ATTD 2021 was held 2-5 June, 2021 and, thanks to dedoc, I had the privilege to attend and live tweet the presentations. However, with many sessions running in parallel, it was not possible to attend every session and many sessions covered similar topics. To address this, I watched the recordings of the sessions I missed and brought them together under common themes. Where the presentation called out that the results were confidential and/or not yet published and not for distribution I left them out of my blog but I can confirm there was nothing presented under confidence which contradicted what I am presenting in these summaries.
This is my first “distillation” covering looping. Once the domain of the online diabetes hacker community, looping (the interaction of a CGM and pump, with minimal human interaction to maintain blood glucose levels) has become mainstream with commercial looping systems available.
Specific questions covered in the presentations were:
- Loop vs Non-Loop: Which is Better?
- Loops Which Bolus vs Those Which Only Adjust Basal: Which is Better?
- Is Faster Insulin Better in Closed Loop Systems?
- What is the Future of Looping?
As usual there is a TL;DR section at the end if you want to cut to the summary.
Loop vs Non-Loop: Which is Better?
Dr. Bruce Buckingham presented a study considering the Omnipod pump with Dexcom looping versus “Standard Treatment” i.e. non-looping options such as multiple daily injection or traditional pumping. For both children and adults, looping brought the HbA1c down to sub-7% levels. As we know from my previous analysis, getting the HbA1c below 7% is important to reduce the risk of long term complications.
Time in Range also improved with looping gaining more than two extra hours in range for the adults and almost four additional hours for the children.
Looping also helped with overnight highs in children and, to a lesser extent, with adults.
When looking at people with Type 2 Diabetes, there was also improvement in Time in Range and a reduction in Time Above Range.
Dr. Charlotte Boughton presented similar research showing a clear improvement of looping over multiple daily injection or a non-looping pump (HCL = Hybrid Closed Loop i.e. looping with declarations/human adjustments)
Dr. Goran Petrovski also provided details on the results of how Medtronic compared to multiple daily injection and CGM showing significant improvement in Time in Range and HbA1c.
He also showed the benefits of the closed loop system become apparent in the first few days of activation and continue to improve over the following months.
Loops Which Bolus vs Those Which Only Adjust Basal: Which is Better?
Dr. Ahmad Haidar provided a great summary of many studies comparing Automated Hybrid Closed Loop (AHCL) systems vs a “Sensor Augmented Pump with Predictive Low Glucose Management” (SAP + PLGM). To translate, comparing a system which gave “shots” of insulin against those which just managed continual rate of release (basal rate) e.g. Medtronic 780G vs 670G. As can be seen, regardless of the technology employed, the improvement was similar across the systems.
Dr. Anders L. Carlson spoke of the Medtronic study.
The results showed statistically significant improvements across all measures, including the time below range.
This was also backed up by a second and third study showing increased Time in Range and reduced time both above range and below range.
The first study showed stronger benefits for adolescents (also seen in the second study and shown on the Pivotal Study image above) and improved Time in Range (TIR) when a more aggressive endpoint was set.
The second study also confirmed the notion that a more aggressive endpoint led to an increased Time in Range and went further to suggest setting the Active Insulin Time to its lowest setting also helped improve Time in Range and lower Time Below Range.
Dr. Thekla von dem Burge showed that the benefits in the Medtronic system extended all the way down to pre-schoolers where there was a significant increase in those achieving range targets.
Dr. Boris Kovatchev presented a study using t:slim technology, instead of Medtronic, comparing Control-IQ to Basal-IQ which also confirmed a fully automated loop system improves Time in Range. It also showed the benefits begin within literally a month of employing the technology.
This study also showed the greatest benefit of the Control-IQ system was in the night time where, at its peak, it achieved 30% higher Time in Range.
As with the Medtronic studies, Time Above/Below Range was also improved with Control-IQ and also brought children’s metrics in line with the adults’.
In line with the Medtronic research, Dr. Jordan Pinsker showed the Control-IQ system provided benefit to all age groups, improving Time in Range and reducing Time Above Range.
Furthermore, the analysis showed those with poorer control (as measured by GMI, an estimation of HbA1c) achieved the greatest improvements. This is interesting because good control is often used as a selection for people to include in studies meaning much of the research could be missing a cohort who will benefit significantly from looping technology.
In line with Medtronic and t:slim, Erik Huneker also found found full looping had benefit over Predictive Low Glucose Suspend (PLGS, suspension of basal insulin when low) for people with highly unstable diabetes when using Diabeloop.
Finally, we had Dr. Roman Hovorka who, with the CamAPS looping setup, saw similar results to the other systems and great improvements in overnight management.
Is Faster Insulin Better in Closed Loop Systems?
Dr. Boris Kovatchev presented a paper comparing the performance of fast insulin to standard insulin in a fully closed loop system (no meal announcements) with moderate-vigorous exercise.
Looking at the traces, we can see both insulins followed a similar path. The authors concluded that the algorithms were possibly better tuned to the standard insulin which gave it the comparable performance.
Dr. Roman Hovorka presented similar results when comparing Aspart and Fiasp in a CamAPS system. In terms of Time in Range and Mean Glucose, there was not a significant difference between the two insulins.
What is the Future of Looping?
Key areas of focus for looping research were highlighted across multiple talks. These include:
- Tailored profiles for different kinds of people for better prediction (pregnancy, children, people with gastroparesis, men, women etc.)
- Improved automation through machine learning of the individuals habits e.g. when they eat, exercise.
- The use of additional sensors was also mentioned to aid the system predict exercise and meals
- Simplified meal declarations to remove the need for carbohydrate counting i.e. declaring a meal and small/medium/large instead
- The use of additional medications in the insulin mix to improve the looping system’s response to blood glucose changes e.g. SGLT-2 inhibitors, GLP-1 agonists, Amylin analogues
The key results of the research presented for loops were:
- Looping vs Non-Loop
- Benefits were seen in measures such as HbA1c and Time in Range
- The benefits of looping systems were present in both adults and children
- The benefits translated to literally hours per day additional Time in Range
- The strongest improvements were seen overnight
- People both with Type 1 and Type 2 diabetes saw improvement
- Benefits were independent of the specific technology employed. It was looping in general which provided the gains
- The benefits became apparent within weeks of looping being activated and were maintained for months
- Looping with Bolus vs Looping which only adjusts Basal Rates
- Pretty much the same results as for Looping vs Non-Loop, although there were no Type 2 studies presented
- Setting a more aggressive target led to an improved Time in Range
- Setting a smaller Active Insulin Time also improved Time in Range
- The greatest improvements were seen in patients with the poorest control, as measured by HbA1c
- Faster Insulins in Closed Loop Systems
- Contrary to what we might predict, there is very little evidence that faster insulins provide significant benefit over slower insulins.
- Future of Looping
- Improved prediction through
- Tailored, preset profiles for groups such as children and pregnant women
- Machine learning the individual instead of the application of generic big data models
- Additional sensors
- Assuming they will be needed, simplified meal announcements to replace carbohydrate counting/declaration
- Different insulin mixes to include other medications to help the looping system respond to things like exercise and meals
- Improved prediction through