I was invited to give a guest lecture to final year Health IT students at The University of Queensland last month about the DIY artificial pancreas technology I’d been using for the past year and a half.
I thought it was important to explain:
history of type 1 diabetes therapy 1980-2019 (personal perspective)
the impact of decisions made by the tech industry
where we are at now in 2019
how it was patients taking matters into their own hands that made all the difference.
and as Slideshare
Like any personal historical account it will contain biases and omissions.
Don’t hesitate to comment below if you notice anything that needs correction or want to add to the story in any way. I’d love to hear from you.
The federal government of Australia is conducting a survey to determine whether continuous glucose monitoring devices (CGM) should be subsidised under the National Diabetes Supply Scheme (NDSS). The following research and outcomes data shows that yes, CGM should be made affordable for all people living with type 1 diabetes as an urgent priority.
Using CGM with an automated insulin delivery (AID) device has had an enormous positive impact on my life.
Artificial pancreas/AID systems are entering the Australian marketplace and have been used by members of the DIY community for over three years. They require CGM. This is the biggest development since insulin in 1922. But there is no use having it if people can’t afford it. Unfortunately the cost of CGM in Australia is currently prohibitive for most people.
This 17 minute ABC Science Show podcast (I’m interviewed with Jim Matheson and Tien-Ming Hing) highlights the urgency very well and explains the health outcomes that are possible IF people can afford CGM
Current situation using blood glucose test strips alone
Australia’s peak diabetes medical body, The Australian Diabetes Society, has set a HbA1c target of less than 7 (NGSP) as the glycaemic goal for people with type 1 diabetes because it is believed to give people the best chance of a healthy, long life. This is currently being achieved by less than 21% of adults with type 1 diabetes (Foster et al, 2019). The major limiting factor in achieving this target HbA1c is hypoglycemia. As discussed in the DCCT trials, achieving target HbA1c using currently subsidised methods only for blood glucose control leads to a 300% increase in hypoglycemia and one in five with type 1 diabetes now have hypoglycaemic unawareness which can be life-threatening.
It is recognised by leading medical practitioners and researchers that the desire for hypoglycemia avoidance contributes to the higher than recommended HbA1c outcomes (Choudhary & Amiel, 2018).
As described in research outcomes below, CGM use alone reduces the incidence of hypoglycaemia and improves HbA1c. When CGM is used in combination with AID ‘artificial pancreas’ systems, HbA1c and hypoglycemia are further reduced (Braune et al, 2019), there is a reduction in glycaemic variability, which has also been linked with a reduction in diabetes complications (Hirsch, 2015), and there are major improvements in quality of life including sleep, mood, well-being and energy levels (Hng & Burren, 2018; Crabtree et al, 2019).
This is a major breakthrough. It is difficult to convey to someone without type 1 diabetes just how significant the impact of these psychological, social, and quality of life improvements can be. Many people using these systems describe them as life-changing.
Automated insulin delivery outcome studies
Over 1440 people around the world are currently using DIY automated delivery systems which means there is over 13,700,000+ hours of user experience and data to draw conclusions from.
CGM improves glycemic control, reduces hypoglycemia, and may reduce overall costs of diabetes management. Expanding CGM coverage and utilization is likely to improve the health outcomes of people with diabetes.
“CGM may also provide a cost-effective means of lowering A1c in the general population. It is important for individuals with type 1 diabetes to have affordable access to and education about this technology”.
Subsidising CGM is an investment up front to save money on:
hospital ‘sick day’ admissions
admission for severe hypoglycaemia
Avoidance of Royal Flying Doctor trips to major centres in DKA for rural patients
Prevention of losing drivers licences due to severe DKA (maintenance of independence/livelihood/survival in rural areas)
cost to the Australian healthcare system of treating complications
“Achievement of target HbA1c in individuals with HbA1c ≥69 mmol/mol (8.5%) would reduce expected chronic complications from 6.8 to 1.2 events per 100 person‐years, and diabetic ketoacidosis from 14.5 to 1.0 events per 100 person‐years. Potential cumulative direct cost savings achievable in the modelled population were estimated at £687 m over 5 years (£5,585/person), with total (direct and indirect) savings of £1,034 m (£8,400/person).”
