Real-time Continuous Glucose Monitoring Research Articles

Cost-Utility of Real-Time Continuous Glucose Monitoring versus Self-Monitoring of Blood Glucose in People with Insulin-Treated Type 2 Diabetes in Spain

Cost-Utility of Real-Time Continuous Glucose Monitoring versus Self-Monitoring of Blood Glucose in People with Insulin-Treated Type 2 Diabetes in Spain

The benefits and accuracy of real-time continuous glucose monitoring in children and adolescents with type 1 diabetes attending a summer camp.

This study evaluated the usability, satisfaction, and accuracy of a real-time continuous glucose monitoring (rt-CGM) in children and adolescents with type 1 diabetes (T1D) attending a summer camp. Seven children and adolescents with T1D (camper) and 31 of healthcare providers (HCPs) participating in a 2-day summer camp in Kumamoto, Japan were enrolled. The usability and satisfaction were evaluated by tailored questionnaire. The accuracy of rt-CGM was evaluated using self-monitoring of blood glucose (BG) and sensor glucose (SG) values before or after (off camp) and during (on camp) the camp. The score of the usefulness of rt-CGM showed 3.29 ± 0.90 in campers and 4.23 ± 0.87 in HCPs (P = 0.017). The degree of recommendation score for rt-CGM was 3.29 ± 1.11 in campers and 4.23 ± 0.79 in HCPs (P = 0.013). Time in range (TIR) off camp was 45.9% and that on camp was 57.0%. Time above range (TAR) off camp was 53.4% and that on camp was 42.4%. The mean absolute relative difference (MARD) off camp was 19.7% ± 25.2%, whereas that on camp was 16.0% ± 14.8% (P = 0.367). Clinically acceptable zones of the error grid analyses were approximately 96% in total. Rt-CGM exhibited higher usability and recommendation scores in HCPs than those in campers. This may be related to relatively lower accuracy in rt-CGM. Overall usability and recommendation are clinically satisfactory, but due to relatively low accuracy, no decision should be made based on a single, non-verified SG value alone.

Machine Learning Algorithms Based on Time Series Pre-Clustering for Nocturnal Glucose Prediction in People with Type 1 Diabetes

Background: Machine learning offers new options for glucose prediction and real-time glucose management. The aim of this study was to develop a machine learning-based algorithm that takes into account glucose dynamics patterns for predicting nocturnal glucose in individuals with type 1 diabetes. Methods: To identify glucose patterns, we applied a hierarchical clustering algorithm to real-time continuous glucose monitoring data obtained from 570 adult patients. Machine learning algorithms with or without pre-clustering were used for modeling. Results: Eight clusters without nocturnal hypoglycemia and six clusters with at least one low-glucose episode were identified by the cluster analysis. When forecasting time series without hypoglycemia with a prediction horizon (PH) of 15 or 30 min, gradient boosting trees (GBTs) with pre-clustering and random forest (RF) with pre-clustering outperformed algorithms based on medoids of time series clusters, the Holt model, and GBTs without pre-clustering. When forecasting time series with low-glucose episodes, a model based on the pre-clustering and GBTs provided the highest predictive accuracy at PH = 15 min, and a model based on RF with pre-clustering was the best at PH = 30 min. Conclusions: The results indicate that the clustering of glucose dynamics can enhance the efficacy of machine learning algorithms used for glucose prediction.

Transitioning from Self-Monitoring of Blood Glucose to Continuous Glucose Monitoring in Combination with a mHealth App Improves Glycemic Control in People with Type 1 and Type 2 Diabetes.

