The OpenAPS community submitted an abstract that was accepted for a poster presentation at the American Diabetes Association’s Scientific Sessions meeting. The embargo lifted this morning, so you can read the abstract here or read below for the content from the poster. We hope everyone in the healthcare provider and diabetes communities can learn from those who have used autotune, either with or without a DIY hybrid closed loop, and share their insights with their friends, colleagues, and patients.

(If you’re at Scientific Sessions, please do stop by and ask questions during the poster session on Sunday from 12-1pm!)

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BACKGROUND:

The #OpenAPS community is an active patient community that is developing DIY tools and resources for people with diabetes. There are over (n=1)*310+ people worldwide self-building various types of DIY hybrid closed loop artificial pancreas systems. As a result of observing hundreds of people in the OpenAPS community, we recognized that most people were relying on poorly tuned underlying insulin pump settings before starting a closed loop system.

Autotune, a tool for automatically tuning insulin pump basal rates, ISF, and carb ratios, was created in January 2017. Autotune was initially intended for primary use in pumpers who are using a DIY closed loop system, but was iterated upon to support non-looping pump users, and is also being used by people on MDI to help tune their basal insulin dosing. (Autotune can be used by anyone with a CGM who manually or automatically uploads insulin dosing and treatment (i.e. carb) data to Nightscout.)

How Autotune Works (Summary, see full details here)

• Insulin dosing and carb data, glucose data from CGM, and pump profile settings are used to calculate expected blood glucose impact (BGI) for each glucose value.
• Each glucose value is then categorized as being most attributable to basal, ISF, or carb sensitivity factor (CSF = ISF / carb ratio), and used to calculate adjustments to basals, ISF, and CSF.
• For each hour, total BGI deviations, and necessary adjustment in basal to bring deviations to 0, are calculated; 20% is applied to the previous 3 hours’ basals.
• Median deviation for entire day’s ISF-attributed data and necessary adjustment in ISF to bring the median deviation to 0 are calculated; 10% is applied.
• Total BGI deviations during observed carb absorption are calculated and compared to total carb intake to calculate new CSF; 10% is applied to the carb ratio.

Self-reported reflections from people using Autotune:

• (n=1)*16 people reported feedback related to their use of Autotune.
• 75% of surveyed users made changes to their insulin pump settings after running autotune.
  • 100% of people felt basal suggestions were accurate: 83% changed their basal rates.
  • They were less sure of carb ratio estimations (only 69% felt the estimates were accurate): 58% changed their carb ratios.
  • 88% of people felt ISF suggestions were accurate: 67% changed their ISF.
• On average in the surveyed population, autotune estimated a needed 10.24% average change in hourly basal rates (net 4.54% increase overall); 29% increase needed in carb ratios; and 19% increase needed in ISF.
• Patients felt strongly that using data to assess changes to pump settings should be the norm rather than relying on the current methods of guessing or weight-based estimations.

Other reflections:

• Most users planned to (or did) discuss Autotune results with their HCP. Most users reported their HCPs were interested and supportive in people using this tool.
• Most users expressed interest in a data-driven tool vs. relying on HCPs guessing about changes.
• Autotune currently works with a single ISF and carb ratio. There is interest from the community to adapt the tool to support use for multiple ISF and carb ratio. There is also interest to use data from this tool to confirm whether multiple ISF and carb ratios are needed or if they are proxies for mistimed insulin dosing at other times of day.

Conclusion:

• These data show many patients are using non-optimal settings.
• Pump users and HCPs could benefit from using this type of tool to help make ongoing changes to ratios and basals.
• The anecdotal number of individuals (hundreds) using this tool reflects the need for pump users and MDI users to have better tools to optimize basic diabetes therapy.

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Autotune is available for use for anyone who is using Nightscout with CGM data and is uploading insulin and carb treatment information. You can find the documentation and information for using autotune in the OpenAPS documentation here. You can find out more about OpenAPS on OpenAPS.org, from the reference design to frequently asked questions (such as what hardware is needed and where the code and documentation can be found).