G6 Continuous Glucose Monitoring System Research Articles

1816-PUB: Training and Support for Hospital Staff in the Use of Continuous Glucose Monitoring as Standard of Care in a Real-World Hospital Setting

Use of continuous glucose monitoring (CGM) in the hospital is limited and staff familiarity with CGM technology is low. During the COVID-19 pandemic and following the non-objection of the FDA to use of CGM in the hospital, the CGM as “standard of care” (CGM as SOC) program was implemented at Scripps Mercy Hospital in San Diego, CA using the Dexcom G6 CGM system. The implementation process of CGM as SOC included generating daily eligible patient lists, deploying specialized teams for CGM placement and connecting to nursing station iPads and centralized monitoring dashboards, and training of hospital nursing staff for CGM readings. A remote Advanced Practice Nurse (APN) served as an on-site trainer and expert consultant for troubleshooting. A Learning Management System (LMS) module was created for staff training and surveys assessed the training process. From May 2020-December 2022, CGM devices were placed on over 1200 adult hospitalized patients with diabetes requiring insulin. The APN conducted 30 live trainings for all units and shifts over 6 months. N=838 RNs completed the LMS module and met the required post-test passing rate of ≥ 80%. A total of N=38 self-report surveys were completed by nursing staff. Survey responses confirmed that most RNs felt confident in using the CGM nursing guide (97%) and had access to experts for troubleshooting (89%). Most common questions were related to technology troubleshooting (71%) compared to clinical issues (29%). Daily bedtime validation was transitioned from the APN to the bedside nursing staff using a validation calculator within EPIC. Despite limited baseline knowledge of CGM by hospital staff, deployment of specialized teams, APN on-site training and delivery of LMS modules supported the rapid implementation of CGM as SOC in a large community-based hospital. Standard training tools and processes can allow replication in health systems for use as part of the current provisional FDA allowance. Disclosure S.Lohnes: Consultant; Dexcom, Inc. R.Acuna: None. S.M.Saenz: None. T.Juarez: None. A.Philis-tsimikas: Advisory Panel; Dexcom, Inc., Novo Nordisk A/S, Sanofi, Other Relationship; Medtronic, Research Support; Novo Nordisk A/S, Lilly, Viking Therapeutics, NIH - National Institutes of Health. A.Bastian: None. A.L.Fortmann: Employee; Dexcom, Inc. L.Talavera: None. R.Belasco: None. H.Sandoval: None. M.Chichmarenko: None. S.R.Spierling bagsic: None. E.Soriano: None.

228-OR: Accuracy and Reliability of Real-Time Continuous Glucose Monitoring in the Intensive Care Unit after Major Abdominal Surgery

Introduction: Blood glucose control in patients requiring intensive care remains a therapeutic challenge; however, recent advancements in glucose sensing technologies have sparked interest in the potential use of real-time continuous glucose monitoring in the subcutaneous compartment (rtCGM) also in the intensive care unit (ICU) setting. We performed a clinical trial assessing the accuracy and reliability of rtCGM in postoperative ICU patients after major abdominal surgery. Methods: Patients undergoing pancreatic surgery, liver transplantation, pancreas (or pancreatic islets) and kidney transplantation were enrolled in the trial. Dexcom G6 (Dexcom, Inc., San Diego, USA) was used for rtCGM. Arterial blood glucose measured by the amperometric principle (ABL 800, Radiometer, Copenhagen, Denmark) served as reference and to calibrate the Dexcom G6 (every 6 hours on day 1, once daily day 2 and 3). Sensor accuracy was assessed by computing mean absolute relative difference (MARD), bias, modified Bland-Altman plot and surveillance error grid for paired samples of glucose values from CGM and ABL. Results: Sixty-one patients after major abdominal surgery staying in ICU post-operatively were included into this analysis. Median monitoring length was 7 days with a 97.1 ± 6.5% proportion of active CGM use. Overall, 1566 paired glucose values measured with CGM and ABL were obtained. MARD for CGM compared with ABL-measured glucose was 9.7% with a bias of 0.9% and coefficient of variation of 14%. In the surveillance error grid analysis, 90.9% of pairs were in the 0 risk zone and 7.9% in the risk zone 1 (out of 7). Throughout the study 3 sensors needed to be replaced due to technical problems. Conclusion: Our results show a clinically applicable accuracy and reliability of the Dexcom G6 continuous glucose monitoring system in postoperative ICU. This opens up new possibilities in intensifying ICU glucose control, lowering hypoglycaemia risk and reducing nursing staff workload. Disclosure B.Hagerf (voglová): None. M.Protus: None. L.Nemetova: None. M.Mraz: None. M.Haluzik: Advisory Panel; Novo Nordisk, Lilly Diabetes, Boehringer-Ingelheim, Research Support; Sanofi, Speaker's Bureau; Abbott, AstraZeneca. P.Girman: None. J.Franekova: None. V.Svirlochova: None. A.Jabor: None. Funding Charles University; Czech Ministry of Health; Institute for Clinical and Experimental Medicine (IKEM, IN00023001); National Institute for Research of Metabolic and Cardiovascular Diseases (EXCELES, LX22NPO5104)

