Guide series

What Gets Measured Gets Managed: The HbA1c and Time in Range Guide

The international consensus says aim for 70% time in range. But 70% is an ensemble target, derived from the average glycator on a small set of CGMs in randomised trials. Your personalised target depends on two things most people never check: your CGM calibration zone and your glycation biology. This guide moves you from the ensemble average to an individual risk prediction.

Type 1 Diabetes HbA1c Time in Range Ensemble to individual mHGI

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Not sure what your HbA1c and time in range are really telling you? Ask Grace and she will take you to the best information.

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What this guide is about

In Type 1 diabetes, two numbers dominate every clinic conversation: HbA1c and time in range. Both are useful. Neither tells the full story alone. And most people assume they are straightforward when they are not.

This guide majors in the majors. It covers two questions that together explain most of the confusion, most of the discordance, and most of the frustration people experience when their numbers do not match what they expect.

The two questions at the centre of this guide

Question 1: Is your time in range what you think it is? Different CGM devices read in different calibration zones. 70% TIR on one device is not the same as 70% on another. Until you know which zone your device reads in, you do not know what your TIR number means relative to someone else’s.

Question 2: Are you a high, low, or average glycator? Some people’s biology attaches more glucose to haemoglobin than others, independent of their actual glucose levels. If your HbA1c runs higher than your glucose predicts, the standard 70% TIR target may not be enough for you. If it runs lower, you may be working harder than you need to.

This is written for well-informed people living with Type 1 diabetes and the clinicians who support them. It is deliberately more technical than most guides on this topic, because the nuance matters. The difference between understanding these two questions and not understanding them can be 10 to 15 percentage points in what your personalised TIR target should be.

A note on what this guide is and what it is not. This guide covers the 20% of things that will get you 80% of the way there: the two biggest sources of confusion in how HbA1c and TIR are interpreted. But HbA1c itself can be distorted by conditions unrelated to glucose (iron deficiency, haemoglobin variants, kidney disease, and others; see the caveat section below). The remaining nuance, including whether these conditions apply to you, can only come from a skilled clinician who knows your individual context. This guide is a discussion tool for your clinic appointment, not a substitute for it.

Before you use the matrix: is your HbA1c telling the truth? Iron deficiency anaemia, haemoglobin variants (HbS, HbC, HbE), chronic kidney disease, haemolytic anaemias, vitamin B12/folate deficiency, and recent blood transfusion can all distort HbA1c independently of glucose. These are analytical interferences, not glycation biology. If any apply to you, check with your care team whether your HbA1c can be interpreted at face value before applying the matrix below. Full detail and clinical workflow in Part 2.

The personalised TIR target matrix

When you combine your CGM calibration zone with your glycation biology, you get a personalised TIR target that may be quite different from the population consensus of 70%.

What is GMI? GMI (Glucose Management Indicator) is the HbA1c that would be predicted from your CGM mean glucose if you were an average glycator, calculated from the Bergenstal 2018 formula (GMI mmol/mol = 12.71 + 4.70587 x mean glucose mmol/L). HGI (Haemoglobin Glycation Index) is the gap between your measured HbA1c and your GMI: a positive HGI means you glycate faster than the average, a negative HGI means slower. mHGI is the mean of HGI across at least 3 paired HbA1c plus 90-day CGM windows over a minimum 9 months. The matrix below uses your mHGI category (low, average, high) and your CGM zone (P or B) to give a personalised TIR target.

Working GNL combination rule, Grade D. The matrix below combines Grade A and Grade B inputs (DCCT, HGI literature, GNL CGM Zone framework) using a GNL-derived rule that has not been validated against any complication endpoint. Treat as an informed discussion tool with your diabetes care team, not as personalised clinical guidance.

	Low glycator (mHGI < -3)	Average glycator (mHGI -3 to +3)	High glycator (mHGI > +3)
Zone P Dexcom G6/G7, Libre 2/3	~60% TBR <4%	~70% TBR <4%	~75% TBR <4%
Zone B Simplera, Guardian 4	~65% TBR <4%	~75% TBR <4%	~80% TBR <4%

The international consensus 70% TIR target sits in one cell of this matrix: Zone P, average glycator. Everyone else is either under-targeted or over-targeted. The TBR ceiling of under 4% (ATTD 2019, ADA 2024) is non-negotiable across every cell so the matrix never trades hypoglycaemia for higher TIR. These targets are derived from the GNL evidence base and the Pemberton-Chalew mHGI framework; they are not yet in mainstream clinical guidelines. Discuss with your diabetes care team. 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). Roche SmartGuide is calibrated to capillary glucose but not yet placed pending head-to-head data; the mHGI portion of the framework still applies. Eversense (implantable) is excluded pending data. See Part 4 for the full matrix with worked examples and the IFCC certification call.

