Continuous and flash glucose monitoring: Taking the mystery out of glycaemic variability

18 Aug 2020

The emergence of continuous glucose monitoring (CGM) and flash glucose monitoring systems have become one of the most important advances in technology for diabetes care, providing valuable information to assess glycaemic control throughout the day explains endocrinologist and diabetes expert Professor Neale Cohen, Director of clinical diabetes at the Baker Heart and Diabetes Institute.

Here Professor Cohen talks to the limbic about the technology that is transforming diabetes management by providing patients and doctors critical data that can quantify time below, within, and above established glucose targets and inform daily treatment decisions.

“The latest devices can read glucose values and their rate of change as much as every five minutes,” says Professor Cohen who recalls having to interpret more than 20 pages of data when the technology first started to be used in practice.

The readings are picked up from a sensor inserted into the skin which measures the level of glucose in the interstitial fluid before sending that data to a patient’s dedicated reader or smart device, allowing patients to learn how foods and physical activity affect their glucose levels.

A variation on CGM is flash glucose monitoring. A sensor, placed on the upper arm, takes readings every minute and stores the data every 15 minutes. Patients can manually scan the sensor as frequently as desired to reveal instantaneous (flash) glucose measurements over a 14-day period.

But while the potential for CGM and flash glucose monitoring to transform diabetes management is clearly recognised, use of the technology remains suboptimal and successful integration in clinical practice is low compared to traditional self monitoring of blood glucose (SMBG), Professor Cohen tells the limbic.

“When we got CGM we thought it was a wonderful technology – we had so much more information – but it became apparent pretty quickly that there needed to be some standardisation for what type of data is required for an adequate CGM report and how to interpret what you’ve got in front of you1”.

Consensus statement outlines core targets to guide clinical care

Within the last year an international panel of physicians, researchers, and CGM technology experts convened by the Advanced Technologies & Treatments for Diabetes (ATTD) Congress met and agreed on a number of core targets to guide diabetes clinical care.

The resulting consensus statement2 for the first time defined the target glucose range for patients using CGM systems, typically 3.9–10 mmol/L, and the duration that should be spent within these thresholds – called the Time in Range (TIR).

Endorsed by major diabetes organisations around the globe, including the Australian Diabetes Society3 (ADS), the recommendations are based on several studies validating the use of the time-in-range measurement including studies that investigated the relationship between time-in-range and HbA1c measures, which found that 70% of time spent in range corresponded to an HbA1c of about 7%.4,5

Meanwhile, spending half of the day in range aligned with an HbA1c of 8%, according to a meta-analysis of more than a dozen trials.5

Time in Range, CGM and flash glucose monitoring metrics

As set out in the consensus statement2,3, the recommendations for most people with type 1 or type 2 diabetes are:

> 70% of readings within a blood glucose range of 3.9-10.0 mmol/L
< 4% of readings < 3.9 mmol/L
< 1% of readings < 3.0 mmol/L
< 25% of readings > 10.0 mmol/L
< 5% of readings > 13.9 mmol/L

For those aged < 25 years for whom the HbA1c goal is < 7.5%, the time-in-range target should be set to about 60%.

The statement also provides recommendations on how much data is adequate for the analysis time period – typically 90% of data over 14 days.

A CGM report should also document mean glucose for comparison to the last recorded value, glucose management indicator (GMI – formerly called estimated A1C), as well as an optimal glycaemic variability target of no more than 36% for adults with type 1 diabetes representing low variability and a relatively stable glucose profile2,3.

According to the expert group, one important way to translate these new CGM targets into clinical practice is to implement a standard CGM report called the ambulatory glucose profile (AGP)2,3.

The AGP: Tailoring therapy to each patient

The AGP is a standardised, single-page glucose report that provides a visual representation of all the key CGM metrics with a summary of statistics, a glucose profile graph and glucose daily calendar graphs that most CGM devices send to the clinician.

In February 2020, the ADS released its own consensus statement3 supporting the use of Ambulatory Glucose Profiling based on the international consensus2 and after convening an expert working group to identify the clinical effectiveness of the AGP report.

