Approaches for Successful Outcomes with Continuous Glucose Monitoring

It is difficult to quantify how often users check real-time CGM data during the day and night, either actively before insulin dosing or passively when alerted to hypoglycemia or hyperglycemia; however, a reasonable estimate is at least 4–12 times/day, including before meals, at bedtime, for physical activity, and in response to alerts and alarms. Quantification of FCGM is easier, as the number of scans per day is provided on the reader and available when uploading data to the LibreView software. In two recent studies using FCGM, the average number of scans per day was reported to be 15 for type 1 diabetes and 8 for type 2 diabetes patients (21,22). A recent analysis of FCGM in >50,000 users worldwide provided additional insight into real-world experience. In this report, the number of scans per day positively correlated with glycemic outcomes, with less time spent in hypoglycemia and hyperglycemia and more time spent in range with increasing number of scans per day. The number of scans per day ranged from 4.4 (every 5.4 hours) to 48 (every 30 minutes) (26). Health care providers should address the ideal frequency of scanning on an individual basis and modify recommendations based on each patient’s treatment regimen and needs.

Careful patient selection is important when recommending CGM therapy. The article on p. 11 of this compendium provides more details about appropriate candidates. Successful outcomes will depend in large part on a person’s trust in the system, willingness to calibrate the system per product specifications, the number of times the person scans or looks at the system, and the type of intervention plan set up with the health care provider. Guidelines for CGM patient selection have been developed by professional societies and other expert forums (27–29).

Regardless of baseline A1C or the degree of glucose variability at CGM initiation, users should be willing to check or scan their device on a near-daily basis to realize the greatest benefit (14–18,21,22). Users should also understand the concept of interstitial fluid versus capillary blood glucose measurements and calibration procedures for systems that require calibration. Of note, for real-time CGM systems, setting alerts and alarms with realistic expectations is essential to avoid alarm fatigue (24). Establishing a plan for sick-day or illness management with CGM is greatly encouraged. Dexcom CGM users should also consider taking advantage of the Share feature, which allows a “follower” (person chosen by the user, such as a parent, family member, or friend) to receive CGM information on a smartphone. Such data, including alerts and alarms, would allow the recipient to potentially assist the user if necessary, such as in the event of hypoglycemia. Educating family members or other caretakers about the CGM system and, for older adults, ensuring that they can see or hear the alerts and alarms, are also fundamental to successful outcomes.

The importance of patient and provider education cannot be overemphasized. People with diabetes should receive training on the meaning of the messages displayed on their system reader. Additionally, setting procedures for alerts and alarms, individualizing trend arrow-based treatment decisions, and reinforcing the dangers of insulin stacking (administering insulin while the previous dose is still active) are crucial to promoting adherence to CGM and improving glycemic outcomes. Although training videos are provided by manufacturers, they should not be seen as a substitute for in-depth patient education, especially when initiating CGM. Without appropriate training, CGM users may not be able to take full advantage of the information provided. Additionally, because most health care providers lack training in the interpretation of CGM data, including retrospective analysis during office visits, the availability of educational resources for health care providers is essential to achieving positive outcomes.

Hypoglycemia is a serious concern for people with diabetes and the major limiting factor in achieving glycemic targets with intensive management. Hypoglycemia risks and frequency are well established in people with type 1 diabetes (30,31), and even self-reported severe hypoglycemia is associated with a 3.4-fold increased risk of death (32). However, hypoglycemia frequency may be underestimated in people with type 2 diabetes; whether on insulin or other antihyperglycemic regimens, these individuals can also have hypoglycemia unawareness (33). CGM technology has been demonstrated to reduce hypoglycemia frequency and hypoglycemia unawareness in people with diabetes (14–18,21,22,34–37).

When recommending CGM to patients, the presence of hypoglycemia unawareness should be evaluated and discussed to aid in selecting the most appropriate system.

Interpretation of data for users and providers still lacks a cohesive approach. When reviewing data, time spent in the various ranges (<54, <70, 70–180, >180, and >250 mg/ dL) as well as coefficient of variation should be addressed. This can be accomplished with Ambulatory Glucose Profile reports available in various software platforms (Dexcom Clarity, Glooko-Diasend, Tidepool, Medtronic CareLink, and LibreView) (38–42). Nocturnal hypoglycemia should be addressed first, with intervention to reduce its severity and frequency. Subsequently, fasting glucose levels should be evaluated, and modifications to basal insulin doses or insulin-pump basal rate settings should be implemented. CGM systems offer great advantage in identifying prandial glycemic excursions; in such cases, mealtime insulin doses and the timing of the boluses should be addressed by instructing patients to monitor glucose before and 2–4 hours after meals to better understand glucose fluctuations and make appropriate regimen adjustments. Recently, use of FCGM was associated with a significant increase in delivering bolus insulin 15–20 minutes in advance of meals (compared to immediately before or after meals) (36). People using insulin should be cautioned against making frequent dose changes in response to above-target post-meal CGM readings on their display tools because insulin stacking is a well-known and avoidable cause of hypoglycemia.

