else is juggling things while hiking too. And it’s really not about speed/pace/time; it’s absolutely about being out there and enjoying it.

So that’s what I’m trying to do: I’m trying to move beyond the comparison from what I did before, and simply compare to “am I going out at all and trying”. Trying = winning; going = winning, and that’s the new mental model that has been working really well for me as I spend more time in Scenario D.

—

PS – if you read this and are in a similar situation of Scenario B, C, or D and want a virtual high five and to feel “seen” for what you’re working through – feel free to comment here or email any time. I see you going out and trying; which means you’re winning! And I’m happy to give a virtual comment the way I am trying to give comments out on the trails and compliment folks for the process of being out moving through the world in all the ways that we can, however we can. 

Running a Multi-Day Ultramarathon (Aiming for 200 Miles)

by Dana Lewis

I used to make a lot of statements about things I thought I couldn’t do. I thought I couldn’t run overnight, so I couldn’t attempt to run 100 miles. I could never run 200 mile races the way other people did. Etc. Yet last year I found myself training for and attempting 100 miles (I chose to stop at 82, but successfully ran overnight and for 25 hours) and this year I found myself working through the excessive mental logistics and puzzle of determining that I could train for and attempt to run 200 miles, or as many miles as I could across 3-4 days.

Like my 100 mile attempt, I found some useful blog recaps and race reports of people’s official races they did for 200-ish mile races. However, like the 100 attempts, I found myself wanting more information for the mental training and logistical preparation people put into it. While my 200 mile training and prep anchored heavily on what I did before, this post describes more detail on how my training, prep, and ‘race’ experience for a multi-day or 200 mile ultra attempt.

DIY-ing a 200

For context, I have a previous post describing the myriad reasons of why I often choose to run DIY ultras, meaning I’m not signing up for an official race. Most of those reasons hold true for why I chose to DIY my 200. Like my 100 (82) miles, I mapped a route that was based on my home paved trail that takes me out and around the trails I’m familiar with. It has its downsides, but also the upsides: really good trail bathrooms and I feel safe running them. Plus, it’s easy and convenient for my husband to crew me. Since I expected this adventure to take 3-4 days (more on that below), that’s a heavy ask of my husband’s time and energy, so sticking with the easy routes that work for him is optimal, too. So while I also sought to run 200 miles just like any other 200-mile ultra runner, my course happens to have minimal elevation. Not all 200 mile ultramarathon races have a ton of elevation – some like the Cowboy 200 are pretty flat – so my experience is closer to that than the experience of those running mountain based ultras with 30,000 feet (or more) of elevation gain. And I’m ok with that!

Sleep

One of the puzzles I had to figure out to decide I could even attempt a 200 miler is sleep. With a 100 mile race, most people don’t sleep at all (nor did I) and we just run through the night. With 200 miles, that’s impossible, because it takes 3, 4, 5 days to finish and biologically you need sleep. Plus, I need more sleep than the average person. I’m a champion sleeper; I typically sleep much longer than everyone else; and I know I couldn’t function with an hour here or there like many people do at traditional races. So I actually designed my 200 mile ultra with this in mind: how could I cover 200 miles AND get sleep? Because I’m running to/from home, I have access to my kitchen, shower, and bed, so I decided that I would set up my run to run each day and come home and eat dinner, shower, and sleep each night for a short night in my bed.

I then decided that instead of winging it and running until I dropped before eating, showering, and sleeping, I would aim for running 50 miles each day. Then I’d come in, eat, shower, and sleep and get up the next morning and go again. 4 days, 3 nights, 50 miles each day: that would have me finishing around 87-90ish hours total (with the clock running from my initial start), including ~25 hours or more of total downtime between the eating/showering/sleeping/getting ready. That breakdown of 3.67 days is well within the typical finish times of many 200 mile ultras (yes, comparing to those with elevation gain), so it felt like it was both a stretch for me but also doable and in a sensible way that works for me and my needs. I mapped it all out in my spreadsheet, with the number of laps and my routes and pacing to finish 50 miles per day; the two times per day I would need my husband to come out and crew me at ‘aid station stops’ in between laps, and what time I would finish each night. I then factored in time to eat and shower and get ready for bed, sleep, and time to get up in the morning. Given the fact that I expected to run slower each day, the sleep windows go from 8 hours down to less than 6 hours by night 3. That being said, if I managed to sleep 5 hours per night and 15 hours total, that’s probably almost twice as much as most people get during traditional races!

Like sleep, I was also very cognizant of the fact that a 200 probably comes down to mental fortitude and will power to keep going; meticulous fueling; and excellent foot care. Plus reasonable training, of course.

Meticulous fueling

I have previously written about building and using a spreadsheet to track my fuel intake during ultras. This method works really well for me because after each training run I can see how much I consumed and any trends. I started to spot that as I got tired, I would tend to choose certain snacks that happened to be slightly lower calorie. Not by much, but the snack selections went from those that are 150-180 calories to 120-140 calories, in part because I perceived them to be both ‘smaller’ (less volume) and ‘easier to swallow’ when I was tired. Doubled up in the same hour, this meant that I started to have hours of 240 calories instead of more than 250. That doesn’t sound like much, but I need every calorie I can get.

I mapped out my estimated energy expenditure based on the 50 miles per day, and even consuming 250 calories per hour, I would end up with several thousand calories of deficit each day! I spent a lot of time testing food that I think I can eat for dinner on the 3 nights to ensure that I get a good 1000 calories or more in before going to bed, to help address and reduce the growing energy deficit. But I also ended up optimizing my race fuel, too. Because I ran so many long runs in training where I fueled every 30 minutes, and because I had been mapping out my snack list for each lap for 50 miles a day for 4 days, I’ve been aware for months that I would probably get food fatigue if I didn’t expand my fuel list. I worked really hard to test a bunch of new snacks and add them to the rotation. That really helped even in training, across all 12 laps (3 laps a day to get 50 miles, times 4 days), I carefully made sure I wouldn’t have too many repeats and get sick of one food or one group of things I planned to eat. I also recently realized that some of the smaller items (e.g. 120 calorie servings) could be increased. I’m already portioning out servings from a big bag into small baggies; in some cases adding one more pretzel or one more piece of candy (or more) would drive up the calories by 10-20 per serving. Those small tweaks I made to 5 of my ~18 possible snacks means that I added about 200 calories on top of what was already represented in those snacks. If I happen to choose those 5 snacks as part of my list for any one lap, that means I have a bonus 200 calories I’ve convinced myself to consume without it being a big deal, because it’s simply one more pretzel or one more piece of candy in the snack that I’m already use to consuming. (Again, because I’m DIYing my race and have specific needs relative to running with celiac, diabetes, and exocrine pancreatic insufficiency, for me, pre-planning my fuel and having it laid out in advance for every run, or in the race every single lap, is what works for me personally.)

Here’s a view of how I laid out my fuel. I had worked on a list of what I wanted for each lap, checking against repeats across the same day and making sure I wasn’t too heavily relying on any one snack throughout all the days. I then bagged up all snacks individually, then followed my list to lay them out by each lap and day accordingly. I also have a bag per day each for enzymes and electrolytes, which you’ll see on the left. Previously, I’ve done one bag per lap, but to reduce the number of things I’m pulling in and out of my vest each time, I decided I could do one big bag each per day (and that did end up working out well).

Two pictures side by side, with papers on the floor showing left to right laps 1-3 on the top and along the left side days 1-4, to create a grid to lay out my snacks. On the left picture, I have my enzymes, electrolytes per day and then a pile of snacks grouped for each lap. On the right, all the snacks and enzymes and electrolytes have been put into gallon bags, one for each lap.