Introduction: Integrating mobile health (mHealth) apps into daily diabetes management allows users to monitor and track their health data, creating a comprehensive system for managing daily diabetes activities and generating valuable real-world data. This analysis investigates the impact of transitioning from traditional self-monitoring of blood glucose (SMBG) to real-time continuous glucose monitoring (rtCGM), alongside the use of a mHealth app, on users' glycemic control. Methods: Data were collected from 1271 diabetes type 1 and type 2 users of the mySugr® app who made a minimum of 50 SMBG logs 1 month before transitioning to rtCGM and then used rtCGM for at least 6 months. The mean and coefficient of variation of glucose, along with the proportions of glycemic measurements in and out of range, were compared between baseline and 1, 2, 3, and 6 months of rtCGM use. A mixed-effects linear regression model was built to quantify the specific effects of transitioning to a rtCGM sensor in different subsamples. A novel validation analysis ensured that the aggregated metrics from SMBG and rtCGM were comparable. Results: Transitioning to a rtCGM sensor significantly improved glycemic control in the entire cohort, particularly among new users of the mySugr app. Additionally, the sustainability of the change in glucose in the entire cohort was confirmed throughout the observation period. People with type 1 and type 2 diabetes exhibited distinct variations, with type 1 experiencing a greater reduction in glycemic variance, while type 2 displayed a relatively larger decrease in monthly averages.

7296 Gestational Diabetes RT-Continuous Glucose Monitoring Users Utilized Fingerstick less in Pregnancy than Recommended Compared to Fingerstick Monitoring Alone with No Difference in A1c Outcomes

Abstract Disclosure: N.M. Ehrhardt: Advisory Board Member; Self; Bayer, Inc., Novo Nordisk, Dexcom. Grant Recipient; Self; Novo Nordisk. Research Investigator; Self; Novo Nordisk, Dexcom. P. Mandava: None. E. Fay: None. G. Abdalla: None. S. Fonda: None. Background: The Federal Drug Agency recently approved continuous glucose monitoring (CGM) use in gestational diabetes (GDM). However, self-monitoring of blood glucose (SMBG) with fingersticks is still recommended as an adjunct to CGM use. Here we report on SMBG with and without CGM and A1c, as part of a randomized controlled trial (RCT) of CGM for women with GDM. Methods: This is an RCT of 104 participants with GDM who were randomized to real-time CGM (RT-CGM) (N=48) or SMBG alone (control group; N=56). Sixty-one percent in the control group (N=34) withdrew after randomization because they desired a CGM device. Data collection was completed remotely given COVID-19 pandemic. A1c data was collected at baseline and 36 weeks gestation. Fingerstick data was collected at each of 4 study visits (2 weeks apart) until 38 weeks or delivery. All participants were advised to perform SMBG by fingerstick as instructed by their obstetric provider. This analysis is of participants who completed the study (control N=22; RT-CGM N=47). Results: The average age was 33.77 (+/- 5.26) years, 68.11% had a college degree or greater, 69.57% had an income of >$50,000, 95.65% had health insurance, 30.43% reported being Asian and 42.03% reported being white. Baseline mean A1c (+/- SD) was 5.39 (+/- 0.39) in the RT-CGM group and 5.41 (+/- 0.37) in in the control group. Mean A1c at ∼36 weeks of pregnancy was 5.44 (+/-0.43) in the RT-CGM group and 5.37 (+/- 0.44) in the control group. In the RT-CGM group, 20/47 (42.55%) provided SMBG data for ≥3 study visits, 18/47 (38.30%) had data for 1-2 visits, and 9/47 (19.15%) provided no SMBG data at all 4 visits. The mean (+/- SD) tests/day for the RT-CGM group who provided any meter data was 1.31 (+/- 1.89). In the control group, 16/22 (72.73%) provided SMBG data for ≥3 visits, 2/22 (9.09%) had data for 1-2 visits, and 4/22 (18.18%) never provided SMBG data. The mean (+/- SD) tests/day for the control group was 3.4 (+/- 0.73). For the RT-CGM group, simple correlation analyses found no association between number of visits in which fingerstick data were provided and A1c at visit 3 (r=-0.14; p=0.40) or average fingerstick tests/day and A1c at visit 3 (r=0.10; p=0.40). For the control group, there was no association between number of study visits in which fingerstick data were provided and A1c at visit 3 (r=0.38; p=0.11). However, for the control group, more fingerstick tests/day was associated with lower A1c at visit 3 (r=-0.45; p=0.07). Conclusions. Data is limited by missing data as participants did not always supply fingerstick data. Overall A1c in both groups remained stable, despite less SMBG testing in the CGM group. This suggests that SMBG data may add little in GDM management in conjunction with CGM use. More data is necessary to remove the recommended requirement for fingerstick with CGM in pregnancy. Presentation: 6/2/2024