Currently blood glucose (BG) test strips are subsidised on the NDSS. People using CGM require significantly fewer strips and therefore receive less subsidy. Once newer CGM sensors become available in Australia (eg Dexcom G6) there will be only minimal need for BG test strips for those using CGM. Patients should be able to use their allocated subsidy for CGM.
CGM use reduces hypoglycaemia
Many with type 1 diabetes lose hypoglycaemic awareness over the years so cannot even detect hypoglycaemia in the midst of it. They need outside help to recover from the hypoglycemia and if it is not received the situation becomes life-threatening. According to researchers, between twenty and forty percent of people with type 1 diabetes experience hypoglycemia unawareness. Since it is repeat hypoglycemia that causes hypoglycaemic unawareness to develop, it stands to reason that CGM use is prophylactic. CGM use reduces the likelihood of developing hypoglycaemic unawareness in the first place. This, in addition to the quality of life, wellbeing and productivity improvements with CGM, is why it is crucial that we subsidise all people with type 1 diabetes, not just a sub group.
As Pratik Choudhary and Stephanie Ariel point out in Diabetologia (2018), ‘hypoglycaemia and the fear it causes make a significant contribution to the higher than desired glucose results seen in national audits and registries.’
More CGM and hypoglycemia research
Real-time continuous glucose monitoring significantly reduces severe hypoglycemia in hypoglycemia-unaware patients with type 1 diabetes. (Choudhary et al, 2013).
Hypoglycemia is the limiting factor to excellent glycemic control in insulin-treated subjects. Intensification of glycemic control was associated with a 300 % increase in the rate of hypoglycemia in the Diabetes Control and Complications Trial. CGM use revealed an alarming rate of daytime and nocturnal episodes of hypoglycemia in patients with type 1 diabetes (Awoniyi et al, 2013).
The studies I have listed in this article are just the tip of the iceberg.
The bottom line is, people with type 1 diabetes have been advised by the medical establishment, since the DCCT trials in 1993, that if they are to remain healthy they need to maintain tight blood glucose levels. Less than 21% of people with type 1 diabetes are able to do this with the tools currently subsidised in Australia. The use of CGM and AID systems means that these glycemic targets are finally achievable, but only if people can access and afford them.
If the government decides against making CGM affordable for all through the NDSS, it really is time to change glycemic reporting to reflect,that no, patient glycemic control is not ‘poor’ or ‘suboptimal’ but, in fact, as has always been the case, people with diabetes are doing the best they can with the blunt tools they have under difficult circumstances.
But why not follow in the footsteps of other countries and fund the thing that works?
“How much is one, pain and complication free, life really worth?”
This is the economic and ethical dilemma for the Australian government. To make your voice heard on the matter, please take a few minutes to fill out this government survey which runs until 25 August 2019 to ensure a healthy future for all with type 1 diabetes in Australia.
Patton, Mary Anne. “One year of DIY looping after 38 years of type 1 diabetes.” Australian Diabetes Educator, vol. 22, no. 2, 2019.
Diabetes Control and Complications Trial Research Group. “The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus.” New England journal of medicine 329.14 (1993): 977-986.
Choudhary, Pratik, and Stephanie A. Amiel. “Hypoglycaemia in type 1 diabetes: technological treatments, their limitations and the place of psychology.” Diabetologia 61.4 (2018): 761-769.
Braune, Katarina, et al. “Real-World Use of Do-It-Yourself Artificial Pancreas Systems in Children and Adolescents With Type 1 Diabetes: Online Survey and Analysis of Self-Reported Clinical Outcomes.” JMIR mHealth and uHealth 7.7 (2019): e14087.
Hirsch, Irl B. “Glycemic variability and diabetes complications: does it matter? Of course it does!.” Diabetes care 38.8 (2015): 1610-1614.
