Understanding Automated Insulin Delivery: A basic book for kids, family, and friends of people living with diabetes

tl;dr – A new book out for kids explaining the basics of automated insulin delivery, using the analogy of scuba diving to explain how the system makes small changes in insulin delivery to manage glucose levels! Watch the narrated video free online, and if you find the analogy useful, it’s available in book form as both a physical, print book as well as on Kindle via Amazon.DanaMLewis_UnderstandingAutomatedInsulinDelivery_KidsBook—-

A few weeks ago I was thinking about what the basic things that I wanted people to know about automated insulin delivery. A good portion of the general public – and even many family members of people with diabetes – thinks that a traditional insulin pump does what an automated insulin delivery system does: adjusting insulin delivery based on continuous glucose monitor (CGM) data. But a traditional pump doesn’t necessarily know about the CGM data and isn’t equipped with the algorithm to make those decisions and changes to insulin delivery, so the person with diabetes is doing a LOT of invisible labor to try to manage glucose levels constantly 24/7/365. That’s why an automated insulin delivery system is so useful, and why I’ve been using a DIY system for more than 5 years. Now, though, we’re (finally) starting to see commercial systems come to market that does the basic functionality similar to what OpenAPS could do five years ago. I want more people to have access to these systems and use them as best as they can be used to give people the best outcomes diabetes-wise and the best quality of life they can possibly have. Helping explain to more people how this technology works is one way I can help do this, and thus an idea was born for another book to explain the basics of automated insulin delivery systems.

Dana's first rough sketch of the scuba diving analogy for explaining automated insulin deliveryI started with a basic sketch of an idea to run it by Scott and a few other people to test the idea. I’m not much for drawing, so it was a *very* rough sketch. But the analogy seemed to resonate, so I moved on to mocking up a basic version on the computer. (I went down a rabbit hole because I thought it would be neat to make an animated video for people to see and share online, to accompany the book. But I don’t know how to illustrate on the computer, let alone animate, so I tried an open source illustration program called Synfig, then several other illustrator programs that were open source to do the basic design to import into Synfig to animate, but then realized what I had in mind was so simple that basic transitions and animations in PowerPoint would suffice for my animated video.) PowerPoint is also how I’ve made my other children’s books for self-publishing, so it was easy to do a widescreen, video design version and then modify a version for the print size book of choice (I chose an 8.5×8.5 to make it easiest to hold and read). 

I went from a paper and pencil sketch on July 18 to mocking up the video animation and designing the print book and requesting printed proofs on July 23. The printed proofs were a bit slow to ship compared to usual (probably something to do with a global pandemic), and arrived on August 4. I reviewed, made a few small changes, and hit ‘publish’ the same day, and Amazon reviewed and approved both the Kindle version and the print version, which are now available today (August 5, 2020) online. It took less than 3 weeks to go from idea to printed book available for shipping worldwide! (I am sharing all these details to hopefully encourage someone else to self-publish if they have an idea for a book they’d like to see available in the world – feel free to reach out if you have any questions about self publishing!)

Print_DanaMLewis_UnderstandingAutomatedInsulinDeliveryKindle_Amazon_DanaMLewis_UnderstandingAutomatedInsulinDeliveryHere is the link to the print book on Amazon.

Here’s the link to the Kindle book version on Amazon – it’s also available as part of Kindle Unlimited and the Kindle Lending Library, so feel free to share it out!

DanaMLewis_UnderstandingAutomatedInsulinDelivery_kidsbook_TheEnd

Also, if you’re looking for something to do with your kids (or have your kids do), I also made some of the scuba diving designs into a coloring sheet – check them out here (downloads as a PDF).

DanaMLewis_freescubacoloringsheets

Poster and presentation content from @DanaMLewis at #ADA2020 and #DData20

In previous years (see 2019 and 2018), I mentioned sharing content from ADA Scientific Sessions (this year it’s #ADA2020) with those not physically present at the conference. This year, NO ONE is present at the event, and we’re all virtual! Even more reason to share content from the conference. :)

I contributed to and co-authored two different posters at Scientific Sessions this year:

  • “Multi-Timescale Interactions of Glucose and Insulin in Type 1 Diabetes Reveal Benefits of Hybrid Closed Loop Systems“ (poster 99-LB) along with Azure Grant and Lance Kriegsfeld, PhD.
  • “Do-It-Yourself Artificial Pancreas Systems for Type 1 Diabetes Reduce Hyperglycemia Without Increasing Hypoglycemia” (poster 988-P in category 12-D Clinical Therapeutics/New Technology—Insulin Delivery Systems), alongside Jennifer Zabinsky, MD MEng, Haley Howell, MSHI, Alireza Ghezavati, MD, Andrew Nguyen, PhD, and Jenise Wong, MD PhD.

