Real-time Continuous Glucose Monitoring Research Articles

Stepping Forward With Real-Time Continuous Glucose Monitoring in the Primary Care Practice.

The goal of this activity is that learners will be better able to use real-time CGM (rtCGM) in appropriate patients with type 2 diabetes.

Are nocturnal hypoglycemia prevention strategies influenced by diabetes technology usage? A BETTER registry analysis

AimTo assess the association of nocturnal hypoglycemia prevention strategies (NH-PS) and diabetes technology usage (insulin pump and/or continuous glucose monitors [CGM]) in people with type 1 diabetes (PWT1D). MethodsLogistic regression models were used to describe associations between self-reported NH-PS and diabetes technology (pump with intermittently-scanned or real-time CGM (isCGM or rtCGM), or automated insulin delivery (AID)), hypoglycemia history, and fear of hypoglycemia (FOH). ResultsAmong 831 adults (65 % female, aged 44 ± 15 years, T1D duration 26 ± 15 years), 32 % reported HbA1c ≤ 7.0 %, 88 % used ≥ 1 diabetes technology, 66 % reported ≥ 1 symptomatic NH in the past month, and 64 % used ≥ 2 NH-PS. Compared to multiple daily injections (MDI) + capillary blood glucose (CBG), bedtime snack consumption was less likely among pump + isCGM (OR [95 %CI]: 0.55 [0.31, 0.98]), pump + rtCGM (0.40 [0.20, 0.81]), and AID (0.34 [0.17, 0.66]) users, while evening insulin basal reduction was associated with CSII + CBG (3.15 [1.25, 7.99]), pump + isCGM 4.00 [1.99, 8.01]), and pump + rtCGM 2.89 [1.28, 6.50] use. Elevated FOH was associated with snack consumption (1.37 [1.00, 1.89]), evening bolus insulin avoidance (1.77 [1.11, 2.83]), limiting exercise (2.50 [1.30, 4.82]), and limiting alcohol consumption (2.33 [1.15, 4.70]) as NH-PS. ConclusionTechnology use and elevated FOH might influence PWT1D’ choice of NH-PS.

Continuous Glucose Monitoring-Guided Insulin Administration in Hospitalized Patients With Diabetes: A Randomized Clinical Trial.

The efficacy and safety of continuous glucose monitoring (CGM) in adjusting inpatient insulin therapy have not been evaluated. This randomized trial included 185 general medicine and surgery patients with type 1 and type 2 diabetes treated with a basal-bolus insulin regimen. All subjects underwent point-of-care (POC) capillary glucose testing before meals and bedtime. Patients in the standard of care (POC group) wore a blinded Dexcom G6 CGM with insulin dose adjusted based on POC results, while in the CGM group, insulin adjustment was based on daily CGM profile. Primary end points were differences in time in range (TIR; 70-180 mg/dL) and hypoglycemia (<70 mg/dL and <54 mg/dL). There were no significant differences in TIR (54.51% ± 27.72 vs. 48.64% ± 24.25; P = 0.14), mean daily glucose (183.2 ± 40 vs. 186.8 ± 39 mg/dL; P = 0.36), or percent of patients with CGM values <70 mg/dL (36% vs. 39%; P = 0.68) or <54 mg/dL (14 vs. 24%; P = 0.12) between the CGM-guided and POC groups. Among patients with one or more hypoglycemic events, compared with POC, the CGM group experienced a significant reduction in hypoglycemia reoccurrence (1.80 ± 1.54 vs. 2.94 ± 2.76 events/patient; P = 0.03), lower percentage of time below range <70 mg/dL (1.89% ± 3.27 vs. 5.47% ± 8.49; P = 0.02), and lower incidence rate ratio <70 mg/dL (0.53 [95% CI 0.31-0.92]) and <54 mg/dL (0.37 [95% CI 0.17-0.83]). The inpatient use of real-time Dexcom G6 CGM is safe and effective in guiding insulin therapy, resulting in a similar improvement in glycemic control and a significant reduction of recurrent hypoglycemic events compared with POC-guided insulin adjustment.

