Personal Continuous Glucose Monitoring Research Articles

Empowering Hospitalized Patients With Diabetes: Implementation of a Hospital-wide CGM Policy With EHR-Integrated Validation for Dosing Insulin.

We aimed to assess the feasibility, clinical accuracy, and acceptance of a hospital-wide continuous glucose monitoring (CGM) policy with electronic health record (EHR)-integrated validation for insulin dosing. A hospital policy was developed and implemented at Stanford Health Care for using personal CGMs in lieu of fingerstick blood glucose (FSBG) monitoring. It included requirements specific to each CGM, accuracy monitoring protocols, and EHR integration. User experience surveys were conducted among a subset of patients and nurses. From November 2022 to August 2023, 135 patients used the CGM protocol in 185 inpatient encounters. This group included 27% with type 1 diabetes and 24% with automated insulin delivery systems. The most-used CGMs were Dexcom G6 (44%) and FreeStyle Libre 2 (43%). Of 1,506 CGM validation attempts, 87.8% met the 20% or 20 mg/dL (%20/20) criterion for CGM-based insulin dosing and 99.3% fell within Clarke zones A or B. User experience surveys were completed by 27 nurses and 46 patients. Most nurses found glucose management under the protocol effective (74%), easy to use (67%), and efficient (63%); 80% of nurses preferred inpatient CGM to FSBG. Most patients liked the CGM protocol (63%), reported positive CGM interactions with nursing staff (63%), and felt no significant interruptions to their diabetes management (63%). Implementation of a hospital-wide inpatient CGM policy supporting multiple CGM types with real-time accuracy monitoring and integration into the EHR is feasible. Initial feedback from nurses and patients was favorable, and further investigation toward broader use and sustainability is needed.

Development of a Continuous Glucose Monitoring Service by Clinical Pharmacists in a Medically Underserved Population.

Background: Continuous glucose monitoring (CGM) is an evolving technology that provides a wealth of information to aid in managing diabetes. Professional CGM (ProCGM) is recommended when personal CGM is not desired or available. Patients in medically underserved areas may have limited access to personal CGM devices, thus ProCGM devices can be used for short-term monitoring and medication adjustment. Clinical pharmacists are well-positioned to help set up and establish personal and professional CGM management services. Objectives: To determine the effect of ProCGM in patients with persistently uncontrolled type 2 diabetes in a medically underserved population (MUP). Methods: Pre-post intervention analysis of a single cohort of patients in a public health center. Patients with persistently uncontrolled (A1c > 9%) and taking at least one daily dose of insulin were included. Included participants wore a ProCGM sensor and met with the clinical pharmacist at least once for ProCGM data interpretation and education. The primary analysis evaluated patients who achieved an A1c <9% 1-6 months after intervention. The change in A1c was also evaluated. Participants completed a pre- and post-survey about their experience. Results: Twenty-two patients were included in the final analysis. Ten patients achieved an A1c <9% (45%). The mean A1c pre- and post-ProCGM was 11.0% and 9.8% respectively, with a decrease of -1.2% (p=0.055) overall and a decrease of -1.7% for patients who wore the sensor for at least 10 days (p=0.012; n=15). Using the CGM data 91% of participants had a change to their medication regimen and 45% achieved an A1c <9%. Six participants experienced hypoglycemia per the CGM report, but only two were aware of it. After reviewing their glucose report with the pharmacist, 95% of the respondents agreed or strongly agreed to feeling more knowledgeable about blood sugar patterns after reviewing the report with a pharmacist. Conclusion: Almost half of the patients in the study achieved an A1c <9%. This study demonstrated glycemic benefit in patients in a MUP who wore a ProCGM for at least 10 days and met with a clinical pharmacist. Data from ProCGM enabled patients to better understand glucose patterns in those with persistently uncontrolled type 2 diabetes.

