Continuous Glucose Monitoring

Diabetes mellitus (DM) has reached epidemic levels of prevalence worldwide. According to Olczuk and Preifer (2018), the cost of treating diabetes and its complications was $825 billion, International. Assuming the trend of increasing prevalence continues, it is estimated that by 2025 there will be at least 700 million patients with diabetes (Olczuk & Preifer, 2018). DM is a complex metabolic disease characterized by disrupted glucose metabolism resulting in hyperglycemia, ketoacidosis, coma, and death if untreated (Kharroubi & Darwish, 2015). Constant monitoring of blood glucose levels is essential to controlling diabetes; since the treatment of diabetes can cause hypoglycemia, patients must track blood glucose constantly in order to know when and what interventions are necessary to maintain a healthy level (Dunn, Xu, Hayter, & Ajjan, 2018). Daily blood glucose monitoring, however, is both painful and inconvenient and as noted by Dunn et al. (2018), is difficult for patients to consistently maintain over a long period of time. Since the finger prick device that most patients use is over 50 years old, a replacement for this antiquated technology is long overdue (Olczuk & Preifer, 2018). Since 1999, a new technology has been gradually introduced to the market; continuous glucose monitoring (CGM) devices (Olczuk & Preifer, 2018). With CGM devices, finger sticks are no longer necessary and blood glucose levels are tracked with greater frequency- as often as once every 15 minutes (Klonoff, Ahn, & Drincic, 2017). The remainder of this paper will discuss one recent paper on the topic of CGM devices, and use additional sources from the literature to evaluate this relatively new technology. 

Continuous Glucose Monitoring 

The primary article reviewed for this paper was written by Dunn et al. in 2018 and consisted or a correlational/descriptive study designed to answer four research questions: 

1. What are the daily number of glucose checks and their pattern across the day for users of the CGM monitor the FreeStyle Libre? 

2. What are the associations between frequency of daily glucose checks and glycemic control markers for users of the CGM monitor FreeStyle Libre? 

3. What are the geographical differences, if any exist; in glycemic parameters for users of the CGM monitor FreeStyle Libre?

4. How do glycemic markers evolve over the period of sensor use for users of the CGM monitor FreeStyle Libre? (Dunn et al., 2018, p. 38).

Like other CGM, the FreeStyle Libre uses a sensor filament inserted into the subcutaneous level to measure glucose concentrations in the interstitial fluid (Klonoff et al., 2017). Klonoff et al. (2017) noted that the sensor cofactors compete with tissue oxygen and may provide an overestimation of blood glucose levels in cases of hypoxia. In general, however, the measurements of CGM have been validated as equally accurate as self-monitoring of blood glucose (SMBG) so long as device directions are heeded (American Diabetes Association, 2019). 

Dunn et al. (2018) collected data from 55,343 monitors over almost two years including 64,288, 918 scans and 392, 187, 678 blood glucose measurements (p. 38). Multiple data sets were derived from these readings including a total number of checks per day per patient, time spent in hyper- or hypoglycemia as determined by the raw readings, and estimated HbA1C as determined by raw readings (Dunn et. al., 2018). Descriptive statistics were also collected including geographic location (Dunn et al., 2018). The authors concluded that the average user conducted 16.3 scans per day- far in excess of the 2.1 checks per day conducted by patients using traditional SMBG techniques and equipment (Dunn et al., 2018). As might be expected, most scans occurred between 6 AM and 12 AM, although patients still averaged 1.6 scans per day during nighttime hours (Dunn et al., 2018). There was a statistically significant variation in the number of scans per day attributed to geographical location, although France was the only geographical region where the number of scans per day was found to be below 14 (Dunn et al., 2018). For the glycemic control parameters that were estimated, the number of scans conducted per day was positively correlated with better control of blood glucose levels (Dunn et al., 2018). That is to say that estimated HbA1C levels and time spend in hypo- or hyperglycemia was inversely proportional to the number of scans. The authors also determined that patient control of blood glucose levels rapidly improved after the adoption of the monitor (Dunn et al., 2018). 

Conclusion 

This study provides strong empirical evidence that the adoption of a continuous blood glucose monitor provides measurable improvement in a patient’s ability to self-manage blood glucose levels. This outcome matches the data found in similar articles in the literature. Klonoff et al. (2017) found similar results in their review of CGM devices and recommended their use by patients with type I DM and provisionally recommended their use for additional patient populations. Olczuk and Preifer (2018) found the data somewhat less compelling but nevertheless suggested that adoption of CGM might be an option for many DM patients and that the field warranted additional research and careful evaluation of new devices as they are released to the market. Perhaps most importantly, the American Diabetes Association (2019) included CGM devices as part of the 2019 recommendations and guidelines for the treatment of DM. Ultimately, it is clear that CGM devices are a novel and exciting addition to the technology that exists for helping patients control their blood glucose. Dunn et al. (2018) make a compelling and well-supported case for the efficacy of these devices, and as suggested by Olczuk and Preifer (2018), it seems prudent to continue to evaluate the technology as it evolves.

References

American Diabetes Association. (2019). 7. Diabetes technology. Standards of Care in Diabetes- 2019, 42(Supplement 1), S71-S80. 

Dunn, T.C., Xu, Y., Hayter, G., & Ajjan, R.A. (2018). Real-world flash glucose monitoring patterns and associations between self-monitoring frequency and glycaemic measures: A European analysis of over 60 million glucose tests. Diabetes Research and Clinical Practice, 137, 37-46.

Kharroubi, A. T., & Darwish, H. M. (2015). Diabetes mellitus: The epidemic of the century. World Journal of Diabetes, 6(6), 850–867. doi:10.4239/wjd.v6.i6.850

Klonoff, Ahn, & Drincic. (2017). Continuous glucose monitoring: A review of the technology and clinical use. Diabetes Research and Clinical Practice, 133, 178-192.

Olczuk, & Priefer. (2018). A history of continuous glucose monitors (CGMs) in self-monitoring of diabetes mellitus. Diabetes & Metabolic Syndrome: Clinical Research & Reviews, 12(2), 181-187.