Real-Time Continuous Glucose Monitoring for People Living With Type 1 Diabetes

&#x0D; Continuous glucose monitoring (CGM) is a method of glucose testing in which a sensor is inserted into the skin and continuously monitors interstitial glucose concentrations. Real-time continuous glucose monitoring (rtCGM) systems automatically measure glucose and display a recent glucose value.&#x0D; Evidence suggests that rtCGM may improve hemoglobin A1C and time in range in adults and pediatric patients with type 1 diabetes, but this is uncertain.&#x0D; Limited evidence suggests that in people with type 1 diabetes, there is little to no difference between rtCGM and self-monitoring of blood glucose (SMBG) on quality of life, diabetic ketoacidosis, and severe adverse events.&#x0D; Safety evidence suggests that rtCGM may decrease severe hypoglycemia in adults and pediatric patients with type 1 diabetes, but this is uncertain.&#x0D; rtCGM may be more cost-effective in the long term than SMBG in adults with type 1 diabetes.&#x0D;

The OPTIMISE study protocol: a multicentre optimisation trial comparing continuous glucose monitoring, snacking habits, sleep extension and values-guided self-care interventions to improve glucose time-in-range in young people (13–20 years) with type 1 diabetes

PurposeThe OPTIMISE study uses a Multiphase Optimisation Strategy (MOST) to identify the best combination of four interventions targeting key diabetes self-care behaviours for use in clinical practice to improve short-term glycaemic outcomes.MethodsThis 4-week intervention trial will recruit 80 young people (aged 13–20 years) with type 1 diabetes ≥ 6 months duration), and pre-enrolment HbA1c ≥ 58 mmol/mol (7.5%) in the prior 6 months. Both main intervention and interaction effects will be estimated using a linear regression model with change in glucose time-in-range (TIR; 3.9–10.0 mmol/L) as the primary outcome. Participants will be randomised to one of 16 conditions in a factorial design using four intervention components: (1) real-time continuous glucose monitoring (CGM), (2) targeted snacking education, (3) individualised sleep extension, and (4) values-guided self-care goal setting. Baseline and post-intervention glucose TIR will be assessed with blinded CGM. Changes in self-care (snacking behaviours, sleep habits and duration, and psychosocial outcomes) will be assessed at baseline and post-intervention to determine if these interventions impacted behaviour change.DiscussionThe study outcomes will enable the selection of effective and efficient intervention components that increase glucose TIR in young people who struggle to achieve targets for glycaemic control. The optimised intervention will be evaluated in a future randomised controlled trial and guide the planning of effective clinical interventions in adolescents and young adults living with type 1 diabetes.Trial registrationThis trial was prospectively registered with the Australian New Zealand Clinical Trials Registry on 7 October 2020 (ACTRN12620001017910) and the World Health Organisation International Clinical Trails Registry Platform on 26 July 2020 (Universal Trial Number WHO U1111-1256-1248).

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.

Fear of hypoglycemia and quality of life in young people with type 1 diabetes and their parents in the era of sensor glucose monitoring.

IntroductionIt is crucial to understand psychosocial outcomes in children and adolescents with type 1 diabetes (T1D) and their families to provide optimal family-centered care. Hence, the aim of this study was to explore psychosocial outcomes in young people with T1D and their parents using currently available glucose monitoring devices in a real-life clinic setting.MethodsChildren and adolescents aged 2-18 years with T1D for more than 6 months and their parents were recruited into a cross-sectional study to complete the Hypoglycemia Fear Survey (HFS) and the Pediatric Quality of Life Inventory (PedsQL) Generic Score Scales, Diabetes Module and Family Impact Module. Demographics and diabetes-specific parameters were obtained from medicals records.ResultsFifty-nine children and adolescents (mean age 15.1 ± 3.0 years) and 49 parents of children (mean age of children 12.5± 3.3 years) of which 44 were child-parent dyads completed the questionnaires. Parents had a higher mean (SD) FOH total and worry subscore than children, total score was 37.9 (14.6) vs. 32.2 (11.9), p = 0.047 and worry subscore was 17.8 (10.4) vs. 12.8 (9.0), p = 0.01. Furthermore, lower parental diabetes-specific QoL score was observed in parents, 78.8 (12.2) vs. 82.7 (10.3), p=0.02. No difference in FOH and QoL between real-time continuous glucose monitoring (rtCGM) and intermittently scanned glucose monitoring (isCGM) users and users of devices with and without alerts was observed. In isCGM users (n=36 completing the child questionnaires, n=33 completing parent questionnaires), higher parental FOH and lower parental diabetes-specific QoL correlated with higher scanning frequency, r = 0.399, p = 0.021, and r = -0.464, p = 0.007 respectively. No significant correlation was documented between scanning frequency and child questionnaire scores.ConclusionsParents are more likely to perceive higher levels of psychosocial burden related to their child’s diabetes than children and adolescents with T1D, especially parents of younger children. This highlights the need for family-based education and treatment resources to support parents in diabetes management in addition to rapidly advancing diabetes technology. In isCGM users, higher parental FOH and lower parent-perceived QoL correlated with a higher scanning frequency, indicating the potential impact of glucose monitoring modality on psychosocial outcomes or vice versa.