SAT142 Utilization Of Continuous Glucose Monitoring In Diagnosis And Management Of Insulinoma

Abstract Disclosure: V. Phan: None. P. kretschmer: None. A.G. Pittas: None. Background: Insulinoma is a rare condition that can cause life-threatening hypoglycemia. Its diagnosis and management are challenging due to the requirement of a prolonged fasting test and frequent blood glucose testing. Continuous glucose monitoring (CGM) is widely available in diabetes management; however, its usage in people without diabetes is limited due to lack of evidence. Here, we report an acutely ill patient where we used professional CGM to streamline and expedite the diagnosis of insulinoma, and personal CGM to titrate medical management with diazoxide. Clinical Case: An 81-year-old woman with complex past medical history was admitted for chest pain and shortness of breath, found to have non-ST-elevation myocardial infarction. During inpatient work up, she experienced several hypoglycemia episodes that resolved with oral glucose intake. She had a history of recurrent hypoglycemia and prior MRI showing pancreatic tumor; however, outside records did not reveal biochemical work-up for insulinoma. Her symptoms were unpredictable, so a professional CGM (Freestyle Libre) was placed. CGM data revealed persistent nocturnal hypoglycemia, and occasional postprandial hypoglycemia. Patient-recorded symptoms were present in less than half of the hypoglycemic periods detected by CGM, indicating hypoglycemia unawareness. Given her acute cardiac condition and knowing her nocturnal hypoglycemia pattern from CGM, we performed a modified 72-hour fasting test that started at midnight and was able to capture a hypoglycemia episode within only 2.5 hours of initiation. Her plasma glucose was 57 mg/dL, insulin was 13 uIU/mL, C-peptide was 1.33 uIU/mL, and proinsulin was 9.5 pmol/L. She had a negative screen for sulfonylurea and there was no evidence of antibodies to insulin, suggesting a diagnosis of insulinoma. While awaiting localization studies, the patient was started on diazoxide. We used the personal CGM connected to our clinic portal to monitor glycemia at home and titrate diazoxide dose and frequency. CGM data showed nocturnal hypoglycemia and minimal daytime hypoglycemia, therefore, we recommended diazoxide only at bedtime to minimize daytime side effects and hyperglycemia. On one occasion, the patient was on as short course of prednisone which typically causes hyperglycemia during the day and hypoglycemia in early morning. CGM allowed us to monitor patterns of steroid-induced hyperglycemia, and we moved the prednisone dose to bedtime which resulted in euglycemia overnight. Conclusion: CGM can be a valuable tool in diagnosing and managing people with insulinomas. The CGM provides information about hypoglycemia frequency and pattern. It also helps detect hypoglycemia unawareness. With CGM, we can choose the right timing for 72-hour fasting test to minimize the length of the procedure. As outpatient, CGM also makes monitoring response to diazoxide a seamless process. Presentation: Saturday, June 17, 2023

Evaluating the Clinical Effect of Personal Continuous Glucose Monitoring in a Diverse Population With Type 2 Diabetes.

Objective: To determine the clinical effect of personal continuous glucose monitoring (CGM) in a diverse population with type 2 diabetes (T2D). Research Design and Methods: A report was created from the electronic health record identifying adults prescribed CGM at an urban family medicine clinic between January 1, 2019, and February 23, 2022. An "index date" was identified as the start of CGM. The closest hemoglobin A1c (A1c) 6 months or more after the index date was identified as the "follow-up date." The primary outcome of this study was to compare the percentage of individuals meeting the MN Community Measure (MNCM) D5 HbA1c goal of <8% at the follow-up date versus the index date. Results: Seventy-two patients were identified after the exclusion criteria were applied. Approximately one-third of patients required utilization of an interpreter and 76% of patients were of a racial or ethnic minority. The mean HbA1c prior to CGM use was 9.8%, with 16.7% of the population meeting the MNCM D5 A1c goal of <8%. At the follow-up date, the mean A1c was 8.4% (mean difference -1.4%; p < 0.001), with 41.7% of the population meeting goal (mean difference +25%; p < 0.001). Subgroup analyses affirm that the results of the primary outcome were sustained despite insulin use status. Conclusion: A diverse population with T2D had a significant reduction in A1c and was more likely to meet the MNCM D5 A1c goal of <8% after an average of 6 months using personal CGM.