940-P: Real-World Concordance between Point-of-Care and Continuous Glucose Monitoring among Hospitalized Patients with Diabetes

Concordance between continuous glucose monitoring (CGM) and point-of-care testing (POCT) in research studies has been promising; however, the accuracy of using CGM for glucose management in real-world settings requires evaluation. Amid the COVID-19 pandemic, the CGM as “standard of care” (CGM as SOC) program was implemented at Scripps Mercy Hospital in San Diego, CA. In this real-world setting, concordance between the Dexcom G6 CGM system and POCT was evaluated among hospitalized adult patients with diabetes requiring insulin from May 2020-July 2022. For N=880 admissions, CGM readings over the first 24 hours of wear were analyzed relative to POCT conducted within 5 minutes. Patients had a median of 3 CGM-POCT data pairs, and the first CGM-POCT pair occurred a median of 2.75 hours after CGM device placement. Mean absolute relative difference (MARD) decreased over the first 24 hours of wear (B= -0.09%, p=0.0005; Figure 1A). Following the %20/20 rule, 62% of CGM readings were concordant upon the first measured POCT; 15.8% did not meet criteria at all during the first 24-hours. Using the Clarke Error Grid to describe concordance between CGM-POCT pairs (n=3015), only 0.7% (n=22) of CGM readings would have led to incorrect treatment decisions indicated by zones D/E (Figure 1B). These findings provide support for the accuracy of CGM for glucose management in the hospital. Disclosure S.R.Spierling bagsic: None. L.Talavera: None. A.Philis-tsimikas: Advisory Panel; Dexcom, Inc., Novo Nordisk A/S, Sanofi, Other Relationship; Medtronic, Research Support; Novo Nordisk A/S, Lilly, Viking Therapeutics, NIH - National Institutes of Health. A.L.Fortmann: Employee; Dexcom, Inc. R.Belasco: None. A.Ritko: None. S.Lohnes: Consultant; Dexcom, Inc. H.Sandoval: None. M.Chichmarenko: None. E.Soriano: None. A.Bastian: None.

949-P: Hypoglycemia Detection during Real-Time Continuous Glucose Monitoring in a Real-World Hospital Setting

Continuous glucose monitoring (CGM) in the hospital can detect hypoglycemia that may go unnoticed by point-of-care testing (POCT). Following the non-objection of the FDA to the use of CGM in the hospital, using the Dexcom G6 CGM system, the “CGM as Standard of Care” (CGM as SOC) program was implemented at Scripps Mercy Hospital San Diego with a 24/7 remote-monitoring team (RMT) using a Digital Dashboard (DD). The DD alerts for glucose ≤80mg/dL and prioritizes patients by clinical risk. Using these alerts, the RMT notifies on-site bedside nurses (RN). Hypoglycemic events, defined as >15 minutes of consecutive glucose readings <70mg/dL, identified in retrospective evaluation of CGM data were analyzed to 1) evaluate appropriateness of response to events and 2) assess the accuracy of the events. 86/745 (12%) unique admissions enrolled in the CGM as SOC program between January 2021-June 2022 experienced a hypoglycemic event during the RMT period. These patients averaged 60.2 years of age, 62% male, 48% Hispanic and 87% with a type 2 diabetes diagnosis. Median number of events per admission = 1.90, for a total of 163 events. All alerts were acknowledged by the RMT, documentation that bedside RN was alerted was found on 134/163 (82%) events. It is possible that the RMT neglected to document RN outreach in the remaining 29 (18%). 90/163 events (55%) were treated as appropriate clinically, with insulin dosing changes as needed. In the remaining 69/163 (42%) events, patients were determined to not be (or no longer be) in an actionable hypoglycemia range that warranted treatment when evaluated by the RN. A small portion (10/69, 14%) were caused by documented compression on device resulting in artificially low CGM values. There were 4 (3%) events with insufficient documentation. These findings provide preliminary support of the value of an RMT in hypoglycemia surveillance in a real-world hospital setting. Additional data and recommendations for process refinements will be presented. Disclosure R.Belasco: None. L.Talavera: None. A.Philis-tsimikas: Advisory Panel; Dexcom, Inc., Novo Nordisk A/S, Sanofi, Other Relationship; Medtronic, Research Support; Novo Nordisk A/S, Lilly, Viking Therapeutics, NIH - National Institutes of Health. A.L.Fortmann: Employee; Dexcom, Inc. S.R.Spierling bagsic: None. A.Bastian: None. S.Lohnes: Consultant; Dexcom, Inc. A.Ritko: None. H.Sandoval: None. M.Chichmarenko: None. E.C.Soriano: None.