Hng, Tien‐Ming, and David Burren. “Appearance of Do‐It‐Yourself closed‐loop systems to manage type 1 diabetes.” Internal medicine journal 48.11 (2018): 1400-1404.
Crabtree, Thomas SJ, Alasdair McLay, and Emma G. Wilmot. “DIY artificial pancreas systems: here to stay?.” Practical Diabetes 36.2 (2019): 63-68.
Lewis, Dana, Scott Leibrand, and OpenAPS Community. “Real-world use of open source artificial pancreas systems.” Journal of diabetes science and technology 10.6 (2016): 1411.
Lewis, Dana M., Richard S. Swain, and Thomas W. Donner. “Improvements in A1C and time-in-range in DIY closed-loop (OpenAPS) users.” (2018): 352-OR.
Choi, Soo Bong, Eun Shil Hong, and Yun Hee Noh. “Open artificial pancreas system reduced hypoglycemia and improved glycemic control in patients with type 1 diabetes.” (2018).
Provenzano, Vincenzo, et al. “Closing the loop with OpenAPS in people with type 1 diabetes—experience from Italy.” (2018): 993-P.
Fonseca, Vivian A., et al. “Continuous glucose monitoring: a consensus conference of the American Association of Clinical Endocrinologists and American College of Endocrinology.” Endocrine Practice 22.8 (2016): 1008-1021.
McQueen, R. Brett, et al. “Cost-effectiveness of continuous glucose monitoring and intensive insulin therapy for type 1 diabetes.” Cost effectiveness and resource allocation 9.1 (2011): 13.
P. Choudhary, P., de Portu, S., Delbaere, A., Lyon, J. & Pickup, J. “A modelling study of the budget impact of improved glycaemic control in adults with Type 1 diabetes in the UK.” Diabetic Medicine 36.1 (2019).
Martín-Timón, Iciar, and Francisco Javier del Cañizo-Gómez. “Mechanisms of hypoglycemia unawareness and implications in diabetic patients.” World journal of diabetes 6.7 (2015): 912.
Choudhary, Pratik, et al. “Real-time continuous glucose monitoring significantly reduces severe hypoglycemia in hypoglycemia-unaware patients with type 1 diabetes.” Diabetes Care 36.12 (2013): 4160-4162.
Awoniyi, Omodele, Rabia Rehman, and Samuel Dagogo-Jack. “Hypoglycemia in patients with type 1 diabetes: epidemiology, pathogenesis, and prevention.” Current diabetes reports 13.5 (2013): 669-678.
First published in Australian Diabetes Educator, 8 July, 2019.
Patton, Mary Anne. “One year of DIY looping after 38 years of type 1 diabetes.” Australian Diabetes Educator, vol. 22, no. 2, 2019.
One year ago I started do-it-yourself (DIY) looping with the hybrid closed loop system, OpenAPS. I’d been living with type 1 diabetes (T1D) for 38 years and had dreamt of a closed loop solution since I was diagnosed at 12 years of age.
The impact of this technology on my life has been so profound, both physically and psychologically, that it feels as though I am no longer even dealing with the same medical condition. I now have access to ‘high fidelity therapy’ , and I am thrilled that commercial products are beginning to roll into the market so that, provided we get funding systems in place to ensure access, all people with T1D could soon have an opportunity to reap the benefits that people in the DIY community have been able to experience.[4-9]
In this article I aim to show how great the impact of hybrid closed looping has been for me, and to outline the features of OpenAPS and Nightscout  that have stood out for me as being particularly beneficial. Note that people with diabetes have found all three DIY systems (AndroidAPS, Loop and OpenAPS) to be extremely effective, and each system has its own advantages.[1, 11-13]
As for most people  my main motivation for using a DIY system was to improve glycaemic control by automating it. The results were immediate and dramatic.
Figure 1. HbA1c over the last 13 years
I’d made many attempts to stabilise my diabetes and reduce my HbA1c over the years, but unfortunately, pre-looping, when my blood glucose levels (BGLs) were in the normal range I often felt hypoglycaemic, or as though I was about to have a hypo. This ‘living on the edge of a hypo’ feeling led me to subconsciously develop strategies, such as under-bolusing for meals, in order to avoid hypoglycaemia. In hindsight I think continuous glucose monitoring (CGM) may have helped with this – I relied on manual blood glucose monitoring until two months before starting OpenAPS – but there were many features of OpenAPS and Nightscout that provided the real key.
