ATTD 2021 Distillations: Pregnancy for Women With Type1/Type2/Gestational Diabetes

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 second “distillation” which is on pregnancy and gestational diabetes. For my first “distillation” covering looping go here. Firstly, let me be clear in my intent: I am a male and never been pregnant. My aim is to present the research, as I understand it, from ATTD 2021. I am not a medical professional and nothing here should be considered medical advice or me telling you what to do with your body. If something I have written is of interest, I strongly encourage you to discuss it with your medical team to determine the best course of action for you. I will also call out that this post discusses the possible adverse outcomes of pregnancy for the baby. Not all pregnancies go to plan and if this subject is distressing for you, you may be triggered by the contents of this post.

A common observation of women with diabetes is their menstrual cycle has a significant impact on their blood glucose level management. It is known in that the fluctuation of hormone levels in the body directly impacts insulin resistance. The same happens in pregnancy with the thinking being that hormone levels increase in a woman’s body to increase insulin resistance so more glucose reaches the baby for growth and development.

For women with diabetes this amplifies an existing health condition and, for women who do not have diabetes, given the stresses this puts the body under, it can trigger diabetes during pregnancy in what is called Gestational Diabetes. ATTD 2021 looked at some of the latest research on diabetes and pregnancy which I present here.

Specific questions covered in the presentations were:

As usual there is a TL;DR section at the end if you want to read the summary of results without the details.

If I am a Woman with Diabetes, What are the Health Risks to my Baby?

Dr. Helen Murphy presented on the risks to the baby for women with Type 1 and Type 2 diabetes. Both Dr. Murphy and other presenters made it clear that there has not been a lot of improvement in adverse outcomes for pregnant women with diabetes (congenital abnormalities and deaths), for decades. As we will see later, there is potential for this to change with tools like continuous glucose monitoring devices (CGMs).

A result which surprised me was the risks to women with Type 1 and Type 2 diabetes was about the same and slightly higher for neonatal death in women with Type 2 diabetes. While there appears to be a trend upwards in some of these graphs, Dr. Murphy pointed out the tending was not statistically significant.

A question I had was how this compares to the general population. Dr. Robert Lindsay, covered this with some earlier data. Assuming the risk level has remained the same for the general population, for stillbirth, women with diabetes have a risk somewhere between 2-4 times higher than the general population.

For adverse outcomes (death and congenital defects), we also see similar risk profiles for women with Type 1 and Type 2 diabetes. Literally 1 in 10 women with diabetes, who do not prepare for pregnancy, have a serious complication with their pregnancy. The good news is, with planning and preparation, this number goes down to 1 in 50 which is close to the rate for the general population.

Planning and preparation in this case means taking folic acid before and during pregnancy and controlling blood sugar levels as well as possible. The guideline is to have an HbA1c below 48mmol/mol (6.5%) which, for many, is easier said than done. Many factors affect a woman’s ability to control their blood sugars beyond the usual diet and exercise. For Type 1 is was shown that other factors include:

  • Age (younger Type 1s often struggle to control their average blood glucose levels compared to their older counterparts)
  • Social disadvantage (Deprivation)
  • Time since diagnosis (while older Type 1s typically have a lower HbA1c, those diagnosed 5 or more years ago typically have a higher HbA1c)
  • BMI (the higher the body mass index, the lower likelihood of a woman with Type 1 having an HbA1c below 6.5%)

For Type 2, social disadvantage was a factor although it does not seem to be as pronounced, time signce diagnosis was a factor, and also BMI.

The only one of these factors which can be easily addressed by a woman looking to get pregnant is BMI but, as many of us know, shifting the needle on weight is not a simple task.

While important before getting pregnant and in the first trimester, HbA1c is also predictive of adverse outcomes as late as the third trimester. For both women with Type 1 and Type 2 diabetes, the risks significantly increase for an HbA1c above 75 mmol/mol (9.0%). Dr. Murphy also pointed out that this result removed confounders (contributing factors such as weight, age etc.) In other words, HbA1c is very predictive of risk.

She also presented details of the relative risks for Neonatal Intensive Care (NICU) admission, preterm birth, and having a “big baby” (LGA: Large for Gestational Age) showing HbA1c also predicts for these events as well.

Dr. Robert Lindsay also presented on factors associated with still birth, including those with Gestational Diabetes.

Not surprisingly, blood glucose levels are a factor here as well even for those diagnosed and treated for gestational diabetes. Given there were different results for the diagnosed and undiagnosed, it suggests there is a factor beyond fasting blood glucose affecting outcomes which treatment is addressing. My assumption is it is the non-fasting glucose levels and their fluctuations.

While the results may seem depressing, there is hope. As we will see in the next two sections, there are new technologies and treatments which can positively impact pregnancy outcomes for women with diabetes of all Types.

Health Benefits of Using a CGM During Pregnancy

Dr. Jennifer Yamamoto presented on the performance and benefits of Continuous Glucose Monitoring (CGMs) for pregnant women with diabetes.

For sensor performance, she spoke of a study looking at placement on the body of the CGM sensor covering women of all Types.

Overall, regardless of placement the accuracy as measured by MARD (Mean Absolute Relative Difference), where a lower number indicates better accuracy, performance was good but the arm was the best area for placement achieving 8.7% accuracy.

In terms of the benefit of using a CGM device, Dr Helen Murphy, presented results specific to Type 1 showing, especially in the third trimester, significantly better results for pregnant women who used a CGM; they literally gained an additional 100 minutes per day in range.

As to be expected, this had a knock-on effect on neonatal outcomes with a statistically significant lowering of risk for a larger baby (LGA), hypoglycaemia, and neonatal ICU admission.

Dr. Claire Meek presented on the predictive power of CGMs for adverse outcomes, using CGM measures such as mean glucose levels (MEAN), Time in Range (TIR), Time Above Range (TAR), Time Below Range (TBR), the coefficient of variation (CV, a measure of variability of levels), and standard deviation (SD, another measure of variability). These were compared to the effectiveness of biomarkers in the blood and the traditional HbA1c.

