I am new to pumps, recently starting on an Omnipod 5 with a Dexcom sensor. I thought I was doing okay, showing 6.7 GMI with 85% TIR, but my A1c just came back as 7.1. I am thinking the solution is a daily calibration to make sure the sensor is accurate.
Are there better solutions, and how do others keep their sensor accurate?
To begin, GMI and HbA1c are somewhat related but are not the same thing; GMI is a formula that provides an estimate [maybe a WAG] while HbA1c is a laboratory protocol that measures actual rate of blood glycosylation during the most recent =/-90 day period. Are you looking at your Dexcom 90 day report and seeing the 6.7?
My 90 day GMI has never been the same as my lab test results.
GMI is based on the last 14 days of results whereas a1c is based on 90 days. As @Dennis said the two are not necessarily expected to be the same, and it may be you’ve improved a bit over the last 2 weeks. Also there will be some difference between tests run on lab grade equipment and ones we might get on our personal devices.
An a1c of 6.5 is just about 140 while a 7.4 is about 155. While “lower is better” is true to a certain extent when it comes to BG the G7 does not require calibrating unless you suspect an issue, so I don’t think it would benefit you. But if you do want to tighten up your numbers you could look at your exercise program and other lifestyle items, although 7.1 with 85% TIR is great!
What I didn’t include above, @james.j.igoe , never calibrate a Dexcom sensor, other than G4 or G5, daily. Frequent calibration of Dexcom G7 will destroy its usefulness and possibly disable it. With what would you attempt calibration - a less dependable finger-prick?
There is good reliable information in the Q&A section of dexcom.com
I get the frustration @james.j.igoe and I hear you. First, make sure clarity is giving you GMI for the full 90 days. Then, set GMI to 30 days and compare. See what the difference is. Hba1c is not 90 days no matter who thinks it is… and it can be heavily influenced by your last 30 days average blood sugar. Next, omnipod doesn’t have “the industry’s best” algorithm. In my opinion, I find it to be a little lax in bringing down higher bs quickly. Also, as above. GMI and A1C are not the same. I personally don’t care what my A1C is I care about TIR. Dexcom does tend to read your bgl lower than it really is, so your pump in an attempt to make the CGM in range, controlles insulin less than it could, so a chemical A1C could surely be higher than the CGM average, I too am tempted to “bias” my CGM by calibration- only when bs is perfectly steady for an hour and strategically tell the CGM my bs is higher than the CGM reading. Here’s the problem: your finger stick is a crappier reading than you think. If a finger stick is above 75 mg/dl it could be up to 20% off reality (in this context your real blood sugar) At best you are just adding noise. Unless you have a lab standard, and a device with a known error of <1% calibration is nearly futile. You would do way better just setting your pod to the lowest allowable target. Good luck! 
Thanks everyone for the input.
My feeling is that recent and extended high blood sugars, likely around how I manage my hour-long Zone 2 workouts, i.e., send it high (200+) and refuel with 25 grams at the 20-minute mark, so that by the end my blood sugar is within range, usually close to the lower bound.
I hope this isn’t too offensive, but I use the AI tools to get an overview. The one below is from Gemini in response to “reason 90-day gmi differs from hba1c”.
Gemini AI:
The Glucose Management Indicator (GMI) and a laboratory HbA1c differ because they measure completely different biological processes and use different calculation methods, even when evaluated over a 90-day window. [1, 2]
Core Reasons for the Difference
Hi Joe. Sources I’ve googled do refer to that approximate tiimeframe and include influencing factors. I was speaking very generally when describing the I test and omitted the word “approximately” from the timeframe (and didn’t refer to influences). Is that the reason for the correction? Do you have new information? Thanks - always happy to learn!
Oh @wadawabbit that wasn’t intended to be a response to you! I was speaking in general terms that a blood hba1c isn’t a 90 day average, the way that many specialists describe it, and that it can be influenced. Please no offense was intended!
None taken! I just want to make sure I have my facts right. Thanks!