Contingency planning

Like I did for my 100, I was (clearly) planning for as many possibilities as I could. I knew that during the run – and each evening after the run – I would have limited excess mental capacity for new ideas and brainstorming solutions when problems come up. The more I prepared for things that I knew were likely to happen – fatigue, sore body, blisters, chafing, dropping things, getting tired of eating, etc – the more likely that they would be small things and not big things that can contribute to ending a race attempt. This includes learning from my past 100 attempt and how I dealt with the rain. First of all, I planned to move my race if it looks like we’ll get 6 months of rain in a single 24 hour period! But also, I scheduled my race so that if I do have a few hours of really hard rain, I could choose to take a break and come in and eat/shower/change/rest and go back out later, or extend and finish a lap on the last day or the day after that. I was not running a race that would yank me from the course, but I did have a hard limit after day 5 based on a pre-planned doctor’s appointment that would be a hassle to reschedule, so I needed to finish by the night after day 5. But this gave me the flexibility to take breaks (that I wasn’t really planning to take but was prepared to if I needed to due to weather conditions).

Training for a 200 mile ultramarathon

Like training plans for marathons and 100 milers, the training plans I’ve read about for 200 mile ultramarathons intimidate me. So much mileage! So much time for a slow run/walker like me. I did try to look at sample 200 mile ultra plans and get a sense for what they’re trying to achieve – e.g. when do they peak their mileage before the race, how many back to back runs of what general length in terms of time etc – and then loosely keep that in mind.

But basically, I trained for this 200 mile ultra just like I trained for my marathon, 50k, 100k, and 82 miler. I like to end up doing long runs (which for me are run/walks of 30 seconds run, 60 seconds walk, just like I do shorter runs) of up to around 50k distance. This time, I did two total training runs that were each around 29 miles, just based on the length of the trail I had to run. I could have run longer, but mentally had the confidence that another ~45 minutes per run wasn’t going to change my ability to attempt 50 miles a day for 4 days. If I didn’t have 3 years of this training style under my personal belt, I might feel different about it. That’s longer than many people run, but I find the experience of 7-8 hours of time on my feet fueling, run/walking, and problem solving (including building up my willpower to spend that much time moving) to be what works for me.

The main difference for my 200 is probably also that it’s my 3rd year of ultrarunning. I was able to increase my long runs a little bit more of a time, when historically I used to add 2 miles a time to a long run. I jumped up 4 miles at a time – again, run/walking so very easy on my legs – when building up my long runs, so I was able to end up with 2 different 29 mile runs, two weeks apart, even though I really kicked off training specifically for this 8 weeks prior (10 weeks including taper) to the run. In between I also did a weekend of back to back to back runs (meaning 3 days in a row) where I ran 16 miles, another 16 miles, and 13 miles to practice getting up and running on tired legs. In past cycles I had done a lot more back to back (2-day) with a long and a medium run, but this time I did less of the 2-day and did the one big 3-day since I was targeting a 4-day experience. In future, if I were to do this again, given how well my body held up with all this training, I might have done more back to back, but I took things very cautiously and wanted to not overtrain and cause injury from ramping up too quickly.

As part of that (trying not to over do it), instead of doing several little runs throughout the week I focused on more medium-long runs with my vest and fueling, so I would do something like a long run (starting at 10 miles building up to 29 miles), a medium-long run (8 miles up to 13 miles or 16 miles) and another medium-ish run (usually 8 miles). Three runs a week, and that was it. Earlier in the 8 weeks, I was still doing a lot of hiking off the season, so I had plenty of other time-on-feet experiences. Later in the season I sometimes squeezed in a 4th short run of the week if we wouldn’t be hiking, and ran without my vest and tried to do some ‘speed work’ (aka run a little faster than my easy long run pace). Nothing fancy. Again, this is based on my slow running style (that’s actually a fixed interval of short run and short walk, usually 30 seconds run and 60 seconds walk), my schedule, my personality, and more. If you read this, don’t think my mileage or training style is the answer. But I did want to share what I did and that it generally worked for me.

I did struggle with wondering if I was training “enough”. But I never train “enough” compared to others’ marathon, 50k, 100k, 100 mile plans, either. I’m a low mileage-ish trainer overall, even though I do throw in a few longer runs than most people do. My peak training for marathon, 50k, and 100k is usually around low 50s (miles per week). Surprisingly, this 200 cycle did get me to some mid 60 mile weeks! One thing that also helped me mentally was adding in a rolling 7 day calculation of the miles, not just looking at miles per calendar week. That helped when I shifted some runs around due to scheduling, because I could see that I was still keeping a reasonable 55-low60s mileage over 7 days even though the calendar week total dropped to low 40s because of the way the runs happened to land in the calendar weeks.

Generally, though, looking back at how my training was more than I had accomplished for previous races; I feel better than ever (good fueling really helps!); I didn’t have any accidents or overtraining injuries or niggles; I decided a few weeks before peak that I was training enough and it was the right amount for me.

Another factor that was slightly different was how much hiking I had done this year. I ran my 100k in March then took some time off, promising my husband that we would hike “more” this year. That also coincided with me not really bouncing back from my 100k recovery period: I didn’t feel like doing much running, so we kept planning hiking adventures. Eventually I realized (because I was diagnosed with Graves’ disease last year, I’m having my thyroid and antibody and other related blood work done every 3 months while we work on getting everything into range) that this coincided with my TSH going too high for my body’s happiness; and my disinterest in long runs was actually a symptom (for me) of slightly too-high TSH. I changed my thyroid medication and within two weeks felt HUGELY more interested in long running, which is what coincided with reinvigorating my interest in a fall ultra, training, and ultimately deciding to go for the 200. But in the meantime, we kept hiking a lot – to the tune of over 225 miles hiked and over 53,000 feet of elevation gain! I never tracked elevation gain for hiking before (last year, not sure I retrospectively tracked it all but it was closer to 100 miles – so definitely likely 2x increase), but I can imagine this is definitely >2x above what I’ve done on my previous biggest hiking year, just given the sheer number of hikes that we went out on. So overall, the strengthening of my muscles from hiking helped, as did the time on feet. Before I kicked off my 8 week cycle, we were easily spending 3-4 hours a hike and usually at least two hikes a weekend, so I had a lot of time on feet almost every hike equivalent to 12 or more miles of running at that point. That really helped when I reintroduced long runs and aided my ability to jump my long run in distance by 4 miles at a time instead of more gently progressing it by 2 miles a week as I had done in the past.

How my 200 mile attempt actually went

Spoiler alert: I DNF (did not finish) 200 miles. Instead, I stopped – happily – at 100 miles. But it wasn’t for a lack of training.

Day 1 – 51 miles – All as planned

I set out on lap 1 on Day 1 as planned and on time, starting in the dark with a waist lamp at 6am. It was dark and just faintly cool, but warm enough (51F) that I didn’t bother with long sleeves because I knew I would warm up. (Instead, for all days, I was happy in shorts and a short sleeve shirt when the temps would range from 49F to 76F and back down again.) I only had to run for about an hour in the dark and the sky gradually brightened. It ended up being a cloudy, overcast and nice weather day so it didn’t get super bright first thing, but because it wasn’t wet and cold, it wasn’t annoying at all. I tried to start and stay at an easy pace, and was running slow enough (about ~30s/mile slower than my training paces) that I didn’t have to alter my planned intervals to slow me down any more. All was fairly well and as planned in the first lap. I stopped to use the bathroom at mile 3.5 and as planned at my 8 mile turnaround point, and also stopped to stuff a little more wool in a spot in my shoe a mile later. That added 2 minutes of time, but I didn’t let it bother me and still managed to finish lap 1 at about a 15:08 min/mi average pace, which was definitely faster than I had predicted. I used the bathroom again at the turnaround while my husband re-filled my hydration pack, then I stuffed the next round of snacks in my vest and took off. The bathroom and re-fueling “aid station” stop only took 5 minutes. Not bad! And on I went.

A background-less shot of me in my ultrarunning gear. I'm wearing a grey moisture-wicking visor; sunglasses; a purple ultrarunning vest packed with snacks in front and the blue tube of my hydration pack looped in front; a bright flourescent pink short sleeve shirt; grey shorts with pockets bulging on the side with my phone (left pocket) and skittles and headphones and keys (right pocket), and in this lap I was wearing bright pink shoes. Lap 2 was also pretty reasonable, although I was surprised by how often I wanted a bathroom. My period had started that morning (fun timing), and while I didn’t have a lot of flow, the signals my abdomen was giving my brain was telling me that I needed to go to the bathroom more often than I would have otherwise. That started to stress me out slightly, because I found myself wishing for a bathroom in the longest stretch without trail bathrooms and in a very populated area, the duration of which was about 5.5 miles long. I tried to drink less but was also aware of trying not to under hydrate or imbalance my electrolytes. I always get a little dehydrated during my period; and I was running a multi-day ultra where I needed a lot of hydration and more sodium than usual; this situation didn’t add up well! But I made it without any embarrassing moments on the trail. The second aid station again only took 5 minutes. (It really makes a world of difference to not have to dry off my feet, Desitin them up, and re-do socks and shoes every single aid station like I did last year!) I could have moved faster, but I was trying to not let small minutes of time frazzle me, and I was succeeding with being efficient but not rushed and continuing on my way. I had slowed down some during lap 2, however – dropping from a 15:08 to 15:20ish min/mi pace. Not much, but noticeable.

At sunset, with light blue sky fading to yellow at the horizon behind the row of tall, skinny bush like trees with gaps and a hot air balloon a hundred or so feet off the ground seen between the trees.Lap 3 I did feel more tired. I talked my husband into bringing me my headlamp toward the end of the last lap, instead of me having to carry it for 4+ hours before the sun went down. (Originally, I thought I would need it 2-3 hours into this last lap, but because I was moving so well it was now looking like 4 hours, and it would be a 2-3 mile e-bike ride for him to bring me the lamp when I wanted it. That was a mental win to not have to run with the lamp when I wasn’t using it!) I was still run/walking the same duration of intervals, but slowed down to about 16:01 pace for this lap. Overall, I would be at 15:40 average for the whole day, but the fatigue and my tired feet started to kick in on the third lap between miles 34-51. Plus, I stopped to take a LOT more pictures, because there was a hot air balloon growing in the distance as it was flying right toward me – and then by me next to the trail! It ended up landing next to the soccer fields a mile behind me after it passed me in this picture. I actually made it home right as the sun set and didn’t have to wear my lamp at all that evening.

Day 1 recovery was better and worse than I expected. I sat down and used my foot massager on my still-socked feet, which felt very good. I took a shower after I peeled my socks off and took a look at my feet for the first time. I had one blister that I didn’t know was growing at all pop about an hour before I finished, but it was under some of my pre-taped area. I decided to leave the tape and see how it looked and felt in the morning. I had 2-3 other tiny, not a big deal blisters that I would tape in the morning but didn’t need any attention that night.

I had planned to eat a reasonably sized dinner – preferably around 1000 calories – each night, to help me address my calorie deficit. And I had a big deficit: I had burned 5,447 calories and consumed 3,051 calories in my 13 hours and 13 minutes of running. But I could only eat ¼ of the pizza I planned for dinner, and that took a lot of work to force myself to eat. So I gave up, and went to bed with a 3,846 calorie deficit, which was bigger than I wanted.

And going to bed hurt. I was stiff, which I could deal with, but my feet that didn’t hurt much while running started SCREAMING at me. All over. They hurt so bad. Not blisters, just intense aches. Ouch! I started to doubt my ability to run the next day, but this is where my pre-planning kicked in (aided by my husband who had agreed to the rules we had decided upon): no matter what, I would get up in the morning, get dressed, and go out and start my first lap. If I decided to quit, I could, but I could not quit at night in bed or in the morning in the bed or in the house. I had to get up and go. So I went to sleep, less optimistic about my ability to finish 50 miles again on day 2, but willing to see what would happen.

Day 2: 34 instead of 50 miles, and walking my first ever lap

I actually woke up before my alarm went off on day 2. Because I had finished so efficiently the day before, I was able to again get a good night’s sleep, even with the early alarm and waking up again at 4:30am with plans to be going by 6am. The extra time was helpful, because I didn’t feel rushed as I got ready to go. I spent some extra time taping my new blisters. Because they hadn’t popped, I put small torn pieces of Kleenex against them and used cut strips of kinesio tape to protect the area. (Read “Fixing Your Feet” for other great ultra-related foot care tips; I learned about Kleenex from that book.) I also use lambs’ wool for areas that rub or might be getting hot spots, so I put wool back in my usual places (between big and second toes, and on the side of the foot) plus another toe that was rubbing but not blistered and could use some cushion. I also this year have been trying Tom’s blister powder in my socks, which seems to help since my feet are extra sweat prone, and I had pre-powdered a stack of socks so I could simply slip them on and get going once I had done the Kleenex/tape and wool setup. The one blister that had popped under my tape wasn’t hurting when I pressed on it, so I left it alone and just added loose wool for a little padding.

A pretty view of the trail with bright blue sky after the sun rose with green bushes (and the river out of sight) to the left, with the trail parallel to a high concrete wall of a road with cheery red and yellow leaved trees leaning over the trail.And off I went. I managed to run/walk from the start, and faster than I had projected on my spreadsheets originally and definitely faster than I thought was possible the night before or even before I started that morning. Sure, I was slower than the day before, but 15:40 min/mi pace was nothing to sneeze at, and I was feeling good. I was really surprised that my legs, hips and body did not hurt at all! My multi-day or back-to-back training seemed to pay off here. All was well for most of the first lap (17 miles again), but then the last 2 or so miles, my pace started dipping unexpectedly so I was doing 16+ min/mi without changing my easy effort. I was disappointed, and tired, when I came into my aid station turnaround. I again didn’t need foot care and spent less than 5 minutes here, but I told Scott as I left that I was going to walk for a while, because my feet had been hurting and they were getting worse. Not blisters: but the balls of my feet were feeling excruciating.

A close up of a yellow shelled snail against the paved trail that I saw while walking the world's slowest 17-mile lap on day 2.I headed out, and within a few minutes he had re-packed up and biked up to ride alongside me for a few minutes and chat. I told him I was probably going to need to walk this entire lap. We agreed this was fine and to be expected, and was in fact built into my schedule that I would slow down. I’ve never walked a full lap in an ultra before, so this would be novel to me. But then my feet got louder and louder and I told him I didn’t think I could even walk the full lap. We decided that I should take some Tylenol, because I wasn’t limping and this wouldn’t mask any pain that would be important cues for my body that I would be overriding, but simply muting the “ow this is a lot” screams that the bones in the balls of my feet were feeling. He biked home, grabbed some, and came back out. I took the Tylenol and sent him home again, walking on. Luckily, the Tylenol did kick in and it went from almost unbearable to manageable super-discomfort, so I continued walking. And walking. And walking. It took FOREVER, it felt like, having gone from 15-16 min/mi pace with 30 seconds of running, 60 seconds of walking, to doing 19-20 minute miles of pure walking. It was boring. I had podcasts, music, audiobooks galore, and I was still bored and uncomfortable and not loving this experience. I also was thinking about it on the way back about how I did not want to do a 3rd lap that day (to get me to my planned 50 miles) walking again.

Scott biked out early to meet me and bring me extra ice, because it was getting hot and I was an hour slower than the day before and risking running out of water that lap if he didn’t. After he refilled my hydration pack and brought it back to me while I walked on, I told him I wanted to be done for the day. He pointed out that when I finished this lap, I would be at 34 miles for the day, and combined with the day before (51), that put me at 85 miles, which would be a new distance PR for me since last year I had stopped at 82. That was true, and that would be a nice place to stop for the day. He reminded me of our ‘rules’ that I could go out the next day and do another lap to get me to 100, and decide during that lap what else I wanted to do. I was pretty sure I didn’t want to do more, but agreed I would decide the next day. So I walked home, completing lap 2 and 34 miles for the day, bringing me to 85 miles overall across 2 days.

Day 2 recovery went a little better, in part because I didn’t do 51 miles (only 34) and I had walked rather than ran the second lap, and also stopped earlier in the day (4pm instead of 7pm). I had more time to shower and bring myself to finally eat an entire 1000 calories before going to bed, again with my feet screaming at me. I had more blisters this time, mostly again on my right foot, but the balls of my feet and the bones of my feet ached in a way they never had before. This time, though, instead of setting my alarm to get up and go by 6am, I decided to sleep for longer, and go out a little later to start my first lap. This was a deviation from my plan, but another deviation I felt was the right one: I needed the sleep to help my body recover to be able to even attempt another lap.

