#165 - AMA #24: Deep dive into blood glucose: why it matters, important metrics to track, and superior insights from a CGM

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Hey everyone, welcome to AMA number 24. In this episode, I am joined, as usual, by Bob Kaplan, and we devote the entire episode to a series of questions that focus around glucose homeostasis. We center the discussion basically around the idea of why one would wear a CGM, especially someone who does not have type 2 diabetes or type 1 diabetes. And we get into the really deep nitty gritty around what is it about glucose that matters so much with respect to health? Why is it that I make such a stink about having lower average blood glucose, fewer peaks of glucose, less glucose variability, and all of the associated things that go with it? So hope you'll check out AMA number 24, and without further delay, here it is.

Hello, Peter.

Hey, Bob.

How's it going?

It's going well, man.

Ready for an ama?

Ready as always.

All right, so in this case, we got great questions about glucose and we aggregated a bunch. I think it'd be good to do a deep dive. I'm going to go through a couple of the questions here, see what you think. So the first question is more of a statement than a question. I've heard Peter talk about how fasting glucose and even HbA1c measurements can often be misleading and how he favors OGTT, which is short for Original Gangster Time Trial.

That's right.

Yeah. Okay, perfect. I think it might be oral glucose tolerance test with insulin measurements and also wearing a CGM to get a better sense of glucose homeostasis. My understanding is that OGTTS and CGMs are typically reserved for people with diabetes. So he's got the following why does Peter find these tests useful in healthy people? What is Peter looking for when assessing someone's glucose levels? What does he like and hate to see? How does Peter define normal versus abnormal control of glucose If I'm not diabetic, Peter, do I have anything to worry about here? And there's another question that was Are you able to do a breakdown of what you look for on different people's CGM data and what you would advise to improve their numbers similar to the ama? You did on lab tests.

All right, so I'm going to pause you right there, Bob, and I want you to answer this question for me honestly. Did you pay this person to ask these questions?

Asking for a friend?

I mean, seriously, these are the perfect questions, the most salient questions, the most important questions. And this might become, by extension then, one of the most important AMAs we do in terms of the aggregate impact it could have on health and longevity. Because these questions really get at the root of where I think I hate to use this term, but for lack of a better word, where the mainstream medical system is just so out of sync with what I believe the future of medicine is going to be. So let's take a step back on all of this for a second. Type 2 diabetes has a definition, and it is defined as having a hemoglobin A1C concentration greater than 6.5%, and that corresponds to an average blood glucose. God, I should know this, but the fact that I pay so little attention to it tells you why I don't even know it. I believe it corresponds to an average blood glucose of approximately 130 milligrams per deciliter. And of course, the way it works is it measures the concentration of glycosylated hemoglobin. So it's taking out red blood cells, and it's looking at how much glucose is stuck to them. And obviously, the more glucose that is stuck to them, the more glucose. You can infer that the average concentration of glucose is higher during the period of a red blood cell's life. But of course, this is potentially misleading, because if a red blood cell has a very short life, for example, see this in a couple of my patients, including a patient who's recovering from prostate cancer, who still has some GI bleeding issues, patients with gastritis, et cetera, but women with a heavy menstrual period. So people who are losing significant amounts of blood have a higher turnover red blood cells. They're going to have an artificially low hemoglobin A1C. Conversely, people who have red blood cells that stick around a very long time, people with a microcytic pattern, meaning they have very small red blood cells that are less likely to get chewed up in the splenic system, which is where we ultimately break down red blood cells, they're going to have an artificially elevated hemoglobin A1C because their red blood cells are living long than the typical person, which is about 90 days. So that's one reason why I'm not a Huge fan of hemoglobin A1C. But the broader point here is that I find it unhelpful to simply say if your hemoglobin A1C is above 6.5 and you have type 2 diabetes, you have quote unquote, a disease. If it is below 6.5, you are normal. Or even if we go one step further and say, well, there's a pre diabetes which is defined as 5.7 to 6.4, and those people we have to watch out for, but anybody at 5.6 and down is completely normal, as though there's some enormous difference between 5.6 and 5.7 or 6.4 and 6.5. So while on the one hand I understand the need to simplify things, I think oversimplification is erroneous and I think we should view these as a continuum. So glucose at the average level is a continuum. And as the person who asked the question noted, I am a far greater proponent of cgm. Now, Bob, I don't know if you're wondering what this thing on my arm is, but in case you are, this is a cgm. This is a continuous glucose monitor and as its name suggests, it measures glucose continuously. And while I do not have diabetes, and while most of my patients don't have diabetes, many of them along with I wear glucose, this device. And I think what we'll get into today is the why. So what are the metrics we're tracking here and what are we describing as ideal and optimal as opposed to acceptable along those metrics? Anything else I can say, broad strokes. Before we jump into the nuts and bolts of this, Bob, I think that.

Covers that other question about the continuous glucose monitor. Wondering if it's like streaming or does it actually take measurements every certain period of time?