As mentioned previously, CGM systems feature trend arrows that provide information on the predicted change of glucose levels over a specific time period. It is important to be aware that the arrows correspond to different rates of glucose change depending on the brand of CGM system. Training users on the meaning of arrows displayed on their particular device will ensure that they take appropriate actions guided by the specific system they use. (See the table on p. 9 of this compendium for details about each available system.) Although approaches to adjusting insulin doses on the basis of trend arrows are frequently discussed and constitute an important aspect of therapeutic CGM, proposed methods have yet to be validated in randomized controlled trials (43–47). The most recently published method is specific to the Dexcom G5 Mobile (47). With this in mind, it is imperative that health care providers take an individualized approach when applying trend arrows to treatment decisions (Table 1).

In view of the aforementioned caveats, the published recommendations made with respect to the Dexcom G5 arrows cannot be extrapolated to the FreeStyle Libre system. However, using a correction factor for trend arrow–guided insulin dose adjustments in combination with mealtime dose calculations based on an insulin-to-carbohydrate ratio offers an advantage over other published methods in that it allows for personalized dose calculations based on insulin sensitivity. A proposed working algorithm for the FreeStyle Libre incorporating this concept is shown in Table 2, and sample dose adjustments are provided in Box 1. The rationale for this non-validated method is to be more aggressive when the reader displays one up-trending arrow because the predicted glucose change over time with the FreeStyle Libre in reality could be much higher than 2 mg/ dL per minute. Moreover, readings in the hypoglycemic range must be confirmed with fingerstick glucose testing because of potential sensor inaccuracy; when glucose is rapidly falling and sensor glucose levels are <100 mg/dL, additional rapid-acting carbohydrate intake (15–30 g) should be considered in the pre-meal period. In the postprandial period, insulin dosing based on trend arrows should be calculated 4 hours after an insulin dose, although this recommendation may change with the recent introduction of insulin analogs with a faster onset of action (48).

Before using trend arrows for insulin dose adjustments, patients should first become familiar with their CGM systems. Because users will work within their own CGM ecosystem, education should be targeted toward patients’ specific device. Although there are no head-to-head trials, all available CGM systems have decreased accuracy in the hypoglycemic range (9,49,50), but in the United States, only the FreeStyle Libre label requires confirmation with fingerstick testing in this range. Thus, individualized guidance may be needed on using trend arrows for insulin dose adjustments when glucose levels are <70 mg/dL. This is especially true in older adults with diabetes, who are at highest risk for severe hypoglycemia and hypoglycemia unawareness (51). For certain high-risk geriatric patients, use of trend arrows for insulin dose changes with the FreeStyle Libre should be assessed on a case-by-case basis, and it may be prudent to confirm glucose levels via fingerstick glucose testing when adjusting insulin per instructions from the reader display; in the setting of rapid glucose changes toward hypoglycemia, fingerstick glucose checks should be strongly recommended for safety, especially when the “check blood glucose” symbol appears on the reader display. Of note, in a small cohort of nursing home residents with type 2 diabetes, FCGM overestimated hypoglycemia, with 51.4% of the interstitial glucose readings <70 mg/dL being falsely low compared to capillary blood glucose levels (52). More studies of FCGM in geriatric populations are needed.

Formal studies of CGM in non-insulin-using patients on antihyperglycemic regimens are scant. For such people, the main goal of CGM should be to achieve target fasting glucose levels and decrease postprandial glycemic excursions with appropriate regimen adjustments, meal quality modifications, and lifestyle interventions (2,53). For people with type 2 diabetes, especially those on sodium– glucose cotransporter 2 inhibitors or glucagon-like peptide 1 receptor agonists, CGM therapy could have significant educational and therapeutic benefits, with the additional advantage of obtaining data relatively painlessly. Developing a plan to review CGM trends in the postprandial period, whether by setting up alerts or by instructing users to scan their FCGM at specific times after meals, can convey the dynamics of post-meal glucose fluctuations to patients and guide providers in personalizing diabetes regimen adjustments based on data accumulated between visits. More studies are needed to address the potential value of FCGM in this clinical setting.

Ideally, all systems should display glucose data on a mobile app so that users do not have to carry multiple tools; this strategy would potentially contribute to acceptance and increase uptake of CGM use in non-insulin-using people with diabetes.

Standards of care recommend that most adults with type 1 or type 2 diabetes engage in daily physical activity, allowing no more than two consecutive days without activity (2,53).

However, blood glucose responses to physical activity, especially in individuals with type 1 diabetes, can be highly variable depending on many factors, including the type and timing of activity, previous food ingestion, and level of insulin on board. Adjustments in medication doses and carbohydrate intake are often required to maintain adequate glucose levels during and after physical activity (54,55).

