| ISO 15197:2013 accuracy criterion |
For glucose-meter results compared with a reference method, at least 95% of results should fall within the applicable accuracy limits, and at least 99% should fall within Consensus Error Grid zones A and B. |
For reference glucose values below 100 mg/dL, the limit is ±15 mg/dL. For values of 100 mg/dL or higher, the limit is ±15%. |
Confirm that the published test used the actual ISO 15197:2013 procedure and an independent reference method. |
Useful benchmark |
| Meaning of MARD |
Mean Absolute Relative Difference is the average absolute difference between device readings and a reference value, expressed as a percentage. |
A lower MARD generally indicates closer average agreement, but MARD alone does not prove that every reading is safe or that ISO requirements have been met. |
Look for the study population, number of paired readings, glucose range, reference method, and confidence interval. |
Important, but not sufficient |
| Smartwatch using only optical signals |
Optical signals such as photoplethysmography or near-infrared measurements can be affected by skin properties, motion, temperature, hydration, sweat, tattoos, and ambient light. |
There is no single MARD value that applies to all optical smartwatch systems. A product-specific, peer-reviewed clinical result is required. |
Reject claims that provide only a laboratory correlation, app screenshots, or a “non-invasive” label without paired clinical glucose data. |
Do not treat as a glucose meter without validation |
| Smartwatch with no glucose-sensing component |
Heart rate, sleep, activity, stress, and calorie sensors do not directly measure blood glucose. |
MARD and ISO 15197:2013 accuracy cannot be calculated for glucose if the watch does not produce a glucose measurement from a validated sensor. |
Check whether the watch actually measures glucose or merely displays manually entered values or data imported from another device. |
Not a glucose monitor |
| Non-invasive prototype or research system |
Early research results may demonstrate feasibility under controlled conditions but may not represent everyday performance. |
Reported MARD values are not interchangeable unless the devices use comparable reference methods, glucose ranges, sampling schedules, and study populations. |
Require a full clinical protocol, an adequate number of participants, hypoglycemic and hyperglycemic data, and results from free-living conditions. |
Promising only if independently validated |
| Minimally invasive interstitial-fluid CGM |
These systems use a sensor inserted under the skin and measure interstitial glucose rather than directly measuring blood glucose. |
MARD is commonly reported for CGM systems, but ISO 15197:2013 is not a complete substitute for a CGM-specific clinical evaluation. Interstitial readings may lag behind blood glucose during rapid changes. |
Review sensor warm-up time, calibration requirements, lag information, alert performance, wear duration, and clinical-study details. |
More clinically established, but not non-invasive |
| Reference method quality |
Accuracy results depend on the method used as the comparison standard. |
Capillary or venous samples should be tested with a recognized laboratory-quality reference method. A comparison against another consumer device is not adequate proof. |
Look for the reference analyzer, sample handling procedure, duplicate testing, and time synchronization between readings. |
Essential evidence check |
| Glucose range coverage |
An average result can look good when most readings are in the normal range while performance is poor during low or high glucose events. |
A credible study should report results across low, normal, and high glucose ranges rather than only reporting one overall average. |
Check separate results for hypoglycemia, euglycemia, and hyperglycemia, including the number of observations in each range. |
Require range-specific results |
| Trend and alarm performance |
A glucose trend estimate and a glucose concentration are different functions. An attractive graph does not prove numerical accuracy. |
MARD does not measure missed alarms, false alarms, rate-of-change accuracy, or time spent in clinically relevant zones. |
Check sensitivity, specificity, alarm delay, false-alert frequency, and performance during exercise, meals, and rapid glucose changes. |
Assess separately from MARD |
| Independent clinical evidence |
Manufacturer testing may be useful, but independent studies reduce the risk of selective reporting. |
The strongest evidence includes a prospective study, a prespecified protocol, a clearly described reference method, and peer-reviewed publication or regulatory documentation. |
Search for an identifiable study rather than relying on testimonials, influencer demonstrations, or unexplained accuracy percentages. |
Prefer independently verified data |
| Safety for treatment decisions |
An unvalidated smartwatch estimate should not be used alone to change insulin, diabetes medication, or emergency treatment. |
No MARD value by itself establishes clinical safety. ISO-style numerical accuracy, error-grid analysis, and real-world safety evaluation are separate requirements. |
Use a validated glucose meter or clinically authorized CGM when treatment decisions depend on the reading, especially when symptoms and displayed values disagree. |
Never rely on an unvalidated estimate alone |