Assessing non-adjunctive CGM safety at home and in new markets (ANSHIN).

Continuous glucose monitoring (CGM) can guide treatment for people with type 1 (T1D) and type 2 diabetes (T2D). The ANSHIN study assessed the impact of non-adjunctive CGM use in adults with diabetes using intensive insulin therapy (IIT). This single-arm, prospective, interventional study enrolled adults with T1D or T2D who had not used CGM in the prior 6 months. Participants wore blinded CGMs (Dexcom G6) during a 20-day run-in phase, with treatment based on fingerstick glucose values, followed by a 16-week intervention phase and then a randomized 12-week extension phase with treatment based on CGM values. The primary outcome was change in HbA1c. Secondary outcomes were CGM metrics. Safety endpoints were the number of severe hypoglycaemic (SH) and diabetic ketoacidosis (DKA) events. Of the 77 adults enrolled, 63 completed the study. Those enrolled had mean (SD) baseline HbA1c of 9.8% (1.9%), 36% had T1D, and 44% were ≥65 years old. Mean HbA1c decreased by 1.3, 1.0 and 1.0 percentage points for participants with T1D, T2D or age ≥65, respectively (p < .001 for each). CGM-based metrics including time in range also improved significantly. SH events decreased from the run-in period (67.3 per 100 person-years) to the intervention period (17.0 per 100 person-years). Three DKA events unrelated to CGM use occurred during the total intervention period. Non-adjunctive use of the Dexcom G6 CGM system improved glycaemic control and was safe for adults using IIT.

Performance of the Dexcom G6 Continuous Glucose Monitoring System During Cardiac Surgery Using Hypothermic Extracorporeal Circulation.

Continuous glucose monitoring (CGM) may be challenged by extreme conditions during cardiac surgery using hypothermic extracorporeal circulation (ECC). We evaluated the Dexcom G6 sensor in 16 subjects undergoing cardiac surgery with hypothermic ECC, of whom 11 received deep hypothermic circulatory arrest (DHCA). Arterial blood glucose, quantified by the Accu-Chek Inform II meter, served as reference. Intrasurgery mean absolute relative difference (MARD) of 256 paired CGM/reference values was 23.8%. MARD was 29.1% during ECC (154 pairs) and 41.6% immediately after DHCA (10 pairs), with a negative bias (signed relative difference: -13.7%, -26.6%, and -41.6%). During surgery, 86.3% pairs were in Clarke error grid zones A or B and 41.0% of sensor readings fulfilled the International Organization for Standardization (ISO) 15197:2013 norm. Postsurgery, MARD was 15.0%. Cardiac surgery using hypothermic ECC challenges the accuracy of the Dexcom G6 CGM although recovery appears to occur thereafter.

Safety and efficacy of once-weekly basal insulin Fc in people with type 2 diabetes previously treated with basal insulin: a multicentre, open-label, randomised, phase 2 study