What this means: a person with high glycation biology on a Zone B CGM device may need to achieve approximately 80% TIR to get the same HbA1c-mediated complication protection as an average glycator on a Zone P device at 70%. That is a 10 percentage point difference in what “good enough” looks like, driven entirely by biology and device choice, not by effort or adherence.

TL;DR

HbA1c is still indispensable. DCCT 1993 plus 30-year EDIC follow-up (Braffett 2025) is Grade A; HbA1c is the strongest predictor of microvascular complications. Lachin 2022 in the same dataset shows HbA1c is a stronger predictor than estimated TIR. Both are needed; neither alone is sufficient.
HbA1c is not a simple average of glucose. Two people with identical mean glucose can have HbA1c values 10 mmol/mol apart, biology not measurement error (McCarter, Hempe and Chalew 2004; Hempe and Hsia 2022). High glycators have higher complication risk at the same mean glucose (Lachin 2007 mean-glucose-adjusted analysis, plus eight follow-on studies; Part 3 walks through the methodological correction to Lachin’s title-line claim).
Ethnicity matters at the population level. In a Birmingham UK paediatric T1D cohort (n=168), Black children and young people had +4 mmol/mol adjusted HbA1c versus White and South Asian peers, independent of mean glucose, technology access, and deprivation (Pemberton, Uday, Krone, Fang and Chalew 2025). Population-level mean difference; does not predict any individual’s glycation rate.
70% TIR is an ensemble target, not a personal one. It assumes average glycation biology and a Zone P CGM. Different CGMs read 5 to 10 percentage points apart for the same physiological glucose, and your glycation biology shifts the target up or down.
Your personalised target combines both. Zone (P or B; head-to-head data only) plus glycator status (low / average / high) gives a cell on the matrix above. TBR ceiling under 4% on every cell so the matrix never trades hypoglycaemia for higher TIR.
The matrix is a discussion tool, not a prescription. Working GNL framework (Grade D combination rule, Grade A/B inputs). Use it with your diabetes care team, not in place of them.

The two things you need to know

1. Your CGM zone

Zone P or Zone B? Check the CGM Guide to find your device’s calibration zone. This tells you whether your TIR number is reading high, low, or in the middle relative to physiological glucose.

2. Your glycator status

High, average, or low? You need at least 3 paired HbA1c results matched with 90-day CGM mean glucose, taken over a minimum 9-month period. The mean difference between your measured HbA1c and your GMI tells you your glycator phenotype. The Glycator Finder below walks you through the maths; a formal GNL Explorer is deferred until peer-reviewed publication and cross-sensor validation are complete.

The full guide covers

Why 70% TIR is not the same on every CGM (Part 1)
Why HbA1c can mislead and what the glycation index means (Part 2)
How to work out your glycator status from your own data (Part 3)
The personalised TIR target matrix and what to do with it (Part 4)
The 90-day rule, ergodicity, and how Nassim Nicholas Taleb’s thinking reframes T1D risk (Part 5)

The Glucose Never Lies Explorers

Two explorers pair directly with this guide. The CGM accuracy framework determines your zone. The future mHGI calculator will determine your glycator status.

CGM Guide and Device Comparison

The five-question CGM selection framework, including accuracy zone classification (Zone A, P, B) for every device on the UK market. Start here to find your zone.

Open the CGM Guide

mHGI Glycator Finder

Enter at least 3 paired HbA1c and 90-day CGM mean glucose values, taken over a minimum 9-month period. The Finder walks you through the maths and shows your glycator status plus your personalised TIR target. This is a teaching tool for discussion with your care team, not a formal GNL Explorer; the formal Explorer is deferred until peer-reviewed publication and cross-sensor validation are complete.

Use the Glycator Finder

The principle behind this guide and the future calculator

What gets measured gets managed. But in diabetes, measuring the wrong thing, or measuring the right thing without knowing what it means for your biology, is a reliable way to manage the wrong target. This guide and the tools it pairs with exist to close that gap.

These tools are for education and discussion, not as medical instruction. Always discuss changes to your targets with your diabetes care team.

Find your personalised TIR target

Select your CGM zone, then enter at least 3 paired HbA1c and mean CGM glucose values from 90-day windows. The finder calculates your glycator status and shows your personalised TIR target.

Step 1: Select your CGM zone

Step 2: Enter your paired HbA1c and mean CGM glucose (at least 3 pairs)

Pair 1:

Pair 2:

Pair 3:

This is an educational estimate based on the Bergenstal 2018 GMI formula and the GNL two-by-three matrix. It is not a diagnostic tool. Discuss your result with your diabetes care team. The more pairs you enter (minimum 3, ideally 4 or 5), the more reliable the estimate.

How to use this guide

Work through the guide in sequence. Each part builds on the previous one. By Part 4, you will have a personalised TIR target based on your own biology and your own device.