CGM can be of benefit by providing users with glucose trend data at any time, thereby decreasing fear of exercise induced hypoglycemia. This is especially relevant when sensor glucose levels are trending toward hypoglycemia. However, very few studies have addressed this issue, and the accuracy of CGM has not been fully validated with different types of exercise. For example, intermittent high intensity interval exercise is associated with metabolic changes (e.g., changes in pH, microcirculation, and oxygen tension) that may potentially interfere with CGM accuracy. In a small study using the Dexcom G4 Platinum system, the accuracy was comparable during continuous moderate and intermittent high-intensity exercise during a cycling session (56). Similarly, the accuracy of real-time CGM (Medtronic Guardian REAL-Time) measured at various prescribed workloads was acceptable for all types of exercises with the exception of continuous high-intensity exercise, where lower accuracy was detected (57). A recent survey of 502 adults from the T1D Exchange’s online patient community, 276 of whom were using CGM either alone or in combination with CSII, showed that, although most respondents adjusted carbohydrate intake and insulin doses around exercise, the majority still reported experiencing hypoglycemia after exercise and having significant difficulties with blood glucose control around exercise (58).

Using CGM trend arrows adds another level of complexity. Although trend arrows are helpful in determining the direction of glucose during exercise and guiding users in the consumption of additional carbohydrate to prevent or reduce hypoglycemia, using them to adjust insulin doses during and after exercise is more challenging. As previously suggested (47), users should be conservative when adjusting their insulin doses before exercise and should refrain from increasing their insulin dose in the presence of up-trending arrows during the active period. In the postexercise period, as previously recommended by Riddell et al. (55), close glucose monitoring is essential. In particular, attention should be paid to the direction of trend arrows in the immediate or even late-post-exercise period to correct impending hypoglycemia with rapid-acting carbohydrate intake, if indicated. Trend arrows may also signal the need for additional carbohydrate or an insulin dose reduction at bedtime to avoid nocturnal hypoglycemia, especially when exercise takes place in the late afternoon or evening (55). It is hoped that additional studies of newer CGM systems and their accuracy in response to various exercise protocols will better define best practice for the use of CGM trend arrows during physical activity.

The opinions expressed are those of the authors and do not necessarily reflect those of Abbott Diabetes Care or the American Diabetes Association. The content was developed by the authors and does not represent the policy or position of the American Diabetes Association, any of its boards or committees, or any of its journals or their editors or editorial boards.

Dualities of Interest

I.B.H. has served as a consultant to Abbott Diabetes Care, Adocia, Bigfoot, and Roche. His institution has received research grant support from Medtronic.

T.B. has served on advisory boards of Bayer Health Care, Boehringer Ingelheim, DreaMed Diabetes, Eli Lilly, Medtronic, Novo Nordisk, and Sanofi. His institution has received research grant support, with receipt of travel and accommodation expenses in some cases, from Abbott Diabetes Care, Diamyd, GluSense, Medtronic, Novo Nordisk, Sandoz, and Sanofi. He has received honoraria for participating on the speakers bureaus of Bayer Health Care, Eli Lilly, Medtronic, Novo Nordisk, Roche, and Sanofi. He owns stock in DreaMed Diabetes.

A.L.P. has served on advisory boards for Abbott Diabetes Care, Becton Dickinson, Bigfoot, Boehringer Ingelheim, Eli Lilly, Lexicon, Livongo, Medscape, Merck, Novo Nordisk, OptumHealth, Sanofi, and Science 37. She has received research grant support from Dexcom and Mannkind. She participates on a speakers bureau for Novo Nordisk.J.J.C. participates in speakers bureaus for Janssen, Merck, Novo Nordisk, and Sanofi.

G.A. has served as a consultant and on a steering committee for Dexcom and on an advisory board for Novo Nordisk, and her institution has received research grant support from AstraZeneca and Novo Nordisk.

R.M.B.’s institution has received payment for his services as a research investigator, consultant, or advisory board member for Abbott Diabetes Care, Becton Dickinson, Boehringer Ingelheim, Bristol-Myers Squibb/AstraZeneca, Dexcom, Eli Lilly, Hygieia, Johnson & Johnson, Medtronic, Merck, Novo Nordisk, Roche, Sanofi, and Takeda. R.M.B. has inherited Merck stock, volunteers for the American Diabetes Association and JDRF, and receives funding from the National Institutes of Health for diabetes technology research.

Acknowledgments

Writing support services for this compendium were provided by Carol Verderese of The Diabetes Education Group in Lakeville, CT. Editorial and project management services were provided by Debbie Kendall of Kendall Editorial in Richmond, VA.

Author Contributions

All authors researched and wrote their respective section(s). Lead author I.B.H. reviewed all content and is the guarantor of this work.

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