A simple question — one that should have a straightforward answer.
But as you’ll soon find out, it’s a little more complicated than that.
Knowing the answer is crucial because it determines how much Time in Range (TIR) you actually need for your CGM system.
On some systems, a 70 % T IR is the target for predicting healthy long-term outcomes. On others, you might need 75-80% TIR to achieve the same long-term outcomes.
So the real question is — which CGM are you using: one where 70% is enough, or one where you’ll need 75-80% ?
I could just tell you the answer… but then you wouldn’t learn anything — and you wouldn’t be able to pass it on.
So put some skin in the game : set aside 20–30 minutes to learn this properly. When you’ve cracked it, you’ll be ready to explain it to others — because the diabetes community needs people who get it and can teach it.
Still here?
A special shoutout to Kirsten de Klerk from South Africa Diabetes Advocacy 🇿🇦.
Kirsten reached out after reading the piece and said,
“Wow — this is amazing, but it can get pretty heavy!”
Kirsten didn’t just give feedback — she gave three powerful upgrades that will make this message hit home.
Highlight the key reasons why this matters so much for people living with diabetes.
Split the FAQ into two parts — one focused on the global overview that’s punchy and powerful, and another that dives into the US and Europe–specific regulatory detail, with the study design deep-dive.
There really needs to be a global petition — something in the spirit of what South Africa Diabetes Advocacy is already driving locally — to demand safe, effective, and equitable access to continuous glucose monitoring (CGM) for everyone, everywhere.
So, I am getting Kirsten on the podcast to tell us all about CGM advocacy.
Kirsten’s Summary: Top Three for CGM Integrity
Not all CGMs measure glucose the same way, and that matters !
Different CGM systems can show very different numbers — not because your body is different, but because some sensors read higher or lower than your true glucose levels.
Some are tested against finger-prick (capillary) blood, while others are compared to lab (venous) blood.
That means some CGMs can read much lower than your real glucose, which makes your Time in Range (TIR) look better than it really is — so you might think everything’s fine when actually you need to make a change.
See the red lines versus the blue lines in the picture.
Would you make the same decisions if your CGM showed numbers closer to your finger-prick readings — or one that reads lower than your hospital blood test (venous)?
Remember — it’s the capillary (finger-prick) levels that show the true highs your body is really exposed to.
And that’s what matters when making day-to-day decisions about food, insulin, and activity.
3. We urgently need a single, global accuracy standard for CGMs.
To ensure fair comparison, clinical validity, and patient safety, all CGMs should align to the same glucose reference (preferably capillary) with transparent, harmonised accuracy reporting. Only then can TIR truly reflect health outcomes.
Thanks, Kirsten, for setting the scene.
Let’s begin part 1 of the journey!
Continuous glucose monitoring (CGM) has no rival in day-to-day glucose management.
The metrics generated by CGM have been proven to be among the strongest predictors of future diabetes complications and overall health.
The CGM readouts provide high-fidelity insights into glucose patterns — capturing lows, time-in-range, and highs with a level of precision unmatched by any other tool in diabetes care
CGM data are increasingly being used to evaluate how effective new drugs and therapies are — showing just how powerful this technology has become.
Special note
The robust evidence is built on CGM data from systems with robust accuracy and performance data. And most importantly, from CGM devices that read close to capillary glucose, not ones that give readings consistently below venous glucose .
But with a new wave of CGM systems gaining approval without publicly available performance data — and lots of existing devices measuring below venous glucose, far lower than the levels used in the studies that built our current evidence base — we’re entering uncertain territory.
For some of these newer CGM systems, because their performance evaluations are not made publicly available, we simply don’t know whether their readings align more closely with capillary or venous glucose.
We also don’t know whether a lot of the new CGMs have been tested rigorously — or on a sufficient number of people with type 1 diabetes, including children. That information just isn’t publicly available.
And that raises a fair question: why not?
EU law — which covers almost all CGM systems currently on the market — doesn’t require manufacturers to share performance data . They’re simply not legally obliged to.
This is beginning to change under MDR (2017/745) , which introduced plans for a central European database of medical device performance data. But that system still isn’t fully operational.