Comparison Between Continuous Versus Flash Glucose Monitoring in Children, Adolescents, and Young Adults with Type 1 Diabetes: An 8-Week Prospective Randomized Trial.

IntroductionTo assess the impact of real-time continuous glucose monitoring (RT-CGM) instead of first-generation flash glucose monitoring (FGM) on hypoglycaemia in children and adolescents with type 1 diabetes.MethodsIn this randomized controlled interventional study, young individuals with type 1 diabetes used RT-CGM or FGM for 8 weeks. We evaluated changes in time below range (TBR), severe hypoglycaemia (SH), HbA1c, glycaemic variability, and impaired awareness of hypoglycaemia with RT-CGM (intervention group) in comparison with FGM.ResultsWe randomly assigned 37 participants to either the intervention group (n = 19) or the control group (n = 18). At 8 weeks, we did not find a decrease in TBR in either group, but there was a significant reduction in SH in the intervention group. For participants with TBR ≥ 5% at baseline, we observed significant reductions in 24-h TBR, wake TBR, sleep TBR, and glucose variability at 8 weeks in the intervention group.ConclusionsThe use of RT-CGM versus FGM decreased SH in young individuals with type 1 diabetes, and TBR and glucose variability in patients with a higher TBR at baseline. The patient's history should be taken into account when advising on the method of blood glucose monitoring, as RT-CGM could be more effective in younger patients at high risk for SH.Trial registrationClinicalTrials.gov NCT04249102.Supplementary InformationThe online version contains supplementary material available at 10.1007/s13300-022-01297-x.

Data-Driven Supervised Compression Artifacts Detection on Continuous Glucose Sensors.

Continuous Glucose Monitoring (CGM) sensors micro-invasively provide frequent glucose readings, improving the management of Type 1 diabetic patients' life and making available reach data-sets for retrospective analysis. Unlikely, CGM sensors are subject to failures, such as compression artifacts, that might impact on both real-time and respective CGM use. In this work is focused on retrospective detection of compression artifacts. An in-silico dataset is generated using the T1D UVa/Padova simulator and compression artifacts are subsequently added in known position, thus creating a dataset with perfectly accurate faulty/not-faulty labels. The problem of compression artifact detection is then faced with supervised data-driven techniques, in particular using Random Forest algorithm. The detection performance guaranteed by the method on in-silico data is satisfactory, opening the way for further analysis on real-data.

A head-to-head comparison between Guardian Connect and FreeStyle Libre systems and an evaluation of user acceptability of sensors in patients with type 1 diabetes.

A user-calibrated real-time continuous glucose monitoring (rt-CGM) system is compared to a factory-calibrated flash glucose monitoring (FGM) system and assessed in terms of accuracy and acceptability in patients with type 1 diabetes (T1D). Ten participants with T1D were enroled from a specialist diabetes centre in Singapore and provided with the Guardian Connect with Enlite Sensor (Medtronic, Northridge, CA, USA) and first-generation Freestyle Libre System (Abbott Diabetes Care, Witney, UK), worn simultaneously. Participants had to check capillary blood glucose four times per day. At the end of week 1 and week 2, participants returned for data download and were given a user evaluation survey. Accuracy evaluation between Guardian Connect and Freestyle Libre includes the overall mean absolute relative difference value (9.7±11.0% vs. 17.5±10.9%), Clarke Error Grid zones A+B (98.6% vs. 98.1%), sensitivity (78.9% vs. 63.4%), and specificity (93.4% vs. 81.0%). Notably, time below range (<3.9mmol/L) was 10.5% for FGM versus 2% for rt-CGM. From the evaluation survey, 90% of participants perceived rt-CGM to be accurate versus 40% for FGM, although the majority found both devices to be easy to use, educational, and useful in improving glycaemic control. However, due to the cost of sensors, only 30% were keen to use either device for continuous monitoring. Although rt-CGM was superior to FGM in terms of accuracy, the value of glucose trends in both devices is still useful in diabetes self-management. Patients and clinicians may consider either technology depending on their requirements.