Day 3: Only 16 miles, but hitting 100 for the first time ever

Instead of 6am, I set out on Day 3 around 8:30am. I would have taken even longer to go, but the forecast was for a warm day (we ended up hitting 81F) and I wanted to be done with the lap before the worst of the heat. I thought there was a 10% chance I’d keep going after this lap, but it was a pretty small chance. However, I set out for the planned 16 mile lap and was pleasantly surprised that I was run/walking at about a 15:40 pace! Again, better than I had projected (although yes, I had deviated from my mileage plan the day before), and it felt like a good affirmation that stopping the day before instead of slogging out another walking lap was the right thing to do.

After a first few miles, I toyed with the idea of continuing on. But I knew with the heat I probably wouldn’t stand more than one more lap, which would get me to 116. Even if I went out again the fourth day, and did 1-2 laps, that would MAYBE get me to 150, but I doubted I could do that without starting to cause some serious damage. And it honestly wasn’t feeling fun. I had enjoyed the first day, running in the dark, the fog, the daylight, and the twilight, seeing changing fall leaves and running through piles of them. The second day was also fun for the first lap, but the second lap walking was probably what a lot of ultra marathoners call the “death march” and just not fun. I didn’t want to keep going if it wasn’t fun, and I didn’t want to run myself into the ground (meaning to be so worn down that it would take weeks to months to recover) or into injury, especially when the specific milestones didn’t really mean anything. Sure, I wanted to be a 200 mile ultramarathoner, something that only a few thousand people have ever done – but I didn’t want to do it at the expense of my well-being. I spent a lot of time thinking about it, especially miles 4-8, and was thinking about the fact that the day before I had started, I had gone to a doctor’s appointment and had an official diagnosis confirming my fifth autoimmune disease, then proceeded to run (was running) 100 miles. Despite all the fun challenges of running with autoimmune conditions, I’m in really good health and fitness. My training this year went so well and I really enjoyed it. Most of this ultra had gone so well physically, and my legs and body weren’t hurting at all: the weakness was my feet. I didn’t think I could have trained any differently to address that, nor do I think I could change it moving forward. It’s honestly just hard to run that many hours or that many miles, as most ultramarathoners know, and your feet take a beating. Given that I was running on pavement for all of those hours, it can be even harder – or a different kind of hard – than kicking roots and rocks on a dirt trail. I figured I would metaphorically kick myself if I tried for 116 or 134 and injured myself in a way that would take 6-8 weeks to recover, whereas I felt pretty confident that if I stopped after this lap (at 100), I would have a relatively short and easy recovery, no major issues, and bounce back better than I ever have, despite it being my longest ever ultramarathon. Yes, I was doing it as a multi-day with sleep in between, but both in time on feet and in mileage, it was still the most I’d ever done in 2 or 3 days.

And, I was tired of eating. I was fueling SO well. Per my plans, I set out to do >500 mg of sodium per hour and >250 calories per hour. I had been nailing it every lap and every day! Day 1 I averaged 809 mg of sodium per hour and 290 calories per hour. Day 2 was even increased from that, averaging 934 mg of sodium per hour and 303 calories per hour! Given the decreased caloric burn of day 2 because I walked the second lap, my caloric deficit for day 2 was a mere ~882 calories (given that I also managed to eat a full dinner that night), even though I skipped the last hour as I finished the walking lap. Day 3 I was also fueling above my goals, but I was tired of it. Sooooo tired of it. Remember, I have to take a pill every time I eat, because I have exocrine pancreatic insufficiency (EPI or PEI). I was eating every 30 minutes as I ran or walked, so that meant swallowing at least one pill every 30 minutes. I had swallowed 57 pills on Day 1 and 48 pills on Day 2, between my enzymes and electrolyte pills. SO MANY PILLS. The idea of continuing to eat constantly every 30 minutes for another lap of ~5 or more hours was also not appealing. I knew if I didn’t eat, I couldn’t continue.

A chart with an hourly break down of sodium, calories, and carbs consumed per hour, plus totals of caloric consumption, burn, and calculated deficit across ~27 hours of move time to accomplish 100 miles run.

And so, I decided to stop after one more lap on day 3, even though I was holding up a respectable 15:41 min/mi pace throughout. I hit 100 miles and finished the lap at home, happy with my decision.

Two pictures of me leaning over after my run holding a sign (one reading 50 miles, one reading 100 miles) for each of my cats to sniff.(You can see from these two pictures that I smelled VERY interesting, sweaty and salty and exhausted at the end of day 1 and day 3, when I hit 50 miles and 100 miles, respectively. We have two twin kittens (now 3 years old) and one came out to sniff me first on the first day, and the other came out as I came home on the third day!)

Because I had only run one final lap (16 miles) on day 3, and had so many bonus hours in the rest of the day afterward when I was done and home, I was able to eat more and end up with only a 803 calorie deficit for the day. So overall, day 1 had the biggest deficit and probably influenced my fatigue and perception of pain on day 2, but because I had shortened day 2 and then day 3, my very high calorie intake every hour did a pretty good job matching my calorie expenditure, which is probably why I felt very little muscle fatigue in my body and had no significant sore areas other than the bottoms of my feet. I ended up averaging 821 mg/hr of sodium and 279 calories per hour (taking into account the fact that I skipped two final snacks at the end of day 2 when I was walking it out; ignoring that completely skipped hour would mean the average caloric intake on hours I ate anything at all was closer to 290 calories/hr!)

In total, I ended up consuming 124 pills in approximately 27 hours of move time across my 100 miles. (This doesn’t include enzyme pills for my breakfast or dinners each of those days, either – just the electrolyte and enzyme pills consumed while running!)

AFTERMATH

Recovery after day 3 was pretty similar to day 2, with me being able to eat more and limit my calorie deficit. I’ve had long ~30 mile training runs where I wasn’t very hungry afterward, but it surprised me that even two days after my ultra, I still haven’t really regained my appetite. I would have figured my almost 4000 calorie deficit from day 1 would drive a lot of hunger, so this surprised me.

So too has my physical state: 48 hours following the completion of my 100 miles, I am in *fantastic* shape compared to other multi-day back to back series of runs I’ve done, ultramarathons or not. The few blisters I got, mainly on my right foot, have already flattened themselves up and mostly vanished. I think I get more blisters on my right foot because of breaking my toe last year: my right foot now splays wider in my shoe, so it tends to get more blisters and cause more trouble than my left foot. I got only one blister on my left foot, which is still fluid filled but not painful and starting to visibly deflate now that I’m not rubbing it onto a shoe constantly any more. And my legs don’t feel like I ran at all, let alone running 51+34+16 miles!

I am tired, though. I don’t have brain fog, probably because of my excellent fueling, but I am fatigued in terms of overall energy and lack of motivation to get a lot done yesterday and today (other than writing this blog post!). So that’s probably pretty on par with my effort expended and matches what I expected, but it’s nice to be able to move around without hurting (other than my feet).

My feet in terms of general aches and ows are what came out the worst from my run. Day 2, what hurt was the bottom of the balls of my feet. Starting each night though, I was getting aches all over in all of the bones of my feet. After day 3, that night the foot aches were particularly strong, and I took some Tylenol to help with that. Yesterday evening and today though, the ache has settled down to very minor and only occasionally noticeable. The tendon from the top of my left foot up my ankle is sore and gets cranky when I wear my sneakers (although it didn’t bother me at all while running any of the days), so after tying and re-tying my shoelaces 18 times yesterday to try to find the perfect fit for my left foot, today I went on my recovery walk in flip flops and was much happier.

What I’m taking away from this 200 mile attempt that was only 100 miles:

I feel a little disappointed that I didn’t get anywhere near 200 miles, but obviously, I was not willing to hurt long enough or hard enough to get there. My husband called it a stretch goal. Rationally, I am very happy with my choices to stop at 100 and end up in the fantastic physical shape that I am in, and I recognize that I made a very rational choice and tradeoff between ending in good shape (and health) and the mainly ego-driven benefits of possibly achieving 200 miles (for me).

Would I do anything different? I can’t think of anything. If I somehow had an alternate do-over, I can’t think of anything I would think to change. I’d like to reduce my risk of blisters but I’m already doing all I can there, and dealing with changes in my right foot shape post-broken toe that I have no control over. And I’m not sure how to train more/better for reducing the bottom ball of foot pain that I got: I already trained multiple days, back to back, long hours of feet on pavement. It’s possible that having my doctor’s appointment the day before I started influenced my mental calculation of my future risk/benefit tradeoff of continuing more miles, and so not having had that then may have changed my calculations to do another lap or two, or go out on the 4th day (which I did not). But, I don’t have a do over, and I’ll never know, and I’m not too upset about that because I was able to control what I could control and am again pretty happy with the outcomes. 100 or 150 miles felt about the same to me, psychologically, in terms of satisfaction.

What I would tell other people about attempting multiple day ultramarathons or 200 mile ultramarathons:

Training back to back days is one option, as is long spurts of time on feet walking/hiking/running. I don’t think “just running” has to be the only way to train for these things. I’m also a big proponent of short intervals: If you hear people recommend taking walk breaks, it doesn’t have to be 1 minute every 10 minutes or every mile. It can be as short as every 30 seconds of running, take a walk break! There’s no wrong way to do it, whatever makes your body and brain happy. I get bored running longer (and don’t like it); other people get bored running the short intervals that I do – so find what works for you and what you’re actually willing to do.

Having plans for how you’ll rest X hours and go out and try to make it another lap or to the next aid station works really well, especially if you have crew/pacers/support (for me, my husband) who will stick to those rules and help you get back out there to try the next lap/section. Speaking of sleep/rest, laying down for a while helps as much as sleeping, so even if you can’t sleep, committing to the rest of X hours is also good for resting your feet and everything. I found that the hour laying down before I fell asleep helped my body process the noise of the “ouch” from my feet and it was a lot easier to sleep after that. Plan that you’ll have some down/up time before and after your sleep/rest time, and figure that into your time plans accordingly.

The cheesy “know your why” and “know what you want” recommendations do help. I didn’t want 200 miles badly enough to hurt more for longer and risk months of recovery (or the inability to recover). Maybe you’d be lucky enough to achieve 200 without hurting that bad, that long, or risking injury – or maybe you’ll have to make that choice, and you might make it differently than I did. (Maybe you’re lucky enough to not have 5 autoimmune things to juggle! I hope you don’t have to!) I kind of knew going in that I was only going to hit 200 if all went perfect.

Diabetes and this 200 mile ultramarathon that was a 100 mile ultra:

I just realized that I managed to write an ENTIRE race report without talking about diabetes and glucose management…because I had zero diabetes-related thoughts or issues during these several days of my run! Sweet! (Pun fully intended.)

Remember, I have type 1 diabetes and use an open source automated insulin delivery (AID) system (in my case, still using OpenAPS after alllllll these years), and I’ve talked previously about how I fuel while ultrarunning and juggling blood glucose management. Unlike previous ultras, I had zero pump site malfunctions (phew) and my glucose stayed nicely in range throughout. I think I had one small drift above range for 2 hours due to an hour of higher carb activity right when I shifted to walking the second lap on day 2, but otherwise was nicely in range all days and all nights without any extra thought or energy expended. I didn’t have to take a single “low carb”/hypoglycemia treatment! I think there was one snack I took a few minutes early when I saw I was drifting down slightly, but that was mostly a convenience thing and I probably would not have gone low (below target) even if I had waited for my planned fuel interval. But out of 46 snacks, only one 5-10 minutes early is impressive to me.

I had no issues after each day’s run, either: OpenAPS seamlessly adjusted to the increasing insulin sensitivity (using “autosensitivity” or “autosens”) so I didn’t have to do manual profile shifts or overrides or any manual interference. I did decide each night whether I wanted to let it SMB (supermicrobolus) as usual or stick to temp basal only to reduce the risk of hypoglycemia, but I had no post-dinner or overnight lows at all.

The most “work” I had to do was deciding to wear a second CGM sensor (staggered, 5 days after my other one started) so that I had a CGM sensor session going with good quality data that I could fall back to if my other sensor started to get jumpy, because the sensor session was supposed to end the night of day 4 of my planned run. I obviously didn’t run day 4, but even so I was glad to have another sensor going (worth the cost of overlapping my sensors) in order to have the reassurance of constant data if the first one died or fell out and I could seamlessly switch to an already-warmed up sensor with good data. I didn’t need it, but I was glad to have done that in prep.

(Because I didn’t talk about diabetes a lot in this post, because it was not very relevant to my experiences here, you might want to check out my previous race recaps and posts about utlrarunning like this one where I talk in more detail about balancing fueling, insulin, and glucose management while running for zillions of hours.)

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TLDR: I ran 100 miles, and I did it my DIY way: my own course, my own (slow pace), with sleep breaks, a lot of fueling, and a lot of satisfaction of setting big goals and attempting to achieve them. I think for me, the process goals of figuring out how to even safely attempt ultramarathons are even more rewarding than the mileage milestones of ultrarunning.

Running a multi-day ultramarathon by Dana M. Lewis from DIYPS.org

You’d Be Surprised: Common Causes of Exocrine Pancreatic Insufficiency

by Dana Lewis

Academic and medical literature often is like the game of “telephone”. You can find something commonly cited throughout the literature, but if you dig deep, you can watch the key points change throughout the literature going from a solid, evidence-backed statement to a weaker, more vague statement that is not factually correct but is widely propagated as “fact” as people cite and re-cite the new incorrect statements.

The most obvious one I have seen, after reading hundreds of papers on exocrine pancreatic insufficiency (known as EPI or PEI), is that “chronic pancreatitis is the most common cause of exocrine pancreatic insufficiency”. It’s stated here (“Although chronic pancreatitis is the most common cause of EPI“) and here (“The most frequent causes [of exocrine pancreatic insufficiency] are chronic pancreatitis in adults“) and here (“Besides cystic fibrosis and chronic pancreatitis, the most common etiologies of EPI“) and here (“Numerous conditions account for the etiology of EPI, with the most common being diseases of the pancreatic parenchyma including chronic pancreatitis, cystic fibrosis, and a history of extensive necrotizing acute pancreatitis“) and… you get the picture. I find this statement all over the place.

But guess what? This is not true.

First off, no one has done a study on the overall population of EPI and the breakdown of the most common co-conditions.

Secondly, I did research for my latest article on exocrine pancreatic insufficiency in Type 1 diabetes and Type 2 diabetes and was looking to contextualize the size of the populations. For example, I know overall that diabetes has a ~10% population prevalence, and this review found that there is a median prevalence of EPI of 33% in T1D and 29% in T2D. To put that in absolute numbers, this means that out of 100 people, it’s likely that 3 people have both diabetes and EPI.

How does this compare to the other “most common” causes of EPI?

First, let’s look at the prevalence of EPI in these other conditions:

  • In people with cystic fibrosis, 80-90% of people are estimated to also have EPI
  • In people with chronic pancreatitis, anywhere from 30-90% of people are estimated to also have EPI
  • In people with pancreatic cancer, anywhere from 20-60% of people are estimated to also have EPI

Now let’s look at how common these conditions are in the general population:

  • People with cystic fibrosis are estimated to be 0.04% of the general population.
    • This is 4 in every 10,000 people
  • People with chronic pancreatitis combined with all other types of pancreatitis are also estimated to be 0.04% of the general population, so another 4 out of 10,000.
  • People with pancreatic cancer are estimated to be 0.005% of the general population, or 1 in 20,000.

What happens if you add all of these up: cystic fibrosis, 0.04%, plus all types of pancreatitis, 0.04%, and pancreatic cancer, 0.005%? You get 0.085%, which is less than 1 in 1000 people.