Hub: What Gets Measured Gets Managed

The two-by-three matrix, the TL;DR, and why both HbA1c and TIR are needed. This page.

You are here

Part 1: Is Your Time in Range What You Think It Is?

CGM calibration zones explained. Zone A, P, and B. Which devices sit where. Why 70% TIR on one CGM is not 70% on another.

Open Part 1

Part 2: HbA1c, the Three-Month Average That Is Not Average

The DCCT evidence. Why HbA1c misleads in some people. High, low, and normal glycators. The ethnicity effect. The biological mechanism.

Open Part 2

Part 3: Know Your Glycator Status

The mHGI concept. How to calculate it from your own data. What it means for your target. Step-by-step worked example, plus the calculator above.

Open Part 3

Part 4: Your Personalised Target

The two-by-three matrix in full. Six worked examples, one per cell. The 3 mmol/mol boundary explained via compounding-interest. Links to the CGM Guide, AID Guide, and GLP-1 thinking. What to discuss with your care team.

Open Part 4

Part 5: How would Nassim Nicholas Taleb use HbA1c and TIR to assess T1D risk?

The 90-day rule. Why CareLink, Clarity, LibreView and Glooko default to a 14-day report and why that default is an ensemble approach to a Black Swan disease. Skin in the Game framing. Use 90 days for risk, 30 days for patterns, 14 days only after a recent change.

Open Part 5

The IOB Trade-Off

Understanding your personalised TIR target changes how you interpret your AID system’s IOB settings. The IOB Trade-Off article shows how four AID systems make different bets on insulin.

Read the IOB Trade-Off

The evidence behind this guide

This guide is built on:

The DCCT trial (1993) and 30-year EDIC follow-up (Braffett 2025): Grade A landmark evidence establishing HbA1c as the primary predictor of microvascular complications.
Lachin 2007 (DCCT secondary analysis): at the same mean glucose, high glycators had higher retinopathy and nephropathy risk. (The paper’s title states “HGI not independent” of HbA1c, which propagates a Table 2 fallacy because HGI is constructed as the residual of HbA1c minus GMI; Part 3 walks through the methodological correction in detail.)
Lachin 2022 (DCCT/EDIC): HbA1c is a stronger predictor of retinopathy than estimated TIR. Both are needed; neither alone is sufficient.
McCarter, Hempe and Chalew 2004: Biological variation in HbA1c exceeds analytical imprecision. HGI is a stable, trait-like characteristic.
Hempe and Hsia 2022, Hempe 2024: The glucose oxidative pathway (GOP) and vitamin C recycling mechanism explaining why some people glycate faster than others.
Pemberton, Uday, Krone, Fang and Chalew 2025 (BMJ Open DRC): in a Birmingham UK paediatric cohort (n=168), Black children and young people with T1D have +4 mmol/mol adjusted HbA1c versus White and South Asian peers, independent of mean glucose, technology access, and socioeconomic status. Also experience more hypoglycaemia, possibly from the “treat-to-target” trap. Population-level mean difference; does not predict any individual’s glycation rate.
Chalew, Pemberton et al. 2026 (ADA poster): The mHGI framework. GMI enables calculation of HGI and reliable classification into high and low risk phenotypes for complications.
GNL CGM accuracy framework (Pemberton 2026 DOM International Clinical Opinion; Eichenlaub 2025 three-CGM performance): Zone A, P, B calibration model applied to glycaemic metrics.

Acknowledgements

This guide is built on the shoulders of decades of research into haemoglobin glycation and its clinical implications.

Deep gratitude to Professor Stuart A. Chalew (Louisiana State University Health Sciences Center), whose work with James Hempe from 2002 onwards established the Haemoglobin Glycation Index and whose recent collaboration with GNL has produced the mHGI framework that underpins this guide. Stuart is GNL’s chief collaborator on glycation biology.

Thank you to Dr James M. Hempe (LSUHSC) for originating the HGI concept and for the brilliant mechanistic work on the glucose oxidative pathway and vitamin C recycling that explains why glycation varies between individuals.

Thank you to Dr Robert J. McCarter for the foundational 2004 paper on biological variation in HbA1c that proved this is biology, not noise.

Thank you to Dr Suma Uday (University of Birmingham) and Dr Ruth Krone (Birmingham Women’s and Children’s) for their partnership on the ethnicity research that first revealed the +4 mmol/mol HbA1c disparity in UK children with Type 1 diabetes.

And thank you to Dr Zhide Fang (LSUHSC) and Dr Ricardo Gomez (LSUHSC) for their statistical and clinical contributions to the mHGI and ADA poster work.

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 guide. The matrix and the ethnicity finding rest in part on his published and in-review work; the wider author groups are named in full above. This is declared so the conflict of interest is visible to the reader.