It’s been a while since I performed an upload into Glooko, but I did so just now and noticed a new layout. Not sure if it’s new or not (it’s been a while since my last upload), but I like the information layout. I don’t recall seeing the below in the old format.
Wow, Liam really uses very little insulin compared to Samson nowadays. His programmed basal has been ramping up progressively, to about 5.3 units per day. And his bolus is typically about 4 to 6 units too. He eats about the same number of carbs – somewhere between 75 and 125 g of carbs most days.
Not sure how, or why…but I guess even though it’s 2.5 years later, he’s still honeymooning…no other explanation for it I guess.
As for his carbs, they just end up being whatever they end up being. We don’t track carbs at all…we just make sure we bolus for w/e he’s eating. He’s not restricted at all…anything his brothers get, he gets (that includes cookies, cakes, just whatever they are having…I don’t want him to feel “left out”). So, as we’ve talked about…I just figure out how to “make it work”…it’s tough sometimes. lol
yeah I mean we don’t restrict carbs but I think it averages out that he eats about the same number per day. Which i guess makes sense – they’re the same age and probably eating about the same number of calories every day to grow.
I don’t know how anyone does A1C estimates. But in general, if an estimate is only averaging BG’s they are missing something.
A very important factor is the length of a high BG.
So if I were coming up with an estimation algorithm, I would look at things like this:
If you have a 250 and a 80, that averages out to 165.
But being 250 and then the meter showing a BG of 80 an hour later, is much different than being 250 and the meter showing a BG of 80 4 hours later. (One of them is a short span of 250, while the other implies a much longer high and more time out-of-range.)
I assume Dexcom does this sort of thing with their A1C estimates, looking at times. But do any other meter thingies (phone apps, meters, glooko’s, etc.) do estimates in a smarter way than simply averaging BG’s?
Where eAG is estimated average glucose. Now you have to do some algebra to go the other way…
Nightscout says this…
This is only a rough estimation that can be very inaccurate and does not replace actual blood testing. The formula used is taken from:Nathan, David M., et al. “Translating the A1C assay into estimated average glucose values.” Diabetes care 31.8 (2008): 1473-1478.
*Assuming your CGM is accurate…ours is off more times than it isn’t unfortunately. So I actually don’t base any “real” evidence off of the CGM data. I base it off of the PDM data (Glooka) because those are at least actual blood checks.
Glooka uses the data directly from the PDM (at least in our case). I think there’s a way to connect the two, but I’ve not looked into it because I don’t want to mix reliable data (PDM) with unreliable data (CGM).
Do you know the formulas they use? I assume they use some type of “time” at different BG’s to factor it.
If someone does enough BG tests, you could also come up with some more reasonable estimates. At least better then the current calculations they use with only “average BG”. Certainly there is some way to look at time between BG tests to come up with better calculations.