6631 A Week With Diabetes: Using Real-Time Continuous Glucose Monitoring In A Simulation Activity With Residents And Fellows

Abstract Disclosure: T. Gallagher: None. C. Donelly: None. R.E. Amori: None. Background: Continuous glucose monitor (CGM) use in managing diabetes mellitus is increasing rapidly. Fellows and residents often prescribe these devices, but most do not themselves have diabetes mellitus and do not use these devices personally. A real-time simulation activity can help physicians in training learn about using the technology in diabetes management and the patient experience living with diabetes mellitus. Objective: Assessing learner’s experiences using a one week real-time CGM simulation. Methods: A real-time simulation using CGM and elements of role playing can enhance knowledge of CGM use and overall diabetes care. Voluntary participants included endocrinology fellows, internal and family medicine residents, and one health professions student. One common structured learning task per day was assigned to all participants over a single seven day period of use in academic year 2022-23. Assessment of each task occurred via personal observations and reflections. Data was collected in an anonymous form and in a group debrief. Results: Eight of 10 participants completed the deidentified post simulation survey and 8/10 participated in the live debrief. Participants reported ease of CGM placement and use. They reported improved insight into the impacts of diabetes on daily activities and increased awareness of diet and exercise impact on glucose levels. Insulin dose calculations were largely correct but errors were seen. All felt the activity was beneficial to their learning. Conclusions: Real-time CGM simulation improves student, resident, and fellow knowledge of the technology and allows the learner to gain insight into a patient’s diabetes self-management. Presentation: 6/3/2024

12503 An Observational Study Of The Glycemic Variability In Type 1 Diabetes Mellitus Women Preconception And During Pregnancy And Its Associations With Adverse Maternal And Neonatal Outcomes

Abstract Disclosure: S. Avula: None. A.R. Ankireddypalli: None. K. Tessier: None. E.R. Seaquist: None. Background: Pregnancy in T1 diabetes mellitus (T1DM) women is associated with increased risk of maternal/fetal complications. Despite glycemic optimization during pregnancy in T1DM, offspring are at increased risk for neonatal complications. Aim: To examine glycemic variability by continuous glucose monitor (CGM) preconception and during pregnancy by trimester and assess the association with adverse maternal/fetal outcomes. Methods: This was a retrospective cohort study of pregnant patients with T1DM who used real-time CGM and delivered at a U.S. tertiary center (2012-2023). Multiple gestations, Cystic fibrosis-related diabetes (CFRD), twin or multiple births, and no valid CGM data for at least one trimester were excluded. 63 met the inclusion criteria. The primary outcome was composite neonatal morbidity (CNM), including large or small for gestational age (LGA/SGA), NICU admission, neonatal hypoglycemia, shoulder dystocia, respiratory distress syndrome, APGAR 1 or 5 minutes < 7, prematurity (<37 weeks), intrauterine growth restriction (IUGR), CPAP, and ventilator. We also collected data about maternal outcomes. Results:54 patients (86%) met at least one outcome included in the CNM. 20 patients (32%) were LGA, 3 (5%) were SGA, 32 (51%) premature, 29 (46%) required NICU admission, 44 (70%) had neonatal hypoglycemia, 3 (5%) had shoulder dystocia, 23 (37%) had respiratory distress, 22 (35%) needed CPAP, 3 (5%) were on ventilator, 11 (18%) had APGAR 1 minute <7. Among maternal outcomes, 18 (29%) developed pre-eclampsia, and 46 (73%) had a cesarean delivery. Overall, individuals with neonatal morbidity had a lower target in range (TIR) and higher target above range(TAR), average glucose, standard deviation(SD), and coefficient of variation (CV) compared with those without the primary composite, but statistical significance was seen for average glucose and TAR. For every 5 mg/dl increase in average glucose (mean of the 3-trimester values), there was a 25% increase in odds of neonatal morbidity (OR 1.25; 95% CI 1.04-1.56; p=0.028). There was a significant association between 1st trimester SD and neonatal morbidity (OR 1.11; 95% CI 1.02-1.24; p=0.027). There was a trend toward significance between the 3rd-trimester average blood glucose and neonatal morbidity (OR 1.26; 95% CI 1.02-1.63; p=0.051). Conclusion: In our single-center cohort, we found maternal average glucose and TAR, as well as first trimester SD, were significantly associated with CNM. This confirms that maternal hyperglycemia and demonstrates that first trimester SD are associated with poorer neonatal outcomes. Presentation: 6/1/2024