Importance of continuous glucose monitoring in the treatment of diabetes mellitus

Background: Emerging evidence suggests that controlling both glycemic variability and hemoglobin A1c is necessary to prevent complications associated with diabetes mellitus. Hence, continuous glucose monitoring (CGM) is crucial for effectively managing diabetes.Current Concepts: There are two primary types of CGM. Retrospective CGM only allows the reviewal of glycemic data after the monitoring period, whereas personal CGM allows real-time monitoring. Personal CGM can be further categorized into real-time CGM and intermittently scanned CGM. To interpret CGM data, time in range (TIR) is considered the standard parameter. A TIR of 70–180 mg/dL for more than 70% of the period has been established as a typical target for both type 1 and type 2 diabetes. Other parameters such as time below range, time above range, coefficient of variation, and glucose management indicator should also be reviewed. Importantly, numerous clinical studies have demonstrated the efficacy of CGM in both type 1 and type 2 diabetes.Discussion and Conclusion: A wealth of clinical evidence supports the application of CGM in diabetes, confirming its effectiveness across various treatment stages. CGM has emerged as a compelling therapeutic option in instances when other treatment choices remain limited. With a growing body of clinical evidence, the widespread adoption of CGM in diabetes management appears inevitable. However, challenges related to user comfort, cost, the need for extensive data interpretation, and necessary system improvements remain unaddressed. Further research is required to validate the appropriate usage and frequency of CGM through costeffectiveness analyses.

970-P: Effectiveness of Continuous Glucose Monitoring Use for Diabetes Management in an Academic Endocrinology Practice

The achievement of individualized glycemic targets in patients with diabetes is often a significant challenge. Empowering patients with technological tools in the ambulatory setting can pave the way for improved glucose control. We retrospectively examined the records of 94 patients managed in an academic endocrinology practice who were referred for management of diabetes over a 12-month period. Forty-one patients (18 females and 23 males, average age 57.7 years), who had at least two hemoglobin A1c measurements and two 14-day periods of personal continuous glucose monitoring (CGM) data, were included in the analysis. Nine patients had type 1 and 32 patients had type 2 diabetes. Eight patients were not on any insulin therapy, 8 patients were on basal insulin, 18 were using multiple daily insulin injections, and 7 were managed with insulin pump therapy. A multidisciplinary management approach was utilized. The pharmacologic regimen, including both insulin and other medications, was adjusted every 2-4 weeks via in-person visits and remote data upload as necessary. The average A1c was 8.4% at initial visit and 7.1% at the most recent follow-up, a decrease of 1.3% (p=0.0002). Review of CGM data showed that the average time-in-range (70-180 mg/dl) increased from 63.6% at first CGM download to 74.1% at a mean follow-up of 301 days (p=0.0097), while the amount of time in the hyperglycemic range (time-above-range, &amp;gt;180 mg/dl) decreased from 33.5% to 22.1% (p=0.0079). Time-below-range (&amp;lt;70 mg/dl) remained statistically unchanged, signifying no worsening of hypoglycemia. In conclusion, in ambulatory patients with diabetes and suboptimal glucose control, frequent and tailored adjustments in insulin and noninsulin medications aided by CGM use with close follow-up can lead to significant improvement in glycemic control. The latter, if sustained, can translate to fewer complications and greater patient satisfaction in the long-term. Disclosure K.N.Grennan: None. A.A.Rizvi: None. A.Kathuria: None.

Use of Personal Continuous Glucose Monitoring (CGM) with Support in People with Type 1 and 2 Diabetes Treated with Insulin in the Outpatient Clinic: A Single-Center Retrospective Cohort Study

Use of Personal Continuous Glucose Monitoring (CGM) with Support in People with Type 1 and 2 Diabetes Treated with Insulin in the Outpatient Clinic: A Single-Center Retrospective Cohort Study

An Integrated Digital Health Care Platform for Diabetes Management With AI-Based Dietary Management: 48-Week Results From a Randomized Controlled Trial.