I needed a system I could learn to trust over time that would minimise my glycaemic variability, help me to avoid hypoglycaemia, and put me firmly in the driver’s seat.
Adjusting to a new sense of normal
The OpenAPS algorithm, by adjusting insulin delivery through setting temporary basal rates, based on CGM readings every five minutes, automatically reduced my BGLs towards the target I’d set. I initially set my target to around 6.5mmol/L while I was getting used to the system and the lower levels, but within weeks I had reduced my target to 5.5mmol/L.
The ambulatory glucose profile (AGP) from Dexcom Clarity over this first year of looping shows this BG normalisation process and the reduction in glycaemic variability over time.
I learned to customise my settings during this time and to adjust them ‘on the fly’ to achieve the results I wanted. Trust in the system developed quickly. Real time data visualisation through the Nightscout website meant I had the confidence to adjust my diabetes behaviours (such as bolus and hypo treatment behaviours) based on feedback I was getting from the system. Over time, the positive feedback loop of OpenAPS and Nightscout visualisation enabled me to readjust to what ‘normal’ levels felt like as I developed a new blood glucose homeostasis.
Realtime data visualisation
Being able to see my detailed data on my mobile phone, at a glance, any time, and to be able to interact with it ‘on the fly’ was exactly what I needed. Mostly I just glance at the CGM glucose line to see what my glucose level is doing (green), the basal line (blue) to see how much insulin I’ve got on board, and the prediction lines (purple) to see what’s likely to happen next. But I can also see how many carbs I’ve got on board, when I last changed my insulin pump site, when I last changed my CGM sensor, how much battery charge is left in my pump and in the Edison/Explorer board rig that runs the system, and how much the glucose levels are deviating from what was expected. I can change the view to a two hour, three hour, six hour, twelve hour or 24 hour view, and I can run reports on predicted HbA1c, average sensor glucose, time in range, standard deviation and more, with just a couple of clicks.
I can’t overemphasise how valuable it was to be able to see this information in real time during my first year of looping, and how much it contrasted to the old way of doing things – downloading BG test results and pump data, using proprietary systems retrospectively, with a lot of effort.
In addition to what I can see at a glance about what is happening in the moment, I can run reports from my mobile phone or computer any time, to check my predicted HbA1c, time in range, average glucose and glucose variability. Most importantly, I can interact with the system quickly and easily to get it to behave differently.
Am I about to have a hypo?
Here is one example of a typical circumstance in which the OpenAPS/Nightscout combination has been critical for establishing trust and changing behaviour.
I loved the Dexcom display, and CGM was a major step forward from finger-prick BG monitoring alone, but as someone concerned about ‘living on the edge of a hypo,’ this type of visual feedback would likely have sent me reaching for glucose.
Compare that to what I was able visualise through Nightscout using OpenAPS just a few moments later.
I could see from the basal line (figure 7) that I had had no insulin delivered for the previous hour and a half because OpenAPS had suspended the insulin due to predicting a low BG. I can also see from the prediction lines that my BG is expected to level off at, or just below, 4mmol/L. If I click on the OpenAPS pill, I can see that the system is recommending I consume 2 grams of carbohydrate in the next 30 minutes to remain in my BG target range. Many people using OpenAPS have this ‘carbs required’ information sent to them automatically as a notification.
Not only is this reassuring, but it gives me options. If I am about to drive, or have a work deadline, for instance, I will choose to eat carbohydrate. If I’m at home relaxing I might just wait it out and see what happens because I have the reassurance from the system that my BGs are not likely to drop too low. Note that with hybrid closed loop systems only a small amount of carbohydrate is generally needed to correct lows because the system has already been suspending insulin.