According to Professor Cohen, the establishment of time-in-range goals and agreement on key CGM metrics means clinicians can now use the AGP to tailor therapy to each patient.

Similar to an ECG for the heart, the AGP is consistent regardless of the CGM device used, adds Professor Cohen, who served as a member of the ADS AGP Working Group.

The main feature of the AGP is the glucose profile itself. Displayed as a waveform graph it shows a median glucose control line – the 25th to 75th percentiles, which represent 50% of the glucose readings over the analysis time period as well as confidence intervals around those, he explains.

Meanwhile, the 5th to 95th percentiles identify any outliers that are contributing to the median result.

The strengths of the profile, says Professor Cohen, are in the ease of interpretation of median glucose levels, identifying both hyperglycaemic and hypoglycaemic glucose trends more comprehensively in a 24-hour period, and variability in glucose levels both between and within days.

“The graphical representation of the modal day – the median glucose and the confidence intervals – is tremendously important.”

At a glance, clinicians and patients can determine the extent to which values are within the target range and the times of day that pose potentially dangerous low or high patterns requiring immediate attention.

The overall management goal is to make or keep the curve as narrow and flat as possible within the designated target range, says Professor Cohen.

“When I look at AGP reports the number one thing I’m looking for is an obvious pattern that I need to be alerted to.”

The AGP is also ‘very good’ at picking up hypoglycaemia – particularly nocturnal hypoglycaemic events – highlighting ‘hotspots’ or specific times during the day or night when events occur. Glucose variability is also a predictor of hypoglycaemia, he adds.

According to Professor Cohen, looking at the confidence intervals in relation to the median line would very quickly reveal whether there is a problem with a specific time of day. In particular very wide and highly variable confidence intervals, which correspond with high glycaemic variability and increased risk for hypoglycaemia, should prompt a closer look at daily CGM data.

“The width of the confidence will tell you a lot – if you look at report that shows very narrow confidence intervals you know there’s a lot of reproducibility there. You can be confident that everyday is very similar. But for ridiculously wide confidence intervals – anywhere from five to 25 during the day – it is likely that something behavioural is going on.”

That’s when Professor Cohen ‘digs down’ day-to-day to find out what might have caused such ‘wild’ variations.

He suggests showing patients their profile highlighting the confidence intervals and asking patients to talk through the events of the time period – diet, exercise, social events, work or stress – to identify ways of reducing glycaemic variability.

“The AGP report gives us the ability to track what’s happened and presents opportunities to ask about specific moments in time so that in most people we can really nut out what’s going on.”

For those patients he can’t, Professor Cohen suggests keeping a food and exercise diary for a week. Matching this data with the AGP can help identify areas for behavioural change that can reduce glycaemic variability.

On the other hand, an out of range but narrow confidence interval usually indicates a patient’s medication needs adjusting.

“It’s generally some sort of aberration, it’s very reproducible and usually means you haven’t got the medication mix right.”

“CGM and AGP gives us such clarity – it really removes the mystique of some of these patients with glycaemic variability who, beforehand, we might never have been able to figure out why and who would just have to live with that. Now we have a lot more clarity over that.”

Moving beyond A1c to look at the bigger picture

Reliance on HbA1c value alone can be misleading says Professor Cohen pointing out that haematological conditions, medications, comorbidities and medical therapies, can all result in an altered HbA1c in patients. And because A1c relies on haemoglobin, which depends on red cell turnover rate that can vary among individuals, it can be unreliable.

It also provides a very limited view of a much bigger picture.

He says endocrinologists need to look beyond the patient’s HbA1C in assessing the need for additional therapies.

“Up until recently we have relied on HbA1c so much that it is pretty much the only thing that some people look at but of course we’ve realised a patient’s A1C does not always tell the whole story. It doesn’t take into account the highs and the lows – it’s an average.”

The use of CGM has recently given rise to estimated A1C (eA1C) value. It’s a measure of what a user’s approximate A1C level is likely to be, based on the average glucose level from their CGM readings over 14 or more days and compared against a large number of individuals with diabetes who have the same average CGM glucose level reading.6

Professor Cohen says this value is the most reliable reflection of HbA1c and is “probably a better measure of average glucose than your actual HbA1c”.