Even for me these graphs are hard to read but the key takeaway is to look at the rows with an asterisk on the end as these are the measures which were significantly predictive. So, for preterm birth, for 12 weeks, CGM and one of the biomarkers fared well and for 24 weeks, CGM, a different biomarker, and HbA1c fared well.

Looking at predictors for a “big baby” (LGA), Neonatal ICU (NICU) admission, and Neonatal Hypoglycaemia (NH) we see CGM and HbA1c are the constant performers for prediction.

Looking at just Time in Range (TIR) and the HbA1c, we see, for early pregnancy a CGM offers good predictability and the opportunity for early intervention. Later in the pregnancy, HbA1c provides stronger predictability.

In conclusion, CGMs not only offer the ability to predict adverse outcomes early on in the pregnancy but their use can also improve them. Yet again we have compelling evidence that CGMs offer tremendous benefit to people with diabetes.

Should Women with Diabetes Take Metformin?

The final presentation I will talk about was a debate on the benefits and risks of using metformin during pregnancy. This was discussed between Professor Denice Feig who argued the “pro” case and Dr. Yariv Yogev who argued against. However, discussions in the question and answer session at the end showed both agreed on many of the key points with little debate between them.

Typically a “Type 2 drug”, metformin has many effects on the body but is broadly known as a drug which reduces insulin resistance. It is known to cross over the placenta into the baby but it is well established that it does not cause birth defects.

It is understandable that the issue of metformin use needs to be discussed/debated because international consensus on whether metformin or insulin should be used as a first line treatment is still mixed.

Professor Feig presented a meta-analysis study showing the benefit of metformin over insulin although it was clear in the discussion that many women with diabetes often used insulin as well as metformin to help control blood glucose levels.

Factors of potential concern were a lower gestational age i.e. babies were born slightly earlier and a slightly higher incidence of “small babies” or what is referred to as SGA (Small for Gestational Age).

Professor Feig presented other studies comparing metformin to insulin with similar results finding:

  • Metformin helped with glucose levels after meals
  • There were less cases of hypoglycaemia with metformin
  • Metformin reduced the amount of weight gain in mothers and the need for c-sections

For women with Type 2 we, again, saw similar results and the potential for a “small baby”.

There was discussion on the long term effects on the baby of exposure to metformin but both presenters agreed the results are mixed and no strong conclusions can yet be drawn that there are detrimental effects.

Dr. Yogev presented a great table showing how metformin compared to a placebo for outcomes (a p-value of 0.05 or less indicates statistical significance) indicating:

  • Lower birthweights with metformin
  • Reduction in the rate of extremely large babies
  • Increase in small babies

Dr. Yogev did point out that in his own studies he could not confirm the increased risk of small babies as a result of using metformin. Both agreed that where there was a risk of babies being born small, metformin may not be advisable e.g. in the case of twins. Professor Feig also made the point that, if a pregnant woman with diabetes was taking metformin and there was indications that her baby was undersized, metformin could be stopped during pregnancy to minimise any problems.

TL;DR

Health risks to the baby for women with diabetes are:

  • Higher risk of stillbirth and neonatal death (death in the first few weeks of birth) compared to the general population
  • Higher risk of congenital defects

These risks can be reduced through taking folic acid both before and during pregnancy and reducing HbA1c. However many factors affect the ability to reduce HbA1c such as age, social disadvantage, time since diagnosis, and weight. While difficult, HbA1c is a strong predictor of outcomes at all stages of pregnancy so any intervention which can help reduce HbA1c is of significant interest.

One intervention which shows promise are CGMs whose measures are predictive of outcomes (especially in early pregnancy while HbA1c is good at predicting outcomes later in pregnancy) and, therefore CGMs can be used to advise early intervention. It was also shown that the use of CGMs for women of all Types saw a reduction in adverse outcome risk. For pregnant women using a CGM while accuracy was good wherever the sensor was placed, placement on the arm showed the most accurate results.

A second intervention which shows promise is metformin, a drug which lowers insulin resistance. While reducing risk across most measures, there was potentially an increased risk in a smaller baby for gestational age (SGA). It was agreed that, in most cases, the risk could be managed through active monitoring of the pregnancy (and taking the pregnant woman off metformin if needed) but for cases where there was an existing known risk of SGA (twin birth, for example) metformin would not be advised.

ATTD 2021 Distillations: Looping

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:

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.

The results showed no significant difference between the standard insulin and fast insulin, as shown in the table below. Significance is indicated by the ‘P value’ in the last column. For statistical significance this value needs to be less than 0.05 which it was not across the key measures meaning the results were comparable between the two insulins and there were no significant differences.

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

TL;DR

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

A Cooling Pouch For Less Than US$5 To Help Keep Your Insulin From Overheating

If you have seen the Glucology or Frio insulin pouches you will already understand the concept of an evaporative cooling insulin pouch. They work really well but the downside is the price. For a two-pen pouch you are looking at around US$30. In this blog I will show you how to make your own for less than US$5 (if you have a sewing machine) or, if that is too much hassle, you can buy a ready-made one from my Etsy shop for around US$20 including shipping anywhere in the world or AU$25 including shipping within Australia. For every one purchased, I will be supplying an identical one to charities around the world who are supplying insulin in developing countries where refrigeration is unreliable.

How Do They Work?

Evaporative cooling pouches work off of the idea that if water is evaporating from something, that something gets cooler. This is how humans cool themselves i.e. sweating. The key technology in the cooling pouches that allow them to remain cool for well over 24 hours are the little beads inside the pouch. These hydrophilic beads (a big word meaning they hold onto water) are the same ones you might know as Orbeez or those squishy spheres you see flowers in sometimes.

Magic Moisturizing Crystal Mud Soil Water Beads For Flower Planting Super  absorbent polymer Crystal Soil Jelly Balls Home Decor|soil water beads|water  beadscrystal mud - AliExpress

Same technology, different application. While the beads love holding onto water, it still evaporates and, while it does, they and anything they are surrounding feels cool to the touch. Embed them in material and that material, and anything it is surrounding also becomes cool.