Then again… it was only agreed back in 2017 — so there’s still time, right?
Yet, the established CGM companies choose to publish their data openly in peer-reviewed journals and on regulatory websites.
That transparency is the foundation of trust — it’s what enables clinicians and people with diabetes to use CGM data with confidence.
At the same time, marketing claims are emerging from devices that under-read venous glucose, resulting in apparently higher time-in-range values — numbers that may look better on screen but don’t necessarily translate into the same long-term health benefits as those from CGMs proven to run close to venous glucose.
Here’s a glimpse into a potential future for many people using CGM — and a reality for some today. You might want to find out if that includes you.
Imagine this…..
You spend four years at university. Your tutor tells you you’re consistently averaging 70% on your assignments — so you’re confident you’ll graduate with a first-class degree.
But when the final marks come in, you discover you’ve actually been scoring 60% all along.
The tutor had been marking too generously. Instead of a first, you graduate with a second-class degree. That one number will follow you for years, closing doors to jobs and opportunities you thought were yours.
Now apply that to diabetes.
Imagine this….
You and your identical twin both have type 1 diabetes. For 20 years, you’ve each worn different CGM systems.
Both of you hit the gold standard—70% TIR —year after year.
You didn’t pay much attention to your HbA1c results because you were told 70% TIR was all that mattered.
You start to get complications first, and they are progressing much faster.
You cannot understand why. Was it just bad luck?
You review your diabetes history and find that your HbA1c has consistently been 7.5% (58 mmol/mol), while your sibling’s has been 6.5% (48 mmol/mol), despite both of you recording the same TIR on your CGMs for 20 years.
Why is my HbA1c 1.0% (10 mmol/mol) higher?
We both had 70% TIR?
There are biological reasons. HbA1c is not determined solely by average glucose; red blood cell lifespan and glycation efficiency vary between people.
For the definitive take, see James Hempe’s work on biological variation and the “hemoglobin glycation index. ”
Believe it or not, the body’s ability to use vitamin C to recycle key antioxidants in the red blood cells may play a key role — but that’s a story for another day, and maybe a podcast with Dr Hempe.
In this hypothetical case of identical twins, we can safely set aside biological variation.
So, we must explore other explanations.
Could it be that your CGM system is reporting glucose differently from your identical twin’s CGM?
Important physiology interlude.
Capillary blood contains glucose freshly delivered from the heart to the tissues, before some is taken up by the body’s cells for energy. Venous blood, on the other hand, represents blood returning from the tissues after glucose has been partly used for energy. For this reason, capillary glucose levels are physiologically 5-10% higher than venous levels overall and up to 30% higher after eating.
Now, imagine if your CGM consistently reports glucose values that are lower than venous glucose, whereas your sibling’s CGM reads very close to capillary glucose.
If that was the case, the natural question.
Wait… the data that linked glucose to risks for my eyes, feet, heart, and brain — was that based on CGMs reading close to capillary glucose, or on ones that run below venous glucose?
Every landmark study in type 1 diabetes — most famously DCCT and EDIC — relied on HbA1c as the key measure of glucose exposure. HbA1c represents how much glucose binds to red blood cells and reflects your average glucose levels over roughly three months.
From these data, robust models were built showing that as HbA1c increases, the risk of both short- and long-term diabetes complications—such as retinopathy, kidney disease, heart attack, and stroke—rises in parallel. The reverse is also true: as HbA1c decreases, complication risk falls.
While HbA1c is not a perfect causal marker, the association is very strong and has been validated over more than 30 years of follow-up. Each 10 mmol/mol (≈1.0% HbA1c) change in either direction modifies complication risk by roughly 30–40% , across both microvascular and macrovascular outcomes.
CGM researchers have shown that a 5% change in TIR corresponds, on average, to about a 5 mmol/mol (≈0.5%) change in HbA1c . As TIR rises, HbA1c tends to fall, and vice versa. The relationship is very strong .
Encouragingly, more recent studies are bypassing HbA1c as the middleman and mapping CGM data directly to complication risk. These data suggest that a sustained 5% improvement in TIR is clinically meaningful and 70% is a good target .