One brilliant feature of OpenAPS is Autotune. It is a program that runs automatically every night and iteratively calculates insulin sensitivity factor (correction factor), basal rates and carb to insulin ratio, based on real data, and uses these values in the next day’s predictions. Most people find testing settings difficult, particularly basal testing, so this program is extremely helpful.
Autotune enabled me to discover that I was much more insulin sensitive than I realised. It turned out that one unit of insulin dropped my glucose level by almost 10mmol/L. This sensitivity, along with my pre-looping glycaemic variability (standard deviation pre-looping was 3.6mmol/L, post-looping it is around 1.8mmol/L) gave me insight into why I’d often felt on the verge of hypoglycaemia prior to looping. If my BG was 5.5mmol/L it really could drop to 2.5mmol/L very quickly. And the under-bolusing behaviour I’d developed for meals also made sense to me now that I realised how insulin sensitive I was. Overestimating the amount of carbohydrate in a meal, and bolusing for it, could lead to severe hypoglycaemia.
The fact that OpenAPS allowed separation of carbohydrate announcement and bolusing for meals was incredibly helpful for me. Prior to looping I had used the normal bolus, dual wave or square wave bolus functions of my pump, for example giving a three-unit bolus with one unit up front and the rest over a one-hour period. Given that three units would drop my blood glucose by around 30mmol/L, a miscalculation (overestimate) of carbs could easily lead to hypoglycaemia, and so I often subconsciously under-bolused.
I was now able to tell the system how many carbohydrates I was about to eat, but I only needed to bolus for part of it. I had a system using a dynamic carbohydrate absorption algorithm to sort out the rest of the insulin via temporary basal rates, based on how rapidly my blood glucose was rising or falling after a meal. This reduced my tendency to under-bolus, and increased my carb counting accuracy, as I no longer had the fear of bolus-induced hypoglycaemia.
An advanced feature of OpenAPS that I enabled after the first month of using the system is Unannounced Meals. This gives the algorithm the power to detect when I have underestimated carbohydrates, based on blood glucose deviations, and give more insulin accordingly.
Another excellent advanced feature I have enabled is Autosens. This detects and responds to sensitivity changes that are caused, for example, by hormones, pump site changes, sick days and stress. Like all features of OpenAPS there are safety caps which constrain how much OpenAPS can adjust settings, but it helps keep BGs in range by modifying basal rates, insulin sensitivity factor and temporary BG targets.
Ease of use
Good usability of diabetes devices is absolutely critical for quality of life with diabetes. I love that I can interact with the system ‘on the fly’ either through the Nightscout site or through the iPhone shortcuts that I’ve set up.
With only a swipe and a click or two I can tell the system how many carbs I’m about to eat, that I’ve changed my pump site or sensor, or set a temporary BG target. The ‘eating soon’ button gets the system to aim for a BG of 4.5mmol/L for one hour, which gets the insulin going before meals, helps control post meal spikes, and can be a safer option for many people than pre-bolusing.
A reassuring shortcut is the hypo recovery shortcut. It tells the system I’ve had 4 or 8 grams of carbohydrates and also tells it to raise my BG target for the next half hour to allow me to recover from the hypo.
Note, some people have set up ‘Hey Siri’ or ‘Ok Google’ voice commands as an alternative to interact with their systems and once again, each DIY system will have different options for this type of control.
Every morning when I wake up to a BG of 5.5mmol/L or close to it, I am reminded of how grateful I am to have access to looping technology. I am extremely grateful to the pioneers who created these systems and shared them openly via open source software. [3, 18-24] I am also extremely grateful to the people testing and enhancing these systems, and the people supporting this vibrant community. The years of dedication involved are staggering to contemplate. Finally, I am grateful to my partner, who has IT expertise, for setting OpenAPS up for me.
I share my story to convey just how powerful this type of technology can be. The three DIY systems in use in Australia are all highly effective. AndroidAPS, which uses the OpenAPS algorithm, can be used with brand new in-warranty pumps.[13, 24] US-based non-profit, Tidepool , has initiated a project to build and support an FDA-regulated version of the DIY system, Loop, and has a vision to partner with a range of commercially available insulin pump companies. Commercial off-the-shelf solutions are emerging. But there is no point in having the technology if people can’t afford it. I believe this technology holds the key to putting an end to T1D complications. Now is the time for us to ensure that funding and subsidies are in place so that all people with T1D can benefit.
