Understanding the Difference Between Open Source and DIY in Diabetes

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

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

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

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

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

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

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

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

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

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

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

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

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

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

What is the “continuation phase”?

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

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

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

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

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

What are the results from the continuation phase?

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

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

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

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

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

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

Conclusion of the continuation study from the CREATE trial

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

Key points to takeaway:

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

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

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

Example citation:

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


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

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

The backstory on this study

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

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

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

Study Design:

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

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

Results:

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

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

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

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

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

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

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

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

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

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

In summary:

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

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


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

Example citation:

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

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

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

Automated Insulin Delivery: How artificial pancreas “closed loop” systems can aid you in living with diabetes (introducing “the APS book” by @DanaMLewis)

Tl;dr – I wrote a book about artificial pancreas systems / hybrid and fully closed loop systems / automated insulin delivery systems! It’s out today – you can buy a print copy on Amazon; a Kindle copy on Amazon; check out all the content on the web or your phone here; or download a PDF if you prefer.

A few months ago, I saw someone share a link to one of my old blog posts with someone else on Facebook. Quite old in fact – I had written it 5+ years ago! But the content was and is still relevant today.

It made me wonder – how could we as a diabetes community, who have been innovating and exploring new diabetes technology such as closed loop/artificial pancreas systems (APS), package up some of this knowledge and share it with people who are newer to APS? And while yes, much of this is tucked into the documentation for DIY closed loop systems, not everyone will choose a DIY closed loop system and also therefore may not see or find this information. And with regards to some of the things I’ve written here on DIYPS.org, not everyone will be lucky enough to have the right combination of search terms to end up on a particular post to answer their question.

Automated_Insulin_Delivery_by_DanaMLewis_example_covers_renderingThus, the idea for a book was born. I wanted to take much of what I’ve been writing here, sharing on Facebook and Twitter, and seeing others discuss as well, and put it together in one place to be a good starting place for someone to learn about APS in general. My hope is that it’s more accessible for people who don’t know what “DIY” or “open source” diabetes is, and it’s findable by people who also don’t know or don’t consider themselves to be part of the “diabetes online community”.

APSBook_NowAvailable_DanaMLewisIs it perfect? Absolutely not! But, like most of the things in the DIY community…the book is open source. Seriously. Here’s the repository on Github! If you see a typo or have suggestions of content to add, you can make a PR (pull request) or log an issue with content recommendations. (There’s instructions on the book page here with how to do either of those things!) I plan to make rolling updates to it, so you can see on the change log page what’s changed between major versions.)

It’s the first book out there that I know of on APS, but it won’t be the only one. I hope this inspires or moves more people to share their knowledge, through blogs or podcasts or future books, with the rest of our community and loved ones who want and need to learn more about managing type 1 diabetes.

“I will immediately recommend this book not just to people looking to use a DIY closed loop system, but also to anybody looking to improve their grasp on the management of type 1 diabetes, whether patient, caregiver, or healthcare provider.”

Aaron Neinstein, MD
Endocrinologist, UCSF

And as always, I’m happy to share what I’ve learned about the self-publishing process, too. I previously used CreateSpace for my children’s books, which got merged with Amazon’s Kindle Direct Publishing (KDP), and there was a learning curve for KDP for both doing the print version and doing the Kindle version. I didn’t get paid to write this book – and I didn’t write it for a profit. Like my children’s books, I plan to use any proceeds to donate copies to libraries and hospitals, and send any remaining funds to Life For A Child to help ensure as many kids as possible have access to insulin, BG monitoring supplies, and education.

I’m incredibly grateful for many people for helping out with and contributing to this book. You can see the full acknowledgement section with my immense thanks to the many reviewers of early versions of the book! And ditto for the people who shared their stories and experiences with APS. But special thanks go in particular to Scott for thorough first editing and overall support of every project I bring up out of the blue; to Tim Gunn for beautiful cover design of the book; and to Aaron Kowalski to be kind enough to write this amazing foreword.

Amazon_Button_APSBook_DanaMLewis

Presentations and poster content from @DanaMLewis at #ADA2019

Like I did last year, I want to share the work being presented at #ADA2019 with those who are not physically there! (And if you’re presenting at #ADA2019 or another conference and would like suggestions on how to share your content in addition to your poster or presentation, check out these tips.) This year, I’m co-author on three posters and an oral presentation.

  • 1056-P in category 12-D Clinical Therapeutics/New Technology–Insulin Delivery Systems, Preliminary Characterization of Rhythmic Glucose Variability In Individuals With Type 1 Diabetes, co-authored by Dana Lewis and Azure Grant.
    • Come see us at the poster session, 12-1pm on Sunday! Dana & Azure will be presenting this poster.
  • 76-OR, In-Depth Review of Glycemic Control and Glycemic Variability in People with Type 1 Diabetes Using Open Source Artificial Pancreas Systems, co-authored by Andreas Melmer, Thomas Züger, Dana Lewis, Scott Leibrand, Christoph Stettler, and Markus Laimer.
    • Come hear our presentation in room S-157 (South, Upper Mezzanine Level), 2:15-2:30 pm on Saturday!
  • 117-LB, DIWHY: Factors Influencing Motivation, Barriers and Duration of DIY Artificial Pancreas System Use Among Real-World Users, co-authored by Katarina Braune, Shane O’Donnell, Bryan Cleal, Ingrid Willaing, Adrian Tappe, Dana Lewis, Bastian Hauck, Renza Scibilia, Elizabeth Rowley, Winne Ko, Geraldine Doyle, Tahar Kechadi, Timothy C. Skinner, Klemens Raille, and the OPEN consortium.
    • Come see us at the poster session, 12-1pm on Sunday! Scott will be presenting this poster.
  • 78-LB, Detailing the Lived Experiences of People with Diabetes Using Do-it-Yourself Artificial Pancreas Systems – Qualitative Analysis of Responses to Open-Ended Items in an International Survey, co-authored by Bryan Cleal, Shane O’Donnell, Katarina Braune, Dana Lewis, Timothy C. Skinner, Bastian Hauck, Klemens Raille, and the OPEN consortium.
    • Come see us at the poster session, 12-1pm on Sunday! Bryan Cleal will be presenting this poster.

See below for full written summaries and pictures from each poster and the oral presentation.

First up: the biological rhythms poster, formally known as 1056-P in category 12-D Clinical Therapeutics/New Technology–Insulin Delivery Systems, Preliminary Characterization of Rhythmic Glucose Variability In Individuals With Type 1 Diabetes!

Lewis_Grant_BiologicalRhythmsT1D_ADA2019

As mentioned in this DiabetesMine interview, Azure Grant & I were thrilled to find out that we have been awarded a JDRF grant to further this research and undertake the first longitudinal study to characterize biological rhythms in T1D, which could also be used to inform improvements and personalize closed loop systems. This poster is part of the preliminary research we did in order to submit for this grant.

There is also a Twitter thread for this poster:

Poster from #ADA2019

Background:

  • Human physiology, including blood glucose, exhibits rhythms at multiple timescales, including hours (ultradian, UR), the day (circadian, CR), and the ~28-day female ovulatory cycle (OR).
  • Individuals with T1D may suffer rhythmic disruption due not only to the loss of insulin, but to injection of insulin that does not mimic natural insulin rhythms, the presence of endocrine-timing disruptive medications, and sleep disruption.
  • However, rhythms at multiple timescales in glucose have not been mapped in a large population of T1D, and the extent to which glucose rhythms differ in temporal structure between T1D and non-T1D individuals is not known.

Data & Methods:

  • The initial data set used for this work leverages the OpenAPS Data Commons. (This data set is available for all researchers  – see www.OpenAPS.org/data-commons)
  • All data was processed in Matlab 2018b with code written by Azure Grant. Frequency decompositions using the continuous morlet wavelet transformation were created to assess change in rhythmic composition of normalized blood glucose data from 5 non-T1D individuals and anonymized, retrospective CGM data from 19 T1D individuals using a DIY closed loop APS. Wavelet algorithms were modified from code made available by Dr. Tanya Leise at Amherst College (see http://bit.ly/LeiseWaveletAnalysis)

Results:

  • Inter and Intra-Individual Variability of Glucose Ultradian and Circadian Rhythms is Greater in T1D
Figure_BiologicalRhythms_Lewis_Grant_ADA2019

Figure 1. Single individual blood glucose over ~ 1 year with A.) High daily rhythm stability and B.) Low daily rhythm stability. Low glucose is shown in blue, high glucose in orange.

Figure 2. T1D individuals (N=19) showed a wide range of rhythmic power at the circadian and long-period ultradian timescales compared to individuals without T1D (N=5).