Better still, data looking over 7 years shows 5% changes in TIR modify the risk of eye and kidney disease by around 20% .
Please note;
All the research establishing 70% TIR as the target has been based on data from CGM systems shown to align closely with capillary glucose , not venous glucose.
Remember, venous runs 5-10% below capillary.
What does that mean in practice?
It means that if you record 70% TIR on CGM consistently reading below venous glucose, your HbA1c will be higher than someone getting 70% TIR on a CGM reading close to capillary glucose.
How much higher?
Well, the most recent analysis of all commercially available Automated Insulin Delivery (AID) systems reports differences of up to 10% in TIR between systems, but almost identical HbA1cs, aka, future health risk!
See below, it should not be a surprise that AID 5 is the only system driven by CGM readings below venous glucose.
AID System – See the 2025 analysis End-of-trial TIR % (95% CI) End-of-trial HbA1c % (95% CI) AID 1 72.4 (57.8–87.0) 7.1 (6.4–7.7) AID 2 71.8 (69.4–74.2) 7.0 (6.9–7.1) AID 367.9 (66.2–69.6) 7.3 (7.1–7.5)* AID 469.0 (67.5–70.5) 7.1 (7.0–7.2)* AID 574.4 (69.7–79.1) 7.1 (6.8–7.4) AID 663.1 (59.4–66.8) 7.2 (7.1–7.3)
To be clear, in our identical twin thought experiment, that would translate to a 20–40% higher risk of eye and kidney disease, and around a 30% higher risk of heart attack and stroke .
So, when the manufacturer of AID 5 publishes ‘real-world data’ showing their AID system achieves 5–10% more time-in-range than the others , does that mean it results in lower diabetes complications risk?
They think so.
“Since the landmark DCCT study, numerous retrospective studies have demonstrated the association between increased Time in Range and a reduction of diabetic complications. There’s no doubt elevated glucose is harmful and the average blood sugars of those living with type 1 diabetes are higher than we should accept as a clinical community,” said ….”The preponderance of data across randomized controlled trials and real-world studies show that the XXXXXXXX system is maximizing Time in Range far surpassing international targets and is taking it a step beyond by getting people closer to euglycemia. In the absence of a cure, our goal is to relentlessly innovate therapies to help people maximize their health without adding burden, which our newest AID system has proven to do.”
What do you think?
Shall we inspect the science?
“numerous retrospective study have demonstrated the association between increased Time in Range and a reduction of diabetic complications.”
This is very correct, as we have discussed earlier.
Remember, the CGM data use in those
“numerous retrospective studies ”
was CGM data from CGM systems reading glucose levels closely aligned to capillary glucose, not CGM data reading below venous glucose (Beck et al 2019 and Beck et al 2023 ).
Why is this important?
It’s been shown that a current market leading CGM device reads glucose levels below venous glucose. This resulted in a systematic over-reporting of TIR by 8% compared to CGM devices reading close to capillary glucose.
The real-world impact of this on people living with type 1 diabetes has now been confirmed. A large, well-conducted meta-analysis found that AID systems powered by CGM devices reporting glucose levels below venous glucose show approximately 5–10% higher time-in-range, yet achieve identical HbA1c outcomes compared with AID systems using CGM devices aligned closely to capillary glucose.
CGM data from systems that report glucose levels below venous glucose are not directly comparable with data from systems that read close to capillary glucose.
Therefore, the findings for health risk modification from that data, for example, the target is 70% TIR, cannot be used off the shelf!
So, these types of claims of superiority may hold true for CGM systems that report glucose values below venous levels.
However, without HbA1c data or direct evidence linking these readings to actual health outcomes, we cannot know whether such “superiority” translates into better long-term health.
Are these AID systems driven by CGM sensor glucose levels reading below venous glucose inferior?
Not for the average person with type 1 diabetes (if there is such a thing).
The honest truth is this: the largest and most robust systematic review shows that all AID systems deliver the same outcome when it comes to the only marker we can trust when comparing different AID systems, that is, HbA1c.