Intermittently Scanned and Real-Time Continuous Glucose Monitoring for People With Diabetes

&#x0D; Continuous glucose monitoring is a method of glucose testing in which a sensor is inserted into the skin and continuously monitors interstitial glucose concentrations. Real-time continuous glucose monitoring (rtCGM) systems automatically measure glucose and display a recent glucose value. Intermittently scanned continuous glucose monitoring (isCGM) systems require the person using the system to scan the sensor to display glucose information.&#x0D; The evidence of the comparative effectiveness of isCGM versus rtCGM for improving time in range, time above range, A1C, and quality of life in people with type 1 diabetes is uncertain. Evidence from some studies suggested there was a significant benefit favouring rtCGM versus isCGM for these outcomes, whereas other studies found no significant differences between treatment groups.&#x0D; Evidence suggested that people with type 1 diabetes using rtCGM spent significantly less time below range/time in hypoglycemia than those using isCGM.&#x0D; The evidence of the comparative safety of isCGM versus rtCGM in people with type 1 diabetes is limited and uncertain. Evidence from 1 study suggested that severe hypoglycemic events were more frequent in those using isCGM. In other studies, there were no severe hypoglycemic events in either treatment group.&#x0D; No studies were identified that evaluated the comparative effectiveness of isCGM versus rtCGM in people living with type 2 diabetes or gestational diabetes.&#x0D;

The impact of socio-economic deprivation on access to diabetes technology in adults with type 1 diabetes.

BackgroundWith advances in technology, there is an emerging concern that inequalities exist in provision and diabetes outcomes in areas of greater deprivation. We assess the relationship between socio‐economic status and deprivation with access to diabetes technology and their outcomes in adults with type 1 diabetes.MethodsRetrospective, observational analysis of adults attending a tertiary centre, comprising three urban hospitals in the UK. Socio‐economic deprivation was assessed by the English Indices of Deprivation 2019. Data analysis was performed using one‐way ANOVAs and chi‐squared tests.ResultsIn total, 1631 adults aged 44 ± 15 years and 758 (47%) women were included, with 391 (24%) using continuous subcutaneous insulin infusion, 312 (19%) using real‐time continuous glucose monitoring and 558 (34%) using intermittently scanned continuous glucose monitoring. The highest use of diabetes technology was in the least deprived quintile compared to the most deprived quintile (67% vs. 45%, respectively; p < 0.001). HbA1c outcomes were available in 400 participants; no association with deprivation was observed (p = 0.872). Participation in structured education was almost twice as high from the most deprived to the least deprived groups (23% vs. 43%; p < 0.001). Adults with white or mixed ethnicity were more likely to use technology compared to black ethnicity (60% vs. 40%; p < 0.001).ConclusionsAdults living in the most deprived quintile had less technology use. Irrespective of socio‐economic status or ethnicity, glycaemia was positively affected in all groups. It is imperative that health disparities are further addressed.

Utilising a Real-Time Continuous Glucose Monitor as Part of a Low Glycaemic Index and Load Diet and Determining Its Effect on Improving Dietary Intake, Body Composition and Metabolic Parameters of Overweight and Obese Young Adults: A Randomised Controlled Trial.