A). Individuals’ CR and UR power, reflecting amplitude and stability of CRs, varies widely in T1D individuals compared to those without T1D. UR power was of longer periodicity (>= 6 h) in T1D, likely due to DIA effects, whereas UR power was most commonly in the 1-3 hour range in non-T1D individuals (*not shown).  B.) On average, both CR and UR power were significantly higher in T1D (p<.05, Kruskal Wallis). This is most likely due to the higher amplitude of glucose oscillation, shown in two individuals in C.

Conclusions:

  • This is the first longitudinal analysis of the structure and variability of multi-timescale biological rhythms in T1D, compared to non-T1D individuals.
  • Individuals with T1D show a wide range of circadian and ultradian rhythmic amplitudes and stabilities, resulting in higher average and more variable wavelet power than in a smaller sample of non-T1D individuals.
  • Ultradian rhythms of people with T1D are of longer periodicity than individuals without T1D. These analyses constitute the first pass of a subset of these data sets, and will be continued over the next year.

Future work:

  • JDRF has recently funded our exploration of the Tidepool Big Data Donation Project, the OpenAPS Data Commons, and a set of non-T1D control data in order to map biological rhythms of glucose/insulin.
  • We will use signal processing techniques to thoroughly characterize URs, CRs, and ORs in the glucose/insulin for T1D; evaluate if stably rhythmic timing of glucose is associated with improved outcomes (lower HBA1C); and ultimately evaluate if modulation of insulin delivery based on time of day or time of ovulatory cycle could lead to improved outcomes.
  • Mapping population heterogeneity of these rhythms in people with and without T1D will improve understanding of real-world rhythmicity, and may lead to non-linear algorithms for optimizing glucose in T1D.

Acknowledgements:

We thank the OpenAPS community for their generous donation of data, and JDRF for the grant award to further this work, beginning in July 2019.

Contact:

Feel free to contact us at Dana@OpenAPS.org or azuredominique@berkeley.edu.

Next up, 78-LB, Detailing the Lived Experiences of People with Diabetes Using Do-it-Yourself Artificial Pancreas Systems – Qualitative Analysis of Responses to Open-Ended Items in an International Survey, co-authored by Bryan Cleal, Shane O’Donnell, Katarina Braune, Dana Lewis, Timothy C. Skinner, Bastian Hauck, Klemens Raille, and the OPEN consortium.

78-LB_LivedExperiencesDIYAPS_OPEN_ADA2019

There is also a Twitter thread for this poster:

Poster from OPEN survey on lived experiences

Introduction

There is currently a wave of interest in Do-it-Yourself Artificial Pancreas Systems (DIYAPS), but knowledge about how the use of these systems impacts on the lives of those that build and use them remains limited. Until now, only a select few have been able to give voice to their experiences in a research context. In this study we present data that addresses this shortcoming, detailing the lived experiences of people using DIYAPS in an extensive and diverse way.

Methods

An online survey with 34 items was distributed to DIYAPS users recruited through the Facebook groups “Looped” (and regional sub-groups) and Twitter pages of the Diabetes Online Community (DOC). Participants were posed two open-ended questions in the survey, where personal DIYAPS stories were garnered; including knowledge acquisition, decision-making, support and emotional aspects in the initiation of DIYAPS, perceived changes in clinical and quality of life (QoL) outcomes after initiation and difficulties encountered in the process. All answers were analyzed using thematic content analysis.

Results

In total, 886 adults responded to the survey and there were a combined 656 responses to the two open-ended items. Knowledge of DIYAPS was primarily obtained via exposure to the communication fora that constitute the DOC. The DOC was also a primary source of practical and emotional support (QUOTES A). Dramatic improvements in clinical and QoL outcomes were consistently reported (QUOTES B). The emotional impact was overwhelmingly positive, with participants emphasizing that the persistent presence of diabetes in everyday life was markedly reduced (QUOTES C). Acquisition of the requisite devices to initiate DIYAPS was sometimes problematic and some people did find building the systems to be technically challenging (QUOTE D). Overcoming these challenges did, however, leave people with a sense of accomplishment and, in some cases, improved levels of understanding and engagement with diabetes management (QUOTE E).

QuotesA_OPEN_ADA2019 QuotesB_OPEN_ADA2019 QuotesC_OPEN_ADA2019 QuotesD_OPEN_ADA2019 QuotesE_OPEN_ADA2019

Conclusion

The extensive testimony from users of DIYAPS acquired in this study provides new insights regarding the contours of this evolving phenomenon, highlighting factors inspiring people to adopt such solutions and underlining the transformative impact effective closed-loop systems bring to bear on the everyday lives of people with diabetes. Although DIYAPS is not a viable solution for everyone with type 1 diabetes, there is much to learn from those who have taken this route, and the life-changing results they have achieved should inspire all with an interest in artificial pancreas technology to pursue and dream of a future where all people with type 1 diabetes can reap the benefits that it potentially provides.

Also, see this word cloud generated from 665 responses in the two open-ended questions in the survey:

Wordle_OPEN_ADA2019

Next up is 117-LB, DIWHY: Factors Influencing Motivation, Barriers and Duration of DIY Artificial Pancreas System Use Among Real-World Users, co-authored by Katarina Braune, Shane O’Donnell, Bryan Cleal, Ingrid Willaing, Adrian Tappe, Dana Lewis, Bastian Hauck, Renza Scibilia, Elizabeth Rowley, Winne Ko, Geraldine Doyle, Tahar Kechadi, Timothy C. Skinner, Klemens Raille, and the OPEN consortium.

DIWHY_117-LB_OPEN_ADA2019

There is also a Twitter thread for this poster:

DIWHY Poster at ADA2019

Background

Until recently, digital innovations in healthcare have typically followed a ‘top-down’ pathway, with manufacturers leading the design and production of technology-enabled solutions and patients involved only as users of the end-product. However, this is now being disrupted by the increasing influence and popularity of more ‘bottom-up’ and patient-led open source initiatives. A primary example is the growing movement of people with diabetes (PwD) who create their own “Do-it-Yourself” Artificial Pancreas Systems (DIY APS) through remote-control of medical devices employing an open source algorithm.

Objective

Little is known about why PwD leave traditional care pathways and turn to DIY technology. This study aims to examine the motivations of current DIYAPS users and their caregivers.

Research Design and Methods

An online survey with 34 items was distributed to DIYAPS users recruited through the Facebook groups “Looped” (and regional sub-groups) and Twitter pages of the “DOC” (Diabetes Online Community). Self-reported data was collected, managed and analyzed using the secure REDCap electronic data capture tools hosted at Charité – Universitaetsmedizin Berlin.

Results

1058 participants from 34 countries (81.3 % Europe, 14.7 % North America, 6.0 % Australia/WP, 3.1 % Asia, 0.1 % Africa), responded to the survey, of which the majority were adults (80.2 %) with type 1 diabetes (98.9 %) using a DIY APS themselves (43.0 % female, 56.8 % male, 0.3 % other) with a median age of 41 y and an average diabetes duration of 25.2y ±13.3. 19.8 % of the participants were parents and/or caregivers of children with type 1 diabetes (99.4 %) using a DIY APS (47.4 % female, 52.6 % male) with a median age of 10 y and an average diabetes duration of 5.1y ± 3.8. People used various DIYAPS (58.2 % AndroidAPS, 28.5 % Loop, 18.8 % OpenAPS, 5.7 % other) on average for a duration of 10.1 months ±17.6 and reported an overall HbA1c-improvement of -0.83 % (from 7.07 % ±1.07 to 6.24 % ±0.68 %) and an overall Time in Range improvement of +19.86 % (from 63.21 % ±16.27 to 83.07 % ±10.11). Participants indicated that DIY APS use required them to pay out-of-pocket costs in addition to their standard healthcare expenses with an average amount of 712 USD spent per year.

Primary motivations for building a DIYAPS were to improve the overall glycaemic control, reduce acute and long-term complication risk, increase life expectancy and to put diabetes on ‘auto-pilot’ and interact less frequently with the system. Lack of commercially available closed loop systems and improvement of sleep quality was a motivation for some. For caregivers, improvement of their own sleep quality was the leading motivation. For adults, curiosity (medical or technical interest) had a higher impact on their motivation compared to caregivers. Some people feel that commercial systems do not suit their individual needs and prefer to use a customizable system, which is only available to them as a DIY solution. Other reasons, like costs of commercially available systems and unachieved therapy goals played a subordinate role. Lack of medical or psychosocial support was less likely to be motivating factors for both groups.

Figure_OPEN_DIWHY_ADA2019

Conclusions

Our findings suggest that people using Do-it-Yourself Artificial Pancreas systems and their caregivers are highly motivated to improve their/their children’s diabetes management through the use of this novel technology. They are also able to access and afford the tools needed to use these systems. Currently approved and available commercial therapy options may not be sufficiently flexible or customizable enough to fulfill their individual needs. As part of the project “OPEN”, the results of the DIWHY survey may contribute to a better understanding of the unmet needs of PwD and current challenges to uptake, which will, in turn, facilitate dialogue and collaboration to strengthen the involvement of open source approaches in healthcare.

This is a written version of the oral presentation, In-Depth Review of Glycemic Control and Glycemic Variability in People with Type 1 Diabetes Using Open Source Artificial Pancreas Systems, co-authored by Andreas Melmer, Thomas Züger, Dana Lewis, Scott Leibrand, Christoph Stettler, and Markus Laimer.

APSComponents_Melmer_ADA2019

Artificial Pancreas Systems (APS) now exist, leveraging a CGM sensor, pump, and control algorithm. Faster insulin can play a role, too.  Traditionally, APS is developed by commercial industry, tested by clinicians, regulated, and then patients can access it. However, DIYAPS is designed by patients for individual use.

There are now multiple different kinds of DIYAPS systems in use: #OpenAPS, Loop, and AndroidAPS. There are differences in hardware, pump, and software configurations. The main algorithm for OpenAPS is also used in AndroidAPS.  DIYAPS can work offline; and also leverage the cloud for accessing or displaying data, including for remote monitoring.OnlineOffline_Melmer_ADA2019

This study analyzed data from the OpenAPS Data Commons (see more here). At the time this data set was used, there were n=80 anonymized data donors from the #OpenAPS community, with a combined 53+ years worth of CGM data.

TIR_PostLooping_Melmer_ADA2019Looking at results for #OpenAPS data donors post-looping initiation, CV was 35.5±5.9, while eA1c was 6.4±0.7. TIR (3.9-10mmol/L) was 77.5%. Time spent >10 was 18.2%; time <3.9 was 4.3%.

SubcohortData_Melmer_ADA2019We selected a subcohort of n=34 who had data available from before DIY closed looping initiation (6.5 years combined of CGM records), as well as data from after (12.5 years of CGM records).

For these next set of graphs, blue is BEFORE initiation (when just on a traditional pump); red is AFTER, when they were using DIYAPS.

TIR_PrePost_Melmer_ADA2019Time in a range significantly increased for both wider (3.9-10 mmol/L) and tighter (3.9-7.8 mmol/L) ranges.

TOR_PrePost_Melmer_ADA2019Time spent out of range decreased. % time spent >10 mmol/L decreased -8.3±8.6 (p<0.001); >13 mmol/L decreased -3.3±5.0 (p<0.001). Change in % time spent <3.9 mmol/L (-1.1±3.8 (p=0.153)), and <3.0 mmol/L (-0.7±2.2 (p=0.017)) was not significant.

We also analyzed daytime and nightime (the above was reflecting all 24hr combined; these graphs shows the increase in TIR and decrease in time out of range for both day and night).

TIR_TOR_DayAndNight_Melmer_ADA2019

Hypoglemic_event_reduction_Melmer_ADA2019There were less CGM records in the hypoglycemic range after initiating DIYAPS.

Conclusion: this was a descriptive study analyzing available CGM data from  #OpenAPS Data Commons. This study shows OpenAPS has potential to support glycemic control. However, DIYAPS are currently not regulated/approved technology. Further research is recommended.

Conclusion_Melmer_ADA2019

(Note: a version of this study has been submitted and accepted for publication in the Journal of Diabetes. Obesity, and Metabolism.)

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

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

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

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

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

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

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

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

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

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

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

Other advice for the return to weight-bearing:

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

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

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

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

Using my nephew's stroller to support me walking in a boot after my ankle fracture as I returned to weight bearing

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

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

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

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

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

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

Proof that I did get there:

Lots of 100 emojis celebrating 100% weight bearing after my broken ankle

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

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

Broken bones (trimalleolar ankle fracture), type 1 diabetes, and #OpenAPS

In January, Scott and I planned and went on a three day hiking trip in New Zealand. NZ is famous for “tramping” and “trekking”, and since we were in the country for a conference (you can see my talk at LinuxConfAU here!), we decided to give it a try. This was my first true “backpacking” type trip where you carry all your stuff on your back; and the first multi-day hiking experience. You could either rent a cot in a hut and carry all your food and cooking utensils and bedding on your back; or you could pay to hike with a company who has a lodge you can stay at (with hot showers and amazing food) and also has guides who hike with your pack. They had me at “gluten free food” and “hot showers”, so I convinced Scott that was the way we should do our Routeburn Track hike!

I planned ahead well for the hike; they gave us a packing list of recommended things to carry and bring. I learned from a friend in NZ, Martin, who had gone trekking a few weeks prior: his pack went over a cliff and was lost – yikes! Therefore, I planned one set of supplies in baggies and put them in both Scott & my pack just in case something happened to one of our packs, we’d still be completely covered.

Day 1 of the hike was awesome – it was overcast and felt like hiking in Seattle, but the scenery and wildlife were still great to experience. Since it was raining off and on, the waterfalls were spectacular.

Day 2 also started awesome – it was a breathtakingly clear morning with blue skies and sunshine as we hiked up above the tree line and over a mountain ridge, along the valley, and onward toward the lunch spot. I was feeling great and enjoying my hike – this was one of my all-time favorite places to hike in terms of the view of the valley and lake that we hiked from; and the mountain views on the other side of the ridge once we topped the mountain and crossed over.

However, about 30 min from the lunch shelter (and about 300 feet of elevation to go), I noticed the lady hiking in front of us decided to sit and slide down a particularly large and angled rock on the trail. I approached the rock planning to stop and assess my plan before continuing on. Before I even decided what to do, I somehow slipped and vaulted (for lack of a better word) left and off the trail…and down the slope. I flipped over multiple times and knew I had to grab something to stop my flight and be able to save myself from going all the way off the mountain slope. I amazingly only ended up about 10 feet off the trail, clinging to a giant bush/fern-like plant.

I had to be pulled back up to the trail by Scott and another hiker who came running after hearing my yell for help as I went down the mountain. (Scott came down off the trail few feet, and had to hold onto the hand of another hiker with one hand while pulling me up with the other, just like in the movies. It’s not a lot of fun to be at the end of the human chain, though!) At that point, I knew I had injured my right ankle and could only use my left foot/leg and right knee to try to climb back up to the trail while they pulled on my backpack. We got me back on to the trail and over to a rock to rest. We waited a few minutes for the back-of-the-pack guides who showed up and taped around my ankle and boot to see if I could walk on it – they thought it was sprained. I could flex, but couldn’t really put weight on it without excruciatingly sharp pain on the right side. I’d never sprained my foot before or broken any bones in my life, so I was frustrated by how painful the ‘sprain’ was. I had an overwhelming wave of nausea that I knew was in response to the pain, too, so at one point I had to sit there and lean back with my eyes closed while everyone else talked around me.

The guides wanted to see if we could get to a nearby river to ice my leg in. I used my poles as pseudo-crutches in front of me, with my arms bent at 90 degree angles, and with Scott behind me to check my balance, would crutch and hop on one leg. It wasn’t like regular crutching, though, where you can press your weight down on your arms and hands. It was really an act of placing the poles slightly forward for balance and then hopping up and forward, pressing off my left leg. My left leg was quickly exhausted and cramping from the effort of hopping forward with my entire body weight. It was also complicated by the rain making things more slippery; and of course; this is a mountain trail with rocks and boulders of different sizes. What I didn’t even notice walking normally on two feet became incredibly frustrating for figuring out when and how to jump up onto a small rock; or around to the side; etc.

“Lucky” for me (eye roll), we happened to be in an ascending section of the trail with quite a few large rocky sections, and there was no way I could hop up the uneven rocks on foot. So instead, I chose to crawl up and over those sections on my hands and knees. Then I would get up at the top and hop again through the “flatter” gravel and rock sections, then crawl again. It was slow and exhausting, and painful when I would get up one one leg again and start hopping again. I was in the most physical pain I’d ever been in my life.

After about a very slow and painful quarter of a mile, and as rain was dripping down more steadily, the guides decided I wouldn’t make it the remaining 300ft of elevation/30 minute (normal) hike to the lunch spot. They radioed for a medevac helicopter to come pick me up. I was incredibly upset and disappointed that I had ruined our hike… but also knew I absolutely wouldn’t even make it to the lunch shelter. I remember saying “I feel so stupid!” to Scott.