Crabtree T, McLay A, Wilmot E. DIY artificial pancreas systems: here to stay? Practical Diabetes. 2019 Mar;36(2):63-8.
Hng TM, Burren D. Appearance of Do‐It‐Yourself closed‐loop systems to manage type 1 diabetes. Internal medicine journal. 2018 Nov;48(11):1400-4.
Lewis D, Leibrand S, # OpenAPS Community. Real-world use of open source artificial pancreas systems. Journal of diabetes science and technology. 2016 Nov;10(6)
Lewis D, Swain R, Doneer T. Improvements in A1C and time-in-range in DIY closed-loop (OpenAPS) users.
Litchman M, Lewis D, Kelly L, Gee P. Twitter analysis of# OpenAPS DIY artificial pancreas technology use suggests improved A1C and quality of life. Journal of diabetes science and technology. 2019 Mar;13(2):164-70.
Petruzelkova L, Soupal J, Plasova V, Jiranova P, Neuman V, Plachy L, Pruhova S, Sumnik Z, Obermannova B. Excellent Glycemic Control Maintained by Open-Source Hybrid Closed-Loop AndroidAPS During and After Sustained Physical Activity. Diabetes technology & therapeutics. 2018 Oct 25;20(11):744-50.
DIWHY Braune K, O’Donnell S, Cleal B, Willaing I, Tappe A, Lewis D, Hauck B, Scibilia R, Rowley E, Ko W, Doyle G. DIWHY–Motivations, barriers and retention factors of DIY artificial pancreas users in real world use: The BolusCal2 Study, an open-label, randomized controlled trial. In Advanced Technologies & Treatments for Diabetes 2019 (Vol. 21, No. S1).
Street, T. Meal times when closed looping: some points to consider. Diabet-tech Diabetes and Technology. 2019 Jan 25. Available from: https://www.diabettech.com/artificial-pancreas/ meal-times-when-closed-looping-some-points-to-consider/
When I started looping with OpenAPS I needed ‘head space’ and time to learn, to monitor my blood glucose levels closely and adjust my settings. I kept a very close eye on my CGM. When I switched to Loop one year later, there was a whole new learning curve. You do have to be vigilant whilst setting things up and getting used to a new system.
Howard, Look, CEO of Tidepool, has just released this caution to the Facebook group, Looped. It is especially relevant to parents of children.
Please read this before you start looping. In Howard’s words… “This post is intentionally blunt and potentially scary.”
“I am posting this as a Dad who happens to have a daughter with T1D who has been using DIY Loop for some time – coming up on 3 years. (I also happen to be CEO of Tidepool. This post is about DIY Loop and is coming from me as a DIY Loop Dad.)
DO NOT USE LOOP if you do not understand the settings. IMPROPER LOOP SETTINGS COULD KILL YOU OR YOUR CHILD.
The Loop algorithm relies on settings to determine how much insulin to give. These settings are exactly the same as the settings you might have in an insulin pump using traditional (a.k.a. open loop) therapy. Loop also has two additional settings that aren’t found in traditional therapy.
If you or your clinician do not understand what appropriate values are for these settings, do not just set up Loop and use numbers that you don’t understand and assume that everything will be OK. Doing so could cause Loop to give an overdose of insulin, and an overdose of insulin can cause a seizure, coma or death.
DIY Loop does not currently put any limits on settings, so you need to be really careful and make sure you don’t enter values that could cause dangerous amounts of insulin to be delivered. Here are some examples:
Correction range: This used to be called “target range” in previous versions of Loop. It is the range that Loop tries to keep your blood glucose in. A correction range of 100-120 mg/dL (5.5-6.6mmol/L) is a reasonable range. To be even more conservative you might want 110-130 (6.1-7.2) or even 120-140 (6.6-7.7).