And, while not a poster at ADA, I also presented the “AID-IRL” study funded by DiabetesMine at #DData20, held in conjunction with Scientific Sessions. A summary of the study is also included in this post.

First up, the biological rhythms poster, “Multi-Timescale Interactions of Glucose and Insulin in Type 1 Diabetes Reveal Benefits of Hybrid Closed Loop Systems” (poster 99-LB). (Twitter thread summary of this poster here.)

Building off our work as detailed last year, Azure, Lance, and I have been exploring the biological rhythms in individuals living with type 1 diabetes. Why? It’s not been done before, and we now have the capabilities thanks to technology (pumps, CGM, and closed loops) to better understand how glucose and insulin dynamics may be similar or different than those without diabetes.

Background:

Mejean et al., 1988Blood glucose and insulin exhibit coupled biological rhythms at multiple timescales, including hours (ultradian, UR) and the day (circadian, CR) in individuals without diabetes. The presence and stability of these rhythms are associated with healthy glucose control in individuals without diabetes. (See right, adapted from Mejean et al., 1988).

However, biological rhythms in longitudinal (e.g., months to years) data sets of glucose and insulin outputs have not been mapped in a wide population of people with Type 1 Diabetes (PWT1D). It is not known how glucose and insulin rhythms compare between T1D and non-T1D individuals. It is also unknown if rhythms in T1D are affected by type of therapy, such as Sensor Augmented Pump (SAP) vs. Hybrid Closed Loop (HCL). As HCL systems permit feedback from a CGM to automatically adjust insulin delivery, we hypothesized that rhythmicity and glycemia would exhibit improvements in HCL users compared to SAP users. We describe longitudinal temporal structure in glucose and insulin delivery rate of individuals with T1D using SAP or HCL systems in comparison to glucose levels from a subset of individuals without diabetes.

Data collection and analysis:

We assessed stability and amplitude of normalized continuous glucose and insulin rate oscillations using the continuous wavelet transformation and wavelet coherence. Data came from 16 non-T1D individuals (CGM only, >2 weeks per individual) from the Quantified Self CGM dataset and 200 (n = 100 HCL, n = 100 SAP; >3 months per individual) individuals from the Tidepool Big Data Donation Project. Morlet wavelets were used for all analyses. Data were analyzed and plotted using Matlab 2020a and Python 3 in conjunction with in-house code for wavelet decomposition modified from the “Jlab” toolbox, from code developed by Dr. Tanya Leise (Leise 2013), and from the Wavelet Coherence toolkit by Dr. Xu Cui. Linear regression was used to generate correlations, and paired t-tests were used to compare AUC for wavelet and wavelet coherences by group (df=100). Stats used 1 point per individual per day.

Wavelets Assess Glucose and Insulin Rhythms and Interactions

Wavelet Coherence flow for glucose and insulin

Morlet wavelets (A) estimate rhythmic strength in glucose or insulin data at each minute in time (a combination of signal amplitude and oscillation stability) by assessing the fit of a wavelet stretched in window and in the x and y dimensions to a signal (B). The output (C) is a matrix of wavelet power, periodicity, and time (days). Transform of example HCL data illustrate the presence of predominantly circadian power in glucose, and predominantly 1-6 h ultradian power in insulin. Color map indicates wavelet power (synonymous with Y axis height). Wavelet coherence (D) enables assessment of rhythmic interactions between glucose and insulin; here, glucose and insulin rhythms are highly correlated at the 3-6 (ultradian) and 24 (circadian) hour timescales.

Results:

Hybrid Closed Loop Systems Reduce Hyperglycemia

Glucose distribution of SAP, HCL, and nonT1D
  • A) Proportional counts* of glucose distributions of all individuals with T1D using SAP (n=100) and HCL (n=100) systems. SAP system users exhibit a broader, right shifted distribution in comparison to individuals using HCL systems, indicating greater hyperglycemia (>7.8 mmol/L). Hypoglycemic events (<4mmol/L) comprised <5% of all data points for either T1D dataset.
  • B) Proportional counts* of non-T1D glucose distributions. Although limited in number, our dataset from people without diabetes exhibits a tighter blood glucose distribution, with the vast majority of values falling in euglycemic range (n=16 non-T1D individuals).
  • C) Median distributions for each dataset.
  • *Counts are scaled such that each individual contributes the same proportion of total data per bin.

HCL Improves Correlation of Glucose-Insulin Level & Rhythm

Glucose and Insulin rhythms in SAP and HCL

SAP users exhibit uncorrelated glucose and insulin levels (A) (r2 =3.3*10-5; p=0.341) and uncorrelated URs of glucose and insulin (B) (r2 =1.17*10-3; p=0.165). Glucose and its rhythms take a wide spectrum of values for each of the standard doses of insulin rates provided by the pump, leading to the striped appearance (B). By contrast, Hybrid Closed Loop users exhibit correlated glucose and insulin levels (C) (r2 =0.02; p=7.63*10-16), and correlated ultradian rhythms of glucose and insulin (D) (r2 =-0.13; p=5.22*10-38). Overlays (E,F).

