ICYMI - we shared ideas earlier this week we called “CoEpi” for a community-based project to help track symptoms and spread of transmissible illnesses, and better inform individuals about their personal level of risk of things like #COVID19 or flu.
In the resulting discussions around the idea, we ran into @hamish_rodda who had a similar idea he was calling “FluSmart”. So we joined forces!
Together along with other individuals in the community (including @Rahatcodes), we’ve begun to build the prototype of #CoEpi.
We’ve also continued to work on our ideas and have added some other features to the development roadmap in the future with regards to useful, context-driven (and location-change-driven) prompts for handwashing and future data integration (e.g. temperature monitoring).
Where we could use help right now: 1) Developers - We need people w/experience with cloud applications with backend data stores and flexible container-based front ends, & mobile app development experience (native iOS/Android/using something like #ReactNative) to help build #CoEpi
2) Taking it further - we’re working on finishing content for the app, thinking through both privacy impact and managing expectations, and planning other communications efforts. If you want to & can help in any of those areas, let us know, too.
And of course, 3) stay tuned (co-epi.github.io/website/), we’ll keep everyone posted as we work toward a prototype and beta testing in our broader communities.
Thanks for all the interest and feedback so far as we continue to work on bringing #CoEpi alive for our communities!
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1/ What if there was a tool to help identify who might have exocrine pancreatic insufficiency (EPI/PEI)?
EPI is a significant issue for many people with diabetes (likely more common than gastroparesis or celiac).
Here's how such a tool can help PWD👇🏼🧵
#ADASciSessions #ADA2024
2/ The Exocrine Pancreatic Insufficiency Symptom Score (EPI/PEI-SS) has 15 symptoms, rated by how frequent they are and how bothersome they are (aka severity).
n=324 ppl participated in a real-world survey.
n=118 were people with diabetes (PWD)!
#ADASciSessions #ADA2024
3/ Methods:
EPI/PEI-SS scores were analyzed and compared between PWD (n=118), with EPI (T1D: n=14; T2D: n=20) or without EPI (T1D: n=78; T2D: n=6), and people without diabetes (n=206) with and without EPI.
📣 Presentation of the primary outcome results from the CREATE Trial, which assessed open source automated insulin delivery (AID) compared to sensor-augmented pump therapy (SAPT) in adults & kids with T1D, at #ADA2022!
The CREATE trial aimed to study the efficacy and safety of an open source automated insulin delivery system, with a large scale, long term randomized controlled trial.
I just realized it's been 3 (!) years since I published my book on automated insulin delivery, with the goal of helping increased conversation and understanding of AID technology for people with diabetes, their loved ones, and healthcare providers!
I'm still very proud that it is available to read for free online, free to download a PDF (both of which have been done thousands of times each: ArtificialPancreasBook.com), or as an e-book, paperback, and now hardback copy. Proceeds from the purchased copies go to Life For A Child.
And, more recently, it has also been translated into French by the wonderful Dr. Mihaela Muresan and Olivier Legendre!
The French translation is available in Kindle, paperback, hardback, or free PDF download formats as well.
1/THREAD - my presentation is kicking off at #EASD2020 about open source automated insulin delivery.
(You can see a full version of my presentation here: bit.ly/DanaMLewisEASD…, or read the summary below!)
Note we should differentiate between open source (where the source of something is open), and DIY (do-it-yourself) implementations of open source code. Open source means it can be reviewed and used by individuals (thus, DIY or #DIYAPS) or by companies.
Poster 988-P at #ADA2020 by Jennifer Zabinsky, Haley Howell, Alireza Ghezavati, @DanaMLewis Andrew Nguyen, and Jenise Wong: “Do-It-Yourself Artificial Pancreas Systems Reduce Hyperglycemia Without Increasing Hypoglycemia”
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_org Big Data Donation Project. #ADA2020
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 from the @OpenAPS Data Commons. People could be using any type of DIYAPS (OpenAPS, Loop, or AndroidAPS) and there were no age restrictions. #ADA2020
Poster 99-LB at #ADA2020 by @danamlewis, @azure_dominique, and Lance Kriegsfeld, “Multi-Timescale Interactions of Glucose and Insulin in Type 1 Diabetes Reveal Benefits of Hybrid Closed Loop Systems“
Background - Blood glucose and insulin exhibit coupled biological rhythms at multiple timescales, including hours (ultradian, UR) and the day (circadian, CR) in individuals without diabetes. But, biological rhythms in longitudinal data have not been mapped in T1D. #ADA2020
It is not known exactly how glucose and insulin rhythms compare between T1D and non-T1D, and whether rhythms are affected by type of therapy (Sensor Augmented Pump (SAP) or Hybrid Closed Loop (HCL)). #ADA2020