The helicopter came in a surprisingly quick amount of time, and they let out one of the EMT’s nearby and then flew over to a hill across from the trail. The EMT saw that I was decently clothed and covered (I had 3/4 length running pants on; a rain jacket and hood; and had a second rain jacket to cover my legs against the rain and wind) and did a verbal status check to confirm I was decent enough for them to lift me off the mountain. They weren’t able to land safely anywhere nearby on the trail because it was so steep and narrow; so they put me in a “sack” that went around my back and looped over my arms and between my legs, and was hooked on to the EMT’s harness. Scott and the guide stood back, while the helicopter came back and lowered the winch. I was winched up from there. However, the EMT had told me once we got up to the helicopter that the team inside would pull me straight back. And that didn’t happen, which was slightly more terrifying because we started flying away from the mountain while still *outside* the helicopter. It turns out the helicopter had unloaded a stretcher and supplies on the nearby hill, and so we were lowered down – with me and the EMT still perched outside the skids – to the hillside there, so the team could then gather the supplies & then load me in so I could sit on the stretcher.

The other terrifying factor about being evacuated off the mountain was that due to the weather that was blowing in hours ahead of schedule, and the “we have to winch you off the mountain” aspect: they couldn’t take Scott with us. So I had to start making plans & preparing myself for going to the hospital by myself in a foreign country. I was terrified about my BGs & diabetes & how I know hospitals don’t always know what to do with people with T1D, let alone someone on a (DIY) closed loop. I tried to tamp down on my worries & make some plans while we waited for the helicopter, so Scott would know I was okay-ish and worry slightly less about me. But at that point, we knew he would have to finish the day’s hike (another 3-4 hours); spend the night; and hike down the next day as planned in order to meet up with me at the hospital.

As we lifted off in the helicopter, I handed the EMT my phone, where I had made a note with my name, age, medical information (T1D & celiac), and the situation about my ankle. He loved it, because he could just write down my information on the accident forms without yelling over the headset. Once he gave me my phone back, a few minutes later we passed back into an area with signal, and I was able to send text messages for the first time in 2 days.

I sent one to my mom, as carefully worded as I could possibly do:

“Slipped off the trail. Hurt ankle. BGs ok. In a helicopter to the hospital in Queenstown. Just got signal in helicopter. Don’t freak out. Will text or call later. Love you”

It had all the key information – something happened; here’s where I’m heading; BGs are fine; pleeeeeeeease don’t freak out.

I also sent a text to Scott’s dad, Howard, who’s an ER doc, with a tad different description:

“Slipped and flipped off the trail. Possible ankle fracture or serious sprain. Being medevac’d off in a helicopter. BGs are fine. But please stand by for any calls in case I need medical advice. Just got signal in the chopper. Scott is still on the trail until tomorrow so I am solo.”

I was quite nervous when we arrived at the hospital. I haven’t been in an ER since high school (when I was dehydrated from a virus). I’ve heard horror stories about T1D & hospitals. However, most of my fears related to T1D were completely unfounded. When I arrived, the EMT did some more paperwork, I talked briefly to a nurse, and then was left alone for quite a while (maybe an hour). Other than mentioning T1D (and that my BGs were fine) and celiac to the nurse, no one ever asked about my BGs throughout the rest of the time in the ER. Which was fine with me. What my BGs had actually done was rise steadily from about 120 up to 160, then stayed there flat. That’s a bit high, but given I was trying to manage pain and sort out my situation, I was comfortable being slightly elevated in case I crashed/dropped later when the adrenaline came down. I just let OpenAPS keep plugging away.

The first thing that was done in the ER about an hour after I arrived was wheeling me to go get an x-ray. It was quick and not too painful. I remember vividly that the radiologist came back out and and said “yes, your ankle is definitely broken. In two places.” I started at her and thought an expletive or two. But for some reason, that made me feel a lot better: my pain and the experience I had on the mountain was not totally disproportionate to the injury. I relaxed a lot then, and could feel a lot of the stress ebbing away. My BGs started a slow sloping drop down almost immediately, and ended up going from 160 down to 90 where I leveled out nicely and stayed for the next few hours.

After I was wheeled back to my area of the ER, the ER doc showed up. He started asking, “So I heard you hopped and climbed off the mountain?” and then followed up by saying yes, my ankle was broken…in three places.

Me: “WHAT? Did you say ::three::?”

The ER doc said he had already consulted ortho who confirmed I would need surgery. However, it didn’t have to be that night (halleluljah), and they usually waited ’til swelling went down to operate, so I had a choice of doing it in NZ or going home and doing it there. He asked when I was planning to leave: this was Sunday evening now; and we planned to fly out Wednesday morning. I asked if there were any downsides to waiting to do surgery at home; any risk to my long-term health? He said no, because they usually wait ~10 days for the swelling to go down to operate. So I could wait in NZ (me: uhhh, no) or fly home and see someone locally. I was absolutely thrilled I wouldn’t need to operate then and there, and without Scott. I asked for more details so I could get my FIL’s opinion (he concurred, coming home was reasonable), and then confirmed that I liked the plan to cast me; send me on my way; and let me get surgery at home.

It took them another 2 hours to get me to the procedure room and start my cast. This was a small, 6-bed ER. When they finally started my cast, the ER doc had his hands on my ankle holding it up…and another nurse rushed in warning that a critical patient was in route, 5 minutes out. The ER doc and the other nurse looked at each other, said “we can do this by then”, and literally casted me in 2 minutes and were wheeling me out in the third minute! It was a tad amusing. I was taken back to x-ray where they confirmed that the cast was done with my ankle in a good position. After that, I just needed my cast to be split so I could accommodate swelling for the long plane rides home; get my prescriptions for pain med; get crutches; and go home.

All that sounds fast, but due to the critical patient that had come in, it took another two hours. They finally came and split my cast (which is done by using the cast cutter to cut a line, then another line, then pull out the strip in between), sold me my crutches, and wrote my prescriptions. The ER doc handed me my script, and I asked if the first rx had acetaminophen (because it would mess up my G4). He said it did, so he scribbled that out and prescribed ibuprofen instead. The nurse then got & apologized for “having to sell me” crutches. New Zealand has a public health policy where they cover everything in an accident for foreigners: I didn’t have to pay for the medevac (!!), the ER visit (!!), the x-rays (!!), the cast …nothing. Just the crutches (which they normally lend for free to NZ but obviously I was taking these home). Then I was on my way.

Thankfully, the company we hiked with had of course radioed into Queenstown, and the operations manager had called the ER and left a message to give to me with his phone number. A few hours prior, when I found out I’d be casted & released that night, I had been texting my mom & had her call the hotel Scott & I were staying at the next (Monday) night to see if they had a room that (Sunday) night that I could check into. The hiking company guy offered to drive me wherever, so he came to pick me up. I had texted him to keep him posted on my progress/timeline of release (nice and vague and unhelpful for the most part). But I also asked as soon as we got in contact if he could radio a message to the lodge & tell Scott that: a) my ankle was broken; b) I was ok; c) I’d be at the hotel when he got in the next day and not to rush, I was ok. The guy said he could do me one better: when he came to pick me up, he’d bring the phone so I could ::call: and talk to Scott directly. (I almost cried with relief, there, at the idea of getting to talk to Scott so he wouldn’t be beside himself worrying for 22 hours). I did get to talk to Scott for about a minute and tell him everything directly, and convince him not to hike out himself in the morning, but stick with the group and the normal transport method back to Queenstown, and just come meet me at the hotel when he got back around 4pm the next day. He agreed.

(What I didn’t find out until later is that Scott had considered doing the rest of the hike completely that night. Two things ended up dissuading him: one was the fact that a guide would have had to go with him and then hike all the way back to the lodge that night. The other was the fact that he talked to me and I would be out of the hospital by the time he arrived; so since I said I was fine alone at the hotel, he’d wait until the next day.)

So, I was taken to the hotel and got help getting up to the hotel room and had ice delivered along with extra pillows to prop up, and our bags brought in. Thankfully, on the mountain, the EMT had agreed to winch my backpack up with me. This was huge, because I noted earlier, I had a full set of supplies in my backpack, and all we had to do on the mountain was grab an extra international adapter and my charger cords out of Scott’s bag and toss it into mine. That made it easy to just pull what I needed that night (my rig; charger cords & adapter; a snack) out of the top of my bag from my perch on the bed. I plugged in my rig; made sure I was looping, took my pain meds, and went to sleep.

Broken_bones_type_1_diabetes_trimalleolar_fracture_OpenAPS_DanaMLewisAmazingly, although you’re probably not any more surprised than I am at this point, my BGs stayed perfectly in range all night. Seriously: after that lowering from 160 once I relaxed and let some of the stress go? No lows. No highs. Perfectly in range. The pain/inflammation and my lack of eating didn’t throw me out of range at all. The day of the fall, all I ate was breakfast (8am); didn’t eat lunch and didn’t bother doing anything until 11pm when I had a beef jerky stick for some protein and half a granola bar (10g carbs). For the next two and a half weeks now, I’ve had no lows, and very few highs.