DIY Step One: The Materials

Firstly, you will need two cooling scarves. They look like this:

You can buy these from Amazon but this will set you back about US$4 each before postage. Go to Ebay and select the international option and, while it might take a little longer to arrive, you can pick them up for around US$1 each.

You will also need a sewing machine or someone with the time to hand stitch them.

DIY Step Two: Stitching

Lay one on top of the other. For symmetry, I have put the seam of one (the white stitching on the edge) to the non-seam side of the other.

Then you will want to do a straight stitch along the edges so the two pieces form a long tube.

The dark line at the bottom on the scarf in the above picture is the straight stitch you need to do on the top and bottom. There is one at the top in the image as well but, because I was using a light brown thread in my bobbin, it is a little tricky to see. While I went a little over in the above picture, you want to go up to the white stitching which runs up and down on the left hand side in the above picture. This gives you the ties on the end of the scarf to secure the pouch, once finished.

DIY Step Three: Inverting

Arguably the fiddly bit, you now push the tube inside of itself to invert it and hide the stitching. I found the best way was to pull it out, rather than trying to push it through with a stick. In the end you will have an inverted tube which looks something like this.

You are now the proud owner of a cooling insulin pouch. Well done!

How To Use Your Pouch

Before use you will need to soak your pouch. I recommend no more than five minutes. Any more than this and the beads will absorb too much water and make it too hard to insert the pens/cartridges/vials. There is probably a risk of splitting the stitches as well.

Once soaked, dry it off with a dishcloth or towel. The material does not have to be wet for it to be effective. It is the beads inside which do the work.

Then, you can insert your hardware.

In the above example, I have my basal and bolus insulin pens and a MedAngel (a Bluetooth thermometer which connects to your phone).

Once inside, you can use the those end ties to keep it all together.

Does It Really Work?

While I am still insulin independent, I always carry insulin whenever I travel overseas for work. Just before the world locked down, I took my pouch to Singapore. Even with Singapore’s humidity, the pouch, within my backpack, was effective at keeping my insulin cool as I walked, in the direct sun, to the office each morning. Tests I have conducted in more controlled conditions show the pouch is as effective as its commercial counterparts.

Here you see three temperature gauges measuring (in Celsius) the temperature in my house (the middle one), the temperature of a commercial pouch (on the left) and my one (on the right). Even inside, both pouches shaved off 2-3 degrees Celsius (4-6 degrees Fahrenheit). The effect becomes even stronger in direct sunlight where I have seen temperature differences of 10 degrees Celsius (20 degrees Fahrenheit) between the ambient temperature and the pouch.

“Recharging”, Storage and Care

The pouch will continue to keep the contents cool for over 24 hours. When you want to “recharge” it, immerse it in water for no more than two minutes. Again, if you over-immerse, you risk expanding the beads too much and making it impossible to insert your pens etc. or breaking the stitching.

If you are not planning on using your pouch for a while, let it completely dry out in the sun or on an air vent and, when completely dry, store it in a cool, dry place.

EASD 2020: Life Expectancy of People with Type 1 Diabetes (A Review of Hope)

Let me cut to the chase on this: if you have been recently diagnosed with diabetes and you maintain good glucose control, based on this evidence, there is NO reason to expect you will not live a long and healthy life

This may sound wrong because it is easy, from a statistical point of view, to work out the difference in life expectancy between people with diabetics and non-diabetics and show people with diabetes live for a few years less than non-diabetics. Sure enough, Mike Stedman and his colleagues did precisely this for EASD 2020.

What this tells us is that Type 1 males live 7 years less than their non-diabetic counterparts and, for women, it is 8.5 years. For Type 2, the difference is less pronounced being 1.4 years lost for men and 2 years lost for women.

The problem is the data, while accurate, is very misleading. Moreover, it hits social media and diabetes groups, and Type 1s think it is inevitable that they will live shorter lives than their friends and families. The stresses of diabetes are plentiful without this kind of burden being added on top.

The fact of the matter is this graph says absolutely nothing about the life expectancy of an individual. Rolled into that average life expectancy are hypo deaths, DKA deaths, and things like heart complications. We know higher HbA1c levels increase the risk of cardiovascular (heart) disease so, for someone with good glucose control, in my opinion, the above graph is meaningless. It also says nothing about age of onset. Someone who was diagnosed 50 years ago (included in the above numbers) had to manage their diabetes with urine, thick needles, and a lot of luck. Someone diagnosed today has much more effective tools at their disposal.

In my opinion, it would be much smarter to look how life expectancy has improved over the years and, where possible, see if it is catching up with the non-diabetic population. This is what I want to write about today. As usual, you can skip to the tl;dr for the summary, otherwise let us go on a journey of optimism, rather than of pessimism. Firstly though, what is up with that gender imbalance in life expectancy?

Why Do Females with Diabetes Have a Shorter Average Life Expectancy?

Again, let me repeat the disclaimer: Average life expectancy says nothing about the life of an individual. A woman with good glucose control has, in my opinion, no reason to expect any shorter life than her non-diabetic peers.

To the question at hand though, another presentation at EASD 2020 looked at this in some detail. Juergen Harreiter presented “What you need to consider for individualised gender-sensitive care”. This looked at the gender differences in diabetes risk and treatments.

Sure enough females with diabetes are at a higher risk of coronary heart disease and stroke than their male counterparts.

and a 40% greater risk of all-cause mortality.

Specific reasons, backed up by data, were light on the ground except for this cited study.

In the above graphs, we have four drugs commonly used to reduce the risk of heart disease. For three of them (statins, RAAS blockades, and beta-blockers) women were routinely under-treated. With males receiving more aggressive treatment, it is not surprising they live longer.

So What About Life Expectancy Improvements over Time?

There is overwhelming evidence that life expectancy is improving every year for people wit diabetes. While the cause of the improvement is not always clear, I suspect it has to do with improvements in management technology (insulin improvements, pumping, glucometers, looping etc.) and possibly improved knowledge and education about the disease. Let us go through the papers I have found.