This is quite a bit less than the 10% prevalence of diabetes (1 in 10 people!), or even the 3 in 100 people (3%) with both diabetes and EPI.

Let’s also look at the estimates for EPI prevalence in the general population:

  • General population prevalence of EPI is estimated to be 10-20%, and if we use 10%, that means that 1 in 10 people may have EPI.

Here’s a visual to illustrate the relative size of the populations of people with cystic fibrosis, chronic pancreatitis (visualized as all types of pancreatitis), and pancreatic cancer, relative to the sizes of the general population and the relative amount of people estimated to have EPI:

Gif showing the relative sizes of populations of people with cystic fibrosis, chronic pancreatitis, pancreatic cancer, and the % of those with EPI, contextualized against the prevalence of these in the general population and those with EPI. It's a small number of people because these conditions aren't common, therefore these conditions are not the most common cause of EPI!

What you should take away from this:

  • Yes, EPI is common within conditions such as cystic fibrosis, chronic pancreatitis (and other forms of pancreatitis), and pancreatic cancer
  • However, these conditions are not common: even combined, they add up to less than 1 in 1000!
  • Therefore, it is incorrect to conclude that any of these conditions, individually or even combined, are the most common causes of EPI.

You could say, as I do in this paper, that EPI is likely more common in people with diabetes than all of these conditions combined. You’ll notice that I don’t go so far as to say it’s the MOST common, because I haven’t seen studies to support such a statement, and as I started the post by pointing out, no one has done studies looking at huge populations of EPI and the breakdown of co-conditions at a population level; instead, studies tend to focus on the population of a co-condition and prevalence of EPI within, which is a very different thing than that co-condition’s EPI population as a percentage of the overall population of people with EPI. However, there are some great studies (and I have another systematic review accepted and forthcoming on this topic!) that support the overall prevalence estimates in the general population being in the ballpark of 10+%, so there might be other ‘more common’ causes of EPI that we are currently unaware of, or it may be that most cases of EPI are uncorrelated with any particular co-condition.

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(Need a citation? This logic is found in the introduction paragraph of a systematic review found here, of which the DOI is 10.1089/dia.2023.0157. You can also access a full author copy of it and my other papers here.)

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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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New Systematic Review of Exocrine Pancreatic Insufficiency (EPI) In Type 1 Diabetes and Type 2 Diabetes – Focusing on Prevalence and Treatment

by Dana Lewis

I’m thrilled that the research I did evaluating the prevalence and treatment of EPI in both Type 1 diabetes and Type 2 diabetes (also presented as a poster at #ADA2023 – read a summary of the poster here) has now been published as a full systematic review in Diabetes Technology and Therapeutics.

Here is a pre-edited submitted version of my article that you can access if you don’t have journal access; and as a reminder, copies of ALL of my research articles are available on this page: DIYPS.org/research!

And if you don’t want to read the full paper, this is what I think you should take away from it as a person with diabetes or as a healthcare provider:

    1. What is EPI? 

      Exocrine pancreatic insufficiency (known as EPI in some places, and PEI or PI in other places) occurs when the pancreas no longer produces enough enzymes to digest food. People with EPI take pancreatic enzyme replacement therapy (PERT) whenever they eat (or drink anything with fat/protein).

    2. If I have diabetes, or treat people with diabetes, why should I be reading the rest of this about EPI?EPI often occurs in people with cystic fibrosis, pancreatitis, and pancreatic cancer. However, since these diseases are rare (think <0.1% of the general population even when these groups are added up all together), the total number of people with EPI from these causes is quite low. On the other hand, EPI is also common in people with diabetes, but this is less well-studied and understood. The research on other co-conditions is more frequent and often people confuse the prevalence WITHIN those groups with the % of those conditions occurring overall in the EPI community.This paper reviews every paper that includes data on EPI and people with type 1 diabetes or type 2 diabetes to help us better understand what % of people with diabetes are likely to face EPI in their lifetime.
    3. How many people with type 1 diabetes or type 2 diabetes (or diabetes overall) get EPI?TLDR of the paper: EPI prevalence in diabetes varies widely, reported between 5.4% and 77% when the type of diabetes isn’t specified. For Type 1 diabetes, the median EPI prevalence is 33% (range 14-77.5%), and for Type 2 diabetes, the median is 29% (range 16.8-49.2%). In contrast, in non-diabetes control groups, the EPI prevalence ranges from 4.4% to 18% (median 13%). The differences in ranges might be due to geographic variability and different exclusion criteria across studies.Diabetes itself is prevalent in about 10% of the general population. As such, I hypothesize that people with diabetes likely constitute one of the largest sub-groups of individuals with EPI, in contrast to what I described above might be more commonly assumed.
    4. Is pancreatic enzyme replacement therapy (PERT) safe for people with diabetes? 

      Yes. There have been safety and efficacy studies in people with diabetes with EPI, and PERT is effective just like in any other group of people with EPI.

    5. What is the effect of pancreatic enzyme replacement therapy (PERT) on glucose levels in people with diabetes?
      PERT itself does not affect glucose levels, but PERT *d0es* impact the digestion of food, which then changes glucose levels! So, most PERT labels warn to watch for hypoglycemia or hyperglycemia but the medicine itself doesn’t directly cause changes in glucose levels. You can read a previous study I did here using CGM data to show the effect of PERT actually causing improved glucose after meals in someone with Type 1 diabetes. But, in the systematic review, I found only 4 articles that even made note of glucose levels, and only 1 (the paper I linked above) actually included CGM data. Most of the studies are old, so there are no definitive conclusions on whether hypoglycemia or hyperglycemia is more common when a person with diabetes and EPI starts taking PERT. Instead, it’s likely very individual depending on what they’re eating, insulin dosing patterns before, and whether they’re taking enough PERT to match what they’re eating.TLDR here: more studies are needed because there’s no clear single directional effect on glucose levels from PERT in people with diabetes.Note: based on the n=1 study above, and subsequent conversations with other people with diabetes, I hypothesize that high variability and non-optimal post-meal glucose outcomes may be an early ‘symptom’ of EPI in people with diabetes. I’m hoping to eventually generate some studies to evaluate whether we could use this type of data as an input to help increase screening of EPI in people with diabetes.
    6. How common is EPI (PEI / PI) compared to celiac and gastroparesis in Type 1 diabetes and Type 2 diabetes? 

      As a person with (in my case, Type 1) diabetes, I feel like I hear celiac and gastroparesis talked about often in the diabetes community. I had NEVER heard of EPI prior to realizing I had it. Yet, EPI prevalence in Type 1 and Type 2 diabetes is much higher than that of celiac or gastroparesis!The prevalence of EPI is much higher in T1 and T2 than the prevalence of celiac and gastroparesis.Celiac disease is more common in people with diabetes (~5%) than in the general public (0.5-1%). Gastroparesis, when gastric emptying is delayed, is also more common in people with diabetes (5% in PWD).However, the  prevalence of EPI is 14-77.5% (median 33%) in Type 1 diabetes and 16.8-49.2% (median 29%) in Type 2 diabetes (and 5.4-77% prevalence when type of diabetes was not specified). This again is higher than general population prevalence of EPI.

      This data emphasizes that endocrinologists and other diabetes care providers should be more prone to initiate screening (using the non-invasive fecal elastase test) for individuals presenting with gastrointestinal symptoms, as the rates of EPI in diabetes are much higher in both Type 1 and Type 2 diabetes than the rates of celiac and gastroparesis.

    7. What should I do if I think I have EPI?
      Record your symptoms and talk to your doctor and ask for a fecal elastase (FE-1) screening test for EPI. It’s non-invasive. If your results are less than or equal to 200 (μg/g), this means you have EPI and should start on PERT. If you or your doctor feel that your sample may have influenced the results of your test, you can always re-do the test. But if you’re dealing with diarrhea, going on PERT may resolve or improve the diarrhea and improve the quality of the sample for the next test result. PERT doesn’t influence the test result, so you can start PERT and re-run the test any time.Symptoms of EPI can vary. Some people experience diarrhea, while others experience constipation. Steatorrhea or smelly, messy stools that stick to the side of the toilet are also common EPI symptoms, as is bloating, abdominal pain, and generally not feeling well after you eat.