The one other high BG I really had was on Sunday after we got home (we got back on Wednesday). It happened after my crutch hit the door coming back to my bedroom from the bathroom, and I did such a good job hopping on my left foot and protecting my casted right foot, that I managed to break the smallest toe on my left foot. I pretty immediately knew that it was broken based on the pain; then my BG slowly rose from 110 up to 160; and then I started to have the same “shadow” bruising spread around my foot from the base of the toe. Scott wasn’t sure; when I had fallen off the trail I had yelled “help!” and “I think I broke my foot!”. I didn’t say it out loud this time; just thought it. Again, after some ibuprofen and icing and resting, within an hour my BG started coming back down slowly to below 100 mg/dL.

On Tuesday, I went to the orthopedic surgeon and confirmed: my left toe is definitely broken. My right ankle is definitely broken: the trimalleolar fracture diagnosis from NZ was confirmed. However, given that none of the ligaments were damaged, and the ankle was in a decent position, the ortho said there’s a good chance I can avoid surgery and heal in place inside a cast. The plan was to take off my split, plaster-based cast they did in NZ and give me a proper cast. We’d follow up in 10 days and confirm via x-ray that everything was going well. I asked how likely surgery would still be with this plan; and he said 20%. Well, given that I was assuming 100% before, that was huge progress! He also told me I shouldn’t travel within 4 weeks of the injury, which unfortunately means I had to cancel my trip to Berlin for ATTD later in February. It may or may not mean I have to cancel another trip; I’ll have to wait and see after the next follow up appointment, depending on whether or not I need surgery.

Up until this point, I had been fairly quiet (for me) on social media. I hadn’t posted the pictures of our hike; I didn’t talk about my fall or the trip home. One friend had texted and said “I wondered if you fell off the face of the earth!” to which I responded “uhhh…well…about that…I ::only:: fell off a mountain! Not earth!” Ha. Part of the reason was not knowing whether or not I would be able to travel as planned, and wanting to be courteous to informing the conferences who invited me to speak about the situation & what it meant for me being able to attend/not. Once I had done that, I was able to start posting & sharing with everyone what had happened.

To be perfectly honest, it’s one thing to have a broken limb and a cast and have to use crutches. It’s an entirely other ball of wax to have a broken toe on the foot that’s supposed to be your source of strength & balance. The ortho gave me a post-op surgical shoe to wear on my left foot to try to help, but it hurt so bad that I can’t use my knee scooter to move easily without my left foot burning from the pain. Thankfully, Scott’s parents’ neighbor also had a motorized sit-scooter that we borrowed. However, due to the snowpocalypse that hit Seattle, I’ve not been able to leave the house since Thursday. We haven’t been able to drive anywhere, or walk/scooter anywhere, in days. I’m not quite stir crazy yet; but; I’ll be really looking forward to the sidewalks being snow-free and hopefully lake-free (from all the melting snow) later in the week so I can get out again. I also picked up a cold somewhere, so I for the most part have been stationary in bed for the last week, propping up my feet and using endless boxes of Kleenex.

OpenAPS, as you can see, has done an excellent job responding to the changes in my insulin needs from being 100% sedentary. (Really – think trips to the bathroom and that’s it.)  In addition to the increased resistance from my cold and being sedentary, there’s one other new factor I’ve been dealing with. I asked my ortho about nutrition, and he wants me to get 1g of protein per kg of body weight, plus 1000mg/day of calcium. He suggested getting the extra protein via a powder, instead of calories (e.g. eating extra food). I found a zero-carb, gluten free powder that’s 25g of protein per scoop, and have been trying it with chocolate milk (which is 13g of carb and 10g of protein).

I’ve been drinking that 2x a day. Interestingly, previous to my injury, unless I was eating a 100% no carb meal (such as eggs and bacon for breakfast), I didn’t need to bolus/account for protein. However, even though I’m entering carbs for chocolate milk (15), I was seeing a spike up to 150 mg/dL after drinking it. I tried entering 30g for the next time (13g of milk; plus about 50% for the 25+10g worth of protein), and that worked better and only resulted in a 10 mg/dL rise in response to it. But even a handful of nuts’ worth of protein, especially on days where I’m hardly eating anything, have a much stronger effect on my BGs. This could be because my body is adjusting to me eating a lot less (I don’t have much appetite); adjusting to the much-higher-protein diet overall; and/or responding to the 100% sedentary pattern of my body now.

Thankfully, it’s not been a big deal, and OpenAPS does such a good job tamping down on the other noise-based factors: it’s nice that my biggest problems are brief rises to 160 or 170 mg/dL (that then come back down on their own). My 7-day and 30-day BG averages have stayed the same; and my % time in range for 80-160 has stayed the same, even with what feels like a few extra protein-related blips, and even when some days I eat hardly anything and some days I manage 2-3 meals.

So to summarize a ridiculously long post:

  • When I break bones, my BGs rise up (due to inflammation and/or the stress/other hormonal reaction) up to 160 mg/dL until I relax, when they’ll come back down. Otherwise, broken bones don’t really phase OpenAPS.
  • Ditto for lack of movement and changes in activity patterns not phasing OpenAPS.
  • The biggest “challenge” has been adjusting to the 3x amount of protein I’m getting as a dietary change.
  • I have a trimalleolar fracture; and that’s about 7% of ankle fractures. I read a lot of blog posts about people needing surgery & the recovery from it taking a long time. I’m not sure I won’t need surgery; but I’m hoping I won’t need it. If so, here’s one data point for a trimalleolar fracture being non-surgical  – I’ll update more later with full recovery timelines & details. Also, here is a Twitter thread where I’m tracking some of the most helpful things for life with crutches.
  • Don’t break your littlest toe – it can hurt more than larger fractures if you have to walk on it!

A huge thank you goes to my parents and Scott’s parents; our siblings on both sides for being incredibly supportive and helpful as well; and Scott himself who has been waiting on me (literally hand and foot) and taking most excellent care of me.

And thank you as well to anyone who read this & for everyone who’s been sending positive thoughts and love and support. Thank you!

4 years DIY closed looping with #OpenAPS – what changed and what hasn’t

It’s hard to express the magnitude of how much closed looping can improve a person with diabetes’ life, especially to someone who doesn’t have diabetes or live closely with someone that does. There are so many benefits – and so many way beyond the typically studied “A1c improvement” and “increased time in range”. Sure, those happen (and in case you haven’t seen it, see some of the outcomes from various international studies looking at DIY closed loop outcomes). But everything else…it’s hard to explain all of the magic that happens in real life, that’s made so much richer by having technology that for the most part keeps diabetes out of the way, and more importantly: off the top of your mind.

Personally, my first and most obvious benefit, and the whole reason I started DIYing in the first place, was to have the peace of mind to sleep safely at night. Objective achieved, immediately. Then over time, I got the improvements in A1c and time in range, plus reduction in time spent doing diabetes ‘stuff’ and time spent thinking about my own diabetes. The artificial pancreas ‘rigs’ got smaller. We improved the algorithm, to the point where it can handle the chaos that is everything from menstrual cycle to having the flu or norovirus.

More recently, in the past ~17 months, I’ve achieved an ultimate level of not doing much diabetes work that I never thought was possible: with the help of faster insulin and things like SMB’s (improved algorithm enhancements in OpenAPS), I’ve been able do a simple meal announcement by pressing a button on my watch or phone..and not having to bolus. Not worrying about precise carb counts. Not worrying about specific timing of insulin activity. Not worrying about post-meal lows. Not worrying about lots of exercise. And the results are pretty incredible to me:

We should be measuring and reducing user burden with AID in addition to improving TIR and A1c

But I remember early on when we had announced that we had figured out how to close the loop. We got a lot of push back saying, well, that’s good for you – but will it work for anyone else? And I remember thinking about how if it helped one other person sleep safely at night..it would be worth the amount of work it would take to open source it. Even if we didn’t know how well it would work for other people, we had a feeling it might work for some people. And that for even a few people who it might work for, it was worth doing. Would DIY end up working for everyone, or being something that everyone would want to do? Maybe not, and definitely not. We wouldn’t necessarily change the world for everyone by open sourcing an APS, but that could help change the world for someone else, and we thought that was (and still is) worth doing. After all, the ripple effect may help ultimately change the world for everyone else in ways we couldn’t predict or expect.

Ripple_effect_DanaMLewisThis has become true in more ways than one.

That ‘one other person’ turned into a few..then dozen..hundreds..and now probably thousand(s) around the world using various DIY closed loop systems.