HCL Results in Greater Coherence than SAP

Non-T1D individuals have highly coherent glucose and insulin at the circadian and ultradian timescales (see Mejean et al., 1988, Kern et al., 1996, Simon and Brandenberger 2002, Brandenberger et al., 1987), but these relationships had not previously been assessed long-term in T1D.

coherence between glucose and insulin in HCL and SAP, and glucose swings between SAP, HCL, and non-T1DA) Circadian (blue) and 3-6 hour ultradian (maroon) coherence of glucose and insulin in HCL (solid) and SAP (dotted) users. Transparent shading indicates standard deviation. Although both HCL and SAP individuals have lower coherence than would be expected in a non-T1D individual,  HCL CR and UR coherence are significantly greater than SAP CR and UR coherence (paired t-test p= 1.51*10-7 t=-5.77 and p= 5.01*10-14 t=-9.19, respectively). This brings HCL users’ glucose and insulin closer to the canonical non-T1D phenotype than SAP users’.

B) Additionally, the amplitude of HCL users’ glucose CRs and URs (solid) is closer (smaller) to that of non-T1D (dashed) individuals than are SAP glucose rhythms (dotted). SAP CR and UR amplitude is significantly higher than that of HCL or non-T1D (T-test,1,98, p= 47*10-17 and p= 5.95*10-20, respectively), but HCL CR amplitude is not significantly different from non-T1D CR amplitude (p=0.61).

Together, HCL users are more similar than SAP users to the canonical Non-T1D phenotype in A) rhythmic interaction between glucose and insulin and B) glucose rhythmic amplitude.

Conclusions and Future Directions

T1D and non-T1D individuals exhibit different relative stabilities of within-a-day rhythms and daily rhythms in blood glucose, and T1D glucose and insulin delivery rhythmic patterns differ by insulin delivery system.

Hybrid Closed Looping is Associated With:

  • Lower incidence of hyperglycemia
  • Greater correlation between glucose level and insulin delivery rate
  • Greater correlation between ultradian glucose and ultradian insulin delivery rhythms
  • Greater degree of circadian and ultradian coherence between glucose and insulin delivery rate than in SAP system use
  • Lower amplitude swings at the circadian and ultradian timescale

These preliminary results suggest that HCL recapitulates non-diabetes glucose-insulin dynamics to a greater degree than SAP. However, pump model, bolusing data, looping algorithms and insulin type likely all affect rhythmic structure and will need to be further differentiated. Future work will determine if stability of rhythmic structure is associated with greater time in range, which will help determine if bolstering of within-a-day and daily rhythmic structure is truly beneficial to PWT1D.
Acknowledgements:

Thanks to all of the individuals who donated their data as part of the Tidepool Big Data Donation Project, as well as the OpenAPS Data Commons, from which data is also being used in other areas of this study. This study is supported by JDRF (1-SRA-2019-821-S-B).

(You can download a full PDF copy of the poster here.)

Next is “Do-It-Yourself Artificial Pancreas Systems for Type 1 Diabetes Reduce Hyperglycemia Without Increasing Hypoglycemia” (poster 988-P in category 12-D Clinical Therapeutics/New Technology—Insulin Delivery Systems), which I co-authored alongside Jennifer Zabinsky, MD MEng, Haley Howell, MSHI, Alireza Ghezavati, MD, Andrew Nguyen, PhD, and Jenise Wong, MD PhD. There is a Twitter thread summarizing this poster here.

This was a retrospective double cohort study that evaluated data from the OpenAPS Data Commons (data ranged from 2017-2019) and compared it to conventional sensor-augmented pump (SAP) therapy from the Tidepool Big Data Donation Project.

Methods:

  • From the OpenAPS Data Commons, one month of CGM data (with more than 70% of the month spent using CGM), as long as they were >1 year of living with T1D, was used. People could be using any type of DIYAPS (OpenAPS, Loop, or AndroidAPS) and there were no age restrictions.
  • A random age-matched sample from the Tidepool Big Data Donation Project of people with type 1 diabetes with SAP was selected.
  • The primary outcome assessed was percent of CGM data <70 mg/dL.
  • The secondary outcomes assessed were # of hypoglycemic events per month (15 minutes or more <70 mg/dL); percent of time in range (70-180mg/dL); percent of time above range (>180mg/dL), mean CGM values, and coefficient of variation.
Methods_DIYAPSvsSAP_ADA2020_DanaMLewis

Demographics:

  • From Table 1, this shows the age of participants was not statistically different between the DIYAPS and SAP cohorts. Similarly, the age at T1D diagnosis or time since T1D diagnosis did not differ.
  • Table 2 shows the additional characteristics of the DIYAPS cohort, which included data shared by a parent/caregiver for their child with T1D. DIYAPS use was an average of 7 months, at the time of the month of CGM used for the study. The self-reported HbA1c in DIYAPS was 6.4%.
Demographics_DIYAPSvsSAP_ADA2020_DanaMLewis DIYAPS_Characteristics_DIYAPSvsSAP_ADA2020_DanaMLewis

Results:

  • Figure 1 shows the comparison in outcomes based on CGM data between the two groups. Asterisks (*) indicate statistical significance.
  • There was no statistically significant difference in % of CGM values below 70mg/dL between the groups in this data set sampled.
  • DIYAPS users had higher percent in target range and lower percent in hyperglycemic range, compared to the SAP users.
  • Table 3 shows the secondary outcomes.
  • There was no statistically significant difference in the average number of hypoglycemic events per month between the 2 groups.
  • The mean CGM glucose value was lower for the DIYAPS group, but the coefficient of variation did not differ between groups.
CGM_Comparison_DIYAPSvsSAP_ADA2020_DanaMLewis SecondaryOutcomes_DIYAPSvsSAP_ADA2020_DanaMLewis

Conclusions:

    • Users of DIYAPS (from this month of sampled data) had a comparable amount of hypoglycemia to those using SAP.
    • Mean CGM glucose and frequency of hyperglycemia were lower in the DIYAPS group.
    • Percent of CGM values in target range (70-180mg/dL) was significantly greater for DIYAPS users.
    • This shows a benefit in DIYAPS in reducing hyperglycemia without compromising a low occurrence of hypoglycemia. 
Conclusions_DIYAPSvsSAP_ADA2020_DanaMLewis

(You can download a PDF of the e-poster here.)

Finally, my presentation at this year’s D-Data conference (#DData20). The study I presented, called AID-IRL, was funded by Diabetes Mine. You can see a Twitter thread summarizing my AID-IRL presentation here.

AID-IRL-Aim-Methods_DanaMLewis

I did semi-structured phone interviews with 7 users of commercial AID systems in the last few months. The study was funded by DiabetesMine – both for my time in conducting the study, as well as funding for study participants. Study participants received $50 for their participation. I sought a mix of longer-time and newer AID users, using a mix of systems. Control-IQ (4) and 670G (2) users were interviewed; as well as (1) a CamAPS FX user since it was approved in the UK during the time of the study.

Based on the interviews, I coded their feedback for each of the different themes of the study depending on whether they saw improvements (or did not have issues); had no changes but were satisfied, or neutral experiences; or saw negative impact/experience. For each participant, I reviewed their experience and what they were happy with or frustrated by.

Here are some of the details for each participant.

AID-IRL-Participant1-DanaMLewisAID-IRL-Participant1-cont_DanaMLewis1 – A parent of a child using Control-IQ (off-label), with 30% increase in TIR with no increased hypoglycemia. They spend less time correcting than before; less time thinking about diabetes; and “get solid uninterrupted sleep for the first time since diagnosis”. They wish they had remote bolusing, more system information available in remote monitoring on phones. They miss using the system during the 2 hour CGM warmup, and found the system dealt well with growth spurt hormones but not as well with underestimated meals.

AID-IRL-Participant2-DanaMLewis AID-IRL-Participant2-cont-DanaMLewis2 – An adult male with T1D who previously used DIYAPS saw 5-10% decrease in TIR (but it’s on par with other participants’ TIR) with Control-IQ, and is very pleased by the all-in-one convenience of his commercial system.He misses autosensitivity (a short-term learning feature of how insulin needs may very from base settings) from DIYAPS and has stopped eating breakfast, since he found it couldn’t manage that well. He is doing more manual corrections than he was before.

AID-IRL-Participant5-DanaMLewis AID-IRL-Participant5-cont_DanaMLewis5 – An adult female with LADA started, stopped, and started using Control-IQ, getting the same TIR that she had before on Basal-IQ. It took artificially inflating settings to achieve these similar results. She likes peace of mind to sleep while the system prevents hypoglycemia. She is frustrated by ‘too high’ target; not having low prevention if she disables Control-IQ; and how much she had to inflate settings to achieve her outcomes. It’s hard to know how much insulin the system gives each hour (she still produces some of own insulin).

AID-IRL-Participant7-DanaMLewis AID-IRL-Participant7-cont-DanaMLewis7 – An adult female with T1D who frequently has to take steroids for other reasons, causing increased BGs. With Control-IQ, she sees 70% increase in TIR overall and increased TIR overnight, and found it does a ‘decent job keeping up’ with steroid-induced highs. She also wants to run ‘tighter’ and have an adjustable target, and does not ever run in sleep mode so that she can always get the bolus corrections that are more likely to bring her closer to target.