We investigated the efficacy of an integrated digital health care platform with artificial intelligence (AI)-based dietary management in adults with type 2 diabetes (T2D). In this 48-week, open-label, randomized, multicenter clinical trial, overweight or obese adults with T2D were randomly assigned to one of three groups in a 1:1:1 ratio: group A received routine diabetes care; group B used the digital integrated health care platform by themselves; and group C used the platform with feedback from medical staff and intermittently applied personal continuous glucose monitoring. The primary end point was the difference of change in HbA1c from baseline to 24 weeks between groups A and B, while secondary end points included changes in HbA1c from baseline to 48 weeks and changes in body weight during follow-up. A total of 294 participants were randomly assigned to group A (n = 99), B (n = 97), or C (n = 98). The decreases in HbA1c from baseline to 24 and 48 weeks in group B (-0.32 ± 0.58% to 24 weeks and -0.28 ± 0.56% to 48 weeks) and group C (-0.49 ± 0.57% to 24 weeks and -0.44 ± 0.62% to 48 weeks) were significantly larger than those in group A (-0.06 ± 0.61% to 24 weeks and 0.07 ± 0.78% to 48 weeks). Groups B and C exhibited greater weight loss than group A from baseline to 24 weeks, and group C demonstrated more weight loss than group A from baseline to week 48. Among adults with T2D, use of an integrated digital health care platform with AI-driven dietary management resulted in better glycemia and more weight loss.

Peculiarities of using personal continuous glucose monitoring in children and adolescents

Recent data from the International Diabetes Federation indicated that at least 500,000 children aged 14 to 18 years worldwide have type 1 diabetes mellitus (T1DM). Currently, there is no cure for T1DM, so the goal of therapy is to achieve and maintain optimal glucose levels, in particular, using insulin therapy, physical activity, and diet. Studies of more than 20,000 children with T1DM have shown the benefits of self-monitoring of glucose levels for episodic glycemic control and long-term reduction of glycated hemoglobin (HbA1c). The purpose of our study was to investigate the specifics of using personal continuous glucose monitoring (CGM) in adolescents. Materials and methods. According to the design, the study included 22 patients (12 adolescents and 10 children) aged 8 to 16 years who were diagnosed with T1DM. Questionnaires offered included the Pediatric Quality of Life Inventory, the PedsQL Diabetes Module, the Hypoglycemia Fear Survey-II, and the Diabetes Treatment Satisfaction Questionnaire (DTSQ). Results. Before the installation of personal CGM systems, patients had average indicators of emotional, social and role functioning. It was noted that these indicators significantly increased in response to the use of personal CGM (p &lt; 0.05 each), while the parameter of physical functioning did not change significantly (р &gt; 0.05). We did not find a significant correlation between the level of HbA1c and the total score on the DTSQ (ρ = 0.13; p &gt; 0.05). This indicates that satisfaction with treatment is not necessarily related to glycemic control. It was found that children who previously used personal CGM were more compliant with further use of personal CGM (p &lt; 0.05). Among the most frequent drawbacks related to the use of personal CGM, children and their parents mentioned: discomfort from the sensor (62.19 %), the need for calibration, i.e. measuring the glucose level using a portable glucometer (58.61 %), stigmatization of the child who wears the sensor by the surrounding society (47.83 %). Conclusions. In our opinion, the use of personal CGM is appropriate and can be recommended for patients with a newly diagnosed T1DM and with a history of the disease in order to optimize therapy, improve the patient’s awareness of disease control, and increase compliance both in terms of communication with the doctor and general treatment.

Improving Continuous Glucose Monitoring Uptake in Underserved Youth with Type 1 Diabetes: The IMPACT Study.

Background: Continuous glucose monitoring (CGM) improves glycemic control. Less than half of youth with type 1 diabetes (T1D) use CGM, with disparities among minority and low-income youth. The aim of this study was to determine if trial CGM use increases uptake of personal CGM. Methods: T1D youth were provided sample CGM placement at the point of care, with CGM education and app setup. Follow-up calls at 5 and 10 days assessed CGM data, and desire to continue using CGM. Follow-up at 3-6 months recorded CGM use, CGM data, and A1c. Participants completed surveys at enrollment, 10 days, and 3 months. Differences were assessed between baseline and follow-up. Results: Of the 26 enrolled participants with T1D, 15 were CGM naive, and 11 were prior CGM users. The mean age was 14.1 ± 2.9 years, 65% male, 42% were Black, 12% were Hispanic, 65% were on public insurance, and 43% had household income of <$50,000. The median duration of diabetes was 4.6 years (interquartile range 2.4-7.7), mean baseline A1c was 10.7% ± 2.4%. After trial CGM use, 85% of participants reported wanting personal CGM, and at 3-6 months follow-up 76% had obtained one and 43% were using a personal CGM. There were no improvements in A1C or time in range, but participants reported an increase in the perceived benefits of CGM usage (4.0 vs. 4.3, p = 0.03). Conclusions: Placing a sample CGM at the point of care can improve uptake of personal CGM and may help mitigate disparities in CGM use in minority and underserved youth. Long-term studies are needed to determine how similar interventions impact glycemic control and patient outcomes. ClinicalTrials.gov: NCT04721145.