And in addition to more people being able to choose to access different DIY systems with more pumps of choice, CGMs of choice, and algorithm of choice, we’ve also seen the ripple effect in the way the world works, too. There is now, thankfully, at least one company who is evaluating open source code; running simulations with it; and where it is out-performing their original algorithm or code components, utilizing that knowledge to improve their system. They’re also giving back to the open source diabetes community, too. Hopefully more companies will take this approach & bring better products more quickly to the market. When they are ready to submit said products, we know at least U.S. regulators at the FDA are ready to quickly review and work with companies to get better tools on the market. That’s a huge change from years ago, when there was a lot of finger pointing and what felt like a lot of delay preventing newer technology from reaching the market. The other change I’m seeing is in diabetes research, where researchers are increasingly working directly with patients from the start and designing better studies around the things that actually matter to people with diabetes, including analyzing the impact and outcomes of open source technology.

After five years of open source diabetes work, and specifically four years of DIY closed looping, it finally feels like the ripples are ultimately helping achieve the vision we had at the start of OpenAPS, articulated in the conclusion of the OpenAPS Reference Design:

OpenAPS_Reference_Design_conclusionIs there still more work to do? Absolutely.

Even as more commercial APS roll out, it takes too long for these to reach many countries. And in most parts of the world, it’s still insanely hard and/or expensive to get insulin (which is one of the reasons Scott and I support Life For A Child to help get insulin, supplies, and education to as many children as possible in countries where otherwise they wouldn’t be able to access it – more on that here.). And even when APS are “approved” commercially, that doesn’t mean they’ll be affordable or accessible, even with health insurance. So I expect our work to continue, not only to support ongoing improvements with DIY systems directly; but also with encouraging and running studies to generalize knowledge from DIY systems; hopefully seeing DIY systems approved to work with existing interoperable devices; helping any company that will listen to improve their systems, both in terms of algorithms but also in terms of usability; helping regulators to see both what’s possible as well as what’s needed to successfully using these types of system in the real world. I don’t see this work ending for years to come – not until the day where every person with diabetes in every country has access to basic diabetes supplies, and the ability to choose to use – or not – the best technology that we know is possible.

But even so, after four years of DIY closed looping, I’m incredibly thankful for the quality of life that has been made possible by OpenAPS and the community around it. And I’m thankful for the community for sharing their stories of what they’ve accomplished or done while using DIY closed loop systems. It’s incredible to see people sharing stories of how they are achieving their best outcomes after 45 years of diabetes; or people posting from Antartica; or after running marathons; or after a successful and healthy pregnancy where they used their DIY closed loop throughout; or after they’ve seen the swelling in their eyes go done; etc.

The stories of the real-life impacts of this type of technology are some of the best ripple effects that I never want to forget.

Running and fueling for runs with type 1 diabetes

This blog post is not for you. (Well that sounds mean, doesn’t it? It’s not meant to be mean. But this post is written for a very small subset of people like me who are stumbling around on page 16 of Google trying to find someone sharing experiences and specific details around methods (both successful and less so) for fueling for longer endurance events such as full marathons or ultramarathons with type 1 diabetes. So – please don’t be offended, but also don’t be surprised if you don’t find this post very useful!)

I’ve started running again, and more, this year, and am now to the point where I’m considering running another full marathon sometime next year. As I adventure into running longer distances, and more miles, I’m reflecting on what I did in my first full marathon that worked related to diabetes, and what I want to try to do differently. This post is logging some of my experiences and notes to date, in honor of fellow page-16-of-Google-seekers, rather than waiting til after I run another full (if I do) and there continuing to be not much info out there.

Some background on my running:

I’m not a runner. And not a good runner. I never liked running. But, I walked the Seattle half marathon in December 2012 and thought it might be fun to then walk the full marathon in December 2013. However, I also tried snowboarding for the first time in January 2013 and majorly damaged my knee. I could barely walk the few blocks to work every day, let alone do my normal activities. It took several months, and several PT sessions, to get back to normal. But part of my frustration and pain manifested into the idea that I should recover enough to still walk that full marathon in December. And in order to be off the course by the time it closed, I would need to run a little bit. And I could barely walk, and never ran, so I would need to do some training to be able to run a mile or two out of the 26.2 I planned to otherwise walk. So I set off to teach myself how to run with the idea of walk/running the full, which evolved into a plan to run/walk it, and mostly eventually run it. And that’s what I did.

Now – this marathon was December 2013. This was right when we created DIYPS, and a year before we closed the loop, so I was in full, old-school traditional manual diabetes mode. And it sucked quite a bit. But now, almost 5 years later, with the benefit of everything I’ve learned from DIYPS and OpenAPS about insulin and food timing etc., here’s what I realized was happening – and why – in some of my training runs.

What I worried about was going low during the runs. So, I generally would set a low temporary basal rate to reduce insulin during the run, and try to run before dinner instead of after (to reduce the likelihood of running with a lot of active insulin in my body). I would also eat some kind of snack – I think for energy as well as making sure I didn’t go low. I would also carry a bottle of Gatorade to drink along the way.

With the benefit of 5 years of lots of learning/thinking about all the mechanics of diabetes, here’s what was happening:

Per the visualization, the carbs would hit in about 15 minutes. If I reduced insulin at the time of the run, it would drive my blood sugar up as well, over a longer time frame (after around 45+ minutes as the lack of insulin really started to kick in and previous basal impact tailed off). The combination of these usually meant that I would rise toward the middle or end of my short and medium runs, and end up high. In longer runs, I would go higher, then low – and sip gatorade, and have some roller coaster after that.

Now, this was frustrating in training runs, but I did ok for my long runs and my marathon had pretty decent BGs with no lows. However, knowing everything I know now, and commencing a new burst of running, I want to try to do better.

Here’s what I’ve been doing this year in 2018:

My original interest in running was to set a mileage goal for the year, because I didn’t run very much last year (around 50 miles, mostly throughout summer), and I wanted to try to run more regularly throughout the year to get a more regular dose of physical activity. (I am very prone to looking at Seattle weather in October-December and January-March and wanting to stay inside!) That mileage goal was ambitious for me since I didn’t plan to race/train for any distance. To help me stick to it, I divided it by 12 to give myself monthly sub-goals that I would try to hit as a way to stay on top of making regular progress to the goal.

(Ps – pro tip – it doesn’t matter how small or big your goal is. If you track % progress toward whatever your mileage goal is, it’s really nice! And it allows you to compete/compare progress, even if your friends have a much bigger mileage goal than you. That way everyone can celebrate progress, and you don’t have to tell people exactly what your mileage goal might be. What’s tiny for you is big for others; and what’s big for you may be small to others – and that doesn’t matter at all!)

Showing number of runs per week with dips during travel weeks

This has worked really well. The first few months I scraped by in keeping up with my monthly goal. Except for February, when I had three weeks of flu and bronchitis, so I surged in March to finish February’s miles and March’s miles. I then settled back into a regular amount, meeting my monthly goals…and then surged again in August, so I was able to finish my yearly mileage in the middle of September! Wahoo! I didn’t plan to stop there, though, so I planned to keep running, and that’s where the idea of running the Seattle half (always the Sunday after Thanksgiving) popped up again, and maybe a full next year. I started adding some longer runs (two 7.5 miles; a 9.35 miler, and now a 13 miler) over the past month, and have felt really good about those, which has enabled me to start thinking more carefully about what I did last time BG-wise and why this time is so much easier.

Earlier in the year, even on my short runs (one mile or so), I quickly realized that because of the shorter peak of Fiasp, I was less likely to have previous insulin activity drive me low during the run. Within the first handful of runs, I stopped eating a snack or some carbs before the run. I also stopped setting a super high target an hour before my run. I gradually moved into just avoiding >1.5u of insulin on board before short runs; and for longer runs, setting a target of ~110 about 30 minutes before I walked out the door, mostly to avoid any of that insulin activity dosed that would kick in right after I started running. (Keep in mind when I talk about setting targets: I’m using OpenAPS, my DIY closed loop system that does automatic insulin dosing; and for fellow DIY closed loop users, I’m also using exercise mode settings so I can set lower targets like 110 and the targets also automatically adjust my sensitivity and recalculate IOB accordingly. So without those settings, I’d probably set the target to 130 or so.)

And this has worked quite well for me.

Increasing the lengths of my runs

Is it perfect? No, I do still go low sometimes..but probably <10% of my runs instead of 50% of them, which is a huge improvement. Additionally, because of having OpenAPS running to pick up the rebound, there’s not usually much of a rebound and resulting roller coaster like I would have in 2013. Additionally, because autosensitivity is running, it picks up within a few hours of any additional sensitivity to insulin, and I don’t have any overnight lows after running. Yay!