A randomised controlled trial to measure the effects of integrating real-time continuous glucose monitor (rtCGM) into a low glycaemic index (GI) and glycaemic load (GL) dietary intervention on dietary intake, body composition and specific metabolic parameters was carried out. A total of 40 overweight young adults [(means ± SD) age: 26.4 ± 5.3 years, BMI: 29.4 ± 4.7 kg/m2] were randomised into an intervention and control groups for a period of eight weeks. Both groups received nutrition education on low GI and GL foods. The intervention group also received an rtCGM system to monitor their glucose levels 24 h a day. While controlling for physical activities and GI and GL nutrition knowledge, the results indicated that the rtCGM system further improved body weight, BMI, fat mass, fasting plasma glucose, HbA1c, total cholesterol, HDL cholesterol and LDL cholesterol in the intervention group (p < 0.05). This trial unveils the robustness of the rtCGM where non-diabetic overweight and obese young adults can benefit from this device and utilise it as a management tool for overweight and obesity and a primary prevention tool for type 2 diabetes, as it provides real-time and personalised information on physiological changes.

Diabetes: the role of continuous glucose monitoring.

Diabetes mellitus is a chronic condition affecting 1 out of every 11 people worldwide. Monitoring of blood glucose allows for therapeutic lifestyle and pharmacotherapy changes to reduce the occurrence of hyperglycaemia and hypoglycaemia. Advancements in technology over the past two decades have increased patient and clinician access to glucose data and trends with continuous glucose monitoring (CGM) systems. This narrative review seeks to investigate the efficacy and safety of CGM for the management of diabetes. In type 1 diabetes (T1DM) and type 2 diabetes, efficacy studies of real-time CGM (rtCGM) or intermittently scanned CGM (isCGM) have shown a decrease in HbA1C (0.3–0.6%) over traditional self-monitoring blood glucose. Percent time in the target glucose range also improved (6.8–17.6%). Rates of hypoglycaemia, including severe hypoglycaemia, decreased in studies of rtCGM and isCGM with most available data in T1DM. In pregnant women with T1DM, rtCGM has shown modest improvements in HbA1C and time in target glucose range and decreased risk of neonatal complications. Multiple studies have shown that the use of rtCGM or isCGM increased diabetes treatment satisfaction amongst patients. Head-to-head studies of rtCGM and isCGM are limited but one study indicates that a CGM system with alarms may be preferred in T1DM to reduce the risk of hypoglycaemia. Selection of a CGM device should depend on patient-specific factors and insurance coverage. The results of one study show that the benefits of CGM device use were not sustained after discontinuing use. Increasing widespread and long-term access to CGM devices is necessary to improve the management of diabetes amongst the greater population.

Real-Time Continuous Glucose Monitoring Can Predict Severe Hypoglycemia in People with Type 1 Diabetes: Combined Analysis of the HypoDE and DIAMOND Trials

Objective: We combined data from two landmark trials (DIAMOND and HypoDE) to examine the diagnostic performance of low glucose measurements derived from open and masked continuous glucose monitoring (CGM) to predict the occurrence of future severe hypoglycemia (SH). Methods: We analyzed hypoglycemia parameters (low blood glucose index [LBGI], % <70 mg/dL, 54-69 mg/dL [level 1 hypoglycemia] and <54 mg/dL [level 2 hypoglycemia]) from masked CGM over 14 days during baseline and from open CGM over 14 days after randomization. We used receiver operating characteristics (ROC) curves to evaluate the screening performance of these measures to predict future SH. Positive likelihood ratios were calculated to indicate the overall diagnostic performance of these parameters. Results: Data from 288 individuals with type 1 diabetes (mean age 45.6 ± 12.8 years, diabetes duration 20.7 ± 13.7 years, HbA1c 8.2% ± 1.0%, Hypoglycemia Unawareness Score 3.4 ± 2.1) were analyzed. Area under ROC-curve (AUC) for LBGI and % <70 mg/dL ranged between 0.68 and 0.75, indicating that LBGI and % <70 mg/dL could significantly predict future SH. Significance of AUC regarding % <54 mg/dL were mixed (0.63-0.72). Positive and negative likelihood ratios ranged between 1.82 to 3.40 and 0.56 to 0.32, respectively. Suggested optimal cutoff values were remarkedly lower in open CGM than in masked CGM. Conclusion: These results indicate that CGM-derived hypoglycemic parameters have a good screening performance to significantly predict future clinical hypoglycemia. In addition, this analysis suggests that cutoff values to indicate elevated hypoglycemia risk in the future are substantially lower in open CGM than in masked CGM. ClinicalTrials.gov registration numbers: HypoDE: NCT02671968. DIAMOND: NCT02282397.

