CGM Series: Episodes 10 to 12

The series has grown — Episodes 35 and 36

Since Episodes 10–12, the CGM Series has expanded with two further episodes that go deeper into the research and real-world clinical practice behind CGM accuracy:

• Episode 35 — CGM Accuracy and Study Design with Professor Othmar Moser
  The independent research perspective. Why MARD alone is misleading, how study design determines what accuracy numbers actually mean, why meal and insulin challenges are non-negotiable, and what CE marking does and does not guarantee. The episode that explains the “why” behind every study design question in the framework above.
• Episode 36 — CGM Accuracy: DSN Forum
  The clinical application. Amanda Williams, Beth Kelly, and Tamsin Fletcher-Salt (DSN Forum UK) explain how the DSN Forum comparison chart was built, why data sufficiency must come before features, what they are seeing in UK clinical practice, and what ATTD 2025 revealed about fully closed loop systems, GLP-1 in type 1 diabetes, and continuous ketone monitoring. The episode that shows how the framework translates into real-world device selection and patient conversations.

Episode 10: CGM Accuracy — study design first, performance after

John Pemberton and Louise Collins explore the importance of understanding CGM accuracy, why study design must be assessed before performance data, and the key questions to ask when evaluating sensor reliability. The conversation covers what robust testing conditions look like, why not all CGMs are equal, and what standardisation in CGM technology may look like in the future.

This chart, developed in collaboration with the DSN Forum UK, helps the community understand study design before considering performance. It is updated every two months.

View the updated CGM comparison chart from the DSN Forum UK

Key takeaways from Episode 10:

• Continuous glucose monitors are crucial for insulin dosing decisions
• Understanding study design is essential before evaluating CGM accuracy
• Not all CGMs are created equal — performance varies significantly between devices
• Key questions include the study population, testing conditions, and comparator used
• Robust testing conditions are necessary for reliable sensor performance data
• Peer-reviewed data matters more than marketing claims
• Standardisation in CGM technology is on the horizon via the IFCC ISO process

Episode chapters: 00:00 Introduction | 02:14 Understanding CGM | 05:11 Accuracy overview | 10:13 Evaluating sensor performance | 15:45 Key questions for accuracy | 20:31 Towards standardisation | 25:03 Summary

• Listen: Episode 10 — CGM accuracy, study design first
• Understanding study design before performance — CGM Systems Guide
• Show notes and transcription — Episode 10 (text file)
• CGM comparison chart from the DSN Forum UK (updated bi-monthly)
• Tim Street at Diabettech — independent CGM analysis

Episode 11: CGM Accuracy — understanding MARD, 20/20, 40/40, and error grids

John and Louise explore the metrics used to assess CGM performance: Mean Average Relative Difference (MARD), 20/20 agreement rates, 40/40 agreement rates, and error grids. The conversation covers why FDA standards are currently the highest for CGM performance, why CE marking does not guarantee accuracy, and why testing against capillary glucose matters.

View the CGM performance comparison chart from the DSN Forum UK

Key takeaways from Episode 11:

• FDA standards are currently the highest available for CGM performance
• CE marking does not guarantee device accuracy or reliability
• Testing conditions significantly impact CGM accuracy results
• The 20/20 standard indicates no risk for insulin dosing decisions at a given reading
• The 40/40 metric identifies high-risk readings in CGM data
• Testing against capillary glucose is essential — venous comparators underestimate post-meal glucose exposure

The chart below illustrates a key finding from a comparative study of glycaemic metrics: the Medtronic Simplera aligns more closely with venous glucose values rather than capillary, leading it to underreport post-meal glucose exposure. The Dexcom G7 and FreeStyle Libre 3 track more closely to capillary glucose, giving users a more accurate picture of actual glucose exposure and future complication risk.

The consequence is that the Medtronic Simplera tends to overestimate time in range and underestimate time above range — users may believe their glucose control is better than it is, only to see HbA1c results higher than expected. Users of the Dexcom G7 and FreeStyle Libre 3 receive a more accurate reflection of capillary glucose levels.

Episode chapters: 00:00 Introduction | 02:07 CGM systems overview | 06:08 Accuracy and performance standards | 10:09 Testing conditions | 14:13 Metrics for accuracy | 18:03 Comparing against capillary glucose | 22:02 Future directions

• Listen: Episode 11 — MARD, 20/20, 40/40, and error grids
• Assessing CGM accuracy performance — the full written guide
• Show notes and transcription — Episode 11 (text file)
• CGM comparison chart from the DSN Forum UK (updated bi-monthly)
• Tim Street at Diabettech — independent CGM analysis

Episode 12: CGM functionality — the bells and whistles

John and Louise explore the features that distinguish CGM systems from each other: calibration options, alarm types and thresholds, size and wearability, connectivity with AID systems, and AI-driven forecasting. The emphasis is on understanding individual priorities and matching them to the right system — because there is no one-size-fits-all.

This summary table from the CGM Systems Guide helps match the right system to the right priorities.

Key takeaways from Episode 12:

• Modern CGMs now use factory calibration, removing the need for routine finger prick calibration
• Optional calibration can be beneficial, but only when using an accurate blood glucose meter
• Alarm fatigue is a real barrier to effective diabetes management — alarm settings need personalisation
• The FreeStyle Libre is noted for its small size and long wear time
• Dexcom products offer the most extensive connectivity with AID systems
• Understanding individual needs is crucial when selecting a CGM
• AI-driven glucose forecasting in CGMs can support more proactive decision-making

Episode chapters: 00:00 Introduction | 02:14 CGM overview | 13:09 Features and alarms | 21:27 Size and connectivity | 27:21 The wrap

• Listen: Episode 12 — CGM functionality and features
• CGM: the bells and whistles — the full written guide
• Show notes and transcription — Episode 12 (text file)
• CGM comparison chart from the DSN Forum UK (updated bi-monthly)
• Tim Street at Diabettech — independent CGM analysis