AID-IRL-Participant3-DanaMLewis AID-IRL-Participant3-cont-DanaMLewis3 – An adult male with T1D using 670G for 3 years didn’t observe any changes to A1c or TIR, but is pleased with his outcomes, especially with the ability to handle his activity levels by using the higher activity target.  He is frustrated by the CGM and is woken up 1-2x a week to calibrate overnight. He wishes he could still have low glucose suspend even if he’s kicked out of automode due to calibration issues. He also commented on post-meal highs and more manual interventions.

AID-IRL-Participant6-DanaMLewis AID-IRL-Participant6-contDanaMLewis6 – Another adult male user with 670G was originally diagnosed with T2 (now considered T1) with a very high total daily insulin use that was able to decrease significantly when switching to AID. He’s happy with increased TIR and less hypo, plus decreased TDD. Due to #COVID19, he did virtually training but would have preferred in-person. He has 4-5 alerts/day and is woken up every other night due to BG alarms or calibration. He does not like the time it takes to charge CGM transmitter, in addition to sensor warmup.

AID-IRL-Participant4-DanaMLewis AID-IRL-Participant4-contDanaMLewis4 – The last participant is an adult male with T1 who previously used DIYAPS but was able to test-drive the CamAPS FX. He saw no TIR change to DIYAPS (which pleased him) and thought the learning curve was easy – but he had to learn the system and let it learn him. He experienced ‘too much’ hypoglycemia (~7% <70mg/dL, 2x his previous), and found it challenging to not have visibility of IOB. He also found the in-app CGM alarms annoying. He noted the system may work better for people with regular routines.

You can see a summary of the participants’ experiences via this chart. Overall, most cited increased or same TIR. Some individuals saw reduced hypos, but a few saw increases. Post-meal highs were commonly mentioned.

AID-IRL-UniversalThemes2-DanaMLewis AID-IRL-UniversalThemes-DanaMLewis

Those newer to CGM have a noticeable learning curve and were more likely to comment on number of alarms and system alerts they saw. The 670G users were more likely to describe connection/troubleshooting issues and CGM calibration issues, both of which impacted sleep.

This view highlights those who more recently adopted AID systems. One noted their learning experience was ‘eased’ by “lurking” in the DIY community, and previously participating in an AID study. One felt the learning curve was high. Another struggled with CGM.

AID-IRL-NewAIDUsers-DanaMLewis

Both previous DIYAPS users who were using commercial AID systems referenced the convenience factor of commercial systems. One DIYAPS saw decreased TIR, and has also altered his behaviors accordingly, while the other saw no change to TIR but had increased hypo’s.

AID-IRL-PreviousDIYUsers-DanaMLewis

Companies building AID systems for PWDs should consider that the onboarding and learning curve may vary for individuals, especially those newer to CGM. Many want better displays of IOB and the ability to adjust targets. Remote bolusing and remote monitoring is highly desired by all, regardless of age. Post-prandial was frequently mentioned as the weak point in glycemic control of commercial AID systems. Even with ‘ideal’ TIR, many commercial users still are doing frequent manual corrections outside of mealtimes. This is an area of improvement for commercial AID to further reduce the burden of managing diabetes.

AID-IRL-FeedbackForCompanies-DanaMLewis

Note – all studies have their limitations. This was a small deep-dive study that is not necessarily representative, due to the design and small sample size. Timing of system availability influenced the ability to have new/longer time users.

AID-IRL-Limitations-DanaMLewis

Thank you to all of the participants of the study for sharing their feedback about their experiences with AID-IRL!

(You can download a PDF of my slides from the AID-IRL study here.)

Have questions about any of my posters or presentations? You can always reach me via email at Dana@OpenAPS.org.

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:

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:

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:

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.

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:

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!

Missing metrics in diabetes measurement by @DanaMLewis

“May I ask what your A1c is?”

This is a polite, and seemingly innocuous question. However, it’s one of my least favorite questions taken at face value. Why?

Well, this question is often a proxy for some of the following questions:

  • How well are *you* doing with DIY closed loop technology?
  • How well could *I* possibly do with DIY closed loop technology?
  • What’s possible to achieve in real-world life with type 1 diabetes?