OR28-6 Combating Therapeutic Inertia: Project ECHO for Diabetes Improves Primary Care Providers’ Comfort and Use of Diabetes Medication and Technology

Abstract Background Despite newer diabetes medications and technology being available, therapeutic inertia persists and there are more people living with "uncontrolled" diabetes than meeting A1c targets. Here we evaluate how the ECHO© model for diabetes management changed prescribing practices among participating primary care providers (PCPS). Methodology Three unique diabetes ECHO programs evaluated comfort or perception of prescribing practice changes for local community PCPs (n=74) in four regions (Illinois, District of Columbia, New Mexico, and Washington). One site representing two regions collected pre- and post-program participant surveys (n=45) while two sites collected post-program surveys only (n=29), in which respondents reported perceptions of changes resulting from participation in ECHO. Participants reported their use of technology (professional and personal continuous glucose monitoring (CGM) and insulin pumps) and medications (insulin and non-insulin). Results On a 4-point Likert scale, PCPs’ (n=45) average self-reported prescription use for newer diabetes medications with cardiovascular indications increased from 3.07 (sometimes) to 3.84 (sometimes-always). Presentation: Tuesday, June 14, 2022 11:00 a.m. - 11:15 a.m.

Medical Nutrition Therapy and Other Approaches to Management of Post-bariatric Hypoglycemia: A Team-Based Approach.

This manuscript provides a review of post-bariatric hypoglycemia (PBH) with a special focus on the role of the registered dietitian-nutritionist (RDN) and medical nutrition therapy (MNT) recommendations as foundational for management. As the number of bariatric surgeries rises yearly, with 256,000 performed in 2019, PBH is an increasingly encountered late complication. Following Roux-en-Y (RYGB) or vertical sleeve gastrectomy (VSG), about 1/3 of patients report symptoms suggestive of at least mild postprandial hypoglycemia, with severe and/or medically confirmed hypoglycemia in 1-10%. Anatomical alterations, changes in GLP1 and other intestinally derived hormones, excessive insulin response, reduced insulin clearance, impaired counterregulatory hormone response to hypoglycemia, and other factors contribute to PBH. MNT is the cornerstone of multidisciplinary treatment, with utilization of personal continuous glucose monitoring to improve safety when possible. While many individuals require pharmacotherapy, there are no currently approved medications for PBH. Increasing awareness and identification of individuals at risk for or with PBH is critical given the potential impact on safety, nutrition, and quality of life. A team-based approach involving the individual, the RDN, and other clinicians is essential in providing ongoing assessment and individualization of MNT in the long-term management of PBH.

What Nephrologists Should Know about the Use of Continuous Glucose Monitoring in Type 2 Diabetes Mellitus Patients on Chronic Hemodialysis

Patients with type 2 diabetes (T2D) and end-stage kidney disease (ESKD) on renal replacement therapy represent a specific population with high morbidity and mortality, an increased risk of hypoglycemic episodes and large intra- and interdialysis glycemic variability. Antidiabetic treatment adjustment is therefore challenging, especially in insulin-treated patients. Continuous glucose monitoring (CGM) is increasingly proposed to T2D patients on hemodialysis (HD), although data regarding flash monitoring systems (FMSs) and real-time CGM (rtCGM) in HD patients are limited. Small CGM pilot studies of a short duration demonstrated improvements in glycemic control and decreased hypoglycemic events, despite a lower accuracy of CGM as compared to capillary blood glucose. Moreover, CGM–drug interactions with vitamin C, mannitol and paracetamol can occur in HD diabetic patients and need further study. Despite these shortcomings, professional CGM has the potential to become an integral part of glucose monitoring of HD patients treated with insulin. Personal CGM prescriptions can especially be useful in highly selected, motivated T2D HD patients on multiple daily insulin injections or experiencing frequent hypoglycemia with preserved diabetes self-management abilities or in whom diabetes is fully managed by medical providers. A close collaboration between the clinical staff working on HD units and diabetology teams, and ongoing patient education, are mandatory for optimal use of CGM.

