CGM Regulation: Achieving Standardisation for Outcomes

TL;DR

Not all CGM systems report the same glucose level on their displays, despite measuring the glucose in the same place!

What!

I get why that feels ridiculous — surely if they all measure in the same place they should report glucose values in the same way? But they don’t.

CGM systems can be grouped into three categories based on what the on-screen number represents — and that on-screen number is the one you act on: treating hypos, giving correction insulin, adjusting food, exercise, or bolus timing.

Those same displayed values also generate your percentage Time in Range (TIR) and Time Below Range (TBR), typically defined as:

•TIR: 3.9–10.0 mmol/L (70–180 mg/dL)

•TBR: <3.9 mmol/L (<70 mg/dL)

They’re the metrics you and your diabetes team use to judge control and risk. So if two devices report systematically different numbers, they can make the same physiology look better or worse on paper, and change decisions!

That’s why knowing which Zone your CGM reads in really matters. It affects day-to-day decisions, how you interpret patterns, what treatment changes you make, and ultimately how well the data reflects your true glucose exposure and long-term health risk.

The Zones

Zone P: Some systems read true physiological blood glucose. In other words, the displayed value closely matches the glucose your body is actually exposed to in the blood.
Zone B: Some systems, by design, and for safety to prevent over-delivery of insulin, read consistently lower than physiological blood glucose. Their readings are systematically below your true blood-glucose exposure.
Zone UKNOWN: Most worryingly, for some systems we don’t know whether they read above, within, or below true blood glucose, because the relevant performance data aren’t publicly available.

Why does this matter?

Because most of our evidence for glucose targets, Time in Range (TIR; 3.9–10.0 mmol/L or 70–180 mg/dL), and long-term complication risk was generated using Zone P systems. That means a benchmark like 70% TIR is appropriate for Zone P devices, but it is too low for Zone B devices.

Zone B systems typically read lower than true physiological blood glucose. So to achieve the same real glucose exposure as 70% TIR on a Zone P device, a person using a Zone B device usually needs a higher displayed TIR target (roughly 75–80%).

This mismatch also matters because it changes:

how AID (automated insulin delivery) systems respond to readings, and
how HbA1c aligns with CGM-reported metrics like TIR and average glucose

What would help fix this mess?

We need three things — in this order:

Public release of performance data for every system.
A clear declaration of which Zone a CGM reports in.
Globally standardised CGM performance testing, so we can make true like-for-like comparisons across devices.

Once that exists, we can finally set Zone-specific targets, based on what the device actually shows the user. Until then, TIR must always be interpreted relative to the Zone your CGM measures in, and your HbA1c MUST guide your understanding of future risk!

The rest of this page puts meat on the bones. If you read it carefully and really understand it, you’ll know more than about 98% of people in the diabetes space about what CGMs actually measure, and how that shapes everything downstream.

The quintessential mantra that should guide all diabetes-related glucose decisions is this:

Understand what your CGM is measuring, and what that number really means.

The best and most effective people in the world never forget the core truth:

“What gets measured gets managed”

So it’s time to find out what your CGM numbers truly represent.

The simple version

Every CGM system measures glucose in the fluid just under your skin. But different companies calibrate their sensors to align with different parts of the glucose ecosystem: either close to true mixed blood glucose (Zone P) or slightly lower than it (Zone B).

This difference is small on paper (5–10%), but it changes how your data look on the screen, how AID systems behave, and how your own decisions feel day to day.

If your CGM reads lower than true glucose (Zone B), your numbers will appear smoother and slightly lower. That means you might hit 70% TIR more easily, even if the body has actually been exposed to more glucose.

If your CGM reads close to true glucose (Zone P), then the target of 70% TIR is valid because the evidence behind this target was built using devices that read in this zone.

So the message is simple: 70% TIR is only equivalent across devices if they measure in the same zone.

The medium version: how CGM zones actually work

CGM systems are calibrated during development to read, on avergae, in one of three physiological “zones”. These zones describe how the CGM’s readings compare with the glucose levels your body is actually exposed to. Reading in a different zone can fundamentally change TIR, AID behaviour, and hypoglycaemia alerts.

Zone A: reads above true glucose

These systems read higher than true physiological glucose. They are likely uncommon, but with CGM systems on the market without publicly available performance data, it is possible there are some. These CGM systems can delay detection of hypoglycaemia and overstate hyperglycaemia and risk over-delivery of insuln.

