Please do not interpret this post as medical advice. Everyone is different and the changes I made might not work, or might even be dangerous, for you. Consult your healthcare provider before making any changes to your diet, medication or any other part of your routine.
If you are interested in improving your diabetes management using data and technology, head over to steady.health to find out more about my new company.
Last year I published a post about how I had started to use experimentation to improve the management of my diabetes. It’s been a few months so I thought it was time to follow up with a progress report. Back then I saw pretty dramatic improvements to my overall A1C, lost weight and was feeling better than ever. I can proudly say that I’m still on an improvement path several months later, and I’m eager to share how I’m doing it. Let’s start with how I used to approach it and why I believe it’s broken.
The traditional way
Before CGMs people relied on a basic method to figure out how much insulin to take for each meal: carb counting. Carb counting is what it sounds like, a manual effort to assess carbohydrates by estimating the carb density of each ingredient on the plate. You quickly realize that for some meals like casseroles, soups etc. its almost impossible to figure out unless you made them yourself from scratch. But, even for meals with fairly distinct ingredients, it turns out to be surprisingly hard. For many years I struggled with this method, not understanding why some meals impacted my blood sugar more than others.
In a study done by researchers at Wingate University, they found that the average accuracy for carb counting was only 59%. What I find remarkable about this is that the average length these subjects had diabetes was 26 years(!). Let me put those facts together, after 26 years of practice, the average accuracy is less than 60%. Ouch. That seems like a pretty poor approach as taking the right amount of insulin for meals is key to good management, if you don’t you’ll end up high, or even worse, low, and have to course correct. What is even more surprising is that even with these results, carb counting is still one of the key methods being recommended by doctors and the ADA for improved management.
I decided to take a different approach: experimentation. After getting a CGM I realized that if I could remember what I had eaten and the insulin dose I could use the blood glucose response to figure out if I had taken enough for that specific meal. And next time I eat the same dish I can look back at last time and make a more informed decision.
I recently moved into a new office and that creates some challenges in managing my levels as I’m exposed to a set of new restaurants and take-out places. After a few weeks of trial and error, I’ve found a bunch of lunch options that I like and that are easy to manage with insulin
- Mixt salads are great but the difference in insulin need between them can be significant, for the Cobb salad I only take 2 units, but for Orchard, I need 3
- The local taco truck is good but only if they serve corn tortillas, flour ones are harder to manage
- Chipotle bowls are surprisingly easy if you skip the rice, neither guacamole or beans require much insulin for me
There are some challenges with this approach as well:
- Remembering to log meals
- A tool to look at food pictures, insulin dose, and your CGM result together doesn’t exist today which makes it hard to piece the data together
- There is no simple way to share the data with your endocrinologist
But, all in all, this method has proven easier, more accurate and consistent for me which brings me to…
Long(er) term results
I’ve been tracking my own data using the Steady platform over the last 6–7 months and I’m pretty excited about my progress.
First of all, let’s look at my average blood glucose on a weekly basis. As you can see, its pretty stable around 112 mg/dL.
Average numbers only capture part of the picture so a better metric is how much time I’m spending inside of my range of 70–140 mg/dL. This, coupled with my average being stable means less variability which is great.
But, what about lows? This might be the progress I’m most excited about. I set a goal for me a few months ago: No more than 3 urgent lows per week, and it seems like I’ve been making strides. Keep in mind that this progress is coupled with stable averages and a reduction in variability 🙌
Experimentation is definitely worth trying if you’re struggling with diabetes, or, just want to get your blood sugar under control. It has significantly improved my health and at the same time made my diabetes easier to manage. If you’re interested but don’t know where to start, head over to steady.health and sign up for more information, or, send me an email at henrik at steady.health
Thanks to David Kjelkerud.