Continuous Glucose Monitor Usage in Diabetic Foot Ulcer Management: A Narrative Review

Diabetic foot ulcers (DFUs) are among the most prevalent and serious complications of diabetes due to injury of the peripheral nervous system and lower limb arterial disease. DFUs affect up to 15% of patients with diabetes, posing risk for hospitalization as well as being the primary cause of minor and major amputation in those with the disease.¹ Although recent papers report a progressive reduction of amputation rates in many developed countries, mainly Europe and the USA, nowadays more than 1 million patients with diabetes worldwide are amputees.¹

Although discussions exist on how continuous glucose monitors (CGMs) can help manage blood glucose levels and identify microvascular complications, none have identified the possible benefits in monitoring and treating diabetic complications such as DFUs. This article will review the literature and critically evaluate the application of continuous glucose monitors and time in range in relation to diabetic foot ulcer management.

Hemoglobin A_1c (HbA_1c), also known as glycosylated hemoglobin, is a biomarker for the severity of an individual’s hyperglycemia. Huisman and colleagues first separated HbA_1c from other types of hemoglobin in 1958 using a chromatographic column.² In 1968, Bookchin and Gallop³ identified HbA_1c as a glycoprotein and a year later, researchers discovered that individuals with diabetes tend to have an increase in HbA_1c. Koenig and colleagues found that HbA1c is a monitoring tool for the level of longer-term glucose control in patients with diabetes4 and since then this value has been regarded as the gold standard test to assess glycemic control over an approximately 3-month period. Hemoglobin A_1c measures the quantity of glycated hemoglobin as a percentage of the red blood cells (RBCs) that have glucose-coated hemoglobin.⁵

Hemoglobin itself is the protein molecule in RBCs that carries oxygen from the lungs to the body’s tissues and returns carbon dioxide from the tissues back to the lungs. Within a RBC, glucose irreversibly attaches to hemoglobin to form glycated hemoglobin. Since RBCs have a lifespan of approximately 100–120 days, HbA_1c is only able to measure the average plasma glucose levels over the previous 2–3 months.

Although target HbA_1c goals differ amongst varying populations, the American Diabetes Association has come to a consensus on some general guidelines.⁵ A normal HbA_1c is under 5.7%. The prediabetes range is 5.7–6.5%. An individual diagnosed with diabetes will have a HbA_1c above 6.5%. The ADA has also established a general correlation between HbA_1c values and the average blood glucose in mg/dL and mmol/L that these percentages roughly represent, as shown in Figure 1.⁶    

There is no doubt as to the value of HbA_1c; however, there are limitations to solely relying on this metric. HbA_1c represents an average blood glucose over a period of months, so it does not capture critical information such as time spent in a target range (70–180 mg/dL) during a hypoglycemic or hyperglycemic episode. One may address the limitations of HbA_1c and the other supplemental tests by focusing on time in range values, which stem from interstitial glucose as opposed to blood glucose measurement. Glucose, in fact, diffuses out of the blood vessels and into the interstitial fluid that surrounds the cells within the tissue. A continuous glucose monitor can measure interstitial glucose.⁷

How Does a CGM Work?

Continuous glucose monitoring allows patients to record real-time blood glucose data, using sensors and either transmitters, monitors, or their phones. CGMs use wired enzyme glucose sensing technology to detect glucose levels in the interstitial fluid every 1–5 minutes. Patients insert sensors subcutaneously, and typically wear them for 10–14 days before replacement. CGMs provide information to the patient’s device on time in range, glucose fluctuations, trends, and alarms when glucose levels are out of range.⁸

A CGM has 3 main components: a sensor, transmitter, and receiver.⁸ Although there are a few popular options, one common system is the Freestyle Libre (Abbott). The sensor is a very thin wire or filament, inserted with the aid of a needle under the skin, usually on the abdomen or arm. An individual only feels mild discomfort upon insertion but it is otherwise pain-free for the entirety of the 14-day application period. This eliminates the need to fingerstick every morning. The sensor attaches to a small transmitter. As the conduit between the sensor and the receiver, the transmitter wirelessly sends information to the receiver through radio waves. The receiver wirelessly transmits information from the sensor via Bluetooth to the patient’s device, which displays current levels and stores past readings.⁹

CGM systems have evolved immensely over the past few years, expanding options available for patients. These systems provide out of range alerts and the option to share data with others, including family members and health care providers. Dexcom (Dexcom) and Guardian 6 (Medtronic) CGMs serve as real-time sensors, transmitting data continuously to a transmitter device or phone. Freestyle Libre instead acts as an intermittently scanned CGM, requiring the patient to scan the sensor using their phone or reader device.

Acquiring Data from the Literature and Sample Reports

We conducted a narrative literature review using PubMed and Embase databases. The initial search used the keywords “continuous glucose monitoring” AND “time in range” AND “a1c” and yielded 797 and 297 results on Embase and PubMed, respectively. The exclusion criteria included articles written in a language other than English, a focus on pathology unrelated to diabetes, and written before January 1, 2012. This search yielded 8 articles. The inclusion criteria were articles that monitored changes in mmol/mol of blood sugar after use of the continuous glucose monitors. Application of the aforementioned inclusion and exclusion criteria yielded 4 papers. Of those, we used 3 research articles in this literature review because they specifically focus on metrics.

Another literature search on PubMed used the term "continuous glucose monitoring" AND “diabetes” and yielded 11,994 articles. The exclusion criteria included articles written in a language other than English, a focus on pathology unrelated to diabetes, research studies conducted by the manufacturers of continuous glucose monitors, and those written before January 1, 2012. This search yielded 504 articles. Inclusion criteria encompassed articles that focus on the effectiveness of continuous glucose monitors as opposed to the technology, costs, or regulatory aspects of the device, yielding 88 results. After abstract and full-text evaluation, we selected 2 articles and included them in this study based on usage indicated for patients with diabetes and CGM usage in maintaining glucose levels.

We conducted an additional literature review on PubMed and Embase to highlight the usage of time in range in detecting microvascular complications. The keywords “time in range type 2 diabetes microvascular complications” yielded 82 results from PubMed and 161 results from Embase. The exclusion criteria included articles written in a language other than English and written before January 1, 2012. This search yielded 54 articles from PubMed and 118 articles from Embase. The inclusion criteria were articles that focused on the usage of continuous glucose monitors to track time in range and vascular complications. Of those, 9 articles were identified, 3 were used in this literature review based on the specificity in relating time in range with microvascular complications.

A literature search was also conducted using Embase with the search keywords “continuous glucose monitoring” AND “podiatry” The exclusion criteria included articles written prior to January 2012. The inclusion criteria were articles involving CGM involvement in physiological prevention and treatment of podiatric medicine yielding 3 articles. We selected 1 article from the results and used in this review. 

Three Abbott LibreView CGM reports were obtained from the patient report cloud libreview.com from the author’s Endocrine Associates of West Village endocrinology clinic. The first report was randomly selected out of 394 patient profiles on August 28, 2021. Each category displayed on the reports were summarized and an explanation provided on its use in evaluation of diabetic care. The latter two reports were selected based on a search for patients with the same Glucose Management Indicator (GMI), sorting from the lowest to highest GMI and differing Glucose Variability. These reports were further evaluated and compared using their TIRs and daily glucose profiles.

What Does the Literature Reveal?

Based on inclusion and exclusion criteria, we identified a total of 150 studies. After abstract and full text review, we included 9 studies published between January 1, 2012 to August 1, 2022. This includes 3 articles pertaining to continuous glucose monitoring, 2 articles on the effectiveness of CGMs in diabetes glucose management, 3 articles discussing the correlation of time in range with microvascular complications, and 1 article discussing CGM usage in podiatric medicine. Below is an overview of key takeaways from our review.

HbA_1c Data. The International Federation of Clinical Chemistry (IFCC) and the NGSP National Glycohemoglobin Standardization Program (NGSP) have established methods that labs use to verify HbA_1c results. These methods of standardization enable labs to report Diabetes Control and Complications Trial (DCCT) traceable HbA_1c values.¹⁰ The DCCT was a landmark medical study conducted by the United States National Institute of Diabetes and Digestive and Kidney Diseases ranging from 1982–1993. The main takeaway from the trial was that intensively controlling HbA_1c in patients with type 1 diabetes to around 7% keeps microvascular complications such as retinopathy at bay, compared to allowing HbA_1c to drift up to 9%. The trials made it clear that A_1c is a valuable tool for patients with diabetes.

Also, NGSP reports that a single A_1c test can have up to a 0.5% margin of error, which means the “true” value might be 0.5% higher or lower than the measured HbA_1c. This can be very misleading in the case of a borderline reading, considering hypoglycemic and hyperglycemic states can have severe consequences to the health of a patient with diabetes. Additionally, there is incredible variation in HbA_1c values amongst people for reasons unrelated to blood glucose. For example, individuals may have different hemoglobin variants, they may have differences in how RBCs and blood sugars bind, and the lifespan of the RBC may be different across the board.¹¹ Remembering that the 3-month picture of the HbA_1c does not account for time in range, nor day to day variations, the literature supports the clinical challenges with HbA1c as a solo metric.

Comorbid Conditions and Medications. Other conditions may impact HbA_1c as well. Kidney disease, for example, falsely leads to elevated HbA_1c. Pregnancy decreases the lifespan of the red blood cell, and therefore the increased RBC production may lower HbA_1c too. Untreated anemia from either B12 or iron deficiency decreases the RBC production and in turn increases HbA_1c. Untreated hypothyroidism increases HbA_1c due to decreased levels of thyroid hormone. Opioid medications or long-term use of over 500 mg of aspirin a day may increase HbA_1c. Other medications such as erythropoietin, Aczone (Almirall), Virazole (Bausch Health), and HIV medications may also decrease HbA_1c. Hepatic cirrhosis affects not only a person’s response to insulin, but also a results in a misleadingly low HbA_1c. Infrequently taken HbA_1c readings often make these misleading values a challenging barrier to proper diabetes care.¹²

Vitamin C, abundantly present in many diets, may also be used in treating cancer and viral infections. Large concentrations of vitamin C can cause falsely elevated glucose levels in Abbott CGM systems compared to blood glucose readings.¹³

In CGM systems that measure hydrogen peroxide, such as Dexcom sensors, acetaminophen may also cause false elevations in glucose values when compared to blood glucose readings. Acetaminophen’s phenolic moiety is oxidized at the sensing electrode, leading to an electrochemical signal that shows an elevation in glucose, despite being independent of glucose.¹⁴

Consensus Points on Time in Range. Despite the benefits of the different tests to determine glucose status (A_1c, GlycoMark, fructosamine), there are glaring limitations still present. It is still difficult to assess the time an individual spends in a day within an appropriate glucose range. The data provided by CGMs show patients and practitioners a potentially more accurate daily blood glucose profile. To promote widespread use of such a data collection method, measures were taken to standardize the results provided by continuous glucose monitors.

The Advanced Technologies & Treatments for Diabetes Congress organized an international panel of individuals with diabetes, clinicians, and researchers with expertise in CGM to develop standardized CGM metrics. The following are some guidelines set forth by the 2017 and 2019 consensus panels.^15,16

2017 Consensus Panel. The panel identified time in range (TIR) as the specific metric to use to guide therapeutic decision-making over HbA1c alone.¹⁵ They defined distinct TIR categories as follows:¹⁵  
    1.    Time below range (TBR) level 2: very low
    2.    TBR level 1: low
    3.    TIR
    4.    Time above range (TAR) level 1: high
    5.    TAR level 2: very high

2019 Consensus Panel. The panel met again to define specific clinical targets for the previously determined CGM metrics. They decided on targets for glycemic cut points and time per day (expressed as a percentage of CGM readings and minutes/hour) not only in individuals with type 1 or type 2 diabetes, but also in other populations, including pregnant women with gestational diabetes and older/high-risk patients.¹⁶

They updated the TIR categories as follows:¹⁶
    1.    TBR level 2 (very low): <54 mg/dL and <1%
    2.    TBR level 1 (low): 54–69 mg/dL and <4%
    3.    TIR: 70–180 mg/dL and >70%
    4.    TAR level 1 (high): 181–250 mg/dL and <25%
    5.    TAR level 2 (very high): >250 mg/dL and <5%

CGMs and Radiological Studies. In the event of radiological procedures such as an MRI or X-ray, one must remove implanted devices such as CGMs. The functional integrity of the CGM post–aforementioned procedures may remain intact, as shown through a study with 48 Dexcom G6 transmitter/sensor units placed inside the coil of an MRI with no data loss or corruption.¹⁷ However, the presence of a CGM sensor remains unsafe for the patient during the procedures due to the metal filament present. In addition, the device may cause alterations in and reduce the quality of the obtained images. However, the presence of a CGM sensor remains unsafe for the patient during the procedures when the metal filament is exposed to radiation/MRI.        

Microvascular Complications. Type 2 diabetes may lead to a wide range of long-term microvascular complications including the triad of diabetic retinopathy, nephropathy, and neuropathy. TIR measured by CGMs may serve as a predictor of these microvascular complications among patients with diabetes. In a 2020 study, a significant inverse relationship existed between the severity of patients’ diabetic retinopathy and TIR measured by Freestyle Libre Pro CGMs.¹⁸ Additionally, a 2022 study utilizing CGMs to measure of glycemic variability and its association with small nerve fiber injury, researchers found lower corneal nerve branch density in patients with higher glycemic variability (P = .007).¹⁹  

Studies also support an association between TIR and diabetic nephropathy severity measured by albuminuria. Specifically, 2 studies have shown a decrease in albuminuria levels alongside a 10% increase in TIR.¹⁸

The severity of diabetic peripheral neuropathy has a link with TIR in multiple studies. In a prospective observational cohort study from 2020, the authors assessed the relationship between TIR and diabetic peripheral neuropathy using the Michigan Neuropathy Screening Instrument (MNSI) to measure symptoms and Medtronic Enlite sensor to measure interstitial glucose levels. There was a significant difference between patients within TIR > 70% of the time, with 43% prevalence of diabetic peripheral neuropathy versus the 74% neuropathy prevalence of those < 70% within the TIR.²⁰ In another 2020 study investigating the relationship between TIR through CGM and peripheral neuropathy, researchers placed 740 patients with type 2 diabetes into tertiles based on their TIR.²¹ Confounding factors such as age, diabetes duration, height, and weight were adjusted, revealing a correlation between a higher TIR and higher composite Z score of nerve conduction velocity (P< .0001), indicating better peripheral nerve function with a higher TIR.

CGM Sample Data Insights

A CGM report from the patient report cloud from the author’s Endocrine Associates of West Village clinic mentioned above shows the data converted into an Ambulatory Glucose Profile (AGP), a 1-page standardized report including glucose statistics and targets, TIR, a glucose profile graph, and daily glucose profiles. Time in range is the percentage of time in which a patient’s glucose is in the target range. The TIR portion of the AGP provides a summary across 3 categories, indicating the percentage of time a patient was in target (70–180 mg/dL), hypoglycemic (<70 mg/dL), and hyperglycemic (>180 mg/dL). Both time below range and time above range further divides into the 2017 consensus levels.¹⁵ Level 1: low, level 2: very low, and level 1: high, level 2: very high, respectively.

As supplements to the information provided by TIR, we can break down glucose statistics into percentage of time CGM is active, average glucose, glucose management indicator (GMI), and glucose variability. The percentage of time the CGM is logged as active reveals the time during which the CGM could acquire readings. The reliability of the report on a patient’s normal patterns depends on the percentage of CGM active time, recommended as > 70% for 14 days by the International Consensus on Time in Range.¹⁵ The AGP also adds a HbA_1c component. Given the average glucose, the report produces a GMI, which serves as an estimated HbA_1c. The glucose variability indicates the percentage of fluctuations from the patient’s average glucose value. The glucose profile graph and daily glucose profiles also reveal the patient’s daily trends, specifically what times of the day the patient experiences changes in glucose levels.

TIR provides a more thorough view of a patient’s glycemic control compared to HbA_1c by evaluating daily trends and identifying durations of hyperglycemic and hypoglycemic occurrences. Between the 2 summary reports provided from the clinic’s patient portal, the patient in the Figure 6 has more fluctuating glucose levels as suggested by the higher variability. The graphs for daily glucose profiles highlight both the patient’s hyperglycemic and hypoglycemic episodes, representing less glycemic control, which would not be indicated through the patient’s HbA_1c.¹⁰

Patients and healthcare providers can access CGM data by viewing the device or the cloud through uploading or remote monitoring. As an example to understand the impact of glucose trends, 2 patients may have the same average glucose and GMI. However, based on the variability, TIR, and daily glucose profiles, one patient may have consistent glucose levels while the other has a lower target range with a higher amount of fluctuating glucose levels. CGMs also provide a more accessible way for patients to observe their blood glucose levels without having to check finger sticks multiple times each day, which can be tedious and painful.

How Else Might Continuous Glucose Monitoring Be Beneficial to Podiatrists?

Access to AGP reports can open doors for all physicians—specifically podiatrists. A complete profile of day-to-day TIR allows practitioners to work with one another to improve health outcomes,¹⁰ and provides clear data to contribute to medical decision-making.

CGM monitoring provides vital information in podiatric management of patients. During a podiatric surgical procedure, as long as the team protects the CGM radiation, it provides information for the anesthesiologist to better manage intraoperative blood glucose. We have noted that many hospitals now allow patients to wear their CGM for better management of glycemic control during surgical procedures and inpatient stays. Also, since wide fluctuations in blood sugar contribute to diabetic peripheral neuropathy, CGM data combined with HbA_1c values may help one counsel a patient more effectively.^22,23 The patient can then work with their multidisciplinary team to target interventions, with the podiatrist playing a key role.

Fear of hypoglycemia is a stumbling block for some patients. Real-time data from a CGM can alleviate the fear of having a hypoglycemic crisis and thus provide greater control of diabetes. Also, patients can use the CGM for lifestyle changes such as changing eating habits. Patients can learn to enjoy foods in moderation instead of partaking in total avoidance or overindulging. Exercise after a carbohydrate-loaded meal while using a CGM may offer positive feedback to prevent excessive blood sugar rise and reinforce positive behavior. Lastly, elevated blood sugar can be a sign of a brewing infection before active signs of infection emerge. A patient may benefit from this knowledge and alert their healthcare provider of any changes.

Podiatrists see firsthand the relationship between glucose control and wound healing. A study conducted by Dhatariya and colleagues in 2018 found a statistically significant association between HbA_1c variability and time to healing. In the low HbA_1c variability group, the geometric mean days to heal was 78.0 days (60.2 to 101.2) vs 126.9 days (102.0 to 158.0) in the high HbA_1c variability group (P=.032).²⁴

In a retrospective study conducted on patients with DFUs with an initial surgery, patients in the TIR <50% group exhibited a higher rate of secondary surgery (15.4% vs 26.2%, P = .032) and longer hospital stay (median, 13.0 days vs 15.5 days, P = .045).²⁵ Additional subgroup analyses performed with the consideration of heterogeneity identified a higher incidence of an additional surgery in groups with a baseline A1c <7.5% vs those with a baseline >7.5%.

In another 2022 retrospective study, researchers evaluated the impact of TIR in toe reamputation and postoperative infection.²⁶ The study displayed a negative correlation between TIR and toe reamputation when comparing patients with TIR <70% and TIR > 70%. In addition to toe reamputation, the study also found a significantly lower rate of postoperative infection in the TIR ≥ 70% group (P=.019) and shorter length of stay (P=.032).

Further studies are necessary to better identify the relationship between TIR and worsening of a patient’s DFU condition.

In Conclusion

HbA_1c has provided both health care experts and patients with diabetes with information to help prevent several life-threatening complications from diabetes. However, solely using HbA_1c levels does not ascertain daily glucose patterns, nor does it identify hypoglycemic and hyperglycemic episodes. An alternative—a better one at that—is using CGMs to acquire TIR data and glucose trends. In doing so, one may note more accurate representation of glucose patterns, and more easily identify damaging glucose fluctuations. Implementing CGMs into diabetes management works to overcome the disadvantages of HbA_1c and provides the ever-growing population of patients with diabetes as well as podiatrists with an additional tool in the fight against severe complications such as diabetic foot ulcers, related surgeries, and potential amputations.

Sophia Quach, BS, is a third-year medical student at New York Medical College.

Ayushi Deshwal, DPM, is a second-year podiatry resident at Ascension St. Joseph Chicago.

Jean Chen-Vitulli, DPM, MS, is a Diabetes Educator at Endocrine Associates of West Village in New York City. She is a Podiatric Medicine and Wound Care Researcher at Endocrine Associates of West Village in New York City.

Anastasios Manessis, MD, FACE, ECNU, ABOM is an Attending Physician at NYU Langone Health Center, New York Presbyterian/Lower Manhattan Hospital, and Mount Sinai Hospital. He is the Medical Director of Endocrine Associates of West Village in New York City. He is the Founder and Clinical Director of NeXendo Wellness and Weight Loss Center at Endocrine Associates of West Village.

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