Life expectancy and survival analysis of patients with diabetes compared to the non diabetic population in Bulgaria (2020)

This study looked at data from 2012-2015 using national databases. Even in this short period of time we see improvements across both Type 1 and 2 and across genders.

While the non-diabetic population did not move at all in their life expectancy, Type 1s, Type 2s, Type 1 females, and Type 2 females all gained around an additional year, on average. Moreover, by 2015, the overall life expectancy of people with diabetes was about the same as the non-diabetic population (almost 75 years).

Improvements in the Life Expectancy of Type 1 Diabetes (2012)

In this study the life expectancy of two cohorts was examined: people with diabetes diagnosed between 1950-1964 and between 1965-1980.

Here we see the percentage of survivors after a certain age. The EDC (Pittsburgh Epidemiology of Diabetes Complications) cohort for 1950-1964 are lower on the graph as fewer survived over the years. In comparison, the 1965-1980 cohorts for EDC and ACR (Allegheny County Type 1 Diabetes Registry) had a much higher survival rate again showing the difference just 15 years made in the life expectancy of people with diabetes.

Long-Term Mortality in Nationwide Cohorts of Childhood-Onset Type 1 Diabetes in Japan and Finland (2003)

This study was designed to compare Type 1 diabetics in Japan and Finland but also had information of improved survival rates over the years.

While in Finland, the survival prospects of a Type 1 child remained excellent for the periods 1965-1969 and 1975-1979 with only minor improvements, we see there was a dramatic improvement in survival probability for children diagnosed in the latter period for Japan.

The 30-Year Natural History of Type 1 Diabetes Complications (2006)

This study looked at five 5-year cohorts (1950-1959, 1960-1964, 1965-1969, 1970-1974, and 1975-1980) also from the Pittsburgh Epidemiology of Childhood-Onset Diabetes Complications Study. Not surprisingly, it came to similar conclusions.

We see a clear improvement in survival rates with around 60% of those diagnosed in the 50s and living with the disease for 30 years surviving, compared to around 95% for those diagnosed in the 70s.

All-Cause Mortality Trends in a Large Population-Based Cohort With Long-Standing Childhood-Onset Type 1 Diabetes (2010)

This study split the previously mentioned ACR study into three diagnosis cohorts (1965-1969, 1970-1974, and 1975-1979) to compare survival rates.

As we have seen in the other studies, there was a dramatic improvement in survival rates between someone diagnosed in the late 60s compared to the 70s.

A Word of Warning

In the above studies we have looked at people with diabetes in Bulgaria, USA, Japan, and Finland and, as mentioned, it is likely the improvements are due to improvements in medical technology and education. For countries where these improvements are not available, there is no reason to expect the same gains. For places in the world where insulin is not readily available, there is no reason why life expectancy should be much better for a person with diabetes than it was before the discovery of insulin 100 years ago. These studies show there are compelling reasons for insulin to be available to all who need it, across the world. We are literally robbing people of decades of life if we choose to do nothing.

tl;dr

There is clear evidence that the survival rates for people with diabetes has improved for those diagnosed between 1950 and 2015. Furthermore, in a study from Bulgaria by 2015, the life expectancy of people with diabetes was the same as non-diabetics.

While the specific cause of the improvements was not examined, it is assumed to be a function of improved technology (insulin, pumps, glucometers, looping etc.) and improved understanding and education of the disease.

Therefore, if you have been recently diagnosed with diabetes and you maintain good glucose control, based on this evidence, there is NO reason to expect you will not live a long and healthy life.

EASD 2020: A Weekly Basal Insulin Being Developed

I am coming to the end of my EASD 2020 series but what a conference it was for announcements and discoveries. It just goes to show that research into diabetes is thriving and it suggests we have a lot to look forward to in the future with continual advancements in medical treatments and technology,

The presentations on Insulin Icodec, a once-weekly basal insulin, was particularly exciting for me.

What is Insulin Icodec?

Insulin has come a long way in the last 100 years. Early forms of insulin were derived from farm animals but, with the advance of recombinant DNA (the ability to combine DNA from multiple sources), it became possible to manufacture insulin with bacteria or yeast. Mass production of ‘regular’ insulin (human-equivalent) followed until the mid-nineties. In 1996 a new form of insulin was introduced to the market by Eli Lilly in the form of ‘Lispro rDNA’. This was a genetically modified form of insulin which acted in the body like regular insulin but with modified properties.

Since then, insulin analog advances have been made to improve how quickly a rapid-acting insulin takes to reach peak activity or, in the case of basal insulins, to make them last for longer and more consistently in the body.

Insulin Icodec is very much in this second camp. While some basal insulins, up until now, could work for around 24 hours, this is not the case for Icodec which makes basal insulin available to the body over a period of one week.

Presentations

Ulrike Hoevelmann presented on the effectiveness of the insulin. As we can see here, it maintains a relatively constant supply of insulin to the body over the seven days.

This particular research involved 50 participants and explored the properties of Icodec compared to Degludec (Tresiba).

Julio Rosenstock presented on a study with 247 participants comparing daily basal injections with weekly injections in a double-blind, double-dummy test. Once-weekly insulin Icodec showed a higher rate of hypoglycaemic events, compared to daily basal insulin glargine U100.

However, Doctor Rosenstock was quick to point out the only difference which was statistically significant was the Level 1 hypos. In all other aspects compared, there was no statistically significant difference in outcomes or adverse events between the two insulins.

Only For Type 2s?

Both studies focussed exclusively on Type 2s. So, will Icodec also work for other Types, such as Type 1? I asked this in one of the presentations and was told it certainly will but this is not where they are researching right now. My guess is the research trials are focussing on the majority of diabetics i.e. Type 2s. It is still early days so I am sure, before Icodec reaches the market, it will also be tested in Type 1s. While some Type 1s I know have expressed concerns around the risks of being subject to a bad dosing decision for an entire week, I think this would affect all patients about the same, regardless of Type. Personally, I think the more technology can remove the burden of management from diabetics and carers, the better and going from 365 injections a year down to 52, for me, is compelling.