970-P: Management of Diabetes after Hospitalization for COVID-Infection

COVID-infection and its treatment can markedly worsen hyperglycemia. Conversely, patients with diabetes who contract SARS CoV-2 are at increased risk of morbidity and mortality, and their management post-hospital stay can be challenging. The aim of this study was to describe a comprehensive and effective approach for monitoring and treating glucose levels in COVID-patients after hospitalization. Over a period of nine months, 37 patients (13 females and 24 males, average age 64 years) were treated, with 18 having a previously known history of diabetes. All patients received therapy with multiple daily injections of insulin and started on personal continuous glucose monitoring (CGM) for use at home. The patients were evaluated every 2-4 weeks via in-person and telehealth visits. During and in between these visits, the outpatient insulin regimen was adjusted by electronic portal communication and remote data upload via software and individual CGM accounts. Ten patients were on basal insulin, while 27 were on multiple daily insulin injections. At a mean follow-up of 4 months post-discharge, the average hemoglobin A1c decreased from 10.3% to 6.9%, an impressive change of 3.4% (p&amp;lt;0.05) . The average time-in-range (TIR) , a key metric used with CGM, increased from 53% at first post-hospital visit, to 74% at 4 months. In conclusion, patients requiring hospital care after being diagnosed with acute COVID-infection manifest with significant exacerbation of hyperglycemia, and in many cases, new-onset diabetes. Most patients require intensive insulin regimens for diabetes control, often in concert with CGM use; this approach can effectively lower A1c and TIR. It is imperative that patients be provided close follow-up and support by maintaining contact on an ongoing basis. Disclosure A.A.Rizvi: None.

IDF21-0083 Standard deviation

Background: Increased standard deviation (SD) has been previously reported to be associated with increased carotid intima-media thickness. It is well unknown how to simplify standard deviation (SD) and achieve target SD. Aim: We studied how to simplify SD. We also studied regarding the useful metrics for achieving target SD. Method: In a cross-sectional study, we analyzed 24-h glucose levels measured using continuous glucose monitoring (CGM) [Medtronic iPro2; Medtronic MiniMed, Northridge, CA, USA] in 150 patients with type 2 diabetes. We analyzed 51 time in range (TIR) (reference ranges: mean glucose level (M) ± 20, M ± 21 … M ± 69, M ± 70 mg/dL [we referred to the underlined numbers as “Margin”]). We analyzed optimal cutoff values of TIR to predict SD below target, corresponding to 51 TIR × 26 target SD (25, 26 … 49, 50 mg/dL), using receiver operating characteristic analysis. Of the 51 reference ranges, the reference range for which TIR had the largest AUC for each target SD was referred to as “optimal reference range 1”. We arranged the patients in ascending order of SD, ranking from 1 to 150. Consecutive 110 patients were selected 41 times while shifting one by one (from “1–110” to “41–150”: 41 groups). Of the 51 reference ranges, the reference range for which TIR most correlated to SD for each group was referred to as “optimal reference range 2”. Results: Mean absolute deviation (MAD) correlated to SD (r = 0.995, p < 0.001; MAD = 0.87 × SD - 1.22) (n = 150). “Margin” of “optimal reference range 1” (M1, mg/dL) tended to increase with increased target SD (mg/dL), from 42 for “target SD of 25” to 66 for “target SD of 50”. Target SD correlated to M1 (r = 0.92, p < 0.001; M1 = 1.31 × target SD + 5.56) (n = 26). The optimal cutoff values of TIR for “optimal reference range 1” was 86.8 ± 4.6 % in 26 target SD. “Margin” of “optimal reference range 2” (M2) tended to increase with increased mean of SD, from 35 for “mean of SD of 30.6” to 64 for “mean of SD of 47.7”. Mean of SD correlated to M2 (r = 0.96, p < 0.001) (n = 41). Discussion: SD means difference from M. If “optimal reference range 1” is used as an alarm threshold in a personal CGM and TIR for “optimal reference range 1” > 80–90 % is achieved, SD below the target may be achieved. The mean of SD in study participants may affect the M2.

