Continuous glucose monitors produce hundreds of readings a day. Studies need the right summary metrics, enough valid wear time, and the context that explains the curves: meals, activity, medication. Capture holds CGM metrics, wear periods and participant logs next to the rest of the study data.
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Time in range 70-180
74%
Time below 70
2.1%
Data sufficiency
93%
What matters in CGM studies
Study design
A CGM endpoint is calculated over a wear period, usually around 14 days before a visit. If a sensor falls off, fails or is removed, the period may not have enough data to be valid. Studies define in advance what counts as sufficient data, track sensor start and end dates, and plan what happens when a period is incomplete, such as extending wear or using the next period.
Glucose curves also need context. A spike after a meal means something different from one after a missed insulin dose. Short participant logs of meals, activity, illness and hypoglycaemia symptoms, completed on their phone, explain what the numbers show and support exploratory analyses.
Raw CGM readings usually stay in the manufacturer's platform or a dedicated data repository, exported for analysis. The study database holds device and sensor identifiers, wear periods, summary metrics and the link to the raw data, so every reported metric can be traced. See digital biomarker validation study software for the same pattern with other devices.
Daily log
Wednesday · CGM wear day 6
Meals today
Exercise today
Hypoglycaemia symptoms
Sensor still attached
CGM metrics
Record each wear period's metrics as numeric fields with units and range checks: time in range, time below and above range, mean glucose, GMI, coefficient of variation and percentage of readings captured. Sensor identifiers and start and end dates sit on the same form, so every metric has its source period.
Edit checks / auto-queries
2Type
Range High
Operator
Greater than
Value
180
Priority: High
Type
Range Low
Operator
Less than
Value
80
Priority: Normal
Query raised automatically
Value 192 violates limit (180). Please verify.
Try both in the free sandbox.
Consensus metrics
| Metric | Definition | Common target (most adults with diabetes) |
|---|---|---|
| Time in range | 70 to 180 mg/dL (3.9 to 10.0 mmol/L) | More than 70% |
| Time below range, level 1 | Below 70 mg/dL (3.9 mmol/L) | Less than 4% |
| Time below range, level 2 | Below 54 mg/dL (3.0 mmol/L) | Less than 1% |
| Time above range | Above 180 mg/dL; above 250 mg/dL | Less than 25%; less than 5% |
| Coefficient of variation | Glycaemic variability | 36% or less |
| Data sufficiency | Readings captured over the period | At least 70% over about 14 days |
Targets differ for older or high-risk adults, pregnancy and children. Use the targets and definitions in your protocol.
Beyond diabetes
People without diabetes are increasingly wearing CGMs in research on diet, weight management, sleep and exercise. These studies often focus on post-meal glucose responses rather than time in range, which makes accurate meal timing and composition the critical data. Standardised test meals at defined times, logged precisely, produce the most reliable comparisons.
For nutrition studies, see clinical trial software for nutrition research, and for glycaemic logs and HbA1c, the HbA1c and glycemic log template.
Study build
Consensus metrics and targets in the protocol.
Length, timing before visits and sufficiency threshold.
Whether participants see their readings.
Sensor IDs, start and end dates, failures.
Meals, activity, illness and symptoms.
Where raw readings live and how they link to the study.
The percentage of CGM readings between 70 and 180 mg/dL (3.9 to 10.0 mmol/L). More than 70% is a common target for most adults with diabetes.
Consensus recommends about 14 days with at least 70% of possible readings captured.
Studies record CGM summary metrics, sensor identifiers and wear periods as structured fields. Raw readings usually stay in the device platform and are exported for analysis.
CGM where participants cannot see their readings, used to measure glucose without changing behaviour.
Yes. Daily logs open from a secure link with no app, with windows and reminders.
Yes, in the free sandbox with every feature.
Keep exploring
Wear periods, metrics and logs in one study. Free sandbox.