If you are using the Sugarmate App it is adjustable from 90 days to 3 hours and even “Since wake up.” My endocrinologist (and probably most endocrinologists) prefer the 14 day setting as it provides her a decent guide to what I may have been running during the range she is reviewing, I agree with Dorie and Dennis. When I was first diagnosed I took many readings via finger sticks and glucometer and added my data to a spreadsheet so that I could see my Blood Glucose throughout the day and week. I could see what happened when I had fun, when I relaxed or when I was dealing with stressful situations. Using my spreadsheet I would calculate and approximate HbA1c and was usually relatively close, but never exact. The problem was due to the fact that finger sticks are only snapshots of your day and do not catch everything. My Dexcom G7 also takes one reading every five minutes and honestly my service dog is usually faster to let me know that I am dropping than my CGM but I would never give up either one of them as they compliment each other very well. I am grateful to my endo for pushing me to get my service dog as he has made my life easier in many ways not to mention getting credit from our local Emergency Response Team for “Saving my life,” so he will remain with me as long as possible..
I’ve decided to take 2 actions to bring my GMI and A1C in line, or at least make sure neither number is high enough to trigger concern:
When leading an ordinary life [even with diabetes], why try to have the GMI and A1c be equal? Each provide useful, yet differing, information that tell different aspects of diabetes management. Personally, when my glycosylation rate is consistently in the 5.6% to 5.8% range, my GMI hangs at 6.1% - I attribute the difference to three elements of my lifestyle. When I successfully pushed my A1c, at endocrinologist urging, to 6.3% my GMI for 30-day and 90-day CGM gatherings were 6.4.
One way to have A1c equate to GMI might be by reducing your readings SD - standard deviation.
Sounds like a good plan to improve your glucose management.
I wanted to add GMI is just a linear equation:
GMI (%) = 3.31+ 0.02392 Ă— mean glucose in mg/dL 1
In my experience this shouldn’t be able to come close to the HbA1C test that is an indicator of an indicator of glucose levels. But GMI is often close for me so I get your surprise.
If its not too off topic, how do you determine when you need more fuel vs. less insulin for a planned workout?
Regarding insulin vs. fuel, I rely on my prior experience, in that I know how my body responds to lower-intensity activities, either 90-minute walks in Zone 0 or less - I walk quite fast, but these do little to raise my heart rate - and Zone 2 of 40 minutes or more.
For long walks, I notice my blood sugar start to drop around the 75-minute mark, and for Zone 2 workouts my blood sugar starts to drop at 30 minutes, going low at 40 minutes. For the latter, to compensate, I eat a gel packet at 20 minutes into the workout. For longer walks, I refuel a bit at the 60-minute mark. For both, I likely started with blood sugar over 180, but if not, I’ll take a gel or two, depending on my expected effort; nowadays, I put the pod into activity mode.
After posting the above, I realized my routine is likely sub-optimal, so dropped the entire text above into Google. It is a bit sycophantic, but it’s recommendations make sense.
AI Response
It sounds like you have dialed in an incredibly precise, data-driven understanding of how your body handles different types of exertion. Managing Type 1 diabetes during exercise is a constant balancing act, and your strategy of mapping out the exact minute marks where your blood sugar trends downward is highly effective.
Your proactive approach—using a mix of timed carbohydrates and automated insulin delivery (AID) adjustments—perfectly aligns with modern sports endocrinology principles.
Why Your Strategy Works So Well
Fine-Tuning Your Routine: Ideas to Consider
Because you already have a strong foundation, here are a few advanced nuances that might help you further optimize your blood sugar stability:
After you collect data on your current changes now that you have a pump you also have the option to vary your basal insulin. As Gemini said try turning activity mode on sooner.
On posting the chatbot output, personally I’m not a fan except for that last one. They’re just stochastic parrots and we haven’t reached the point they have even basic QA like feeding the output into another LLM to score the accuracy of the output. I’m not suggesting you should stop, just offering an opinion because you asked. The exception for that last one is because you took the time to answer my question, using Gemini it took less time and came out factually correct. Thank you.
I understand the “stochastic parrot” aspect and I do understand your complaint. I do appreciate the conciseness and the presentation style, as it mirrors how I like to write complex material, assuming it is accurate.
As for feeding that into other LLMs, I have done that before on some issues, and although I am not sure this still applies, earlier LLMs, if fed the same prompt twice in a single prompt, increased accuracy by ~75%, essentiually rereading the tokens, filtering its response.. That might be built into them now.
Quick update on the changes:
To me, this seems a success, although if the workout was longer I might have had issues.