CGM Metrics Calculator: GMI, Time in Range & Variability

Paste your CGM glucose readings to get the standardised metabolic metrics: GMI, time in range and %CV.

  • 2 cited sources
  • Calculates in your browser

Paste your glucose readings (one per line or comma-separated).

Glucose unit

1 readings detected

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Appears here as you enter your details. No demo figures — the number is yours, or it is nothing.

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Methodology

This tool computes the four standardised continuous-glucose-monitoring (CGM) metrics from the international consensus, entirely in your browser:

  • Mean glucose, the simple average of your readings.
  • Glucose Management Indicator (GMI), an estimate of HbA1c from CGM data: GMI(%) = 3.31 + 0.02392 × mean glucose (mg/dL) (Bergenstal et al., Diabetes Care 2018). Readings in mmol/L are converted to mg/dL first (× 18.0182).
  • Glucose variability (%CV), standard deviation ÷ mean × 100. The consensus stability target is below 36%.
  • Time in range (TIR), the percentage of readings between 3.9 and 10.0 mmol/L (70 to 180 mg/dL), the consensus target range (Battelino et al., Diabetes Care 2019). We also show time below and above range.

Paste your readings (one per line, or comma-separated; rows like timestamp, glucose work too. We take the glucose value from each line).

Interpreting your result

For people managing diabetes, these are the numbers clinicians actually use: a common target is at least 70% time in range with %CV below 36%, and GMI gives a CGM-based estimate of HbA1c between lab tests. Two averages that look identical can hide very different variability, which is why %CV sits next to the mean.

If you don’t have diabetes, read this carefully. These metrics were developed for diabetes care. The popular idea that healthy people should chase a “flat” glucose line is not well supported. There is limited evidence that flattening normal post-meal rises in a metabolically healthy person improves health outcomes. Minor spikes after meals are normal physiology. Use these numbers as interesting self-tracking data, not as a diagnosis or a target to optimise anxiously.

Limitations

  • GMI is an estimate of HbA1c from glucose, not a lab measurement; the two can differ, especially with conditions affecting red blood cells.
  • Metrics are only as good as the data: short recording windows, sensor warm-up artefacts and compression lows can distort them.
  • Targets (time-in-range goals, acceptable variability) are individual and set with a clinician. This tool reports the numbers, it does not prescribe goals.
  • This is educational self-tracking, not a medical test. Anything concerning belongs with your doctor.

Sources

Pull the receipts, 2 cited sources

FitTools · sources

  1. 01 Bergenstal RM, et al. Glucose Management Indicator (GMI): a new term for estimating A1C from CGM. Diabetes Care 2018;41:2275-2280
  2. 02 Battelino T, et al. Clinical targets for continuous glucose monitoring data interpretation: recommendations from the international consensus on time in range. Diabetes Care 2019;42:1593-1603

Every formula cited ✓

Frequently asked questions

What is GMI?
The Glucose Management Indicator estimates what your HbA1c would be, from your average CGM glucose. It uses the published formula GMI(%) = 3.31 + 0.02392 × mean glucose (mg/dL). It is an estimate from CGM data, not a lab HbA1c.
What is a good time in range?
The international consensus target for many people with diabetes is at least 70% of readings between 3.9 and 10.0 mmol/L (70 to 180 mg/dL). Targets are individual and set with your clinician; this tool reports the number, it doesn't prescribe a goal.
What does %CV tell me?
The coefficient of variation measures how much your glucose swings around its average. The consensus stability threshold is below 36%, and lower means steadier glucose. It is reported alongside the average because two people with the same average can have very different variability.
I don't have diabetes: should I chase a flat line?
Honestly, the evidence is thin. For people without diabetes, there's limited proof that flattening normal post-meal glucose rises improves health outcomes. These metrics were designed for diabetes management; treat them as interesting data, not a health verdict.
Is my data private?
Yes. Everything is computed in your browser. Your glucose readings are never uploaded or stored anywhere.

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