Time In Range – The New HbA1c

Most diabetics, certainly most Type 1s, know their HbA1c. As described previously, the HbA1c is a measure of the ‘average sugariness’ of the blood over the last three months. As a diagnostic test, the HbA1c has been with us for a little over 40 years and has served us well. However, as technology has improved for the management of diabetes, the ways we keep tabs on our blood has also evolved and a new measure: Time in Range is growing in popularity among both diabetics and researchers alike. In fact, quite a few talks at EASD 2020 spoke directly at Time in Range and linked it to the long term health of diabetics.

In this blog I will talk about what the HbA1c tells us, its limitations, and the additional insights we can gain through the Time in Range. As usual, at the end, we have the ‘Cliff Notes’ tl;dr.

Benefits of Measuring the HbA1c

As I have shown previously, many papers examine the relationship between long term HbA1c and complications and this was reiterated by Professor Pratik Choudhary at EASD 2020 with this excellent graph.

The Limitations of the HbA1c

While of diagnostic value, there are limitations with the HbA1c measure.

Firstly, the measure assumes the lifespan of the red blood cells as part of the calculation so, if this assumption is invalid, it can affect the HbA1c. Common causes of false HbA1c readings include:

  • Anaemia
  • Excessive alcohol consumption
  • Excessive use of opiates
  • Pregnancy
  • Blood transfusions

The second and arguably biggest limitation of the HbA1c measure is while it speaks to the ‘average sugariness’ it says nothing of the variation. This is why, historically, doctors have erred on the side of a higher HbA1c with Type 1s, often to the diabetic’s frustration. The reason is simple: if the diabetic’s glucose levels fluctuate significantly, and they keep a lower glucose level, they are at an increased risk of hypo whose effects are immediate (groggy, fall over, go unconscious etc.) whereas running a little ‘high’ and fluctuating mitigates the risk of hypos at the expense of increasing the risk of long term nerve damage. To put it simply, with limited visibility of the fluctuations using strip glucose monitors, it makes sense that doctors err to minimize risk today and encourage their patients to run a little higher with a view that the longer term risks can be managed later.

Interestingly, in his talk, Professor Choudhary blamed his patients for running high and having high fluctuations, suggesting they are driven by fear of a hypo which then leads to over-correcting and large fluctuations.

Fortunately, Continuous Glucose Monitoring (CGM) technology gives a much clearer picture of the fluctuations, informing both the doctor and patient, and allowing them to proceed informed, rather than out of fear.

Time in Range

It has taken a while for a standardization of Time in Range guidelines but in August 2019 we got one from the ADA.

The standard is adjusted for various sub-groups of diabetics.

What is more, these ranges are not random, or at the whim of some group of doctors, but backed up by statistically significant links to both long term complications and the equivalent HbA1c.

Some of these were highlighted by Professor Richard M. Bergenstal.

and Anass El Malahi at EASD 2020.

As we can see, we can link changes in Time in Range to changes in the risk of retinopathy, microalbuminuria, microvascular complication, and nephropathy.

Professor Bergental also showed, using the CGM data of three of his patients, how much more insightful Time in Range can be, compared to HbA1c.

Here the three patients have exactly the same HbA1c but very different experiences with their diabetes. with the third patient spending a lot more time in hypo and much less time in range.

Bringing together the Time in Range with the latest data on what it means for long term complications, the Ambulatory Glucose Profile (AGP) Report captures the key metrics along with statistically significant guidelines in one page.

As we can see the report captures:

  • Percentage time in the different BGL ranges
  • Average Glucose
  • Glucose Management Indicator (GMI): an estimation of the HbA1c
  • Glucose variability: a measure of fluctuation

which, given the GMI on its own is a proxy for the HbA1c, shows we are considering a lot more information in the AGP report than simply ‘average sugariness’.

The Big Problem with Time in Range

The big problem with Time in Range analysis is it requires a Continuous Glucose Monitor (CGM) to capture the data: it is a metric of privilege. While many of us have no exposure to it in the West, in places like Mexico, some Type 1 diabetics are given literally one strip per day to manage their blood glucose levels. Fortunately, research shows the proportion of finger pricks in, below or above range can still be correlated to HbA1c estimations and, therefore, give an indication of long term risk.

Also, with an increase in Time in Range of 10% leading to a lowering of HbA1c of 0.5%, using the above, we see that for someone whose finger pricks are in range 70% of the time, this correlates to an HbA1c of roughly 7%, as with the CGM data. This means the AGP Report and the guidelines it contains can be applied to CGM or finger pricking equally. So, while a diabetic’s management technology may change over time, their reporting for their health care team does not have to.

tl;dr

With the advent of Continuous Glucose Monitoring (CGM) we have new and insightful ways of examining our data beyond what is available with finger pricking and the HbA1c. One such way is analysing the Time in Range of our data. Time in Range provides a wealth of knowledge about both average sugariness and the glucose level fluctuations. One way to present this information is with an Ambulatory Glucose Profile (AGP) Report.

While driven by CGM technology, it is possible to use the AGP Report with finger pricking by considering the proportion of results that fit in the low medium or high categories. This now means we have a common report whether we are finger pricking or using CGMs.

Clinical research using Time in Range analysis has also established that it is predictive for a range of long term diabetes complications. This means, Time in Range analysis and the AGP Report are now a viable alternative to the HbA1c and provide much richer insights.

The Benefits of Incretin Mimetics For All Diabetics

I first read about incretin mimetics in Dr. Bernstein’s fourth edition of “Dr. Bernstein’s Diabetes Solution” published in 2011. He devotes nine pages to this class of drugs and it is a good place as any to describe what they do. It should be noted for those unfamiliar with Dr. Bernstein, his focus is on the treatment of Type 1 diabetes. While incretin mimetics are sometimes hailed as a ‘Type 2 drug’, they can be of benefit to diabetics of all Types as I will show in this blog.

From there I will update the information based on some peer reviewed papers from recent years (specifically relating to LADA) and the presentations at the recent EASD 2020 conference and then onto my own experience using them. As usual, there is the tl;dr at the end if you want the short version.

What Are Incretin Mimetics?

To understand the role of incretin mimetics, it is important to understand that beta cells produce, not just insulin, but also another hormone called amylin. Amylin is a ‘satiety’ hormone i.e. it makes you feel full. So, as the beta cells become damaged they are less able to produce this hormone. Amylin is released in response to the presence of ‘gut hormones’ in the blood, released when the gut is stretched. These ‘gut hormones’ are called ‘incretins’.

Based on all this, Dr. Bernstein suggests that diabetics of all persuasions are likely to not feel as ‘full’ as their non-diabetic counterparts. For me, this poses the question: “If someone who has impaired beta cell function cannot effectively regulate their eating, is it possible Type 2 diabetes and pre-diabetes causes obesity and not the other way around?” but that is a blog for another day.

At the time of writing his book, Dr. Bernstein describes incretin mimetics as being used to lower blood sugar levels after meals and for weight loss. We now know they have many more effects on the human body.

GLP-1 Receptor Agonists (GLP-1RAs) are one such incretin mimetic. As per the above we see, among other things, they can:

  • Lead to weight loss (likely due to the increased sensitivity to feeling full)
  • Lower glucagon secretion (meaning the liver releases less glucose into the blood)
  • Stimulate insulin secretion and production (to process the food that is causing the stomach to feel full)
  • Decrease beta cell apoptosis (this is the fancy name for programmed cell death. Cells in the body are given a countdown clock. When that clock reaches zero the cell destroys itself. Incretin mimetics tinker with that clock to extend the life of beta cells)
  • Offer protection from heart disease
  • Lower blood pressure

I should note that while these drugs do stimulate insulin production like, say, sulfonylureas unlike ‘sulfs’ the evidence shows this does not accelerate the demise of the diabetic’s honeymoon. My guess is the suppression of apoptosis counters the effect. Another possible explanation is, because the insulin is getting triggered earlier and harder, the blood sugars are not getting the opportunity to rise as high. Dr. Bernstein talks about how it takes more insulin to bring blood sugar down by a fixed amount when it is at a high level than when it is lower. So, the mimetics get the insulin out early when it is more effective and therefore the net production for a given meal is less.

Types of Incretin Mimetics

There are three types of incretin mimetics. These are:

  • Amylin analogs: To my knowledge the only one on the market is Symlin (pramlintide). This is available by injection. I have not tried this one. EASD 2020 had a presentation on using it in a dual-hormone therapy (pumps with insulin and pramlintide) but the benefit of the additional pramlintide, in this context, was minimal.
  • GLP-1 agonists (mentioned above): This is mentioned above with the associated effects. Until recently this was also only available via injection. Recently an oral version has been released (more of that later). I am currently on a once-weekly injection of this drug. Here are the six GLP-1s on the market at the time of writing.
  • DPP-4 inhibitors: DPP-4s destroy GLP-1s in the body so this drug opposes that destruction and therefore, in principle, eliminates the need to inject GLP-1s. DPP-4s are available in an oral form and I took these for at least six months before moving to the GLP-1 agonists.

Contraindications and Side Effects

I will list some of the more common side effects but this list, like for most drugs, is far from exhaustive so discuss your specific history with your health care team to get a full picture of how well these drugs might suit your circumstances and complication risk profile.

Firstly, incretin mimetics slow stomach emptying so this can make gastroparesis (a condition not uncommon in Type 1s) worse. This slowing can also induce nausea. People on social media will be more than willing to tell you how incretin mimetics made them violently ill. For me, I feel mild nausea a day after injecting the GLP-1 agonist (akin to very mild car sickness) but felt no such effect when taking the DPP-4 inhibitors.

One side effect that was actually beneficial for me was constipation. As I also take Metformin, I have found the GLP-1 agonist and Metformin balance themselves out nicely giving me a lot of freedom I did not have when taking Metformin with the DPP-4 inhibitor. It is different for everyone though as GLP-1 agonists are also reported to have diarrhoea as a side effect.

One of the more serious side effects is the risk of reversible pancreatitis. I am informed pancreatitis is one of the most painful things you can experience and is usually characterized as a sudden, severe abdominal pain extending through the body from the back to the front. As the name suggests, stopping the medication reverses the condition.

LADA-Related Studies on DPP-4 Inhibitors

Given I am a Type 1 LADA trying to preserve my beta cells as long as possible and avoid the financial and mental stresses of insulin management, many of the studies I have earmarked, up to EASD 2020, are focussed on blood glucose management and beta cells preservation. Here are a few:

Presentations From EASD 2020

Tina Vilsbøll presented on Semaglutide, a new GLP-1 which can be taken as a once-weekly injection or as a once-daily oral pill, both being equally effective.

Juris Meier went into more detail as to the efficacy of the oral version, compared to other GLP-1 agonists, in Type 2s, showing it was more effective at reducing HbA1c.

The oral version of Semaglutide also compared favourably to the DPP-4 inhibitor Sitagliptin at doses above 3mg for Hba1c reduction and weight loss.

The downside was an increase in adverse reactions at the higher doses, compared to Sitagliptin.

So, if you are considering swapping out Sitagliptin for Semaglutide, understand that for a superior effect on HbA1c and weight loss you are also at a greater risk of those adverse effects.

Alice Cheng showed how the injectable version compared favorably to both DPP-4 inhibitors and other GLP-1 agonists for reducing HbA1c and weight loss.

For adverse effects, Semaglutide was comparable to other GLP-1 agonists.

My Experiences With DPP-4 Inhibitors and GLP-1 Agonists

As mentioned, I have used both in an attempt to preserve my beta cell mass. For me, the DPP-4 Inhibitor had no side effects or, at least, any side effects were washed out by the ones from Metformin. The DPP-4 Inhibitor did nothing for me in terms of HbA1c reduction (although it is already in the mid-5% for this is not surprising), satiety, or weight reduction.

My experience with the injected GLP-1 agonists has been very different. Given the trouble I was having with Metformin, I halved that dosage but found the two drugs balanced each other nicely, as touched on before. I have lost five kilograms over a couple of months (I have it to lose) which I attribute to my significantly reduced appetite and improved sense of satiety. It is only now I realise it has been years since I actually felt full eating food and the GLP-1 agonist has given this back to me.

tl;dr

While traditionally considered a ‘Type 2 drug’, there can be benefits in incretin mimetics for all Types of diabetics. For all Types we have the general benefits of:

  • Lowering blood pressure
  • Lowering the risk of cardiovascular disease
  • A sense of feeling ‘full’ which may be lacking in diabetics
  • A lowering of HbA1c
  • Weight loss (especially for the GLP-1 agonists)

For Type 2s, the benefits also include the lowering of blood sugar levels through the increased release of insulin after meals and supressed release of glucose from the liver.

For Type 1 LADAs there is growing evidence that incretin mimetics can help preserve beta cell function and prolong the honeymoon. Certainly the latest guidelines for managing LADA fully embrace incretin mimetics even if, formally, they are not approved for use in Type 1s.

In terms of side effects, incretin mimetics can cause stomach issues and nausea but, generally, these are mild and much less pronounced in DPP-4 inhibitors.

New innovations in incretin mimetics include:

  • An improved once-weekly GLP-1 injection and
  • An oral GLP-1 taken once-daily

While superior to similar products on the market in terms of their effects on HbA1c and weight loss, it comes at the cost of increased risk of side effects such as nausea, diarrhoea, and vomiting.

EASD 2020: Is Cycling Good For Diabetics?

I posted this Tweet based on one of the presentations at EASD 2020.

It is worth going through some of the details because it seems incredible that as little as one hour a week of cycling really reduces all-cause mortality by more than 20% in diabetics. It is also a great study to see the limitations of research and statistics. As usual, if you want to cut to the chase, head on over to the tl;dr section.

Details of the Study

Presented by Mathias Ried-Larsen, data was taken from the “European Prospective Investigation into Cancer and Nutrition” (EPIC). This is a massive study across 10 European countries with over half a million participants looking at factors such as diet, environment, lifestyle, and chronic disease.

They took the data and filtered it to people with diabetes at the start of the EPIC study and for which relevant data had been recorded. This brought the number of participants down to 7,513 of which 63% were confirmed to have diabetes with the others being self-reported. A second cohort was considered at the second examination point to see how a change in cycling habits changed mortality rates. This second group comprised of 5,506 people.

The forms of mortality looked at were all-cause mortality (dying for any reason) and cardiovascular mortality (presumably because it is a common killer and one which is a higher risk in diabetics).

Looking at other factors of the diabetes group, it was seen that the participants were mostly middle-aged and overweight, and most did no cycling at all.

Despite the shrinking cohort numbers, they still obtained the graph I tweeted.

The bars on the four points can be thought of as the error in the value (with this level of error we are 95% confident the value is correct, equivalent to a p-value of 0.05 and is considered statistically significant). So, for example, if I do between 1 and 59 minutes of cycling in a week, my risk of all-cause mortality (ACM) drops to somewhere between 60% and 95% of the baseline risk.

The presenter claimed the covariates (other factors we know about the people) were statistically removed from affecting the numbers attributed to the cycling. So, for example, given women generally live longer than men, this could have an effect on the results so this was accounted for when looking at the results.

The presenter further claimed that there was a j-curve relationship with the data i.e. the benefits are reduced at the 300+ minute mark. To explore this, rather than bucket the cycling times into four groups, they looked at the cycling times as they were i.e. a continuous spread of values between zero and nine hours of cycling per week.

While there is a curve with a maximum benefit around 4-5 hours, there is a fairly wide error margin (UCL = Upper confidence level, LCL = Lower confidence level i.e. the upper and lower values with a 95% confidence of being right). In other words, while the curve seems to head up after five hours, the error means it could just as easily be heading down to between 0.6 to 0.7. Similar results were obtained when cardiovascular mortality was specifically examined.

Next was the review of the effect of changing cycling habits.

The takeaway here is starting to cycle yields at least a 10% reduction in all-cause mortality while maintaining a cycling habit reduces risk by between 20% and close to 50%. For cardiovascular risk, maintaining a cycling habit had slightly better results with the risk reducing by 30-60%.

Recognised Limitations

The presentation did talk at some of the limitations:

  • Confounding factors: As mentioned they looked at the influence other factors, such as age and smoking had but claim their results still stand
  • Medication: There was no information on the medications being used by the diabetics and the effect they would have on mortality
  • Underlying disease leading to less exercise and more mortality (reverse causation): As with the confounding factors, they looked at the potential influence and ruled it out as affecting the results
  • There was no distinction in EPIC between Type 1 and Type 2 diabetes so no conclusions between the Types could be made but it is assumed the distribution in the study is close to the general population and, therefore 80-90% of the cohort was Type 2

tl;dr

For middle-aged Western European diabetics, the study showed:

  • Cycling reduces all-cause mortality and cardiovascular mortality
  • The level of benefit is harder to quantify but, the best benefit was shown to be at around 4-5 hours per week of cycling where the reduction in risk was roughly between 20-40%. Additional cycling may be of benefit but the error margins were too high to confirm this one way or the other
  • Starting a cycling habit or maintaining one shows benefit with the most benefit being for someone who maintain a cycling habit with the reduction in risk being between 20-50% for all-cause mortality and 30-60% for cardiovascular mortality
  • There was no distinction of Type so it is best to assume these results apply most strongly to Type 2 but I can see no reason why it would be different to Type 1s except for the additional risk of hypo if insulin dependent

No More StereoTypes: The ‘No True Diabetic’ Fallacy

T1D I am diabetes and these are my companions.. ignorance stereotype and rudeness
Image: https://www.healthline.com/diabetesmine

It is often said that every diabetic’s journey is unique and it is true. While many of us have similar, isolated experiences, no two journeys are the same.

Paradoxically, the diabetic community can be quite tribal with groups excluding those who diverge from the ‘norm’. As a Type 1 LADA I see this a lot. As an example, when it is said ALL Type 1s use insulin and I have the temerity to point out I do not, I am dismissed as not being a ‘true’ Type 1. Only when my honeymoon ends, it seems, will the LADA be accepted into the tribe as a ‘real’ Type 1. I see little value in this dismissal of diversity.

Is LADA Really Type 1 Though?

If we define the Types by etiology (cause) then LADA falls squarely in the Type 1 camp. Both are auto-immune and, at a point in time, there is literally no test that can be performed to distinguish a LADA from a honeymooning Type 1. The only difference between someone with LADA and someone with ‘classic’ Type 1 is the rate of progress of the disease. While the honeymoon period of a ‘typical’ Type 1 is, at most, a few weeks, a LADA can be insulin independent for up to decade. It is a long time to wait for acceptance.

The other option would be to define the Types phenotypically (how it presents) but it is hard to derive an adequate criteria to separate Types 1, 2, and LADA (or any other Type) on this basis. As alluded to above, the dependence on insulin is often suggested as the distinguishing factor but there are many Type 2s/MODYs/Gestational diabetics who use insulin and all LADAs eventually progress to insulin dependence meaning, by this paradigm, LADAs gradually transition from one Type to another which, in itself, is problematic.

Diabetes UK unambiguously consider LADA as a form of Type 1. Similarly JDRF Australia say “A slower onset form of Type 1 diabetes, known as Late-onset Autoimmune Diabetes of Adulthood (LADA) generally presents with milder symptoms of hyperglycaemia, and insulin therapy may not be immediately required at the time of diagnosis.”

The Struggle for Recognition for all Diabetics

The concept of the only ‘true’ Type 1 being one which uses insulin is a fallacy and is akin to the ‘No True Scotsman’ fallacy.

Person A: “No Scotsman puts sugar on his porridge.”
Person B: “But my uncle Angus is a Scotsman and he puts sugar on his porridge.”
Person A: “But no true Scotsman puts sugar on his porridge.”

This struggle is not unique to LADAs though; all Types have their frustrations when it comes to recognition. This became clear to me at ‘docday’. Docday was a gathering of the dedoc Voices with presentations by some of the Voices on their advocacy work. Ken Tait presented on his frustrations as an insulin dependent Type 2. It was Ken’s talk which inspired me to write this post.

So often Type 2s are assumed to have brought the disease on themselves and that it is a ‘lifestyle’ disease. It is also often assumed that if they changed their ‘lifestyle’ the disease would go away. While there are lifestyle ‘risk factors’, there is no known cause of Type 2 diabetes and many Type 2s simply do not fall into any of these ‘lifestyle factors’. No amount of sugar eating gives you diabetes, there are plenty of overweight people who are not diabetic (and skinny ones who are), and while Type 2 can go into remission through a low calorie diet or gastric surgery, this is only effective in something like 70% of cases. Just as it would be foolish to assume someone from Australia has blonde hair and blue eyes, it is equally as foolish to assume the journey of every Type 2 is the same.

For Type 1s, the struggle is often to be seen as separate from Type 2s. While the cause of Type 2 is unknown, Type 1 is auto-immune (the reason for the immune system going haywire is still unknown but I digress). Type 2s represent around 90% of all diabetics so a lot of research and a lot of articles in the popular press focus on Type 2s almost exclusively. Frequently Type 1s are told that they can put their disease into remission. While this is only partially true for Type 2s, it is completely untrue for Type 1s. Short of a pancreas/islet transplant and immune suppression drugs, there is no remission for Type 1 diabetes.

As mentioned, for LADAs we are rarely seen as ‘true’ Type 1s. We are either labelled as ‘self-loathing Type 2s’ or ‘honeymooning Type 1s’. With a honeymoon that can last up to a decade, for me, dismissing their voice as meaningless is short changing 10% of the Type 1 community. If we can accept other diseases as having stages/progression, why is this so hard for Type 1 diabetes?

Clinical Consequence

Where the issue becomes a little more serious is in the consideration of treatment for the various Types. According to the NDSS (registration database for all diabetics in Australia) there are literally no Type 1 diabetics in Australia who are insulin independent. Given I am one, how is this possible? Like with the registration forms of many diabetes associations, it is simply assumed that if you are Type 1, you use insulin.

To make matters worse, subsidies for medication and equipment is often separated down Type lines. The medications I use to help preserve my beta cells and maintain my insulin independent honeymoon are considered ‘Type 2’ medications so I receive no subsidy for these and obtain them through a ‘private prescription’ at full price. While proven to be effective and safe, this means there are many LADAs who, for no good reason, cannot access the medications they need to remain healthy and live to their full potential.

The notion of Type 1 and Type 2 medications is problematic, not just for LADAs. The same drugs which help me, can help insulin dependent Type 1s with insulin resistance (yes, some Type 1s are insulin resistant) and satiety (one of the hormones which make you feel ‘full’ after a meal is missing in Type 1s i.e. Amylin). This notion of feeling full can also prevent Type 1s over-eating, reduce the amounts of insulin they need, and ameliorate weight gain which is often associated with insulin when it is first used.

Strength in Diversity

Accepting that not all diabetics are the same, even within a Type, does not diminish the journey of any one individual. What it does do is give a voice to all and give other diabetics and health care professionals a more nuanced understanding of this heterogeneous disease. With diversity of experience comes diversity of thought and better solutions to the problems we all face. Every diabetic’s journey is different but we can still walk together and exclusion simply means we walk alone.

Becoming a dedoc Voice

It is always humbling when strangers puts their faith in you. This happened to me this week when I was accepted as a dedoc Voice. Dedoc is an international network of diabetes advocates. What is more, it is Type agnostic: all are welcome.

Dedoc also paid for me to virtually attend EASD 2020 (the annual meeting of the European Association for the Study of Diabetes). Usually such conferences are exclusively for medical professionals but dedoc negotiated to allow their ‘Voices’ to attend with a view of socialising the research for a wider audience. Scientists are not always the best at communicating their discoveries so I believe this can only be a good thing.

There was way too much for me to communicate in one blog post so I will be posting a few. For some of the ‘soundbyte’ discoveries, check out my Twitter feed.