But if I answered this question directly with “X.x%”, it leaves out so much crucial information. Such as:

  • What my BG targets are
    • Because with DIY closed loop tech like OpenAPS, you can choose and set your own target.
    • (That’s also one of the reasons why the 2018 OpenAPS Outcomes Study is fascinating to me, because people usually set high, conservative targets to start and then gradually lower them as they get comfortable. However, we didn’t have a way to retrospectively sleuth out targets, so those are results are even with the amalgamation of people’s targets being at any point they wanted at any time.)
  • What type of lifestyle I live
    • I don’t consider myself to eat particularly “high” or “low” carb. (And don’t start at me about why you choose to eat X amount of carbs – you do you! and YDMV) Someone who *is* eating a lot higher or lower carb diet compared to mine, though, may have a different experience than me.
    • Someone who is not doing exercise or activity may also have a different experience then me with variability in BGs. Sometimes I’m super active, climbing mountains (and falling off of them..more detail about that here) and running marathons and swimming or scuba diving, and sometimes I’m not. That activity is not so much about “being healthy”, but a point about how exercise and activity can actually make it a lot harder to manage BGs, both due to the volatility of the activity on insulin sensitivity etc.; but also because of the factor of going on/off of insulin for a period of time (because my pump is not waterproof).
  • What settings I have enabled in OpenAPS
    • I use most of the advanced settings, such as “superMicroBoluses” (aka SMB – read more about how it works here); with a higher than default “maxSMBBasalMinutes”; and I also use all of the advanced exercise settings so that targets also nudge sensitivity in addition to autosensitivity picking up any changes after exercise and other sensitivity-change-inducing activities or events. I also get Pushover alerts to tell me if I need any carbs (and how many), if I’m dropping faster and expected to go below my target, even with zero temping all the way down.
  • What my behavioral choices are
    • Timing of insulin matters. As I learned almost 5 years ago (wow), the impact of insulin timing compared to food *really* matters. Some people still are able to do and manage well with “pre-bolusing”. I don’t (as explained there in the previous link). But “eating soon” mode does help a lot for managing post-meal spikes (see here a quick and easy visual for how to do “eating soon”). However, I don’t do “eating soon” regularly like I used to. In part, because I’m now on a slightly-faster insulin that peaks in 45 minutes. I still get better outcomes when I do an eating-soon, sure, but behaviorally it’s less necessary.
    • The other reason is because I’ve also switched to not bolusing for meals.
      • (The exceptions being if I’m not looping for some reason, such as I’m in the middle of switching CGM sensors and don’t have CGM data to loop off of.)

These settings and choices are all crucial information to understanding the X.x% of A1c.

Diabetes isn’t just the average blood glucose value. It’s not just the standard deviation or coefficient of variation or % time in range or how much BG fluctuates.

Diabetes impacts so much of our daily life and requires so much cognitive burden for us, and our loved ones. That’s part of the reasons I appreciate so much Sulka & his family being candid about how their A1C didn’t change, but the amount of work required to achieve it did (way fewer manual corrections). And ditto for Jason & the Wittmer family for sharing about the change in the number of school nurse visits before/after using OpenAPS. (See both of their stories in this post)

For me, my quality of life metric has always been first about sleep: can I sleep safely and with peace of mind at night? Yes. Then – how long can I safely sleep? (The answer: a lot. Yay!)  But over time, my metrics have also evolved to consider how I can cut down (like Sulka) on the amount of work it takes to achieve my ideal outcomes, and find a happy balance there.

As I mentioned in this podcast recently, other than changing my pump site (here’s how I change mine) and soaking and swapping my CGM sensors (psst – soak your sensor!), I usually only take a few diabetes-related actions a day. They’re usually on my watch, pressing a button to either enable a temp target or entering carbs when I sit down to eat.

That’s a huge reduction in physical work, as well as amount of time spent thinking/planning/doing diabetes-related things. And when life happens – because I get the flu or the norovirus or I fall off a mountain and break my ankle – I don’t worry about diabetes any more.

So when I’m asked about A1c, my answer is not a simple “X.x%”. (And not just for the reason I’m annoyed by how much judging and shaming goes on around A1c, although that influences it, too.) I usually remind people that I first started with an “open loop” for a year, and that dropped my A1c by X%. And then I closed the loop, which reduced my A1c further. And we made OpenAPS even better over the last four years, which reduced it further. And then I completely stopped bolusing! And got less lows…and kept the same A1c.

And then I ask them what they’d really like to know. :) If it’s a fellow person with diabetes or a loved one, we talk about what problems they might be having or what areas they’d like to improve or what behaviors they’d like to change, if any. That’s usually way more effective than hearing “X.x%” of an A1c, and them wondering silently how to get there or what to do differently if someone wants to change things. (Or for clinicians who ask me, it turns into a discussion about choices and behaviors and tradeoffs that patients may choose to make.)

Remember, your diabetes may (and will) vary (aka, YDMV). Your lifestyle, the phase of life you’re in, your priorities, your body and health, and your choices will ALL be different than mine. That’s not bad in any way: that’s just the way it is. The behaviors I choose and the work I’m willing to do (or not do) to achieve *my* goals (and what my goals are), will be different than what you choose for yours.