Abstract P158: Hypoglycemia Prediction From The Coefficient Of Variation For Each Hba1c Value

It has also been reported that the coefficient of variation (CV) corresponding to the number of hypoglycemia cases decreases as HbA1c values decrease. Therefore, when an association between the CV and hypoglycemia is considered, the possibility that the CV varies according to HbA1c values should be considered. If hypoglycemia can be predicted from both HbA1c values and the CV, the relationship between glycemic variability and hypoglycemia can be assessed in detail. Thus, we studied a formula that could predict hypoglycemia based on HbA1c values and the CV. Materials and Methods This was a prospective observational study. One hundred and one outpatients with type 2 diabetes mellitus underwent HbA1c testing, wore a flash glucose monitor (FGM: FreeStyle Libre Pro, Abbott Diabetes Care, Alameda, CA, USA), and did not change diabetic treatment at the hospital visit. The CV and mean glucose levels were calculated using the FGM data over 24-h х 13 days. The glucose management indicator (GMI) was calculated using the mean glucose levels, and we compared the GMI to the HbA1c values mainly to detect differences between sensor glucose levels (SG) and blood glucose levels. It has been previously reported that the HbA1c value minus (-) GMI &gt;0.5% is associated with the risk of hypoglycemia, and the GMI - HbA1c value &gt;0.5% is associated with the risk of hyperglycemia. Therefore, we assessed the difference between the GMI and HbA1c value with real numbers. We calculated the “percentage of mean absolute deviation to mean glucose levels” (Metric1) as a new metric. Hypoglycemia (&lt;70 mg/dL) absence could be significantly predicted from the CV, HbA1c value, and “glucose management indicator (GMI) minus HbA1c value” (ΔA1c) (Nagelkerke=0.68, p&lt;0.001). When a response variable was hypoglycemia absence and explanatory variables were the CV, HbA1c value, and ΔA1c, the optimal predicted value for the logistic regression analysis was 0.35 (sensitivity: 90%, specificity: 84%; area under the curve: 0.93, p&lt;0.001) (predicted values=1÷(1+e -(-0.28хCV+2.18хHbA1c+1.85хΔA1c-7.48) ) [e: Napier's constant]), where CVs corresponding to HbA1c values of 6%, 7%, 8%, 9%, and 10% were 22.0%, 29.8%, 37.5%, 45.3%, and 53.0%, respectively. The CV correlated with Metric1 (r=0.99, p&lt;0.001, Metric1=0.82хCV-0.006 [formula1]). The CV should be reduced more to prevent hypoglycemia as HbA1c values decrease. For avoiding hypoglycemia, an “alarm threshold using ‘mean glucose levels (Mean) corresponding to the HbA1c values’, and ‘Metric 1 corresponding to the CV calculated using formula 1’ ” (Mean ± Mean х Metric 1 ÷ 100) should be used for personal continuous glucose monitoring, and all glucose levels should be kept within the alarm threshold.

A Position Statement of the Utilization and Support Status of Continuous Glucose Monitoring in Korea

The accuracy and convenience of continuous glucose monitoring (CGM), which efficiently evaluates glycemic variability and hypoglycemia, are improving. There are two types of CGM: professional CGM and personal CGM. Personal CGM is subdivided into real-time CGM (rt-CGM) and intermittently scanned CGM (isCGM). CGM is being emphasized in both domestic and foreign diabetes management guidelines. Regardless of age or type of diabetes, CGM is useful for diabetic patients undergoing multiple insulin injection therapy or using an insulin pump. rt-CGM is recommended for all adults with type 1 diabetes (T1D), and can also be used in type 2 diabetes (T2D) treatments using multiple insulin injections. In some cases, short-term or intermittent use of CGM may be helpful for patients with T2D who use insulin therapy other than multiple insulin injections and/or oral hypoglycemic agents. CGM can help to achieve A1C targets in diabetes patients during pregnancy. CGM is a safe and cost-effective alternative to self-monitoring blood glucose in T1D and some T2D patients. CGM used in diabetes management works optimally with proper education, training, and follow up. To achieve the activation of CGM and its associated benefits, it is necessary to secure sufficient repetitive training and time for data analysis, management, and education. Various supports such as compensation, insurance coverage expansion, and reimbursement are required to increase the effectiveness of CGM while considering the scale of benefit recipients, policy priorities, and financial requirements.

