There’s been a lot of discussion in the DOC about BG test strips. There’s the strip safely campaign focused on making sure all test strips for sale in the US are subjected to the same rigorous quality control measures to ensure optimal accuracy; many discussions over whether or not 20% error allowed by the FDA is good enough, and countless user experiences.
So, from where does this problem stem? And how big of a problem is it really? The FDA has imposed an ISO standard on glucose monitoring. The standard is this:
ISO 15197 specifies that
> or =95% of the BG results shall fall within +/-15 mg/dL of the reference method at BG concentrations <75 mg/dL and within +/-20% at BG concentrations > or =75 mg/dL
This means that for BGs less than 75 mg/dL, our meters spit out results that are up to 15% off from reality 95% of the time, and when our BGs are over 75, they can be up to 20% off from reality. Compliance to this standard is often shown via a Clarke error grid, like the one below (for freestyle test strips).
As you’ll notice in the picture, the black dots are all within the region labeled A which is the 15-20% bracket. You’ll also notice that while the 20% range seems huge for larger BG values, this window is actually quite small for lower BG values. Also, for any given plasma glucose value, there is a normal distribution of BG values from 0% (completely accurate) to ±20% (with up to 5% of numbers being more than 20% inaccurate). I think it helps to visualize wha this really means by looking at this generic normal distribution:
Imagine that you kept a running list of the error of every one of your BG meter readings compared to your real plasma blood glucose. Then you graphed this data with the %error on the horizontal axis and the number of reading per % error on the vertical axis, you’d see a distribution very much like the one in the picture. Replace the “2σ” and “-2σ” with +20% and -20% and the “µ” with 0% on the horizontal. (I haven’t yet found reliable data to label the y axis with, but it would likely vary from brand to brand and I think it might be reported on that little piece of paper we always throw away when we open a new box of strips.) The light blue tail regions represent the 5% of numbers that are outside of the 15-20% BG allowance and the other 95% are in the two darker blue regions with most being concentrated nearer to the middle which represents your actual BG level.
With that in mind, let’s now consider what effect the FDA regulation has in practice. What I’m really interested in is how this error translates to errors in my diabetes regimen and the impact on my BG/A1C. Below, I’ll walk you through my calculation of insulin doses delivered based on meter reading and the resulting corrected BGs. To simplify, I calculated using a 20% error for all BG values from 40-400 mg/dL with a target range of 70-120 mg/dL.
Fisrt, let’s look at the range of meter readings you might expect compared to your real BG. Keep in mind that these lines contain 95% of all readings, with at least 68% of those readings concentrated closer to the dotted line than either solid line.
Using my insulin sensitivity factor, I then calculated the dose of insulin my pump would deliver in response to the meter readings shown above. Again, remember that numbers are concentrated more closely to the dotted line than either solid line.
Assuming no other influences (ie spherical diabetes in a vacuum), the next graph shows how my BG will respond to getting either the min or max insulin correction. These represent REAL BG values resulting from inaccurately dosed corrections caused by the 20% error in meter readings. The space between the lines contains 95% of all possible outcomes.
And lastly, I converted the above graph into percentages (because I like them). You’ll see the maximum percent over the target range (red, from under correcting a high or over correcting a low) and under the target range (orange, from over correcting a high or under correcting a low). This isn’t the % of resulting BG values outside of the range, just the % off from the target of a single BG resulting from inaccuracy in meter readings. And again, the space between the lines contains 95% of all possible outcomes.
I’m going to say it one more time because I think it is very important. These pictures represent the extremes – 95% of BG values are 20% accurate or better, with 68% of the values concentrated closer to reality. This then means that all of my calculations represent ranges of data with a similar distribution.
So, there it is. In pictures. The direct impact of the 20% FDA-approved error on our BG values (in a vacuum).
And now for my opinion on the subject: Personally, I feel like it’s just not that big of a deal. Since I am more likely to treat a low with a standard regimen of 15-30g of carbs and protein, the under correction there is mostly irrelevant.The possibility of over or under correcting a high over 240 is very real but since I’m already in the habit of double checking higher numbers (making sure there’s no rogue sugar on my finger tips) I don’t see that as a huge problem either. Plus the introduction of a second BG reading is enough to assure me that I’m comfortably in the 68% of readings that are far less than 20% off and not on the outskirts.
Here’s a copy of the excel sheet I used to generate these pictures. Have fun if you like that sort of thing and please let me know if you disagree with any of my calculations (or my opinion).
Here are a few other articles and opinions on the 20% issue: