Guide series, Part 4 of 5
Your Personalised Time in Range Target
The 70% TIR consensus is an ensemble target, derived from average-glycator patients on a small set of CGMs in randomised trials. This page moves you from that ensemble average to an individual risk prediction. Combine your CGM zone (Part 1) with your glycator status (Part 3); each cell carries an approximate TIR figure plus a TBR ceiling of under 4%. The matrix only names sensors with publicly available head-to-head accuracy data covering dynamic glucose conditions (Pemberton 2026, Sanfilippo 2025, Eichenlaub 2025, Freckmann 2025); the IFCC stress protocol (Pleus 2025) is published, no manufacturer has yet completed formal certification. If your CGM is not on the matrix, the mHGI half of the framework still applies. Working GNL framework (Grade D combination rule, Grade A/B inputs); discuss any change to your target with your diabetes care team.
The anchor: 70% TIR corresponds approximately to 53 mmol/mol (7%)
Across average glycators on Zone P CGMs, 70% time in range (3.9 to 10.0 mmol/L) corresponds approximately to an HbA1c of 53 mmol/mol (around 7.0%). This is the international consensus target endorsed by ATTD 2019 and ADA 2024, and it is the benchmark the entire matrix is calibrated against.
The matrix asks one question per cell: what TIR figure, on this device and for this biology, lands at the same HbA1c (around 53 mmol/mol) as an average glycator on Zone P at 70%? Same biological outcome, different number on the screen.
Why this anchor matters. The 70% target was set as a population average. It works as a population statement; it under-targets high glycators and over-targets low glycators when applied to individuals. The matrix translates the population target into a personal one without changing the underlying biology you are aiming at.
Why 3 mmol/mol HbA1c is the boundary that matters
The mHGI categories use a boundary of plus or minus 3 mmol/mol HbA1c. That number is not arbitrary. It comes from a chain of conversions and a long-term risk lens that turns a small-looking number into a large lifetime exposure.
The conversion chain
Three relationships, applied in order:
- Beck 2019 (longitudinal change-on-change): a 10 percentage point change in TIR corresponds to roughly a 0.6% change in HbA1c. Conservatively, 1% HbA1c maps to about 15 percentage points of TIR.
- ADAG (A1c-Derived Average Glucose): ΔHbA1c (%) = Δmean glucose (mg/dL) divided by 28.7. A 0.20% HbA1c difference equates to roughly 5.7 mg/dL (about 0.32 mmol/L) in mean glucose.
- Bergenstal 2018 (GMI): GMI mmol/mol = 12.71 + 4.70587 x mean glucose mmol/L. The conversion that lets you swap between mmol/mol and mean glucose at the level of a 90-day window.
So a 3 mmol/mol HbA1c boundary is approximately:
| HbA1c gap (IFCC mmol/mol) | NGSP equivalent | Mean glucose gap (ADAG) | TIR gap (Beck slope) |
|---|---|---|---|
| 3 mmol/mol | ~0.27% | ~7.9 mg/dL (~0.44 mmol/L) | ~4 percentage points TIR |
| 5 mmol/mol | ~0.46% | ~13.1 mg/dL (~0.73 mmol/L) | ~7 percentage points TIR |
| 10 mmol/mol | ~0.92% | ~26.4 mg/dL (~1.46 mmol/L) | ~14 percentage points TIR |
A 3 mmol/mol HbA1c gap looks like nothing on a clinic letter. In TIR terms it is the difference between roughly 66% and 70%, a gap most diabetes teams would consider clinically meaningful. The mHGI category boundaries make biologically and clinically calibrated jumps; they are not statistical convenience. Conversions: NGSP from IFCC via the standard 10.929 factor; mean glucose from NGSP via ADAG (×28.7); TIR from NGSP via the Beck 2019 conservative slope (15 percentage points TIR per 1% HbA1c).
The compounding-interest principle, why small differences matter over a lifetime
T1D is not a 12-month disease. It is a 50 to 70 year exposure condition, and the leading cause of premature mortality (cardiovascular disease) is itself a compound exposure problem driven by decades of cumulative glycaemic and lipid load. Differences that look small on a single clinic visit do not stay small when they accumulate.
An analogy that is easier to feel
Imagine you save 5% of your monthly salary. A friend saves 6%. After one month the difference is barely noticeable. Assume both pots earn the same modest 5% annual growth, on a £2,000 monthly salary (so £100 vs £120 going in each month). After:
| Years saved | You at 5% (£100/mo) | Friend at 6% (£120/mo) | Gap (compounded at 5% AER) |
|---|---|---|---|
| 20 years | ~£41,000 | ~£49,000 | ~£8,000 |
| 40 years | ~£153,000 | ~£183,000 | ~£30,000 |
| 60 years | ~£452,000 | ~£543,000 | ~£91,000 |
Indicative figures using a £2,000 monthly salary, 5% annual compounding, constant contributions. Exact numbers depend on contributions, returns, inflation, and tax wrappers. The structural point holds across reasonable assumptions: a 1 percentage point gap in monthly contribution becomes a five- to six-figure gap by retirement, and the gap itself grows roughly with the same compounding ratio as the principal.
Apply the same logic to glycaemic exposure
From the published DCCT/EDIC long-term data (Bebu et al. 2020), HbA1c is the strongest modifiable risk factor for first cardiovascular events in T1D, with a hazard ratio of 1.38 per 1% higher HbA1c. The crude 30-year cumulative incidence of at least one cardiovascular event in DCCT/EDIC was 16.6%.
Modelled, deterministic scenario (no treatment intensification, proportional hazards held over 30 years, single-cohort point estimate from Bebu 2020):
- A sustained 3 mg/dL higher mean glucose (~0.1% HbA1c) compounds to roughly a 3 to 4% relative and ~0.5% absolute increase in 30-year first cardiovascular event risk.
- A sustained 8 mg/dL higher mean glucose (~0.3% HbA1c, the upper bound of the OP5 simplified bolus non-inferiority margin) compounds to roughly a 9 to 10% relative and ~1.4% absolute increase.
The compounding direction (small persistent gaps matter over decades) is robust. The absolute numbers depend on whether the gap is genuinely sustained, the assumed hazard ratio (Bebu 2020 1.38 per 1% HbA1c is a single point estimate from one cohort), and competing risk assumptions. Use the figures as a sense of scale, not a prediction.
This is the structural reason a 3 mmol/mol mHGI boundary deserves to be treated as clinically real. A 3 mmol/mol HbA1c gap, sustained over a T1D lifetime, is not a rounding error. It is a six-figure savings gap in cardiovascular event terms, paid out over decades. Taleb would call this the antifragility test: the small, consistent exposure that looks harmless in any single quarter compounds into something that defines your trajectory. The Via Negativa principle applies directly; removing a persistent 3 mmol/mol overshoot matters more than adding a new therapy.
For clinicians and reviewers, GNL working analysis
Why a 2 percentage point TIR difference matters when sustained over a lifetime. Non-inferiority claims in real-world AID-system literature often accept a TIR margin of 3 percentage points (or higher) alongside a mean-glucose margin of 8 mg/dL, treating the two as roughly equivalent. They are not. Under the best long-term datasets we have (DCCT/EDIC, Bebu 2020), even a sustained 2 percentage point TIR difference compounds over a 30 to 40 year T1D lifetime into a clinically meaningful absolute cardiovascular risk gap, with the directional principle reproducible across the conversion chain.
Methods assessed (GNL working analysis, unpublished)
- Real-world AID-system cohort, ≥12 months follow-up, paired CGM and HbA1c
- TIR and mean glucose differences across phenotypes within the same AID system
- Conversion chain: Beck 2019 (TIR-to-HbA1c slope), ADAG (HbA1c-to-mean-glucose), Bergenstal 2018 (GMI)
- Lifetime risk projection via DCCT/EDIC hazard ratio (Bebu 2020: HR 1.38 per 1% HbA1c, 16.6% 30-year cumulative first CV event incidence)
Findings (modelled, deterministic, no-intervention scenario)
- Sustained 2 pp TIR gap (~3.8 mg/dL mean glucose, ~0.13% HbA1c) → ~4 to 5% relative and ~0.7 pp absolute increase in 30 to 40 year first CV event risk
- Sustained 3 pp TIR gap (~5.7 mg/dL, ~0.2% HbA1c) → ~7% relative and ~1.1 pp absolute increase
- Sustained 8 mg/dL mean-glucose gap (~0.3% HbA1c) → ~10% relative and ~1.4 pp absolute increase
- Direction is robust across reasonable parameter choices; absolute numbers depend on whether the gap is genuinely sustained, the assumed hazard ratio, and competing risk assumptions
Non-inferiority should be a graded trade-off framed in lifetime exposure terms, not a binary pass/fail compared against the easier of two thresholds. The structural argument is mostly an ergodicity argument (cumulative-exposure paths matter for individuals); the Skin-in-the-Game flavour is around how target-setting decisions are made by reviewers and editors. See Part 5 for the full ergodicity critique.
Unpublished. Full dataset and methods available on request from john@theglucoseneverlies.com. Manuscript in preparation.
Critique built on John Pemberton’s working real-world dataset analysis (anonymised, manuscript in preparation), DCCT/EDIC (Bebu 2020 hazard ratios), Beck 2019 (TIR-to-HbA1c slope), and ADAG (HbA1c-to-mean glucose conversion). A methodological note for reviewers: GMI is sometimes used as the non-inferiority anchor in real-world analyses where ADAG would be the methodologically correct conversion. Critical appraisal in T1D research has to interrogate the conversion chain, not accept the headline number.
Before you use this matrix: is your HbA1c telling the truth?
The matrix below assumes your HbA1c reliably reflects your glucose exposure. For most people it does. But HbA1c is not a perfect measurement, and in some people it is distorted by conditions unrelated to glucose or glycation biology.
Conditions that can make HbA1c unreliable:
- Iron deficiency anaemia: can falsely raise HbA1c, making glucose control appear worse than it is.
- Vitamin B12 or folate deficiency: can falsely raise HbA1c through altered red blood cell turnover.
- Haemoglobin variants (HbS, HbC, HbE; including sickle cell trait): can raise or lower HbA1c depending on the laboratory assay method, producing results that do not reflect glucose at all.
- Chronic kidney disease: shortened red blood cell lifespan can falsely lower HbA1c.
- Haemolytic anaemias: any condition that accelerates red blood cell destruction shortens the glycation window and can falsely lower HbA1c.
- Recent blood transfusion: introduces donor haemoglobin with a different glycation history, disrupting the 90-day window.
These are analytical interferences, distinct from the biological glycation variation (HGI) this guide covers. If your HbA1c and GMI disagree, the first clinical step is to rule out these analytical causes before attributing the gap to glycation biology (Lenters-Westra et al, 2025, Diabetic Medicine).
If any of these conditions apply to you, your HbA1c may not reflect your true glucose exposure, and the personalised targets below may not apply. Your diabetes care team can check whether your HbA1c is analytically reliable before you interpret it through the glycation lens.
This guide covers the 20% of things that will get you 80% of the way there. The remaining nuance, the individual context that determines whether this framework applies to you specifically, can only come from a skilled clinician who knows your history, your blood results, and your circumstances. The matrix is a discussion tool, not a prescription.
The full personalised TIR target matrix
Working GNL framework, Grade D, peer review pending. The numbers below are approximate; thresholds may shift as the Pemberton-Chalew mHGI manuscript is finalised. This is for discussion with your diabetes care team, not for autonomous target changes.
| Low glycator (mHGI < -3 mmol/mol) | Average glycator (mHGI -3 to +3) | High glycator (mHGI > +3) | |
|---|---|---|---|
| Zone P Stress-tested only: Dexcom G6, G7, FreeStyle Libre 2, 3 | Steady P ~60% TIR to ~53 mmol/mol (7.0%) TBR ceiling <4% | Standard P ~70% TIR to ~53 mmol/mol (7.0%) TBR ceiling <4% | Stretched P ~75% TIR to ~53 mmol/mol (7.0%) TBR ceiling <4% |
| Zone B Stress-tested only: Medtronic Simplera, Guardian 4 | Steady B ~65% TIR to ~53 mmol/mol (7.0%) TBR ceiling <4% | Standard B ~75% TIR to ~53 mmol/mol (7.0%) TBR ceiling <4% | Stretched B ~80% TIR to ~53 mmol/mol (7.0%) TBR ceiling <4% |
Each cell shows the approximate TIR you would need on that device, given that biology, to land at the consensus HbA1c target of around 53 mmol/mol (7.0%). The international 70% TIR target sits in one cell only: Standard P. The mHGI thresholds (±3 mmol/mol) and the TIR cell numbers are working values from the Pemberton-Chalew framework (manuscript under peer review, ADA 2026 poster accepted) and may shift slightly as the manuscript is finalised; the categories matter more than the exact decimals. The TBR ceiling of under 4% is the international consensus (ATTD 2019, ADA 2024) and is non-negotiable across every cell. The matrix never trades hypoglycaemia for higher TIR. If a cell’s TIR target cannot be reached without crossing the TBR ceiling, the target is wrong for you; review with your diabetes care team. The Pemberton 2025 ethnicity finding showed exactly that risk: the Black ethnic group experienced more time below range when managed to the same HbA1c target as peers despite different biology. The matrix’s TBR ceiling is the corrective. Devices on the matrix are limited to those with publicly available head-to-head accuracy data covering dynamic glucose conditions (Pemberton 2026, Sanfilippo 2025, Eichenlaub 2025, Freckmann 2025). The IFCC stress protocol (Pleus 2025) has been published; no manufacturer has yet completed formal certification under it. Roche SmartGuide is calibrated to capillary glucose (consistent with Zone P architecture) but does not yet have comparable head-to-head dynamic data; it cannot be placed on the matrix until it does. Eversense (implantable) is excluded pending sufficient comparative data. The Zone B vs Zone P offset shown here uses a central estimate of ~5 percentage points TIR; head-to-head accuracy data places the upper bound nearer 10 percentage points (CGM Pack 1 head-to-head dataset), so individual variation may be larger than the matrix suggests.
If your CGM is not on the matrix yet (Roche SmartGuide, Eversense, others)
The matrix only names sensors with publicly available head-to-head accuracy data covering dynamic glucose conditions. Other CGMs are not on it because the head-to-head evidence to place them honestly is not yet published, not because they are bad devices.
- Roche SmartGuide is aligned to capillary glucose, which is consistent with Zone P architecture. Until it has comparable head-to-head dynamic accuracy data published, it cannot be assigned to a matrix cell for individual risk prediction.
- Eversense (implantable) is excluded pending sufficient comparative data.
- Other consumer CGMs entering the market: same gate. Head-to-head dynamic data first, then matrix placement.
What you can still do today. The mHGI half of the framework applies to any CGM user. You can compute your glycator status and discuss what it means with your diabetes care team using the manual method in Part 3. You just cannot yet read off a Zone-adjusted TIR cell for your specific device.
Why IFCC certification must become mandatory internationally
A CGM can look perfectly accurate at steady state and still systematically over- or under-read during meals, when glucose is rising fast. The IFCC stress protocol (Pleus et al., 2025) deliberately drives the rate of glucose change above the threshold (mean rate of change of at least 0.06 to 0.07 mmol/L/min in at least 7.5% of the data) where calibration lag is exposed. One practical route to achieving that rate is a meal challenge taken without insulin so that the post-meal spike is large enough to stress the sensor’s response. The protocol is published; no manufacturer has yet completed formal certification under it. Until they do, the field relies on independent head-to-head accuracy studies to approximate the same insight, which is what the matrix’s device list rests on.
The GNL position. Formal IFCC certification under Pleus 2025 must become mandatory for CGM regulatory clearance internationally. Without it, the field cannot honestly classify devices for individual risk prediction; manufacturers can publish steady-state accuracy and the conversation stops there, even though the post-meal phase is exactly where the high-glycator and high-variability T1D users carry their excess risk. This is the single biggest lever the regulatory community holds for moving from ensemble glucose targets to individual risk prediction. Until certification is mandatory, the matrix above will only ever cover the small handful of devices whose head-to-head data has been independently published.
Why this is a manufacturer ask, not a manufacturer indictment. Roche SmartGuide is a well-engineered device; it is on the right side of capillary alignment. The point is not that it is bad. The point is that the field has reached a stage where accuracy claims for individual risk prediction need to be earned via head-to-head dynamic data, not assumed from steady-state performance. Every CGM manufacturer can submit to formal IFCC certification; we are asking the regulators to require it.
Six worked examples, one per cell
Steady P, low glycator on Dexcom G6/G7 or Libre 2/3
“My TIR is 62%, my HbA1c is 50 mmol/mol. My care team is asking me to push for 70%. Should I?”
If your mHGI sits at, say, -4, your biology produces lower HbA1c for the same glucose. 62% TIR landing at 50 mmol/mol is consistent with that. Pushing for 70% TIR would likely take your HbA1c into the low 40s, which may not be desirable and may risk more hypoglycaemia. The discussion with your care team is whether the standard target is the right one for your biology.
Standard P, average glycator on Dexcom G6/G7 or Libre 2/3
“My TIR is 70%, my HbA1c is 53 mmol/mol. Both targets met.”
This is the cell the consensus was designed around. The standard interpretation applies. No adjustment needed.
Stretched P, high glycator on Dexcom G6/G7 or Libre 2/3
“My TIR is 70% but my HbA1c keeps coming back at 60 mmol/mol. What is going wrong?”
If your mHGI sits at, say, +6, you are glycating faster than average. 70% TIR is genuinely producing the glucose pattern it should, but your biology converts that exposure into more glycated haemoglobin. On the GNL framework, the standard 70% target may not be enough for you if HbA1c-mediated complication risk is what you care about. One conversation worth having with your care team: whether ~75% TIR is a reasonable goal for you (often AID-led, sometimes with adjunctive therapy where clinically indicated), and whether your HbA1c can be interpreted through this lens rather than your insulin pushed up to chase a target your biology may not reach at standard TIR.
Steady B, low glycator on Simplera / MiniMed Guardian 4
“My TIR is 65% on the new sensor, my HbA1c is 50 mmol/mol.”
Your underlying TIR is closer to 60% (Zone B reads about 5 percentage points higher than Zone P), and your biology also flatters your HbA1c. Both effects align. 65% TIR on a Zone B device for a low glycator is roughly equivalent to 60% on Zone P for an average glycator. The consensus 70% may be more than your biology needs; the device makes that gap look smaller than it is.
Standard B, average glycator on Simplera / MiniMed Guardian 4
“I switched from Libre to Simplera and my TIR jumped from 70% to 75% with no real change in my management. Have I improved?”
No, you have changed device. Zone B reads about 5 percentage points higher than Zone P for the same physiological glucose. Your biology has not changed; your HbA1c will be similar. The matrix tells you: 75% on a Zone B device for an average glycator is the equivalent of 70% on Zone P. Both land at around 53 mmol/mol HbA1c.
Stretched B, high glycator on Simplera / MiniMed Guardian 4
“My TIR is 75%, my HbA1c is 60 mmol/mol. Same disconnect as before.”
You have two effects working together: a Zone B device that reads about 5 percentage points high, and biology that glycates faster than average. On this framework, ~80% TIR on a Zone B device would be the figure that lands at around 53 mmol/mol; whether that is the right target for you is a conversation with your care team. It is the highest-target cell in the matrix and the one most likely to need AID system support and (where clinically indicated) adjunctive therapy to reach without driving hypoglycaemia.
What to do with your cell
If your target moved down from 70% (Steady P or Steady B)
You are not under-managing. Your biology produces lower HbA1c for the same glucose. The conversation with your care team is whether your current target is the right one, or whether it is harder than your biology requires. Pushing harder may carry costs (hypoglycaemia, cognitive load, time) worth weighing against the additional benefit you would expect.
If your target stayed at 70% (Standard P)
The standard interpretation works for you. Use HbA1c and TIR as you normally would. The matrix is informative but does not change your day-to-day numbers.
If your target moved up (Standard B, Stretched P, Stretched B)
You are likely working harder than your TIR number suggests. Two practical levers exist, both worth discussing with your care team:
- AID systems (automated insulin delivery) can push TIR higher without proportional increases in hypoglycaemia. The AID Guide explains how each system gets there.
- Adjunctive therapy (GLP-1, GIP) can reduce insulin demand and glycaemic variability in selected patients with insulin resistance. Discuss eligibility and tradeoffs with your care team.
The other thing the matrix changes: how you interpret your HbA1c relative to your TIR. If your HbA1c reads higher than peers with similar TIR, glycator biology is one likely explanation worth discussing with your care team alongside other possibilities (recent illness, CGM coverage, assay variation). The IOB Trade-Off piece explains how four AID systems trade IOB risk against TIR gain in different ways.
What to discuss with your diabetes care team
- Bring at least 3 paired HbA1c and 90-day CGM mean glucose values, taken over a minimum 9-month period. Show your mHGI calculation and the cell of the matrix you sit in. (A single bad week is not a glycator phenotype; the n≥3 over ≥9 months gate is the noise filter.)
- Ask whether the standard 70% TIR target is the right one for your biology, given your mHGI category.
- If you are a high glycator, ask whether your clinic is open to interpreting your HbA1c through the HGI lens (rather than treating it as the same number-for-number target as everyone else). The Pemberton 2025 ethnicity work and the broader HGI literature support this.
- If you are a low glycator on a tight target, ask whether your hypoglycaemia exposure is proportionate to the benefit you are getting.
- If you wear a Zone B device, make sure your TIR is being interpreted on the right scale (not directly compared with consensus targets that were set on Zone P).
The mHGI framework is in the peer-review pipeline (Chalew, Pemberton et al., ADA 2026 poster accepted; manuscript in revision). Your care team may not have come across it yet. The hub page links to the underlying evidence (Lachin 2007, McCarter 2004, Hempe 2024, Pemberton 2025) which is established and citeable.
Where to go next
- CGM Guide: full device-by-device classification and the Zone framework in detail.
- AID Systems Guide: how each AID system gets your TIR higher without driving hypoglycaemia.
- The IOB Trade-Off: how Control-IQ, MiniMed 780G, CamAPS FX and Omnipod 5 each take a different bet on insulin.
- IOB Guide: the mechanism-first guide to insulin on board.
- Exercise Guide: how activity interacts with insulin exposure and glucose.
- GNL Explorers Hub: all interactive tools.
This guide is educational. The personalised TIR matrix is derived from the GNL evidence base (DCCT, Lachin, McCarter, Hempe, Pemberton, Bergenstal) and the Pemberton-Chalew mHGI framework (under peer review; ADA 2026 poster accepted). It is not yet codified in mainstream clinical guidelines. The numbers are approximate, calibrated against the consensus 70% TIR / 53 mmol/mol HbA1c anchor; individual variation exists. Discuss your personalised target with your diabetes care team before changing your management.
Evidence cited: DCCT 1993; Braffett 2025; Lachin 2007, 2022; McCarter, Hempe and Chalew 2004; Hempe and Hsia 2022; Hempe 2024; Pemberton, Uday, Krone, Fang, Chalew 2025 (BMJ Open DRC); Bergenstal 2018 (GMI); Pemberton 2026 DOM International Clinical Opinion (CGM Zone framework); Bebu 2020 (DCCT/EDIC CVD risk factors); Pleus 2025 (IFCC stress protocol); Pemberton 2026, Sanfilippo 2025, Eichenlaub 2025 (three-CGM performance), Freckmann 2025 (head-to-head accuracy data); Chalew, Pemberton et al. 2026 (ADA poster, mHGI); Lenters-Westra et al. 2025 (HbA1c-GMI discordance, analytical interference framework, Diabetic Medicine).
Author note. John Pemberton (GNL founder) is lead author on Pemberton, Uday, Krone, Fang, Chalew 2025 (BMJ Open Diabetes Research and Care) and co-author on the Chalew, Pemberton et al. 2026 mHGI manuscript currently under review. Both papers are load-bearing in this matrix. Declared so the conflict of interest is visible to the reader.