Personal Continuous Glucose Monitoring Use Among Adults with Type 2 Diabetes: Clinical Efficacy and Economic Impacts.

Purpose of ReviewThis article reviews recent clinical efficacy research and economic analysis of the use of personal continuous glucose monitoring (CGM) in type 2 diabetes (T2D).Recent FindingsStudies from the past 5 years include a variety of randomized controlled trials, meta-analyses, and other studies which generally favor CGM over self-monitoring of blood glucose (SMBG) in T2D, especially among people with T2D treated with insulin. Concurrently, some studies show no significant difference, but there is no evidence of worse outcomes with CGM. CGM is frequently associated with greater reduction in HbA1c than is SMBG. HbA1c reductions tend to be greater when baseline HbA1c is higher. Reductions in hypoglycemia and hyperglycemia have also been demonstrated with CGM in people with T2D, as have comfort with, preference for, and psychosocial benefits of CGM compared to SMBG. There is a small but growing evidence base on the economics and cost-effectiveness of CGM in T2D.SummaryCGM has been clearly demonstrated to have clinical benefits in people with T2D, especially among those treated with insulin. Economic and cost-effectiveness data are more scant but are generally favorable. CGM should be an important consideration in the management of T2D, and its use is likely to increase as efficacy data accumulate further and as costs associated with CGM gradually decrease.

Continuous glucose monitoring in persons with type 2 diabetes not using insulin

ABSTRACT Introduction CGM is an evidence-based intervention to improve glycemic control in persons with T1D and T2D using insulin. Use of CGM in persons with T2D not using insulin is not well studied. Areas covered Existing clinical evidence for the use of CGM in persons with T2D is reviewed with a focus on persons with T2D not using insulin. Additional perspective and consideration are provided on the role and rationale for using CGM in persons with T2D not using insulin. Expert opinion On the basis of available evidence, persons with T2D not using insulin benefit clinically through reduction in HbA1c, and improvement in time in range. Additional benefits include improvement in behavior modification, satisfaction, quality of life, empowerment, and diabetes distress. Drivers of these benefits are independent of insulin use in persons with T2D and may include an improved understanding of how diet, lifestyle, and exercise impact diabetes through CGM use. Clinical benefits from CGM independent of medication use include ability to modify health behavior and subsequently improve self-management.

Describing the application and barriers of pharmacist‐led professional continuous glucose monitoring in the ambulatory care setting

AbstractIntroductionAdvances in technology for continuous glucose monitoring (CGM) contribute to the care of persons with diabetes and CGM systems are recommended in multiple guidelines. There are limited studies describing CGM use by clinical pharmacists in the ambulatory care setting.ObjectivesThe primary objective of this study is to identify and describe the current use, application, and barriers of CGM by clinical pharmacists in the ambulatory care setting. Secondary objectives include identifying the prevalence of professional CGM use by clinical pharmacists, recognizing specific barriers faced by pharmacists when implementing professional CGM into clinical practice, and determining interest in professional CGM implementation by ambulatory care pharmacists as an alternative for patients unable to afford personal CGM.MethodsThis was a self‐administered, voluntary, web‐based questionnaire distributed to 2207 ambulatory care pharmacists. Questions were stratified to identify the clinical use and barriers for those who do and do not use professional CGM, respectively. The survey was active for 9 weeks and results from the survey were analyzed based on question type.ResultsOne hundred and eighty five survey responses were included in the study results. Most participants (70.8%) indicated currently working in a primary care clinic, and 8.1% indicated working in an endocrinology office. Results identified that 18.9% of participants use personal CGM and 35.1% use professional CGM to facilitate the management of persons with diabetes. The most common barriers to professional CGM implementation include lack of funding for startup costs (65.9%), lack of time for device placement and result interpretation (45.8%), and unpredictable patient follow‐up (48.3%).ConclusionStudy participants indicated that the majority of patients they manage have diabetes; however, lack of education and training on device use, data interpretation, and reimbursement opportunities were commonly cited barriers to CGM use. Additional training opportunities should be considered to facilitate the implementation of CGM by ambulatory care pharmacists into clinical practice.