6567 Novel Indication of GLP-1 Receptor Agonists Beyond Weight Loss: Addressing Post-Gastric Bypass Late Dumping Syndrome

Abstract Disclosure: G. Arevalo: None. S. Gra Menendez: None. D. Soliman: None. R.J. Galindo: Consulting Fee; Self; Novo Nordisk, Eli Lilly & Company, Sanofi, Bayer, Inc., Boehringer Ingelheim, Pfizer, Inc., Abbott Laboratories. Grant Recipient; Self; National Institute of Diabetes and Digestive and Kidney Diseases (2P30DK111024), National Institute of Diabetes and Digestive and Kidney Diseases (K23DK123384). Other; Self; Novo Nordisk, Eli Lilly & Company, Dexcom. Background: Late dumping syndrome, characterized by postprandial hyperinsulinemic hypoglycemia (PHH), represents a complex clinical challenge in post-bariatric patients. GLP-1 receptor agonists are being explored as an effective therapeutic option. Clinical Case: A 47-year-old overweight (BMI of 29.86 kg/m²) woman, with a medical history of scleroderma and esophageal dysmotility, underwent a gastric sleeve gastrectomy later requiring conversion to Roux-en-Y gastric bypass to improve esophageal motility. Eleven months post-bypass, she began experiencing recurrent episodes of hypoglycemia (venous glucose 49-70 mg/dL, n >70 mg/dL) accompanied by sweating, palpitations, drowsiness, and weakness. Initial tests were consistent with postprandial hyperinsulinemic hypoglycemia: serum insulin (13.5 µIU/mL, n < 3 µIU/mL), and c-peptide (4.1 ng/mL, n < 0.6 ng/mL). The Sigstad score and the Arts dumping severity score were positive for late dumping syndrome with a score of 26 and 14, respectively. During glucagon administration, the patient's blood glucose level increased by up to 50 mg/dL within 10 minutes of administration. Both sulfonylurea screening and insulin antibody tests were negative. Real-time CGM measurements showed patterns of postprandial hyperglycemic peaks, up to 160-180 mg/dL (n <140 mg/dL), approximately 30 to 60 min after meals, followed by rapidly declining glucose (1-2 hours later), resulting in hypoglycemic events as low as 49 mg/dL. Initial management with dietary changes and pharmacological treatment was unsuccessful due to poor medication tolerability of acarbose and diazoxide, and low adherence to the prescribed diet due to her esophageal dysmotility. The CGM patterns and symptom presentation raised suspicion that late dumping syndrome was triggered by rapid hyperglycemic responses after oral ingestions of typical meals, resulting in the desynchronization of hormonal responses (insulin and GLP-1), and post-prandial hypoglycemia. Hence, the consideration for a GLP-1 receptor agonist emerged. A weekly subcutaneous injection of a long-acting GLP-1 receptor agonist, semaglutide 0.25 mg exhibited marked improvement in her glycemic profile: fewer episodes of postprandial hyperglycemia, and the subsequent descents in blood glucose were less pronounced. The patient demonstrated a favorable response with no severe hypoglycemic episodes reported during a follow-up period of three months. Conclusion: This is the first case to demonstrate semaglutide's efficacy as a standalone treatment for PHH in post-bariatric patients. In this case, semaglutide effectively controlled glycemia and improved the patient's quality of life, presenting a promising therapeutic option for such complex cases. Presentation: 6/1/2024

Clinical perspective on innovative insulin delivery technologies in diabetes management.