Zone P: reads close to true physiological glucose

These systems, on average, align with true glucose exposure, reading between capillary and venous glucose. Every major CGM evidence dataset (TIR → HbA1c mapping, complication risk modelling, pregnancy outcomes) was built using Zone P systems. When targets say “70% TIR”, they assume you are using a Zone P device.

Zone B: reads below true physiological glucose

These systems typically read 5–10% lower than venous glucose. They trigger low alerts earlier, smooth post-meal peaks, and make TIR appear higher than actual glucose exposure. To match the long-term risk profile of a Zone P system achieving 70% TIR, a Zone B device usually requires closer to 75–80% TIR.

Diagram showing CGM Zones A, P, and B relative to physiological glucose

This is why 70% TIR on one CGM is not automatically equivalent to 70% TIR on another. It depends entirely on whether the system displays glucose values close to the body’s true exposure or consistently below it.

Where current systems sit

Most established CGM systems fall clearly into Zone P or Zone B. However, a growing number of devices provide no publicly available paired accuracy data, making it impossible to classify them — and this lack of transparency represents an unknown risk.

CGM systems reading in Zone P

These systems align with physiological glucose exposure and match the CGM systems that provided the data current global CGM targets (including 70% TIR) were derived from.

Device	Manufacturer	Bias to Venous Blood Glucose	Comparator
FreeStyle Libre 2 / 2 Plus / 3 / 3 Plus	Abbott	+5%	Venous
Dexcom G7 / ONE+	Dexcom	+5%	Venous
Dexcom G6 / ONE	Dexcom	+3%	Venous
Roche SmartGuide	Roche	+3% (inferred)	Capillary

CGM systems reading in Zone B

These systems, on average, read below venous glucose. This often results in higher TIR values that underreport true physiological glucose exposure.

Device	Manufacturer	Bias to Venous Blood Glucose	Comparator
Eversense E3 / 365	Senseonics	−5%	Venous
Medtronic Simplera / Guardian 4	Medtronic	−8%	Venous

CGM systems with unknown measurement zone

These systems cannot be classified because they either publish no performance data, do not report study design in suffienct detial, or have insufficient paired glucose samples,. Without this information it is not possiibe, to stae with confidence, if they read on avergae, in Zone A, , P or B.

Device	Manufacturer	Rationale
SiBionics GS1	SiBionics	Insufficient paired data (<8000 and/or <30 people with T1D)
Sinocare iCan	Sinocare	Insufficient paired data (<8000 and/or <30 people with T1D)
Linx CGM	MicroTech	Insufficient paired data (<8000 and/or <30 people with T1D)
Yuwell CT3	Yuwell / POCTech	Insufficient paired data (<8000 and/or <30 people with T1D)
Urathon CGM	Urathon / POCTech	Insufficient paired data (<8000 and/or <30 people with T1D)
Syai Tag	Syai Health Technology	Insufficient paired data (<8000 and/or <30 people with T1D)
GlucoRx AiDEX	MicroTech	Insufficient paired data (<8000 and/or <30 people with T1D)
Medtrum A8 Nano	Medtrum	Insufficient paired data (<8000 and/or <30 people with T1D)
i-SENS CareSens Air	i-SENS	Insufficient paired data (<8000 and/or <30 people with T1D)
Infinovo GlucoNovo	Infinovo	Insufficient paired data (<8000 and/or <30 people with T1D)

These differences are not cosmetic. They shape everything: how your AID system interprets glucose, how clinicians judge your stability, how TIR maps to HbA1c, and ultimately, long-term risk. This is why understanding your CGM’s measurement zone is essential.

Understanding the physiology: why capillary and venous glucose differ

Capillary blood reflects glucose freshly delivered to tissues, before uptake. Venous blood reflects what remains after the tissues have extracted glucose for energy. This creates a consistent 5–10% difference between them, and after meals the gap can reach 30%.

Every CGM system must choose which physiological signal it aligns with. That choice determines how glucose appears on the screen, how quickly levels seem to rise or fall, and ultimately how AID algorithms and users behave in response the glucose vlaues and trend arrows.

The identical twin problem: same TIR, different outcomes

Imagine two identical twins with type 1 diabetes. One uses a Zone P CGM; the other uses a Zone B system. Both hit 70% TIR for 20 years. One develops complications earlier and has consistently higher HbA1c. Why?

