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Inside the Intuitive System: Lessons from Glucose Monitoring

 


I have previously written about my work with a team studying continuous glucose monitor (CGM) use by adolescents with type 1 diabetes. I recently had the opportunity to try a CGM sensor myself for a couple of weeks. I don't have diabetes, so my scores were all "in range," but there were still some interesting patterns in blood sugar over the course of the day. Wearing the sensor for 14 days also gave me insight into what the experience is like for patients who use a CGM for a longer time.

There's a debate in the medical literature about whether healthy people should ever use a CGM. On the one hand, some experts suggest that a CGM can help people to improve their diet, especially if they are at risk for diabetes or have signs of "pre-diabetes" already. CGMs can also help people to learn more about how stress and exercise affect their blood glucose. Dr. Peter Attia, in his book Outlive, makes one of the strongest cases for self-monitoring as a route to knowledge and long-term health promotion. He argues that if you would like to stay healthy and independent into your 80s and 90s, you need to be more than just healthy in your 40s and 50s -- you need to be at the high end of the continuum of health, so that when problems inevitably happen they only set you back on a more normal aging trajectory. My personal evidence for this comes in the form of a fasting blood glucose score, which is one of the early indicators of diabetes. We have been experimenting with a lower-carbohydrate diet in my household, and this year my primary care doctor was surprised to note that my fasting BG was down at 84, after years of scoring in the low- to mid-90s. A score of 100 or more suggests someone is on the road to diabetes, so it's interesting that he never thought to mention how close I was to the dividing line! Now I'm further away, which gives me more wiggle room in the long term.

On the other hand, perhaps using a CGM will make otherwise healthy people limit their carbs unnecessarily or excessively. No great danger of that in my case (how I love bread products), but there are other risks. Accuracy may suffer over time, particularly in detecting instances of low blood sugar. There's also a concern that CGM manufacturers are marketing their products as a way of "optimizing" blood sugar with no supporting data. So far, there's no evidence that CGM data can actually improve health for people without diabetes in any concrete way. For people who do have diabetes, these devices are clearly helpful in supporting self-management. For the rest of us, researchers posit that maybe they satisfy our curiosity or give us an "illusion of control" over our health. 

My own experience with a CGM suggests that I might be gaining more than just an illusion of control. One interesting finding was that some of the normal patterns I expected from the diabetes literature did not apply in my case. For example, many people with diabetes have the most blood-sugar reactivity in response to carbs at dinnertime. That wasn't true for me. No matter what I ate for dinner, my blood sugar seemed to have only a small bump that quickly resolved. If I took a walk after dinner, my blood sugar was actually more likely to go low. I told my family at those times that "my CGM says I need a cookie," which probably was a counter-productive result! My problem meal, on the other hand, seems to be lunch. Over the 2 weeks that I wore the monitor, lunchtime produced the biggest jump in blood sugar, again relatively independently of what I ate. It never went out of range (again, I don't have diabetes), but the more-reactive pattern of blood sugar certainly goes along with my usual postprandial slump in the early afternoon, and consequent need for a cup of coffee. I haven't figured out how to fix that one, but it's an area to focus my efforts. One other learning was that when I have a late-night snack (a habit that I've had a hard time breaking), eating carbs is likely to produce up-and-down blood sugar in the night, and to contribute to much worse sleep. The best solution would be to quit snacking, which I will continue to work on. But I discovered that adding a little protein to the snack also drastically reduced the scale of the problem, so I might at least get a better night's sleep out of this experiment.

In the negative column, my top reasons for not wanting to continue using the CGM were perfectly consistent with what our adolescent participants have told us in prior research: hassle and dislike of the feeling of the CGM on my arm. Something that I particularly disliked was the need to keep an app running on my phone at all times to communicate with the CGM -- if I closed it by mistake, my phone emitted a loud and annoying alarm. Couldn't the data tracking be cloud-based, and send me a text if there were a problem with the device instead? Keeping an app open on my phone is counter to my usual practice, and it ran down the battery faster than usual. None of this was a dealbreaker, and certainly I would use the CGM if I actually needed it, but it was a low-level annoyance to me the whole time.

One last annoyance had to do with data inter-operability. I found that my CGM (made by Abbott Labs) communicated only with its own proprietary app -- I had no choice about how to view my data. Further, I discovered that Abbott hadn't bothered to link their app with Apple HealthKit and had no concrete plans to do so. Therefore, I couldn't view my glucose data on my usual iPhone health dashboard or on my Apple Watch. Again, these were annoyances rather than real drawbacks, but I was not happy. I found the proprietary Abbott interface a little clunky, and I really wanted to be able to see my glucose trend on my watch! Yes, I'm the kind of person who always tweaks the settings on his computer. This was an interesting example of locked-down health data systems meeting highly customizable personal electronics, and my expectations as a user were a lot higher for a product that to me seemed to be in the same basic space as Fitbits and Garmin watches. Those products, of course, are not regulated as "medical devices" by the FDA, while CGMs are! (Where the agency draws that line is a perpetual gray area, and their official guidance actually says that they do consider smartwatches to be medical devices, they are just choosing not to enforce the rules right now in this arena). Fortunately for me, the inter-operability problem has already been solved by some clever young people with diabetes (younger and more tech-savvy than me in any case), who found a way to port my CGM data out of the proprietary app and into several other pieces of free software that eventually, like a game of "telephone," passed them along to my Apple HealthKit app and Apple Watch. Below are some examples of different ways that the exact same data can be displayed in different apps -- from left to right, these show (a) the default Libre app from Abbott, (b) the NightGuard app that has a corresponding widget for Apple watch, (c) the Gluroo open-access app that syncs with Apple Health but also displays some of the most interesting additional statistics like a multi-day time in range and an estimated hemoglobin A1c, and (d) the Apple Health display, which is actually a bit basic but is at least in the same place with all of my other health data. Clearly there is still considerable room for software improvement and standardization in this industry, and for research on the best ways to display data to facilitate user decision-making.

In our studies with adolescents, we have argued that CGM data is a way to develop situational awareness and expertise in managing diabetes. People who better understand their own body's reactions to various foods can then take advantage of various TMT-based strategies to change the way they eat, rest, and exercise, and can continue looking at the CGM data over time to determine what works personally for them. In summary, I do recommend trying a CGM either as a person with diabetes or as someone without diabetes. It's an interesting data source that can help you to gain insights and facilitate trial and error learning about your own state of health.

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