The primary objective of this study is to report the results of an online questionnaire and the in-person discussion sessions of physicians specializing in diabetes care in which their opinions about current diabetes management was obtained. The Diabetes Innovation Summit 2023 drew attendance from a diverse group of specialized physicians from multiple countries. A comprehensive literature review was conducted to examine the technologies and medical needs associated with diabetes management. Using the results of the review, a questionnaire was developed by three experts from the steering committee to solicit feedback from specialized physicians. The online survey was made accessible between 10th December 2022 and 10th January 2023. Following the online survey, six structured in-person discussion sessions were conducted with specialized physicians from the Middle East, Central-Eastern Europe, and North Africa regions. The study revealed that about 59% of survey requests were answered, with many participants being pediatric endocrinologists from North Africa. Around 60% of diabetes patients followed Multiple Daily Injections (MDI) according to specialized physicians. Among MDI users, 62% employed Blood Glucose Monitors (BGM), 31% used intermittent-scanning Continuous Glucose Monitors (isCGM), and 23% used CGM. In North Africa, nearly 90% of patients used MDI due to financial constraints. While physicians focused on both Time in Range (TIR) and HbA1c for MDI-treated patients, satisfaction with TIR achieved was expressed by 31%, while 74·1% believed Real-Time CGM (rtCGM) was effective. Concerns arose about potentially misleading HbA1c results and the relatively low patient achievement of target TIR despite CGM usage. The Smart MDI System was seen favorably compared to other applications. The system's affordability was a significant barrier, particularly in the Middle East and Africa. The present study highlights that physicians are generally supportive of utilizing new technology. The questionnaires and the open discussion revealed the expectation that the Smart MDI technology provides better control, primarily by identifying missed boluses, while expressing concerns on the use of the technology by teenagers and children, who might forget the device and be reluctant to use in public, and by the older population, who might be challenged by the technology.

Efficacy and safety of henagliflozin combined with continuous subcutaneous insulin infusion in the treatment of Chinese inpatients with type 2 diabetes mellitus based on a continuous glucose monitoring system: protocol of a multicentre, open-label, inpatient, randomised, controlled trial

IntroductionThe role of sodium-glucose cotransporter 2 inhibitors (SGLT2is) in diabetes treatment is expanding; however, few studies have investigated the efficacy and safety of combining SGLT2is with insulin pump therapy. Notably,...

Improved Glycemic Control during a One-Week Adventure Camp in Adolescents with Type 1 Diabetes-The DIACAMP Study.

Adolescence remains a crucial age associated with diabetes distress in individuals living with type 1 diabetes (T1D). The Austrian organization "Diabär" regularly hosts a one-week adventure camp for adolescents (12-18 years) living with T1D. The camp focuses on "fun activities" without a structured educational protocol in order to minimize diabetes distress and increase diabetes management skills. In contrast to educational camps, training is kept to a minimum. However, attendees analyze the glycemic data of the previous day with their medical supervisor once daily during the camp. All subjects used a standardized real-time continuous glucose monitoring (CGM) system (DexcomG7) throughout the whole study. Glycemic metrics were prospectively analyzed during three periods: week 1 = home phase, week 2 = adventure camp, and week 3 = after the camp. Safety (time below range 1 [TBR1], 69-54 mg/dL, and time below range 2 [TBR2], <54 mg/dL) and efficacy (time in range [TIR], 70-180 mg/dL) were assessed by comparing the CGM data during weeks 1-3. The CGM data of 14 participants were analyzed. The TIR was higher during the camp week versus week 1 (70.4 ± 11.1% vs. 53.1 ± 20.2%; p = 0.001). The TBR1 significantly increased during camp compared to week 1 (2.5 ±1.7% vs. 1.3 ± 1.2%; p = 0.009), whereas the TBR2 did not differ. No serious adverse events occurred. This adventure camp without a main focus on education showed feasibility and safety in adolescents with T1D.