And that’s therefore why A1c is not “enough” to me as a metric and something that we should compare people on, even though A1c is the “same” for everyone: because the work, time spent, behavioral tradeoffs, and goals related to it will all vary.

Missing_metrics_@DanaMLewis

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!

Scuba diving with a flash glucose monitor (Libre)

Scuba_Flash_Glucose_Monitoring_DanaMLewisI just went scuba diving in Australia* at the Great Barrier Reef, and I took a flash glucose monitor (Libre) with me under the water.

WHAT! Yes, really. Scuba diving with a Libre. (Your mileage may vary, of course! The Libre receiver is not waterproof in of itself, and obviously not rated/tested for depth. I did some of that testing for myself. See below 😉 )

Historically (and you can read more in this post for more detail on what else I do regarding pump, CGM, and everything else for scuba diving with diabetes and other diabetes devices),  I only had a CGM that did not work underwater, and did not work for around an hour after I went diving since it would get waterlogged.

A few months ago when Libre was FDA approved in the US, I paid cash out of pocket (for a receiver + 3 sensors) to try it to see how it did compared to my CGM.  For most purposes, a CGM still makes sense for me, because I rely on it for closed looping, and on its low and high glucose alarms.  But I know from previous dives and other water activities that my CGM doesn’t work well after a long time in (deep) salt water: I often get false-positive highs for an hour (or more) afterward.  So for this trip, I was thinking I would wear a Libre sensor for the dive trip, and just scan when I got out of the water, so I didn’t have to do a fingerstick test after every dive.

In the weeks leading up to our trip, I also saw a picture and heard rumblings of people going scuba diving and taking their Libre receiver under the water. I couldn’t find any details about it, though: What case? What depth? etc. ARGH.

So we decided to pick out a waterproof phone case and just give it a try during our trip. Worst case, we’d just ruin the receiver. Scott found this waterproof phone case/bag (<–Amazon affiliate link) and ordered it, and I packed it for the trip. Probably other similar phone cases would work, too – brand likely doesn’t matter, but you obviously would want a case that’s not going to leak, and should perform a leak test on it before you leave home.

We did a “liveaboard” for 3 days and 2 nights (really, ~48 hours on the boat). There’s a transfer boat that takes you out to the “liveaboard”, which is essentially a floating hotel. When you get there, you’re allowed to do a snorkel session before lunch; the first dive briefing is after lunch, and you can then dive during the sessions (max 3 day dives total and 1 night dive) after that during your stay. All this detail to explain that we popped the Libre receiver in the waterproof bag and took it into the water with us when we went snorkeling. And it worked great! So that gave me the courage I needed to take it down during our first dive.

The waterproof case had a strap where you could wear it around your neck, which is what I did. That ended up being annoying occasionally (because the bag would float above you during the die, and sometimes got caught on my snorkel), but it worked. (For future trips I’d probably find a stretchy cord to attach it to my BCD where it was accessible but didn’t have to float or be hung around my neck.)

I wore two wetsuits (I get cold easily!), and even with two layers of wetsuit; the waterproof case; and you know, the water – I was still able to easily press the button on the Libre receiver through the bag, swipe it over my arm, and pick up a BG reading! It was super cool for it to work. The hardest part: finding the Libre sensor under 2 layers of wetsuit on my arm.

The first few dives were somewhat shallow – 9-12 meters of depth, but over the course of all my dives, I ended up testing it down to 16 meters. I also tested it on 9 total sessions – 1 snorkel, 2 morning sunrise dives, 2 night dives (whoa), and 4 daytime dives. The bag did fine throughout each submersion and never leaked.

I was also expecting the sensor to peel up, so I did four strips of flexifix tape (like I do to my CGM sensor) around the outside edges of the sensor. The tape itself didn’t end up peeling up, and the sensor stayed on just fine! (It probably helped that I wasn’t sunscreening the edges of the tape, since I was pretty much in 2 layers of wetsuit every time I was out in the water and in the sun.) If the sensor ripped out, that would have been a pain as the one I have is the original one approved in the US that requires a 12 hour warmup (ugh) – thankfully, that didn’t happen, and also thankfully, the day we got off the boat we heard that the Libre is now approved in the US for 14 day wear (instead of 10) and now only ONE hour warmup (yay!). That’ll make it nice and easy (if I get the updated sensors) for future dive trips if a sensor rips off.

In terms of accuracy and sensor performance:

My first Libre sensor that I had tried at home a few months ago when we got it ran low pretty consistently, and ran REALLY low when my BG was normal. That drove me nuts and I was pretty sure that I wouldn’t want to rely on it the way some people do. So I was planning to not be able to rely on the numbers, and just use it for trends when diving. However, this second sensor (that I did all my scuba diving with) was spot on, even when high and low. I cross checked with finger sticks before and after the first dive, but quickly tailed off fingersticks (other than calibrating my CGM) for the most part, and was able to rely on Libre to double-check my CGM. (As expected, because of the waterlogging, the CGM ran falsely high, sometimes 100 mg/dL off, for about an hour after the dive.)