      If you’ve been diagnosed with EPI, you may also want to check out some of my other posts (DIYPS.org/EPI) about my personal experiences with EPI and also this post about the amount of enzymes needed by most people with EPI. You may also want to check out PERT Pilot, a free iOS app, for recording and evaluating your PERT dosing.

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If you want to read the full article, you can find copies of all of my research articles at DIYPS.org/research

If you’d like to cite this specific article in your future research, here’s an example citation:

Lewis, D. A Systematic Review of Exocrine Pancreatic Insufficiency Prevalence and Treatment in Type 1 and Type 2 Diabetes. Diabetes Technology & Therapeutics. http://doi.org/10.1089/dia.2023.0157

Why DIY AID in 2023? #ADA2023 Debate

by Dana Lewis

I was asked to participate in a ‘debate’ about AID at #ADA2023 (ADA Scientific Sessions), representing the perspective that DIY systems should be an option for people living with diabetes.

I present this perspective as a person with type 1 diabetes who has been using DIY AID for almost a decade (and as a developer/contributor to the open source AID systems used in DIY) – please note my constant reminder that I am not a medical doctor.

Dr. Gregory P. Forlenza, an Associate Professor from Barbara Davis Center, presented a viewpoint as a medical doctor practicing in the US.

FYI: here are my disclosures and Dr. Forlenza’s disclosures:

On the left is my slide (Dana M. Lewis) showing I have no commercial support or conflicts of interest. My research in the last 3 years has previously been funded by the New Zealand Health Research Council (for the CREATE Trial); JDRF; and DiabetesMine. Dr. Forlenza lists research support from NIH, JDRF, NSF, Helmsley Charitable Trust, Medtronic, Dexcom, Abbott, Insulet, Tandem, Beta Bionics, and Lilly. He also lists Consulting/Speaking/AdBoard: Medtronic, Dexcom, Abbott, Insulet, Tandem, Beta Bionics, and Lilly.

I opened the debate with my initial presentation. I talk about the history of DIY in diabetes going back to the 1970s, when people with diabetes had to “DIY” with blood glucose meters because initially healthcare providers did not want people to fingerstick at home because they might do something with the information. Similarly, even insulin pumps and CGMs have been used in different “DIY” ways over the years – notably, people with diabetes began dosing insulin using CGM data for years prior to them being approved for that purpose. It’s therefore less of a surprise in that context to think about DIY being done for AID. (If you’re reading this you probably also know that DIY AID was done years before commercial AID was even available; and that there are multiple DIY systems with multiple pump and CGM options, algorithms, and phone options).

And, for people with diabetes, using DIY is very similar to how a lot of doctors recommend or prescribe doing things off label. Diabetes has a LOT of these types of recommendations, whether it’s different types of insulins used in pumps that weren’t approved for that type of insulin; medications for Type 2 being used for Type 1 (and vice versa); and other things that aren’t regulatory approved at all but often recommended anyway. For example, GLP-1’s that are approved for weight management and not glycemic control, but are often prescribed for glycemic control reasons. Or things like Vitamin D, which are widely prescribed or recommended as a supplement even though it is not regulatory-approved as a pharmaceutical agent.

I always like to emphasize that although open source AID is not necessarily regulated (but can be: one open source system has received regulatory clearance recently), that’s not a synonym for ‘no evidence’. There’s plenty of high quality scientific evidence on DIY use and non-DIY use of open source AID. There’s even a recent RCT in the New England Journal of Medicine, not to mention several other RCTs (see here and here, plus another pending publication forthcoming). In addition to those gold-standard RCTs, there are also reviews of large-scale big data datasets from people with diabetes using AID, such as this one where we reviewed 122 people’s glucose data representing 46,070 days’ worth of data; or another forthcoming publication where we analyzed the n=75 unique (distinct from the previous dataset) DIY AID users with 36,827 days’ of data (average of 491 days per participant) and also found above goal TIR outcomes (e.g. mean TIR 70-180 mg/dL of 82.08%).

Yet, people often choose to DIY with AID not just for the glucose outcomes. Yes, commercial AID systems (especially now second-generation) can similarly reach the goal of 70+% TIR on average. DIY helps provide more choices about the type and amount of work that people with diabetes have to put IN to these systems in order to get these above-goal OUTcomes. They can choose, overall or situationally, whether to bolus, count carbs precisely, announce meals at all, or only announce relative meal size while still achieving >80% TIR, no or little hypoglycemia, and less hyperglycemia. Many people using DIY AID for years have been doing no-bolus and/or no meal announcements at all, bringing this closer to a full closed loop, or at least, an AID system with very, very little user input required on a daily basis if they so choose. I presented data back in 2018(!) showing how this was being done in DIY AID, and it was recently confirmed in a randomized control trial (hello, gold standard!) showing that between traditional use (with meal announcements and meal boluses); meal announcement only (no boluses); and no announcement nor bolusing, that they all got similar outcomes in terms of TIR (all above-goal). There was also no difference in those modes of total daily insulin dose (TDD) or amount of carb intake. There was a small difference in time below range being slightly higher in the first mode (where people were counting carbs and bolusing) as compared to the other two modes – which suggests that MORE user input may actually be limiting the capabilities of the system!

The TLDR here is that people with diabetes can do less work/provide less input into AID and still achieve the same level of ideal, above-goal outcomes – and ongoing studies are showing the increased QOL and other patient-reported outcomes that also improve as a result.

Again, people may be predisposed to think that the main difference between commercial and DIY is whether or not it is regulatory approved (and therefore prescribable by doctors and able to be supported by a company under warranty); the bigger differences are instead around interoperability across devices, data access, and transparency of how the system works.

There’s even an international consensus statement on open source AID, created by an international group of 48 medical and legal experts, endorsed by 9 national and international diabetes organizations, supporting that open source AID used in DIY AID is a safe and effective treatment option, confirming that the scientific evidence exists and it has the potential to help people with diabetes and reduce the burden of diabetes. They emphasize that doctors should support patient (and caregiver) autonomy and choice of DIY AID, and state that doctors have a responsibility to learn about all options that exist including DIY. The consensus statement is focused on open source AID but also, in my opinion, applies to all AID: they say that AID systems should fully disclose how they operate to enable informed decisions and that all users should have real-time and open access to their own data. Yes, please! (This is true of DIY but not true of all commercial systems.)

The elephant in the room that I always bring up is cost, insurance coverage, and therefore access and accessibility of AID. Many places have government or insurance that won’t cover AID. For example, the proposed NICE guidelines in the UK wouldn’t provide AID to everyone who wants one. In other places, some people can get their pump covered but not CGM, or vice versa, and must pay out of pocket. Therefore in some cases, DIY has out of pocket costs (because it’s not covered by insurance), but is still cheaper than AID with insurance coverage (if it’s even covered).

I also want to remind everyone that choosing to DIY – or not – is not a once-in-a-lifetime decision. People who use DIY choose every day to use it and continue to use it; at any time, they could and some do choose to switch to a commercial system. Others try commercial, switch back to DIY, and switch back and forth over time for various reasons. It’s not a single or permanent decision to DIY!

The key point is: DIY AID provides safety and efficacy *and* user choice for people with diabetes.

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Dr. Forlenza followed my presentation, talking about commercial AID systems and how they’ve moved through development more quickly recently. He points to the RCTs for each approved commercial system that exist, saying commercial AID systems work, and describing different feature sets and variety across commercial systems. He shared his thoughts on advantages of commercial systems including integration between components by the companies; regulatory approval meaning these systems can be prescribed by healthcare providers; company-provided warranties; and company provided training and support of healthcare providers and patients.

He makes a big point about a perceived reporting bias in social media, which is a valid point, and talks about people who cherry pick (my words) data to share online about their TIR.

He puts an observational study and the CREATE Trial RCT data up next to the commercial AID systems RCT data, showing how the second generation commercial AID reach similar TIR outcomes.