Does real time continuous glucose monitoring improve glycaemic control in patients with Wolfram syndrome and insulin dependent diabetes mellitus?

Does real time continuous glucose monitoring improve glycaemic control in patients with Wolfram syndrome and insulin dependent diabetes mellitus?

Outcomes of real-time continuous glucose monitoring in adults with type 1 diabetes - quality improvement in diabetes care in a regional diabetes service in Ireland

Outcomes of real-time continuous glucose monitoring in adults with type 1 diabetes - quality improvement in diabetes care in a regional diabetes service in Ireland

Real-time continuous glucose monitoring vs. self-monitoring of blood glucose: cost-utility in South Korean type 2 diabetes patients on intensive insulin

Aims This study investigated the cost-utility of real-time continuous glucose monitoring (rt-CGM) versus self-monitoring of blood glucose (SMBG) in people with type 2 diabetes (T2D) receiving intensive insulin therapy in South Korea. Methods The IQVIA Core Diabetes Model (CDM v9.5) was used, with clinical effectiveness data obtained from a large-scale real world study. Costs were obtained from South Korean sources and inflated to 2022 South Korean Won (KRW). A South Korean payer perspective was adopted over a lifetime horizon, with future costs and effects discounted at 4.5% per annum. Baseline characteristics included a mean baseline HbA1c level of 8.6% (71 mmol/mol), and a mean age of 64.4 years. A willingness-to-pay (WTP) threshold of KRW 46.0 million was used. Results Rt-CGM led to an increase of 0.683 quality-adjusted life years (QALYs) versus SMBG (7.526 QALYs for rt-CGM versus 6.843 QALYs for SMBG). An increase in costs of KRW 16.4 million (from KRW 90.4 million to KRW 106.8 million) was associated with rt-CGM. The incremental cost-utility ratio was KRW 24.0 million per QALY gained, significantly lower than the KRW 46 million threshold. Conclusions For individuals with T2D managed by intensive insulin therapy in South Korea, rt-CGM is cost-effective relative to SMBG.

Effect of Real-Time Continuous Glucose Monitoring Versus Flash Glucose Monitoring on Glycemic Control in Adults with Type 1 Diabetes Mellitus: A Systematic Review and Meta-Analysis.

Objective: This meta-analysis aimed to compare the effect of the real-time continuous glucose monitoring (rt-CGM) and flash glucose monitoring (FGM) on glycemic control in adults with type 1 diabetes mellitus (T1DM). Methods: A systematic literature search of all relevant studies comparing the clinical effectiveness of rt-CGM and FGM in adults with T1DM on Cochrane Library, PubMed, Embase, Web of Science, and Scopus from January 2015 to June 2023 was performed. The primary endpoints were glycated hemoglobin (HbA1c) and TIR (time in range). Secondary endpoints included time below range [TBR (<3.9 mmol/L) and (<3.0 mmol/L)], time above range [TAR (>10.0 mmol/L) and (>13.9 mmol/L)], mean glucose, and glycemic variability (GV) [standard deviations (SD) and coefficient of variation (CV)]. Results: Six studies with 1516 TIDM patients, including three randomized controlled trials and three observational studies, were enrolled in this meta-analysis. Compared to FGM, rt-CGM led to greater glycemic control, represented by higher TIR (%, 3.9 ∼ 10 mmol/L) (SMD = 0.59, 95%CI: 0.37 ∼ 0.81, p < 0.001), decreased TBR (%, <3.9 mmol/L) (SMD = -1.45, 95%CI: -2.33 ∼ -0.57, p = 0.001), decreased TAR [(%, >10.0 mmol/L) (SMD = -0.38, 95%CI: -0.71 ∼ -0.04, p = 0.03) and (%, >13.9 mmol/L) (SMD = -0.42, 95%CI: -0.79 ∼ -0.04, p = 0.03), respectively], lower mean glucose (SMD = -0.18, 95%CI: -0.31 ∼ -0.06, p = 0.003), decreased SD (SMD = -0.70, 95%CI: -1.09 ∼ -0.31, p < 0.001), and decreased CV (SMD = -0.76, 95%CI: -1.05 ∼ -0.47, p < 0.001). However, there was no difference in lowering HbA1c and TBR (%, <3.0 mmol/L) between groups. Conclusion: The rt-CGM outperformed FGM in improving several key CGM metrics among adults with T1DM, but there is no significant difference in HbA1c and TBR (<3.0 mmol/L).