Accomplishing 78% of my yearly run goal so far

However, that all assumes I’m running at a normal-for-my-body or slower speed.

There’s a nice (annoying) phenomenon that if you sprint/run faster than your body can really handle, your liver is going to dump and your BG will spike as a result:

Sprinting can drive BGs up

I didn’t ever notice this in 2013, but I’ve now run enough and at varying paces to really understand what my fitness level is, and see very obvious spikes due to surges like this when I’m sprinting too fast. Some days, if I run too fast (even for a mile), I’ll have a surge up to 180 or 200 mg/dL, and that’ll be higher than my BG is for the rest of that 24 hour period. Which is annoying. Funny, but annoying. Not a big deal, because after my run OpenAPS can take care of bringing my down safely.

But other than the running-too-fast-spikes, my BGs have been incredible during and following my runs. As I thought about contributing factors to what’s working well, this is what’s likely been contributing:

  • with a mix of Fiasp & another short-acting insulin, I’m less likely to have the ‘whoosh’ effect of any IOB
  • but I’m also not starting with much IOB, because I tend to run first thing, or several hours after a meal
  • and of course, I have a DIY closed loop that takes care of any post-run sensitivity and insulin adjustments automatically

As I thought more about how much I’ve been running first thing in the morning/day, and usually not eating breakfast, that made me start reading about fasted long runs, or glycogen depleted runs, or low carb runs. People call them all these things, and I’m putting them in the post for my fellow page-16-of-Google-seekers. I call it “don’t eat breakfast before you run” long runs.

Now, some caveats before I go further into detail about what’s been working for me:

  • Your Diabetes May Vary (YDMV). in fact, it will. and so will your fitness level. what works for you may not be this. what works for you will probably not work for me. So, use this as input as one more blog post that you’ve read about a potential method, and then tweak and try what works for you. And you do you.
  • I’m not doing low carb. (And different people have different definitions of low carb, but I don’t think I’m meeting any of the definitions). What I’m talking about is not eating breakfast, a snack, or a meal before my runs in the morning. When I return from runs, I eat lunch, or a snack/meal, and the rest of my day is the usual amount/type of food that I would eat. (And since I have celiac, often times my gluten free food can be higher carb than a typical diet may be. It depends on whether I’m eating at home or eating out.) So, don’t take away anything related to overall carb consumption, because I’m not touching that! That’s a different topic. (And YDMV there, too.)
  • What I’m doing doesn’t seem to match anything I’ve read for non-T1D runners and what they do (or at least, the ones who are blogging about it).

Most of the recommendations I’ve read for glycogen depletion runs is to only do it for a few of your long runs in a marathon training cycle; that you should still eat breakfast before a full marathon; and you should only do fasted/glycogen depletion for slow, easy long runs.

I’m not sure yet (again, not in a full marathon cycle training), but I actually think based on my runs to date that I will do ok (or better) if I start without breakfast, and take applesauce/gatorade every once in a while as I feel I need it for energy, and otherwise managing my BG line. If I start a downtick, I’d sip some carbs. If I started dropping majorly, I’d definitely eat more. But so far, managing BG rather than trying to prescriptively plan carbs (for breakfast, or the concept of 30-60 per hour), works a lot better for me.

Part of the no-breakfast-works-better-for-me might be because the longevity of insulin in your body is actually like 6 hours (or more). Most non-T1D runners talk about a meal 3 hours before the start of your race. And they’re right that the peak and the bulk of insulin would be gone by then, but you’d still have a fair bit of residual insulin active for the first several hours of your race, and the body’s increased sensitivity to that insulin during exercise is likely what contributes to a lot of low BGs in us T1 runners. There’s also a lot of talk about how fasting during training runs teaches your body to better burn fat; and how running your race (such as a marathon) where you do carb during the race (whether that’s to manage BGs or more proactively) will make your body feel better since it has more fuel than you’re used to. That’s probably true; but given the lower insulin action during a run (because you’ve been fasted, and you may be on a lower temp basal rate to start), you’re likely to have a larger spike from a smaller amount of carbs, so the carb-ing you do before or during these long runs or a marathon race may need to be lower than what a non-T1D might do.

tl;dr – running is going better for me and BG management has been easier; I’m going to keep experimenting with some fasted runs as I build up to longer mileage; and YDMV. Hope some of this was helpful, and if you’ve done no-breakfast-long-runs-or-races, I’d love to hear how it worked for you and what during-race fueling strategy you chose as a result!

Presentations and poster content from @DanaMLewis at #2018ADA

DanaMLewis_ADA2018As I mentioned, I am honored to have two presentations and a co-authored poster being presented at #2018ADA. As per my usual, I plan to post all content and make it fully available online as the embargo lifts. There will be three sets of content:

  • Poster 79-LB in Category 12-A Detecting Insulin Sensitivity Changes for Individuals with Type 1 Diabetes using “Autosensitivity” from OpenAPS’ poster, co-authored by Dana Lewis, Tim Street, Scott Leibrand, and Sayali Phatak.
  • Content from my presentation Saturday, The Data behind DIY Diabetes—Opportunities for Collaboration and Ongoing Research’, which is part of the “The Diabetes Do-It-Yourself (DIY) Revolution” Symposium!
  • Content from my presentation Monday, Improvements in A1c and Time-in-Range in DIY Closed-Loop (OpenAPS) Users’, co-authored by Dana Lewis, Scott Swain, and Tom Donner.

First up: the autosensitivity poster!

Dana_Scott_ADA2018_autosens_posterYou can find the full write up and content of the autosensitivity poster in a post over on OpenAPS.org. There’s also a twitter thread if you’d like to share this poster with others on Twitter or elsewhere.

Summary: we ran autosensitivity retrospectively on the command line to assess patterns of sensitivity changes for 16 individuals who had donated data in the OpenAPS Data Commons. Many had normal distributions of sensitivity, but we found a few people who trended sensitive or resistant, indicating underlying pump settings could likely benefit from a change.
2018 ADA poster on Autosensitivity from OpenAPS by DanaMLewis

 

Presentation:
The Data behind DIY Diabetes—Opportunities for Collaboration and Ongoing Research’

This presentation was a big deal to me, as it was flanked by 3 other excellent presentations on the topic of DIY and diabetes. Jason Wittmer gave a great overview and context setting of DIY diabetes, ranging from DIY remote monitoring and CGM tools all the way to DIY closed loops like OpenAPS. Jason is a dad who created OpenAPS rigs for his son with T1D. Lorenzo Sandini spoke about the clinician’s perspective for when patients come into the office with DIY tools. He knows it from both sides – he’s using OpenAPS rigs, and also has patients who use OpenAPS. And after my presentation, Joyce Lee also spoke about the overarching landscape of diabetes and the role DIY plays in this emerging technology space.

Why did I present as part of this group today? One of the roles I’ve taken on in the last few years in the OpenAPS community (among others) is a collaborator and facilitator of research with and about the community. I put together the first outcomes study (see here in JDST or here in a blog post form on OpenAPS.org) in 2016. We presented a poster on Autotune last year at ADA (see here in a blog post form on OpenAPS.org). I’ve also worked to create and manage the OpenAPS Data Commons, as well as build tools for researchers to use this data, so individuals can easily and anonymously donate their DIY closed loop data for other research projects, lowering the friction and barriers for both patients and researchers. And, I’ve co-led or led several research projects with the community’s data as a result.

My presentation was therefore about setting the stage with background on OpenAPS & how we ended up creating the OpenAPS Data Commons; presenting a selection of research projects that have utilized data from the community; highlighting other research projects working with the OpenAPS community; announcing a new international collaboration (OPEN – more coming on that in the future!) for research with the DIY community; and hopefully encouraging other diabetes researchers to think about sharing their work, data, methods, tools, and insights as openly possible to help us all move forward with improving the lives of people with diabetes.

That is, of course, quite an abbreviated summary! I’ve shared a thread on Twitter that goes into detail on each of the key points as part of the presentation, or there’s a version of this Twitter/presentation content also written below.

If you’re someone who wants to do research with retrospective data from the OpenAPS Data Commons, you can find out more about it here (including instructions on how to request data). And if you’re interested in prospective research, please do reach out as well!

Full content for those who don’t want to read Twitter:

Patients are often seen as passive recipients of care, but many of us PWDs have discovered that problems are opportunities to change things. My journey to DIY began after I was frustrated by my inability to hear CGM alarms at night. 4 years ago, there was no way for me to access my own device data in real time OR retrospectively. Thanks to John Costik for sharing his code, I was able to get my CGM data & send it to the cloud and down to my phone, creating a louder alarm. Scott and I created an algorithm to push notifications to me to take action. This was an ‘open loop’ system we called #DIYPS. With Ben West’s help, we realized could combine our algorithm with small, off-the-shelf hardware & a radio stick to automate insulin delivery. #OpenAPS was thus created, open sourcing all components of DIY closed loop system so others could close the loop, too. An #OpenAPS rig consists of a small computer, radio chip, & battery. The hardware is constantly evolving. Many of us also use Nightscout to visualize our closed loop data, and share with loved ones.