649-P: Real-Time Continuous Glucose Monitoring in the Hospital Identifies and Prompts Treatment for Hypoglycemia

Reliance on point-of-care (POC) blood glucose measurements for inpatient diabetes management can result in long between-measurement intervals, which contribute to undetected and untreated dysglycemia. The G6 real-time continuous glucose monitoring (RT-CGM) system (Dexcom) allows for remote monitoring. In the hospital, this may reduce the need for close interactions and infectious disease transmission between patients and hospital staff. A man in his mid-60s was admitted to a non-intensive care unit in an acute care facility with a diagnosis of COVID-19. His preadmission type 2 diabetes was managed with twice-daily intermediate-acting insulin and prandial rapid-acting insulin; steroids and POC glucose testing (prandial and bedtime with a FreeStyle Precision Pro meter [Abbott]) were added to this regimen. A G6 was placed on the abdomen and was set to alert the staff to glucose values ≤85 mg/dL or predicted to be &amp;lt;55 mg/dL within 20 minutes. Two hypoglycemic events occurred which triggered three G6 alerts (Figure) . The G6 alerts prompted ad hoc POC measurements that confirmed the hypoglycemic events, prompted appropriate interventions, and documented the patient’s return to euglycemia. All seven G6 readings were within 20 mg/dL or 20% of POC values ≤100 or &amp;gt;100 mg/dL, respectively. Inpatient RT-CGM use can detect existing or impending hypoglycemia and assist in diabetes management. Disclosure M.Baker: Other Relationship; Dexcom, Inc. J.Welsh: Employee; Dexcom, Inc. Funding Dexcom, Inc.

74-LB: Real-World Glycemic Outcomes in Adult Patients with Type 1 Diabetes Using a Real-Time Continuous Glucose Monitor Compared with an Intermittently Scanned Glucose Monitor and Self-Measured Blood Glucose—A Retrospective Observational Study from the Canadian

Real-time continuous glucose monitoring (rtCGM) and intermittently scanned CGM (isCGM) have both been shown to improve glycemic outcomes in people with T1D. In this retrospective analysis, we propensity score matched CGM naïve adults with T1D who initiated a rtCGM or an isCGM device. HbA1c and CGM metrics were assessed at 6-12-months. Among the 143 matched patients/cohort (age 43 ± 14 years; T1D duration 22 ± 14 years; HbA1c 8.4 ± 1.0%) , rtCGM users had a significantly greater change in HbA1c (-0.7 ± 0.1%) compared to isCGM users (-0.4 ± 0.1%) (p=0.01) . There was a significantly greater change in HbA1c for rtCGM compared to isCGM when baseline HbA1c was &amp;lt;8.5% (difference -0.4% [-0.6 to -0.2], p&amp;lt;0.001) , and in MDI users (difference -0.3% [-0.5 to 0.0], p=0.04) . Compared to isCGM users, rtCGM users had significantly greater time in range (58.3 ± 16.1% vs. 54.5 ± 17.1%, p=0.03) , lower time below range (2.1 ± 2.7% vs. 6.1 ± 5.0%, p&amp;lt;0.001) and lower glycemic variability (Table) . In this real-world analysis of adults with T1D, rtCGM users had a significantly greater reduction in HbA1c at 6-12 months, significantly greater time in range, lower time below range, and lower glycemic variability, compared to a matched cohort of isCGM users. Disclosure R. E. Brown: None. L. Chu: None. G. J. Norman: Employee; Dexcom, Inc. A. Abitbol: Consultant; Amgen Inc., AstraZeneca, Bayer Inc., Boehringer Ingelheim International GmbH, Dexcom, Inc., Eli Lilly and Company, Janssen Pharmaceuticals, Inc., Novo Nordisk, Other Relationship; AstraZeneca, Bayer Inc., Boehringer Ingelheim International GmbH, Dexcom, Inc., Eli Lilly and Company, Insulet Corporation, Janssen Pharmaceuticals, Inc., Merck &amp; Co., Inc., Novo Nordisk, Novo Nordisk, Sanofi, Senseonics. Funding DexCom Canada, Co.