I left the Libre on even beyond the dive boat part of our trip, and it’s been spot on alongside my CGM (which is also spot on) compared to fingersticks.

So to summarize my experience: Libre is great for scuba diving. I tested it down to 16 meters and was happy with how it worked underwater! I loved being able to check mid-dive and see my trends. I never had a low during my 8 dives in 48 hours, and I never worried about going low since I wasn’t diving “blind” to my BGs. I definitely plan to use this for future scuba diving trips, and would also consider using it for any beach/water-based activities. The convenience is worth (for me) paying out of pocket cash for a few sensors to be able to access my BGs easily during these activities.

* One final note: Australia has some of the strictest diving laws in the world regarding your health. If you have type 1 diabetes, you have to have a very particular Australian dive medical form filled out before any company will let you dive. Now, many companies will tell you to just show up in Cairns and use the dive medical centers for a cheap and easy dive medical. HOWEVER: we called three of them in advance. One said “NOPE” out of hand to approving a (perfectly healthy) person with type 1, solely because that person (me) has type 1. The second wasn’t sure and asked us to email a full medical history to give us an opinion. They never responded to the email. The third didn’t answer phone or email. Ugh. So: my advice is, get the form, and go talk **in person** to your physician of choice about this and the necessary information needed to have a physician fill out this form. I stressed a lot about this; but once I handed in the special form along with the standard medical form everyone has to fill out – they didn’t say a word to me, ask me about diabetes, or prevent me from diving. So my advice is to go prepared with your form!

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

Getting ready for #2018ADA (@DanaMLewis) & preparing to encourage photography

We’re a few weeks away from the 78th American Diabetes Scientific Sessions (aka, #2018ADA), and I’m getting excited. Partially because of the research I have the honor of presenting; but also because ADA has made strides to (finally) update their photography policy and allow individual presenters to authorize photography & sharing of their content. Yay!

As a result of preparing to encourage people to take pictures & share any and all content from my presentations, I started putting together my slides for each presentation, including the slide about allowing photography, which I’ll also verbally say at the start of the presentation. Interestingly to me, though, ADA only provided an icon for discouraging photography, saying that if staff notice that icon on any photos, that’s who will be asked to take down photos. I don’t want any confusion (in past years, despite explicit permission, people have been asked to take down photos of my work), so I wanted to include obvious ‘photography is approved’ icons.

And this is what I landed on for a photography encouraged slide, and the footer of all my other slides:

Encouraging photography in my slides Example encouraging use of photography in content slidesEncouraging photography in the footer of my slides

And, if anyone else plans to encourage (allow) photography and would like to use this slide design, you can find my example slide deck here that you are welcome to use: http://bit.ly/2018ADAexampleslides

I used camera and check mark icons which are licensed to be freely used; and I also licensed this slide deck and all content to be freely used by all! I hope it’s helpful.

Where you’ll find me at #2018ADA

And if you’re wondering where and what I’ll be presenting on with these slides…I’ll be sharing new content in a few different times and places!

On Saturday, I’m thrilled there is a full, 2-hour session on DIY-related content, and to get to share the stage with Jason Wittmer, Lorenzo Sandini, and Joyce Lee. That’s 1:45-3:45pm (Eastern), “The Diabetes Do-It-Yourself (DIY) Revolution”, in W415C (Valencia Ballroom). I’ll be discussing some of the data & research in DIY diabetes! A huge thanks to Joshua Miller for championing and moderating this session.

I’m also thrilled that a poster has been accepted on one of the projects from my RWJF grant work, in partnership with Tim Street (as well as Scott Leibrand, and Sayali Phatak who is heading our data science work for Opening Pathways). The embargo lifts on Saturday morning (content will be shared online then), and the poster will be displayed Saturday, Sunday, and Monday. Scott and I will also be present with the poster on Monday during the poster session from 12-1pm.

And last but not least, there is also an oral presentation on Monday evening with a new study on outcomes data from using OpenAPS. I’ll be presenting during the 4:30-6:30pm session (again in W415C (Valencia Ballroom)), likely during the 6-6:15pm slot. I’m thrilled that Scott Swain & Tom Donner, who partnered on this study & work, will also be there to help answer questions about this study!

As we have done in the past (see last year’s poster, for example), we plan to share all of this content online once the embargo lifts, in addition to the in-person presentations and poster discussions.

A huge thanks, as always, goes to the many dozens of people who have contributed to this DIY community in so many ways: development, testing, support, feedback, documentation, data donation, and more! <3