CGMs reveal measurement-range blind spots in diabetes care

Overview

Continuous glucose monitors (CGMs) have transformed life for people with type 1 diabetes by providing near real-time glucose data and smartphone alerts. A new study analyzed nearly 47 million CGM readings from 948 participants across four international trials and found a blind spot: when glucose levels exceed the CGM’s measurement range, the sensor can only indicate that levels are extremely high or extremely low, not their exact values. The analysis showed that while standard clinical metrics remain robust, there is a loss of detail during the most extreme glucose events. This summary of the study, as reported by The Conversation, highlights the practical implications for clinicians and software developers.

• CGMs have a fixed measurement range; extreme values may be imprecise
• Most participants experienced readings at the measurement limits
• High-glucose episodes at the upper limit can last from one to several hours
• Reporting sensor limits in apps could improve data interpretation

Original publisher: The Conversation

Introduction

Continuous glucose monitors have reshaped diabetes management by providing a stream of data that helps people track glucose responses to meals, activity, sleep, and insulin. New research synthesizes nearly 47 million CGM readings from 948 individuals with type 1 diabetes across four large international trials to examine a blind spot in CGMs: when glucose moves beyond the device's measurable range, the sensor no longer reports exact values, only that glucose is very high or very low.

What CGMs measure and their limits

CGMs continuously measure glucose levels every few minutes and relay results to a smartphone app. Like any instrument, CGMs operate within a fixed measurement range. When glucose rises above or falls below this range, CGMs indicate that levels are extreme but cannot quantify how far beyond the limit the value is. An apt analogy is a kitchen thermometer that reads up to 100°C; once it hits the ceiling, it can confirm heat but not whether it is 120°C or 180°C. This is the essence of the blind spot observed in CGMs when events become severe.

Study design and key findings

The researchers pooled nearly 47 million publicly available CGM readings from 948 people with type 1 diabetes in four large trials. They found that between 93.5% and 100% of participants experienced at least one reading that reached an upper or lower measurement limit. The distribution was not uniform; more than one third of high glucose episodes in three studies remained at the upper limit for at least an hour, with the longest episodes lasting two to three hours. Younger participants experienced upper-limit readings more frequently, reflecting known challenges in managing glucose during adolescence. Additionally, participants with higher HbA1c were more likely to reach the measurement limits, indicating that those with poorer baseline control are more exposed to this limitation.

Importantly, comparisons with finger-prick glucose measurements showed that standard clinical summary measures—such as time in range, average glucose, and glucose variability—were largely robust even when sensors hit measurement limits. The loss of detail occurs primarily during extreme events, not in the usual range of readings that drive most clinical decisions.

Implications for care and software design

The authors note that current CGM apps and cloud-based software summarize glucose data in many ways but rarely state whether a sensor has reached its measurement limits, how often that happened, or how long those periods lasted. Adding explicit reporting of measurement limits would be a relatively simple software update but could help clinicians identify individuals for whom this blind spot is most relevant and improve interpretation of CGM data. The message is not to discourage CGMs, but to acknowledge their limits and to use this information to enhance decision making in diabetes care.

What should change?

In daily practice, clinicians rely on summary statistics that remain reliable even when measurement limits are reached. To improve data interpretation, developers and researchers should integrate indicators of measurement-limit events into CGM visualizations and analyses. Such changes could help tailor treatment plans for patients who frequently cross the limits and inform research that seeks to understand extreme glucose dynamics more precisely.

Conclusion

Continuous glucose monitors represent a major leap forward in diabetes care. Recognizing their measurement-range limits is a natural next step to extracting the maximum value from CGM data, guiding better clinical interpretation, and driving future improvements in device design and software tools.