647-P: Improved Glycemic Control and Continuous Glucose Monitoring (CGM) Utilization: A Comparison of Real-Time CGM and Intermittent Scanning CGM

Evolution of CGM technology has equipped the market with different systems. This study compared two types of CGM devices, real-time (rt) CGM and intermittently scanned (is) CGM on clinical outcomes among persons with diabetes using intensive insulin therapy. A retrospective analysis was performed using Optum Clinformatics® Database comprised of administrative claims data. CGM naïve patients with type 1 or type 2 diabetes initiated rtCGM (Dexcom G6®) or isCGM (FreeStyle Libre®) between 8/1/2018 through 3/31/2020 (index date = earliest observed pharmacy claim) . Patients with continuous health plan enrollment 12-months pre and post index date, age ≥18 years, with ≥1 sensor pharmacy claim, with A1C lab values during baseline and follow up were included in the study. Outcomes were the proportion reaching a target A1C of &amp;lt; 7% and the change in number of severe hypoglycemia (SH) inpatient/ER visits. A total of 272 rtCGM (average age = 47.3 (sd = 13.1) years, 46.7% female) and 467 isCGM (average age = 50.9 (sd = 12.7) years, 37.5% female) patients on intensive insulin therapy met inclusion criteria. After adjusting for baseline, rtCGM users were nearly twice as likely, compared to isCGM users, to reach an A1C of &amp;lt; 7% (OR = 1.97, 95% CI, 1.32 to 2.95, p&amp;lt;0.01) . A significant reduction was found in SH events from 40 to 13 after rtCGM initiation (baseline mean = 0.15, sd=0.49; and follow up mean = 0.05, sd=0.23, p&amp;lt;0.01) . For isCGM users SH events reduced from 42 to 32 (mean = 0.09, sd=0.44; and follow up mean 0.07, sd=0.35, p=0.239) . Findings suggest CGM naïve patients benefit from rtCGM compared to isCGM through significantly greater numbers achieving A1C &amp;lt; 7%. Improved access to rtCGM should help more patients achieve optimal glycemic control and reduce health care encounters due to SH. Disclosure K.Hannah: Employee; Dexcom, Inc. P.Nemlekar: None. D.A.Price: Employee; Dexcom, Inc. G.J.Norman: Employee; Dexcom, Inc.

885-P: Real-World Evidence on Health Care Costs Related to Self-Monitoring of Blood Glucose (SMBG) Compared with Continuous Glucose Monitoring (CGM) in Nonintensively Treated Type 2 Diabetes Mellitus (T2DM)

Background: Type 2 diabetes poses an economic burden to healthcare systems. For individuals with non-intensively treated T2DM, it is unclear whether the use of CGM would add health-economic value. The aim of this study was to compare the costs of SMBG compared to CGM in non-intensively treated T2DM. Methods: A retrospective cost-analysis using the IBM® MarketScan® Databases was conducted. T2DM patients aged ≥18 years who were using SMBG or initiated CGM between Jan 2018 and March 20were eligible for inclusion. Inclusion criteria included two consecutive claims for T2DM or one claim for T2DM and a claim for glucose lowering therapy, at least one pharmacy claim for SMBG strips or CGM sensors and continuous enrollment for 1-year before and after the index date. Individuals with CGM in pre-index period, pregnancy, rapid-acting insulin, glucagon, T1DM, gestational or secondary diabetes were excluded. SMBG and CGM patients were matched using a propensity score and all cause costs during a one-year follow-up period were compared. Results: A total of 3,498 patients were included in each matched cohort. For CGM patients, 77% used flash monitoring and 23% a real-time CGM. 35% of SMBG and 37% of CGM users were on basal insulin. Considering median values, SMBG total healthcare costs per person/year were $1,934 less vs. CGM users (p &amp;lt; 0.05) . SMBG patients had significantly lower pharmacy cost (-$2,257, p&amp;lt;0.05) and lower expenses for glucose-lowering treatments (-$1,045, p&amp;lt;0.05) than CGM. Both SMBG and CGM cohorts had similar costs related to inpatient and emergency room admissions. Conclusion: This analysis shows that SMBG is less costly than CGM in non-intensively treated T2DM patients and is associated with lower pharmacy costs, including glucose-lowering medications. Furthermore, no significant differences in the number of emergency room visits or hospitalizations are seen in SMBG and CGM users. Disclosure D. Kerr: Advisory Panel; Abbott Diabetes, Novo Nordisk A/S, Sanofi. Consultant; Evidation Health. Research Support; Novo Nordisk A/S. Stock/Shareholder; Glooko, Inc., Hi.Health. I. Duncan: Consultant; Onduo LLC. F. Giorgino: Advisory Panel; AstraZeneca, Boehringer Ingelheim International GmbH, Novo Nordisk. Consultant; Lilly Diabetes, Sanofi. Research Support; Lilly Diabetes, Roche Diabetes Care, Takeda Pharmaceutical Company Limited. E. Repetto: Employee; Roche Diabetes Care. C. Perkins: Employee; Roche Diagnostics USA. R. Maroun: Employee; Amgen Inc., Roche Diagnostics. M. Rivers: Employee; Roche Diabetes Care. A. Wu: None.

