When a continuous glucose monitor (CGM) claims to be ‘accurate’, what does that actually mean? For patients making daily decisions about insulin dosing, food, and activity (and for clinicians interpreting those decisions) accuracy is not a marketing term. It is a clinical threshold with a precise definition, and not all devices meet it equally.
The Standard Behind the Claim
Accuracy in CGM is most commonly measured using Mean Absolute Relative Difference (MARD) which is a statistical measure of how closely a device’s readings align with a reference blood glucose value. The lower the MARD percentage, the more closely the CGM reading tracks the actual glucose level in the blood.
But MARD alone does not tell the full story. The metric that matters most for clinical decisions is the percentage of readings that fall within 20% or 1.1 mmol/L of the reference value, whichever is greater. This is the standard used to determine whether a device qualifies as non-adjunctive, meaning its readings can be used to make insulin dosing decisions without a confirmatory finger-prick test.
Non-adjunctive status is not a given. It requires rigorous clinical validation and is awarded only to devices that consistently meet this threshold across a range of glucose levels, times of day, and wear periods. It is, in effect, the gold standard for CGM accuracy.
How Dexcom One+ Performs Against This Standard
Dexcom One+ achieves more than 95% of readings within the 20/20 accuracy threshold at glucose values above 5.5 mmol/L and greater than 90% at lower glucose values, where accuracy is harder to maintain. This performance has been validated across more than 77,000 data points, including paediatric populations, making it one of the most comprehensively studied CGM sensors available.
This level of accuracy carries a direct clinical implication: clinicians and patients can make confident decisions from the data they see on the display, without needing to cross-reference a glucometer. For patients who have historically relied on multiple daily finger-prick tests, this represents a meaningful shift in how diabetes management feels and functions.Why CGM Reads Interstitial Fluid, Not Blood
There is an important physiological nuance that often goes unexplained. CGM devices (including Dexcom One+) measure glucose in interstitial fluid, the fluid between cells in subcutaneous tissue, not glucose in blood directly. Because glucose moves from blood into interstitial fluid, there is a natural physiological lag of approximately 5 to 15 minutes between blood glucose and interstitial glucose readings.
This is not a flaw. It is an inherent characteristic of all interstitial CGM technology. Patients and clinicians who understand this lag can interpret CGM data more accurately, particularly during rapid glucose excursions, and make better-informed decisions as a result. Dexcom’s trend arrows are designed precisely to contextualise this: they indicate the rate and direction of glucose change, giving users the information needed to act ahead of where the glucose number currently sits.
Accuracy Across the Wear Period
A detail that often goes unexamined is how accuracy changes across the life of a sensor. Independent clinical data shows that Dexcom One+ maintains strong accuracy performance across the full 10.5-day wear period and not just in the first 24 to 48 hours when calibration is freshest.
Day-by-day accuracy data shows that MARD remains consistent from Day 2 through Day 10, with no meaningful degradation. This matters practically: a sensor that performs well on day one but drifts by day seven creates clinical uncertainty at the point where many patients are least vigilant, incidentally when they have grown most comfortable with the device.
The iCGM Designation
Dexcom sensors, including the One+, carry the FDA iCGM designation which is a classification reserved for integrated CGM systems that meet the most stringent accuracy and reliability requirements in existence. Only a small number of CGM manufacturers worldwide hold this designation. It is the regulatory expression of what clinical accuracy actually means and for HCPs recommending devices to their patients, it is a meaningful differentiator worth understanding.
Accuracy in CGM is not a feature. It is the foundation on which every other benefit rests. Without it, trend arrows mislead. Alerts misfire. Decisions based on faulty data can cause harm. With consistently validated, non-adjunctive accuracy, CGM becomes what it was designed to be: a tool that makes diabetes genuinely easier to manage.