A correction range of 20-40 mg/dL (1.1-2.2mmol/L) is NOT a reasonable setting for anyone, and is extremely dangerous.
(Mary Anne here: I used 120 mg/dL (6.5-6.5mmol/L) as my correction range (BG target) when I first started looping and only reduced it to 100mg/dL (5.5mmol) after a few weeks once I had reassured myself that the settings were working safely.)
Insulin Sensitivities: This is also called “correction factor” in your Omnipod PDM. This is the amount of BG drop that insulin will cause. 50 mg/dl/U (2.8mmol/L/U) means that 1 Unit of insulin will cause a 50 mg/dL (2.8mmol/L) drop in BG. That’s pretty typical for an adult. Kids are typically much more sensitive, meaning insulin causes more of a drop. It’s not uncommon to see have an ISF of 80 (4.4), 100 (5.5) or 120 (6.6) in kids. Higher numbers are more conservative.
An Insulin Sensitivity of 1 mg/dL/U is NOT a reasonable settings for anyone, and is extremely dangerous.
Basal Rates: These are the underlying level of insulin that your body needs, and it typically varies slightly over the course of the day. Kids often have basal rates in the range of .25 Units per hour to .50 Units per hour. Adolescents may go up to 1.0 Units per hour. Adults are typically in the .75 to 1.0 range.
A default basal rate of 10 Units per hour is NOT a reasonable settings for anyone, and is extremely dangerous.
Carb Ratio: This is how many grams of carbs are “covered” by one unit of insulin bolus. If you don’t know your carb ratio… wait – don’t start Looping yet. Speak to your endo or health care provider to determine your value. You should not just enter a “placeholder” value without having some idea if it is representative of your insulin needs.
These are just a few examples. Again, if you do not have insulin pump settings that you already trust or think are at least close to accurate, do not just start Looping! If you do, make sure you put the right settings in the right places. Don’t get Correction Range and Insulin Sensitivities mixed up.
This blog post may be helpful to you to understand if your pump settings are similar to what other people use. As will be clear if you read the article, there are wide ranges for every setting, for every age, so you really should test your settings and work with your care team:
The Looped Facebook group also has hundreds and hundreds of posts/comments encouraging people to test their settings prior to using any DIY looping system, please respect that advice.”
(Mary Anne here: Please note that some adults can be very insulin-sensitive too. One unit of insulin reduces my blood glucose levels by over 9mmol/L (162mg/dL). As someone with extreme insulin sensitivity I have seen first hand how much variability can occur and how difficult getting meal boluses right can be. Better to be conservative and safe, especially with your precious children.
I was interviewed as part of an ABC Science Show program on DIY looping which was broadcast last weekend. Wonderful coverage of what it’s like to live with Type1 diabetes psychologically, two peoples’ experiences of using a DIY system, and why we need to get CGM coverage for adults in Australia ASAP.
Jim Matheson, one of the first 16 people to build a DIY looping system, was also interviewed, along with endocrinologist, Tien-Ming Hng.
It really is a fantastic piece. It covers:
what it was like to live with diabetes 40 years ago
the precarious nature of keeping blood sugar ‘not too high, not too low’
DIY artificial pancreas tech overview
how immediate and dramatic the changes were for two people with type 1 diabetes when they started using the systems
a plea to government to subsidise CGM costs in Australia by shifting money from the complications end of diabetes care to the complication-prevention end so that all can benefit from the technology that’s about to arrive at our doorstep
People in the DIY artificial pancreas community are talking about sensory changes in the way they experience their diabetes.
Some, like Thacher Hussain @Thachert1d, find that DIY looping causes them to regain their hypoglycaemia awareness.
“Feeling shaky at 84… means #Loop is keeping me in range enough that my body’s own hypo-awareness is readjusting to my goal range of 80-180 and (according to #DexcomClarity) only 6% under 80 in the last 30 days… #holyshit this is amazing”
Others like Tim Gunn @TwistaTim found that once they were looping they had less tolerance of blood glucose levels higher than normal range.