Are we Ready for Real-Time Continuous Glucose Monitoring in the Hospital Setting? Benefits, Challenges, and Practical Approaches for Implementation : Case Vignette: Remote Real-Time Continuous Glucose Monitoring for Hospitalized Care in Quincy Koala.

While preliminary evidence for use of real-time continuous glucose monitoring (rtCGM) in the hospital setting is encouraging, challenges with currently available devices and technology will need to be overcome as part of real-world integration. This paper reviews the current evidence and guidelines regarding use of rtCGM in the hospital and suggests a practical approach to implementation. There is now a considerable body of real-world evidence on the benefits of reducing dysglycemia in the hospital using both traditional point-of-care (POC) glucose testing and rtCGM. Benefits of rtCGM include decreased frequency of hypo- and hyperglycemia with reduced need of frequent POC checks and it is both feasible and well-accepted by nursing staff and providers. If expansion to additional sites is to be considered, practical solutions will need to be offered. Recommendations for an operational workflow and tools are described to guide implementation in the non-ICU setting. Further testing in randomized controlled trials and real-world dissemination and implementation designs is needed, together with industry and technology collaborations, to further streamline the integration into health systems.

Differences Between Glycated Hemoglobin and Glucose Management Indicator in Real-Time and Intermittent Scanning Continuous Glucose Monitoring in Adults With Type 1 Diabetes.

This study demonstrates the difference between glucose management indicator (GMI) and glycated hemoglobin (HbA1c) according to sensor mean glucose and HbA1c status using 2 continuous glucose monitoring (CGM) sensors in people with type 1 diabetes. A total of 275 subjects (117 Dexcom G6 [G6] and 158 FreeStyle Libre 1 [FL]) with type 1 diabetes was included. The G6 and FL sensors were used, respectively, over 90 days to analyze 682 and 515 glycemic profiles that coincide with HbA1c. The mean HbA1c was 6.6% in Dexcom G6 and 7.2% in FL profiles. In G6 profiles, GMI was significantly higher than HbA1c irrespective of mean glucose (all P < .001, mean difference: 0.58% ± 0.49%). The GMI was significantly higher than the given HbA1c when HbA1c was below 8.0% (all P < .001). The discordance was the highest at 0.9% for lower HbA1c values (5.0%-5.9%). The proportion of discordance >0.5% improved from 60.1% to 30.9% when using the revised GMI equation in G6 profiles. In FL profile, the overall mean difference between GMI and HbA1c was 0 (P = .966). The GMI was significantly lower by 0.9% than HbA1c of 9.0% to 9.9% and higher by 0.5% in HbA1c of 5.0% to 5.9% (all P < .001). The GMI is overestimated in G6 users, particularly those with well-controlled diabetes, but the GMI and HbA1c discordance improved with a revised equation from the observed data. The FL profile showed greater discordance for lower HbA1c levels or higher HbA1c levels.