Illustration of twins comparing TIR results

Set aside biological variation — identical twins share glycation efficiency and red-cell lifespan. The remaining explanation is measurement. A Zone B device systematically under-reports true exposure. TIR appears better, but HbA1c reveals the truth.

The health cost? The literature estimates that each 10 mmol/mol (≈1.0% HbA1c) increase raises microvascular and macrovascular complication risk by roughly 30–40%.

How TIR leads to HbA1c — and why CGM zone affects both

Mounting evidence shows a clear relationship: each 10% change in TIR corresponds to about a 5 mmol/mol (≈0.5%) change in HbA1c. Importantly, Zone P systems were used to generate the data for these relationships.

Newer long-term studies show that a sustained 5% improvement in TIR predicts around a 20% reduction in risks for eye and kidney disease. But again, this is based on Zone P CGM data. If your CGM measures in Zone B, a reported 70% TIR very liklely will meaa a higher physiological glucose exposure, than someone hitting 70% TIR on a Zone P CGM system.

AID systems: why measurement zone changes algorithm behaviour

AID systems rely entirely on CGM data. If a CGM consistently reads below true glucose, the algorithm will:

reduce insulin earlier, thinking hypos are coming
suspend insulin more often
allow higher post-meal exposure

The user may also overtreat “false lows”, pushing true glucose higher than intended. This effect is magnified at night and before meals.

The result: smoother CGM traces and often higher TIR on screen, but higher HbA1c. This pattern appears in pregnancy data and in several real-world AID comparisons.

Regulation: why this problem exists and why it is worsening

EU MDR (2017/745) recognises the need for public performance datasets but its central database is still not operational. This leaves gaps where devices can enter the market without releasing paired accuracy data.

Established CGM companies publish clinical data voluntarily. Others do not. Some systems are already being prescribed for insulin dosing with:

no published comparator type
unknown bias
insufficient T1D data
no transparent accuracy dataset

This creates a situation where 70% TIR on one device may correspond to 60% or 80% physiological exposure on another — an untenable situation for clinical care.

A practical analogy: the degree classification problem

If you study for four years and your tutor marks generously, telling you you’re averaging 70%, you expect a first-class degree. But if their marking runs 10% high, your true score might be closer to 60% — and your future opportunities change dramatically.

Analogy illustration for inflated marking

CGM works the same way. A generous (Zone B) CGM can make your glucose exposure look “first class” while your true exposure is not.

What this means for you: practical actions

Your CGM’s calibration zone shapes how your numbers appear, how your AID system behaves, how you make insulin and hypo treatment decisons, and how you interpret time in rnage targets. After all,

“What gets measured, gets managed”

If you use a Zone P CGM

You can use standard international targets as intended:

≥70% TIR (3.9–10.0 mmol/L)
<4% below 3.9 mmol/L
<1% below 3.0 mmol/L
GMI roughly aligns with HbA1c

Your data already reflect true physiological exposure and maps with the data used to set the international targets. Interpretation is straightforward.

If you use a Zone B CGM

These systems typically under-read true glucose exposure. This means the same TIR value likely corresponds to higher actual glucose exposure. To match the risk profile of 70% TIR on a Zone P device, consider aiming for:

75–80% TIR (3.9–10.0 mmol/L or 70-180 mg/dL)
Expect less aggressive AID behaviour after meals
Expect earlier low alerts and more false lows

The safest approach is to combine TIR, HbA1c, and consult with your health care team.

If you use an Unknown-zone CGM

You cannot reliably interpret TIR. The CGM device may be under-reading, over-reading, or shifting across glucose ranges.

Be cautious with targets — TIR may not map to risk
AID systems using glucose values from these CGM devices present an unkown risk

What clinicians should consider

70% TIR is not universal — it depends on CGM measurement zone
HbA1c/TIR mismatch often reflects device bias rather than user behaviour
AID performance depends on CGM bias
Evidence-based targets require Zone P alignment and other CGM devcies may require different targets

Until global accuracy standards are enforced, CGM zone awareness must be part of routine interpretation to allow for clinical target adjustment.

Choices from here:

What the different CGM systems offer
Top 10 tips for optimising time-in-range using CGM systems
Skincare when using CGM systems
Undersanding risk and CGM testing
Understadning the different accuracy measures of CGM systems
Detailed deep dive in CGM regulation

Or know you are zone aware, jump to read about what the different systems offer.

References

Below are the core scientific sources underpinning the physiology, accuracy, and clinical implications discussed on this page. All links open in new tabs.

CGM: What gets measured gets managed!