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Tags: average, data, Dexcom, range, standard deviation
Categories : neutral times
I just downloaded data from my Dexcom and have been taking a look at it. There’s so much data and so many different ways of looking at it; it’s hard to tell what to make of it. There are a few items I like to focus on:
Modal Day screen
- average blood sugar for the month
- average blood sugar for the past 3 months
- standard deviation
Glucose Distribution screen
- % in range for the month
- % in range for the past 3 months
Success Report screen
- compare data montly
- compare data quarterly
The average will tell me about what my A1c will be. I use this chart and I have found that comparing my Dexcom average to this chart is very close to my actual A1c.
The standard deviation will tell me if I am doing too much of a rollercoaster. Lower is better. I will confess, mine is not as low as I would like, so I know that I need to level it out.
% in range is very important to me. Knowing that I am in range 75% of the time is greatly empowering. Knowing that I am 95% in range upon waking is even more empowering. Of course, knowing I am only 50ish% in range after lunch tells me that I need to work on that area.
Comparing the data from month to month is great for trends. I can see that my average in October was less that what it was in September, which is great. I can also see that my average for the last quarter is lower than the previous quarter, so I imagine that my A1c will be lower as well.
Using the Dexcom software can be a little overwhelming (there’s so much more data available than I even mentioned), but if I focus on these few things, I feel like I have a pretty good handle on my diabetes control.
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Tags: Agamatrix, data, Freestyle, glucometer, Keynote, Wavesense
Categories : good times
I’ve been using the Keynote for about a week now, so today I sorted through all the data and made a few graphs and analyses. (Let me know if you cannot view the link)
meter comparison spreadsheet
Here are some of the observations I saw from the data:
- The overall average is nearly identical. The Freestyle (for the first few days of the spreadsheet, I was using the Flash, then I switched over to the Lite. I don’t think it made much of a difference) had an average of 124.9, while the Keynote had an average of 125. UPDATE: I removed a couple lines where I only had a number for one of the meters (but not both). This resulted in a Freestyle average of 124.5 and a Keynote average of 123.5. Still not a huge difference, but in this case, the Keynote gives a LOWER average.
- The Keynote has a lower standard deviation. Freestyle’s standard deviation was 57.4, while the Keynote has only 50.5. This is very important. Lower standard deviation means fewer/less extreme values. This is what they mean by the “plus or minus 20%” or whatever. A lower standard deviation means it can be “plus or minus” by a lower amount. This indicates increased accuracy, which is what Agamatrix claims in the first place. As a result of my update in #1, the Freestyle std dev is now 57.7 and the Keynote is 49.6
- Related to #2, the Keynote produced a higher average when blood sugar was 100 or below; and a lower average when blood sugar was above 100. Again, this indicates a lower standard deviation and fewer extreme values.
- The biggest difference in standard deviation was when blood sugar was above 100. I feel that this is very important, because that means high numbers are more accurate. As such, there is lower risk of over treating a high and thereby ending up low.
If anyone wants to offer any more observations they find in the data, feel free to leave a comment below. Try to keep the comments about the differences in Freestyle vs. Wavesense and not about my numbers/care/treatment/etc.