He then says “what are you #notwaiting for?”, pointing out in the US that there are 4 commercial systems FDA approved for type 1 diabetes. He says “Data from the DIY trials themselves demonstrate that DIY users, even with extreme selection bias, do not achieve better glycemic control than is seen with commercial systems.” He concludes that commercial AID has a wide variety of options; commercial systems achieve target-level outcomes; a perception that both glucose outcomes and QOL are being addressed by the commercial market, and that “we do not need Unapproved DIY solutions in this space”.

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After Dr. Forlenza’s presentation, I began my rebuttal, starting with pointing out that he is incorrectly conflating perceived biases/self-reporting of social media posts with gold-standard, rigorously performed scientific trials evaluating DIY. Data from DIY AID trials do not suffer from ‘selection bias’ any more than commercial AID trials do. (In fact, all clinical trials have their own aspects of selection bias, although that isn’t the point here.) I reminded the audience of the not one but multiple RCTs available as well as dozens of other prospective and retrospective clinical trials. Plus, we have 82,000+ data points analyzed showing above-goal outcomes, and many studies that evaluate this data and adjust for starting outcomes still show that people with diabetes who use DIY AID benefit from doing so, regardless of their starting A1c/TIR or demographics. This isn’t cherry-picked social media anecdata.

When studies are done rigorously, as they have been done in DIY, we agree that now second-generation commercial AID systems reach (or exceed, depending on the system) ADA standard of care outcomes. For example, Dr. Forlenza cited the OP5 study with 73.9% TIR which is similar to the CREATE Trial 74.5% TIR.

My point is not that commercial systems don’t work; my point is that DIY systems *do* work and that the fact that commercial systems work doesn’t then override the fact that DIY systems have been shown to work, also! It’s a “yes, and”! Yes, commercial AID systems work; and yes, DIY AID systems work.

The bigger point, which Dr. Forlenza does not address, is that the person with diabetes should get to CHOOSE what is best for them, which is not ONLY about glucose outcomes. Yes, a commercial system- like DIY AID – may help someone get to goal TIR (or above goal), but DIY provides more choice in terms of the input behaviors required to achieve those outcomes! There’s also possible choice of systems with different pumps or CGMs, different (often lower) cost, increased data access and interoperability of data displays, different mobile device options, and more.

Also, supporting user choice of DIY is in fact A STANDARD OF CARE!

It’s in the ADA’s Standards of Care, in fact, as I wrote about here when observing that it’s in the 2023 Standards of Care…as well as in 2022, 2021, 2020, and 2019!

I wouldn’t be surprised if there are people attending the debate who think they don’t have any – or many – patients using DIY AID. For those who think that (or are reading this thinking the same), I ask a question: how many patients have you asked if they are using DIY AID?

There’s a bunch of reasons why it may not come up, if you haven’t asked:

  • They may use the same consumables (sites, reservoirs) with a different or previous pump in a DIY AID system.
  • Their prescribed pump (particularly in Europe and non-US places that have Bluetooth-enabled pumps) may be usable in a DIY AID.
  • They may not be getting their supplies through insurance, so their prescription doesn’t match what they are currently using.
  • Or, they have more urgent priorities to discuss at appointments, so it doesn’t come up.
  • Or, it’s also possible that it hasn’t come up because they don’t need any assistance or support from their healthcare provider.

Speaking of learning and support, it’s worth noting that in DIY AID, because it is open source and the documentation is freely available, users typically begin learning more about the system prior to initiating their start of closed loop (automated insulin delivery). As a result, the process of understanding and developing trust in the system begins prior to closed loop start as well. In contrast, much of the time there is limited available education prior to receiving the prescription for a commercial AID; it often aligns more closely with the timeline of starting the device. Additionally, because it is a “black box” with fewer available details about exactly how it works (and why), the process of developing trust can be a slower process that occurs only after a user begins to use a commercial device.

With DIY AID, because it is open source and the documentation is freely available, users typically begin learning more about the system prior to initiating their start of closed loop (automated insulin delivery). As a result, the process of understanding and developing trust in the system begins prior to closed loop start as well. In contrast, much of the time there is limited available education prior to receiving the prescription for a commercial AID; it often aligns more closely with the timeline of starting the device. Additionally, because it is a black box with less available details about exactly how it works (and why), the process of developing trust can be a slower process that occurs only after a user begins to use a commercial device. The learning & trust in AID timelines is something that needs more attention in commercial AID moving forward.

I closed my rebuttal section by asking a few questions out loud:

I wonder how healthcare providers feel when patients learn something before they do – which is often what happens with DIY AID. Does it make you uncomfortable, excited, curious, or some other feeling? Why?

I encouraged healthcare providers to consider when they are comfortable with off-label prescriptions (or recommending things that aren’t approved, such as Vitamin D), and reflect on how that differs from understanding patients’ choices to DIY.

I also prompted everyone to consider whether they’ve actually evaluated (all of) the safety and efficacy data, of which many studies exist. And to consider who benefits from each type of system, not only commercial/DIY but individual systems within those buckets. And to consider who gets offered/prescribed AID systems (of any sort) and whether subconscious biases around tech literacy, previous glucose outcomes, and other factors (race, gender, other demographic variables) result in particular groups of people being excluded from accessing AID. I also remind everyone to think about what financial incentives influence access and available of AID education, and where the education comes from.

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Although Dr. Forlenza’s  rebuttal followed mine, I’ll summarize it here before finishing a recap of my rebuttal: he talks about individual selection bias/cherry picked data, acknowledging it can occur in anecdotes with commercial systems as well; talks about the distinction of regulatory approval vs. off label and unapproved; legal concerns for healthcare providers; and closes pointing out that many PWD see primary care providers, he doesn’t believe it is reasonable to expect PCPs to become familiar with DIY since there are no paid device representatives to support their learning, and that growth of AID requires industry support.

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People probably wanted to walk out of this debate with a black and white, clear answer on what is the ‘right’ type of AID system: DIY or commercial. The answer to that question isn’t straightforward, because it depends.

It depends on whether a system is even AVAILABLE. Not all countries have regulatory-approved systems available, meaning commercial AID is not available everywhere. Some places and people are also limited by ACCESSIBILITY, because their healthcare providers won’t prescribe an AID system to them; or insurance won’t cover it. AFFORDABILITY, even with insurance coverage, also plays a role: commercial AID systems (and even pump and CGM components without AID) are expensive and not everyone can afford them. Finally, ADAPTABILITY matters for some people, and not all systems work well for everyone.

When these factors align – they are available, accessible, affordable, and adaptable – that means for some people in some places in some situations, there are commercial systems that meet those needs. But for other people in other places in other situations, DIY systems instead or also can meet that need.

The point is, though, that we need a bigger overlap of these criteria! We need MORE AID systems to be available, accessible, affordable, and adaptable. Those can either be commercial or DIY AID systems.

The point that Dr. Forlenza and I readily agree on is that we need MORE AID – not less.

This is why I support user choice for people with diabetes and for people who want – for any variety of reasons – to use a DIY system to be able to do so.

People probably want a black and white, clear answer on what is the ‘right’ type of AID system: DIY or commercial. It depends on whether a system is even AVAILABLE. Not all countries have regulatory-approved systems available, meaning commercial AID is not available everywhere. Some places and people are also limited by ACCESSIBILITY, because their healthcare providers won’t prescribe an AID system to them; or insurance won’t cover it. AFFORDABILITY, even if insurance coverage, also plays a role: commercial AID systems (and even pump and CGM components without AID) are expensive and not everyone can afford them. Finally, ADAPTABILITY matters for some people, and not all systems work well for everyone. The point is that we need a bigger overlap of these criteria! We need more alignment of these factors - more AID (DIY and commercial) available, accessible, affordable, and adaptable for people with diabetes. I support user choice for people with diabetes, which includes DIY AID systems

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PS – I also presented a poster at #ADA2023 about the high prevalence rates of exocrine pancreatic insufficiency (EPI / PEI / PI) in Type 1 and Type 2 diabetes – you can find the poster and a summary of it here.

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.

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