Before looping I used to be much more tolerant to a high BG, but with Looping, my body must have got used to me having such good control, when I have a High BG now…. I feel like crap.
For me, a sustained period of building trust using OpenAPS and Nightscout technology allowed me to finally let go of the thing that had haunted me for decades. Normal blood sugar levels feeling like ‘living on the edge of a hypo.’
Just looking at the ambulatory glucose profile (AGP) gives a clue as to how this normal (euglycaemic) glucose homeostasis re-establishes itself.
I am planning to write more about the psychological and behavioural aspects of this over the coming weeks. In the meantime, if you have experiences to share, I’d love to hear from you. Please leave a comment.
The children’s ward was a bright and colourful place, and the whole two week experience was actually ok, apart from my first hypo. My memories after 39 years are a little vague, but here is what I do remember…
One morning, just after I finished breakfast, in bounced Julie. Julie was young and full of a tingly kind of energy, probably in her early 20s. She oozed warmth and fun and she introduced herself as my ‘diabetic sister’. I thought all my Christmases had come at once. Diabetes seemed like one big adventure with Julie.
There were rules and they seemed easy enough to follow (in hospital at least!). We had ‘portions’ of carbohydrate and a book to show us what things equalled a portion. One slice of bread, one banana, one potato. I had a food plan. Three portions for breakfast, three portions for lunch and three portions for dinner. One portion for morning tea, afternoon tea and supper. 3-1-3-1-3-1 made me think of a piano scale.
The book with the ‘portions’ in it I just called ‘the red book.’ It explained everything I wanted to know about diabetes. It was easy to read and practical.
The best thing about ‘the red book’ was the page with the circuit diagram of the technology that scientists were busy working on. The Artificial Pancreas. The Closed Loop. I loved that diagram, and once diabetes got hard after I left hospital, I turned to that page a lot. Around ten years later, when I was diagnosed with proliferative retinopathy, and told I had a 50% chance of going blind without laser therapy, I remember trying to find the book again, but it had been thrown out.
The other good thing about the book was a list I called the ‘forbidden food list’. (I can’t actually remember what it was called, but at one stage I actually did have a list with the title, ‘forbidden food’.) It had things I could buy at my school tuckshop in it with the equivalent portions listed. One Dracula ice cream equalled 1.5 portions.
I had one injection a day in the morning. It was pork insulin. Hypo signs were intense and easy to recognise, which was lucky, because we had no BG meter, just urine testing tablets.
My mum came to see me when she could. She learned to inject an orange first, then me. Like others, I found the injection by my poor mother was the only one that really ever hurt.
One day a very good looking boy about my age was wheeled into the ward and placed in the room I had been in for the first two days while I was on the drip. We were the two oldest kids in the ward. He called out at night, moaning as though he was in pain, and sometimes he called out during the day too. There was always someone sitting with him, next to his bed. Almost always his parents. I used to skulk past trying to get a look at him, and once I caught his eye. I felt so sorry for him, alone in there with all those adults, but what could I do? One day when my ‘diabetic sister’ came to visit I asked her about him and she whispered that he had a brain tumour.
Every day a lovely paediatrician came to see me. He was a round man with a kind, smiling face. His mother had had type 1 diabetes and he used to give her her injections apparently.
Another memory from those two weeks was that I was super anxious at missing two weeks of school. I knew there was a Maths test planned for the day I got back. I panicked and figured I would fail the test as I’d miss so much work. I had to rely on the textbook. It was hard going, working through the worked examples and extremely detailed explanations for everything, and I had to go over pages a few times to make sense out of them. I showed up that first day back at school, carefully measured milk in my drink bottle (one portion), urine test tablets and test tube in my bag, sat the Maths test and was completely gobsmacked to get a score of 100%.
It was the only time in my life I got 100% in a test and I wish I’d realised the significance, the ‘take home message’. Read the documentation. Find the answers yourself and check them. There was no internet then. The only information we had was from doctors and the quarterly magazine from the diabetes association, which was peppered with dire warnings, people who were older than me, and anxiety-inducing outcome data that I didn’t realise applied to the previous generation. I read every word.