Despite AID 5 reporting 5-10% more TIR, across systems, average HbA1c levels consistently sit at ~52 mmol/mol (7.0%).
So when it comes to future health, AID 5 is not better than the rest—it’s on par.
And maybe for these type of CGM devices, the target is actually 75-80%?
Which would be 5-10% more than the 70% needed of those CGM devices reading close to capillary glucose?
What about special populations, where small glucose measurement errors carry a bigger impact.
Pregnant ladies with type 1 diabetes?
A new real-world study of 137 women with type 1 diabetes (Quirós et al., 2025) reported some interesting data.
Women using an AID system paired with a CGM that reads below venous glucose ended up with higher HbA1cs and a greater chance of having large-for-gestational-age babies .
In contrast, women using systems with CGMs aligned reading close to capillary glucose had lower HbA1cs and fewer large-for-gestational-age babies .
The reason?
Put simply: when a CGM reading approaches hypoglycaemia, the AID algorithm suspends insulin delivery to prevent levels from falling further — and ideally nudges glucose back into the target range, but may cause insulin deficiency, especially just before eating, leading to higher after-eating levels.
Also, if the user sees the level trending low, what will they do? Treat with carbohydrate to push the glucose higher.
So, if the CGM readings are reading lower than venous glucose , then the true capillary glucose —the level that actually drives HbA1c and fetal growth—will be getting increased unnecessarily!
I’m not stating this as certain, but it is a very plausible mechanism explaining the findings.
Now, this wasn’t a randomised controlled trial, and we don’t yet have multiple studies pooled in a meta-analysis—so it’s not causal evidence.
But given the thread of evidence already discussed, you can make your own mind up about which CGM you’d want driving an AID system in pregnancy.
Can CGM be used in early type 1 diabetes in people with islet autoantibodies?
Would I use CGM to track the progression of early-stage type 1 diabetes for my son, Jude?
Possibly — but only if the CGM is closely aligned to capillary glucose .
A CGM device reading below venous glucose won’t reliably catch those after-meal capillary spikes with the fidelity needed to track progression.
So yes, I’d probably use CGM — but with conditions:
I’d choose one aligned to capillary glucose.
I’d calibrate it every morning against an accurate finger-prick meter aligned to capillary glucose (e.g., Contour Next or Roche Smart Guide ).
I’d focus on 30-day averages , not single blips in a day that are likely measurement error that every CGM has!.
That way, you get the best of what CGM can offer, while avoiding being misled by under-reporting sensors, and being stressed every minute of every day!
This screening and monitoring piece really needs a full FAQ in itself — and that’s coming soon.
⚠️ And Now for the Scary Bit
All of the CGMs we’ve talked about so far are market leaders backed by robust, publicly available clinical data.
But today, CGMs are being sold without any public clinical evidence at all .
We don’t know if they read closer to venous or capillary glucose, we don’t know their accuracy, and some are being prescribed for insulin dosing and used to make assumptions about future health risks.
This is exactly why standardisation and stronger regulation are urgently needed.
Bottom line : until CGM performance is standardised and we can see the data, 70% on one system may not be the same as 70% on another .
This is why 2025’s hottest topic is standardisation of CGM performance — to get clarity for people living with diabetes, clinicians, and future research determining the evidence base.
I’ve deliberately avoided mentioning specific CGM or AID system names, because this isn’t about calling out companies. It’s about highlighting a major issue that needs tackling.
Getting lost in petty arguments over small details is pointless. What we need is to come together to make the future clearer — and to standardise so that 70% TIR on one CGM system means at least 68–72% on another.
We’ll never achieve absolute perfection, but we can get far closer than the current 60–80% spread. That level of inconsistency simply isn’t acceptable in 2025, especially in high-resource countries.
Nice work — you made it to the end! 🎉
You’ve now got everything you need to teach others or share this 101 as a starting point.
Want to level up and become a CGM accuracy pro ?
Ready for Part 2: The Deep Dive : Regulation & Study Design — how accuracy is defined, tested, and reported, and what that means for real-world decisions.