Yeah, so actually I thought it would be helpful, Bob, to just sort of show you and obviously listeners kind of what this looks like. So it connects to your phone and every five minutes it is spitting out a number. If you look at it in a 24 hour fashion, when you turn your phone on your side, you get sort of a 24 hour tracing. So for my last 24 hours I've averaged about 90 milligrams per deciliter and my variability has been about 9 or 10 milligrams per deciliter or my standard deviation, my peak level has been, let me see, I have to go back and look, my peak was 102 and by extension then I've had no peaks above 140. That's going to come up later on. So obviously if my peak was 102, I was never above 140 and my nadir was 77, so range of 77 to 102. So anyway, that's the kind of data you get out of these things. And obviously they have reports that will spit out your average blood glucose over 1 day, 7 day, 14 days, 30 days, 60 days, 90 days, et cetera, along with the standard deviation and things like that. And the way these things work, of course, is they're not actually measuring in the blood, they're measuring in the interstitial fluid. And that of course, is the remarkable technology, right? It's that it's able to impute what the glucose level is in the blood without actually having to sample the blood. That's the magic of these things.

Knowing you, I suspect I already know the answer, but. But I'll ask it anyway. Have you looked at your CGM and compared say your three month data to your HBA1C?

Of course, yeah. And there's no comparison. So because I actually have something called beta thalassemia minor, or I carry the trait for beta thalassemia. I have tiny little red blood cells, or as my roommate in med school, Matt McCormick, used to call it, shite for blood. The size of my red blood cells is very small, so my mean corpuscular volume and mean corpuscular hematocrit are very low. I'm not anemic because I make up for it by having a lot of them. So I have a lot of red blood cells, they're just all very small. So I have normal hemoglobin, hematocrit, oxygen carrying capacity. But my hemoglobin A1C always runs high. I've measured it as high as 5.8. The lowest I've ever had measured is 5.1. But anytime I've measured it, because I've been wearing CGM for almost six years now, if I go and check my A1C versus my trailing 90 day CGM, it almost always suggests that the hemoglobin A1C is higher by 0.5 to 0.8. If I measure a 5.7 on the hemoglobin A1C, it's overstating my blood glucose and it should really be about a 5.1 or a 5.2. And we see the opposite in some people. We have some patients where their CGM is actually showing us a much higher level of average blood glucose than what their hemoglobin A1C predicts. So it's important to understand hemoglobin A1C is a measurement that predicts average blood glucose. CGM actually gives you average blood glucose and you can reverse Engineer an imputed A1C. It's obviously the latter that is much more interesting because you're directly measuring the variable of interest.

Yeah, it's amazing. It's amazing technology. It's the difference between a snapshot and a movie.

Yeah, entirely. And from when I started wearing these things nearly six years ago, I thought, I don't know why everyone in the world isn't wearing it. Notwithstanding the cost and the logistics of it. And the obvious reason why everyone wasn't wearing it was they're cost prohibitive. And certainly back then they were quite involved. But they're getting better and better and better. And I'd like to believe that there will be a day when you go to your first visit at your doctor, or prior to your first visit with your doctor, they mail you a CGM and you wear it for 30 days. And that data is looked at by your doctor and your doctor, by the time you arrive in the office, he or she has that information. And instead of looking at an A1C or a fasting glucose, they can really look at what your glucose excursions have looked like over a period of time. In the real world, they do that.

With, I guess, if things look fishy, but they'll do it with sphygmomanometer. They'll send you home with a blood pressure monitor and you'll take it every so often, maybe three times a day or whatever it is, to get a look at your blood pressure that way.

Right. We do that with our patients, most of our patients, there's a particular blood pressure monitor we fancy and we have them keep it at home. We have a special log, we have a method that we want them to go about doing it, recording it, and we'll track that as well. Unfortunately, in the wearable space, blood pressure is still far from prime time. We've tried a bunch of the wearables in that space and have not been impressed yet. I think there's going to be wearables in the blood pressure space soon. Okay, so where do you want to start on this? Because I know that part of the question that was posed is what are the metrics that we track? I want to go back and state my thesis, or call it my hypothesis. I guess my hypothesis is that outside of the formal diagnosis of type 2 diabetes, so now I'm referring to what the person asking the question called, as normal people, it's important that we leave quotes on that because I'm going to argue that that term has no meaning. But in the non diabetic, which may be a better way to describe it population, what is my argument? My argument is the lower average blood glucose is better. A hemoglobin A1c of 5.1 is better than a hemoglobin A1c of 5.5, even though neither of those people are anywhere near having type 2 diabetes. Two more you can minimize glucose variability the better. And of course glucose variability is very difficult to measure without a cgm. Using a cgm, the standard deviation is the obvious mathematical tool to do that, and lower is better. Stated another way, if you have two people who both have an average glucose of 100 milligrams per deciliter, which by the way corresponds to about a hemoglobin A1C of 5 to 5.1, which would be excellent, and one of them has a standard deviation of 10 milligrams per deciliter and the other one has a standard deviation of 20, the person with the lower one is better off. Third, minimizing glucose peaks is important irrespective of the first two things I said average glucose and variability. Although obviously the more peaks you have, it's going to all things equal. Push up glucose and it will certainly increase variability. But I would argue specifically that glucose peaks are problematic and that we want to minimize them Getting a little bit ahead of myself what are the three metrics we are constantly tracking in our patients? And what am I constantly tracking in myself?

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Sam.