How to Read Your CGM Data: Time in Range Explained

The first few days with a sensor are usually spent scanning it constantly — before meals, after meals, whenever you remember. It is genuinely interesting, and it is also the least valuable thing a CGM does. Any glucometer can tell you a number right now. What a sensor gives you that nothing else can is the summary: fourteen days of glucose seen all at once, as a shape rather than a scatter of isolated readings. That summary is where the money you paid actually goes, and most people never open it.

In the LibreView or LibreLink app this is the glucose report, sometimes labelled the Ambulatory Glucose Profile. Whatever it is called on your screen, four or five numbers on it carry almost all the meaning.

Time in range: the number to look at first

Time in range is simply the percentage of the day your glucose sat between 70 and 180 mg/dL. It is a fundamentally different question from "what is my sugar" — it asks how much of your life is spent in a safe band, which is closer to how diabetes actually affects you. In 2019 an international panel published agreed targets for these metrics in Diabetes Care (opens in a new tab), and those numbers are what your app is quietly comparing you against.

Two things about this table are worth saying plainly. The first is that 70% is a target, not a pass mark — if your report says 45%, that is information about where to start, not a verdict on you. The second is that the low-glucose rows come first in priority even though they look small. A report showing 75% time in range and 6% below 70 is not a better report than one showing 60% in range with no lows; it is a report with a safety problem sitting inside a good-looking average.

The reason time in range is worth chasing at all is that it moves with the outcome you already track. Reviews of the consensus data describe roughly a 0.8% change in HbA1c for every 10% change in time in range (opens in a new tab). Ten percent is two and a half hours a day — the difference one changed breakfast or one evening walk can plausibly make.

GMI is not your HbA1c

Your report will also show a Glucose Management Indicator, or GMI — a percentage that looks exactly like an HbA1c result and is very easy to mistake for one. It is not a lab test. It is an estimate calculated from your average sensor glucose using a formula derived from just over 500 adults, and it can differ meaningfully from what your blood actually shows.

How meaningfully? In the original study behind the metric, 28% of participants had a gap of half a percentage point or more between their GMI and their laboratory A1C, and later studies found discordance rates ranging from 26% to 68% (opens in a new tab) depending on the group studied. The gap is not a sensor malfunction — HbA1c depends on how long your red blood cells live and how glucose binds to haemoglobin, which varies from person to person and is affected by conditions like anaemia that are common here. Treat GMI as a rough progress indicator between lab visits, not as a replacement for the test your doctor orders.

Reading the daily graph

Below the metrics sits the part most people scroll past: a single 24-hour graph built from all fourteen days stacked on top of each other, with a shaded band showing the spread. You are not looking for individual spikes here. You are looking for the times of day where the whole band sits high, or where it dips, because those repeat — and a pattern that repeats is something you can change.

Three places on that graph tend to hold the answers. The overnight stretch, roughly midnight to 6am, should be a fairly flat line; a slow climb toward morning or an unnoticed dip at 3am both explain a lot of confusing fasting readings. The two hours after your usual meals show what your actual portions do, which is the window a finger-prick almost never catches. And the late afternoon, around the time chai and something fried tends to appear, is where many Pakistani reports show a rise nobody had suspected.

Turning a pattern into a change

A fourteen-day report usually reveals three or four things at once, and the instinct is to fix all of them. That rarely works, because when everything changes together you cannot tell what helped. Pick the single biggest slice of time outside range, change one thing about it, and let the sensor tell you whether it worked — you already have a measurement running.

That might mean swapping the second roti at dinner for a bowl of salad and watching whether the 10pm plateau flattens. It might mean walking for twenty minutes after lunch instead of after dinner. It might mean nothing more than eating your usual meal in a different order. The point is not the specific change; it is that you get an answer within two days instead of waiting three months for the next HbA1c.

Do you have enough data to conclude anything?

This matters especially if you are using a single sensor as a one-off investigation, which is how most people in Pakistan can afford to use one. The consensus panel set a floor: at least 14 days of data, with the sensor active at least 70% of that time, before drawing conclusions. If your sensor fell off on day six, or you went a full day without scanning on a Libre 2 — which stores only eight hours of readings between scans (opens in a new tab) — your percentages are describing a partial week, not your life.

Incomplete data is still useful for spotting an obvious repeating pattern. It is just not a number to build a treatment decision on, and it is worth telling your doctor which it is when you hand over the report.

Keep the story after the sensor comes off

A sensor shows you fourteen days; your log carries what you learned into the months afterwards. Recording meals, medicines and readings together in Diatic is what makes the next report comparable to this one.

Start logging (opens Diatic on Google Play in a new tab)