While many patients’ eA1C will closely approximate a laboratory-measured A1C it might be higher or lower for others depending on their red cell turn over rate, whether they have certain haematological comorbid conditions or are taking certain medications, for instance2,3.

Experts say the discordance could prove confusing for patients and the US Food and Drug Administrator said it was concerned that the term eA1C implies a more direct relationship with the measured A1C than is actually the case6.

In 2018 an expert panel coined a new term for eA1C to address the concern. The value is now referred to as the glucose management indicator (GMI) and is calculated from the mean CGM glucose similarly and reported in the same units.6

While a difference between a patient’s laboratory measured A1C and their GMI is not unexpected, it may be important to consider when setting targets.

“For example, if the target A1C is 7.5% and the GMI is always higher (say 7.9%), it might be safe to set the A1C target slightly lower, such as at 7.2%, in order to minimise excessive hyperglycemia,” the expert panel suggests.6

CGM and flash glucose monitoring use in Australia is growing

Use of CGM and flash glucose monitoring among patients in Australia will continue to grow says Professor Cohen and being able to interpret the AGP is becoming increasingly important.

“In young people CGM [including flash glucose monitoring] is available for patients with Type 1 diabetes under 21 free of charge and we’ve had approval now in pregnant women and people on healthcare cards9 so there’s a large volume of patients who will be using CGM to manage their diabetes.”

In February, the Government expanded eligibility for fully subsidised access to CGM and flash glucose monitoring devices to people with Type 1 diabetes over the age of 21 who have concessional status under its CGM Initiative8.

In Australia flash glucose monitoring technology is currently only available in the FreeStyle Libre product9.

The FreeStyle Libre flash glucose monitoring system is the first product in the flash glucose monitoring category. It’s factory calibrated and designed to last 14 days. A quick scan of the reader or FreeStyle LibreLink app over the sensor provides a complete picture of the glucose profile including the current glucose reading, 8-hour history and trend arrow showing if the glucose level is going up, down or staying steady.

Professor Cohen said the impact of flash glucose monitoring and CGM on diabetes is important and has already changed management and outcomes.

“This is absolutely state of the art management now for diabetes so it does require up skilling – you need to see a few of these just as you need to see a few ECGs if you’re interpreting them. The more you see the quicker and more efficient you are at interpreting them. CGM in addition to closed loop and artificial pancreas systems are really going to change things enormously.”

 

References

  1. Rodbard D. Continuous glucose monitoring: a review of successes, challenges, and opportunities. Diabetes Technol Ther 2016;18(Suppl. 2): S3–S13
  2. Battelino T, et al “Clinical targets for continuous glucose monitoring data interpretation: recommendations from the international consensus on time in range” Diabetes Care 2019; DOI: 10.2337/dci19-0028
  3. Consensus Position Statement on: Utilising the Ambulatory Glucose Profile (AGP) combined with the Glucose Pattern Summary to Support Clinical Decision Making in Diabetes Care
  4. https://diabetessociety.us14.list-manage.com/track/click?u=fb3e68e8dbae2add462e5be84&id=1d8b64c7ac&e=2236400591
  5. Beck RW, Bergenstal RM, Cheng P, et al. The relationships between time in range, hyperglycemia metrics, and HbA1c. J Diabetes Sci Technol. 13 January 2019
  6. Vigersky RA,McMahon C.The relationship of hemoglobin A1C to time-in-range in patients with diabetes. Diabetes Technol Ther 2019;21: 81–85
  7. Bergenstal RM, Beck RW, Close KL, et al. Glucose Management Indicator (GMI): A New Term for Estimating A1C From Continuous Glucose Monitoring Diabetes Care Nov 2018, 41 (11) 2275-2280; DOI: 10.2337/dc18-1581
  8. National Diabetes Services Scheme https://www.ndss.com.au/living-with-diabetes/managing-diabetes/continuous-glucose-monitoring/
  9. Ministers Department of Health press release 58,000 type 1 diabetics to have free access to new glucose monitoring device https://www.health.gov.au/ministers/the-hon-greg-hunt-mp/media/58000-type-1-diabetics-to-have-free-access-to-new-glucose-monitoring-device

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