Exploring the Continuous Glucose Monitoring in Pediatric Diabetes: Current Practices, Innovative Metrics, and Future Implications.

Continuous glucose monitoring (CGM) systems, including real-time CGM and intermittently scanned CGM, have revolutionized diabetes management, particularly in children and adolescents with type 1 diabetes (T1D). These systems provide detailed insights into glucose variability and detect asymptomatic and nocturnal hypoglycemia, addressing limitations of traditional self-monitoring blood glucose methods. CGM devices measure interstitial glucose concentrations constantly, enabling proactive therapeutic decisions and optimization of glycemic control through stored data analysis. CGM metrics such as time in range, time below range, and coefficient of variation are crucial for managing T1D, with emerging metrics like time in tight range and glycemia risk index showing potential for enhanced glycemic assessment. Recent advancements suggest the utility of CGM systems in monitoring the early stages of T1D and individuals with obesity complicated by pre-diabetes, highlighting its therapeutic versatility. This review discusses the current CGM systems for T1D during the pediatric age, established and emerging metrics, and future applications, emphasizing the critical role of CGM devices in improving glycemic control and clinical outcomes in children and adolescents with diabetes.

Advancing elderly diabetes care: exploring the usability and acceptance of continuous glucose monitoring (CGM)

ObjectivesThis study aimed to evaluate the acceptability, usability, compliance, and satisfaction of Continuous Glucose Monitoring (CGM) among elderly diabetic patients. DesignUtilizing a mixed-methods approach, the study involved 30 participants, averaging 74.79 years in age. Participants wore two CGM devices, and their experiences, along with survey data, were comprehensively analyzed to gauge the effectiveness of CGM in managing diabetes. ResultsThe study demonstrated that -CGM- is highly usable and acceptable among elderly diabetic patients. Participants effectively utilized CGM to monitor and predict blood glucose trends, positively influencing their glucose control and lifestyle. The average adherence rate was found to be 81 %, indicating a substantial level of effective self-management and treatment decision-making. ConclusionThe study recommends developing CGM educational programs tailored for the elderly, educating healthcare professionals, expanding insurance coverage for CGM, and promoting real-time CGM technology to improve usability and acceptance among the elderly.

Impact of Continuous Glucose Monitoring on Glycemic Control and Lifestyle Changes among Diabetes Patients: Evidence from a Diverse Indian Cohort

Background: Continuous glucose monitoring (CGM) has emerged as a pivotal technology in diabetes management, offering real-time insights into glucose fluctuations. This study aims to assess the impact of CGM on glycemic control and lifestyle changes among diabetes patients in India. Methodology: A retrospective observational study was conducted on a cohort of 556 diabetes patients from 3 diabetes centers across India. Data were collected using a structured questionnaire focusing on demographics, CGM usage patterns, lifestyle changes, and glycemic outcomes, particularly hemoglobin A1c (HbA1c) levels. The analysis included descriptive statistics and inferential methods, such as paired t-tests and regression analysis, to evaluate the relationship between CGM usage and changes in glycemic control and lifestyle behaviors. Results: The study revealed a significant reduction in HbA1c levels, with an average decrease of 0.85% across the cohort. A higher frequency of CGM use was associated with greater improvements in glycemic control. Patients who made dietary improvements and managed stress levels effectively, as guided by real-time CGM feedback, exhibited more pronounced reductions in HbA1c. The study also identified that demographic factors such as age and gender had minimal influence on glycemic outcomes. A clustering analysis grouped patients based on their HbA1c improvement, identifying distinct patterns of lifestyle changes and CGM usage. Conclusion: CGM significantly improves glycemic control and promotes positive lifestyle changes among diabetes patients in India. The findings underscore the importance of frequent CGM usage and patient engagement in achieving optimal outcomes. Despite the challenges related to cost and accessibility in the Indian context, CGM presents a valuable tool for enhancing diabetes management. Future research should focus on optimizing CGM usage patterns and addressing barriers to its widespread adoption.