70-LB: Lower A1C with Real-Time CGM than with Intermittently-Scanned CGM after One Year—The CORRIDA LIFE Study

We investigated the efficacy of real-time continuous glucose monitoring (rtCGM) and intermittently scanned continuous glucose monitoring (isCGM) on change in A1C. CORRIDA LIFE was a 12 month, real-world, non-randomized trial that assessed the impact of rtCGM (Dexcom G5 or G6) vs. isCGM (FreeStyle Libre 14-Day, Abbott) on A1C and other CGM metrics in adults with T1D. Patients on MDI therapy or CSII with no automatic functions were included. One hundred ninety-one adults with T1D (mean age 40±13 years, A1C 8.1±3.4% [65±14 mmol/mol]) participated in this study; 81 patients initiated rtCGM and 110 initiated isCGM. After 12-months, A1C was significantly lower with rtCGM vs. isCGM (7.1±3.1% [54.1±10.1 mmol/mol] vs. 7.7±3.3% [61.2±12.2 mmol/mol]) , p=0.0001. (Figure 1) The percentage of time in hypoglycemia (&amp;lt;70 mg/dL [&amp;lt;3.9 mmol/L]) was lower among rtCGM vs. isCGM participants (4.3±2.8% vs. 6.4±5.3%) , p=0.003) . Patients with rtCGM spent less time in clinically significant hypoglycemia (&amp;lt;54 mg/dL [&amp;lt;3.0 mmol/L]) (0.9±1.0% vs. 2.3±2.5%, p&amp;lt;0.0001) and more time in target range (70-180 mg/dL [3.9-10 mmol/L]) than isCGM users (67.5±14.8% vs. 57.8±17.0%) , p=0.0002. Use of rtCGM was superior to isCGM in reducing A1C and hypoglycemia and improving other glycemic outcomes. Disclosure L. Radovnická: Consultant; Medtronic, Speaker’s Bureau; Boehringer Ingelheim International GmbH, Eli Lilly and Company, Novo Nordisk, Sanofi. M. Prazny: Advisory Panel; Bayer AG, Consultant; Boehringer Ingelheim International GmbH, Speaker’s Bureau; Abbott Diabetes, Amgen Inc., Eli Lilly and Company, Medtronic, Merck Sharp &amp; Dohme Corp., Novartis Pharmaceuticals Corporation, Novo Nordisk, Sanofi. J. Soupal: Advisory Panel; Abbott Diabetes, Roche Diabetes Care, Speaker’s Bureau; Boehringer Ingelheim International GmbH, Dexcom, Inc., Lilly Diabetes, Medtronic, Novo Nordisk. A. Hásková: None. Q. Do: None. E. Horova: None. V. Navrátilová: None. O. Mikes: None. D. Cihlár: None. C. Parkin: Consultant; Abbott Diabetes, CeQur SA, Dexcom, Inc., LifeScan, MannKind Corporation, Novo Nordisk, Provention Bio, Inc., Roche Diabetes Care. G. Grunberger: Advisory Panel; LifeScan, Nevro Corp., Research Support; Medtronic, Speaker’s Bureau; Abbott Diabetes, Eli Lilly and Company, Novo Nordisk. Funding Ministry of Health, Czech Republic, General University Hospital in Prague