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I closed the loop in December of 2015. As people learned about it, I got pushback: “It works for you, but how do you know it’s going to work for others?” I didn’t, and I said so. But that didn’t mean I shouldn’t share what was working for me.

Once we had dozens of users of #OpenAPS, we presented a research study at #2016ADA, with 18 individuals sharing outcomes data on A1c, TIR, and QOL improvements. (See that publication here: https://twitter.com/danamlewis/status/763782789070192640 ). I was often asked to share my data for people to analyze, but I’m not representative of entire #OpenAPS community. Plus, the community has kept growing: we estimate there are more than (n=1)*710+ (as of June 2018) people worldwide using different kinds of DIY APs. (Note: if you’d like to keep track of the growing #OpenAPS community, the count of loopers worldwide is updated periodically at  https://openaps.org/outcomes ).  I began to work with Open Humans to build the #OpenAPS Data Commons, enabling individuals to anonymously upload their data and consent to share it with the Data Commons.

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Criteria for using the #OpenAPS Data Commons:

  • 1) share insights back with the community, especially if you find something about an individual’s data set where we should notify them
  • 2) publish in an accessible (and preferably open) manner

I’ve learned that not many are prepared to take advantage of the rich (and complex) data available from #OpenAPS users; and many researchers have varying background and skillsets.  To aid researchers, I created a series of open source tools (described here: http://bit.ly/2l5ypxq, and tools available at https://github.com/danamlewis/OpenHumansDataTools ) to help researchers & patients working with data.

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We have a variety of research projects that have leveraged the anonymously donated, DIY closed loop data from the #OpenAPS Data Commons.

  • 2018ADA_Slide 112018ADA_Slide 12One research project, in collaboration with a Stanford team, evaluated published machine learning model predictions & #OpenAPS predictions. Some models (particularly linear regression) = accurate predictions in short term, but less so longer term when insulin peaks. This study is pending publication, but I’d like to note the challenge of more traditional research keeping pace with DIY innovation: the code (and data) studied was from January 2017. #OpenAPS prediction code has been updated 2x since then.
  • In response to the feedback from the #2016ADA #OpenAPS Outcomes study we presented, a follow up study on #OpenAPS outcomes was created in partnership with a team at Johns Hopkins. That study will be presented on Monday, 6-6:15pm (352-OR).
  • 2018ADA_Slide 13Many people share publicly online their outcomes with DIY closed loops. Sulka Haro has shared his script to evaluate the reduction in daily manual diabetes interventions after they began using #OpenAPS. Before: 4.5/day manual corrections; now they treat <1/day.
  • #OpenAPS features such as autosensitivity automatically detect sensitivity changes and insulin needs, improving outcomes. (See above at the top of this post for the full poster content).
  • If you missed it at #2017ADA (see here: http://bit.ly/2rMBFmn) , Autotune is a tool for assessing changes to basal rates, ISF, and carb ratio. Developed for #OpenAPS users but can also be used by traditional pumpers (and some MDI users also utilize it).

I’m also thrilled to share a new tool we’ve created: an #OpenAPS simulator to allow us to more easily back-test and compare settings changes & feature changes in #OpenAPS code.
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  • Screen Shot 2018-06-22 at 4.48.06 PM2018ADA_Slide 16  We pulled a recent week of data for n=1 adult PWD who does no-bolus, rough carb entry meal announcements, and ran the simulator to predict what the outcomes would be for no-bolus and no meal-announcement.

 

  • 2018ADA_Slide 172018ADA_Slide 18 We also ran the simulator on n=1 teen PWD who does no-bolus and no-meal-announcement in real life. The simulator tracked closely to his actual outcomes (validated this week with a lab-A1c of 6.1)

 

 

 

The new #OpenAPS simulator will allow us to better test future algorithm changes and features across a diverse data set donated by DIY closed loop users.

There are many other studies & collaborations ongoing with the DIY community.

  • Michelle Litchman, Perry Gee, Lesly Kelly, and myself have a paper pending review analyzing social-media-reported outcomes & themes from DIY community.
  • 2018ADA_Slide 19There are also multiple other posters about DIY outcomes here at #2018ADA:
  • 2018ADA_Slide 20 There are many topics of interest in DIY community we’d like to see studies on, and have data for. These include: “eating soon” (optimal insulin dosing for lesser post-prandial spikes); and variability in sensitivity for various ages, pregnancy, and menstrual cycle.
  • 2018ADA_Slide 21I’m also thrilled to announce funding will be awarded to OPEN (a new collaboration on Outcomes of Patients’ Evidence, with Novel, DIY-AP tech), a 36-month international collaboration assessing outcomes, QOL, further development, access of real-world AP tech, etc. (More to come on this soon!)

In summary: we don’t have a choice in living with diabetes. We *do* have a choice to DIY, and also to research to learn more and improve knowledge and availability of tools for us PWDs, more quickly. We would love to partner and collaborate with anyone interested in working with the DIY community, whether that is utilizing the #OpenAPS Data Commons for retrospective studies or designing prospective studies. If you take away one thing today: let it be the request for us to all openly share our tools, data, and insights so we can all make life with type 1 diabetes better, faster.

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A huge thank you as always to the community: those who have donated and shared data; those who have helped develop, test, troubleshoot, and otherwise help power the #OpenAPS and other DIY diabetes communities.

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Presentation:
Improvements in A1c and Time-in-Range in DIY Closed-Loop (OpenAPS) Users

(full tweet thread available here; or a description of this presentation below)

#OpenAPS is an open and transparent effort to make safe and effective Artificial Pancreas System (APS) technology widely available to reduce the burden of Type 1 diabetes. #OpenAPS evolved from my first DIY closed loop system and our desire to openly share what we’ve learned living with DIY closed loops. It takes a small, off-the-shelf computer; a radio; and a battery to communicate with existing insulin pumps and CGMs. As a PWD, I care a lot about safety: the safety reference design is the first thing in #OpenAPS that was shared, in order to help set expectations around what a DIY closed loop can (and cannot) do.

ADA2018_Slide 23ADA2018_Slide 24As I shared about my own DIY experience, people questioned whether it would work for others, or just me. At #2016ADA, we presented an outcomes study with data from 18 of the first 40 DIY closed loop users. Feedback on that study included requests to evaluate CGM data, given concerns around accuracy of self-reported outcomes.

This 2018 #OpenAPS outcomes study was the result. We performed a retrospective cross-over analysis of continuous BG readings recorded during 2-week segments 4-6 weeks before and after initiation of OpenAPS.

ADA2018_Slide 26For this study, n=20 based on the availability of data that met the stringent protocol requirements (and the limited number of people who had both recorded that data and donated it to the #OpenAPS Data Commons in early 2017).  Demographics show that, like the 2016 study, the people choosing to #OpenAPS typically have lower A1C than the average T1D population; have had diabetes for over a decade; and are long-time pump and CGM users. Like the 2016 study, this 2018 study found mean BG and TIR improved across all time categories (overall, day, and nighttime).

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Overall, mean BG (mg/dl) improved (135.7 to 128.3); mean estimated HbA1c improved (6.4 to 6.1%). TIR (70-180) increased from 75.8 to 82.2%. Overall, time spent high and low were all reduced, in addition to eAG and A1c reduction. Overnight (11pm-7am) had smaller improvement in all categories compared to daytime improvements in these categories.

Notably: although this study primarily focused on a 4-6 week time frame pre-looping vs. 4-6 weeks post-looping, the improvements in all categories are sustained over time by #OpenAPS users.

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ADA2018_Slide 35Conclusion: Even with tight initial control, persons with T1D saw meaningful improvements in estimated A1c, TIR, and a reduction in time spent high and low, during the day and at night, after initiating #OpenAPS. Although this study focused on BG data from CGM, do not overlook additional QOL benefits when analyzing benefits of hybrid closed loop therapy or designing future studies! See these examples shared from Sulka Haro and Jason Wittmer as example of quality of life impacts of #OpenAPS.

A huge thank you to the community: those who have donated and shared data; those who have helped develop, test, troubleshoot, and otherwise help power the #OpenAPS and other DIY diabetes communities.

And, special thank you to my co-authors, Scott Swain & Tom Donner, for the collaboration on this study. Lewis_Donner_Swain_ADA2018