The burden of daily basal insulins often causes hesitancy and delays in the initiation of insulin therapy. Basal insulin Fc (BIF, insulin efsitora alfa), designed for once-weekly administration, is a fusion protein combining a novel single-chain insulin variant with a human immunoglobulin G (IgG) Fc domain. In this study, we explored the safety and efficacy of BIF in people with type 2 diabetes who had been previously treated with basal insulin. For this phase 2, 44-site (clinical research centres and hospitals), randomised, open-label, comparator-controlled, 32-week study in the USA, Puerto Rico, and Mexico, we enrolled participants with type 2 diabetes. Eligible participants had to be adults (aged ≥18 years) and to have been treated with basal insulin and up to three oral antidiabetic medicines. Participants were randomly assigned (1:1:1) to subcutaneous administration of BIF (BIF treatment group 1 [BIF-A1] or 2 [BIF-A2]) or insulin degludec. Randomisation was stratified by country, baseline HbA1c values (<8·5% or ≥8·5%; <69·4 or ≥69·4 mmol/mol), use of sulfonylureas (yes or no), and baseline BMI (<30 or ≥30 kg/m2). The randomisation scheme was performed using an interactive web-response system, which ensured balance between treatment groups. Different fasting glucose targets for the BIF-A1 (≤7·8 mmol/L or ≤140 mg/dL; titrated every 2 weeks), BIF-A2 (≤6·7 mmol/L or ≤120 mg/dL; titrated every 4 weeks), and degludec (≤5·6 mmol/L or ≤100 mg/dL) groups were selected. Patients randomly assigned to BIF received a one-time loading dose ranging from 1·5-3 times their calculated weekly dose. The first weekly dose was administered 1 week after the loading dose. We used interstitial fasting glucose measurements from the Dexcom G6 continuous glucose monitoring system to titrate the basal insulin. The primary measure of glycaemic control was change in HbA1c from baseline to week 32 for BIF. BIF was also compared with degludec (with a non-inferiority margin of 0·40%). The efficacy analysis set consisted of data from all randomised study participants who received at least one dose of the study medication and participants were analysed according to the treatment they were assigned. The safety population was the same as the efficacy analysis set. The completed trial is registered at ClinicalTrials.gov (NCT03736785). Between Nov 15, 2018 and Feb 18, 2020, 399 participants were enrolled and randomised to BIF-A1 (n=135), BIF-A2 (n=132), or degludec (n=132); 202 (51%) were female and 197 (49%) were male. 379 were analysed for the primary outcome (BIF-A1: n=130; BIF-A2: n=125; degludec: n=124). Mean HbA1c change from baseline to week 32, the primary outcome, was -0·6% (SE 0·1%) for BIF-A1 and BIF-A2. Degludec achieved a change from baseline of -0·7% (0·1%). The pooled BIF analysis achieved non-inferiority versus degludec for the treatment difference in HbA1c (0·1% [90% CI -0·1 to 0·3]). The hypoglycaemia (≤3·9 mmol/L or ≤70 mg/dL) event rates (hypoglycaemia events per patient per year) in the BIF groups were 25% lower than those in the degludec group (treatment ratio BIF-A1 vs degludec was 0·75 [0·61-0·93]; and BIF-A2 vs degludec was 0·74 [0·58-0·94]). BIF was well tolerated; treatment-emergent adverse events were similar across groups. Weekly BIF achieved a similar efficacy compared with degludec despite higher fasting glucose targets in the BIF groups. Higher fasting glucose targets and lower glucose variability might have contributed to lower hypoglycaemia rates for BIF compared with degludec. These findings support continued development of BIF as a once-weekly insulin treatment for people with diabetes. Eli Lilly and Company.

Accuracy of Real Time Continuous Glucose Monitoring during Different Liquid Solution Challenges in Healthy Adults: A Randomized Controlled Cross-Over Trial.

Continuous glucose monitoring (CGM) represents an integral of modern diabetes management, however, there is still a lack of sensor performance data when rapidly consuming different liquids and thus changing total body water. 18 healthy adults (ten females, age: 23.1 ± 1.8 years, BMI 22.2 ± 2.1 kg·m−2) performed four trial visits consisting of oral ingestion (12 mL per kg body mass) of either a 0.9% sodium chloride, 5% glucose or Ringer’s solution and a control visit, in which no liquid was administered (control). Sensor glucose levels (Dexcom G6, Dexcom Inc., San Diego, CA, USA) were obtained at rest and in 10-min intervals for a period of 120 min after solution consumption and compared against reference capillary blood glucose measurements. The overall MedARD [IQR] was 7.1% [3.3–10.8]; during control 5.9% [2.7–10.8], sodium chloride 5.0% [2.7–10.2], 5% glucose 11.0% [5.3–21.6] and Ringer’s 7.5% [3.1–13.2] (p < 0.0001). The overall bias [95% LoA] was 4.3 mg·dL−1 [−19 to 28]; during control 3.9 mg·dL−1 [−11 to 18], sodium chloride 4.8 mg·dL−1 [−9 to 19], 5% glucose 3.6 mg·dL−1 [−33 to 41] and Ringer’s solution 4.9 mg·dL−1 [−13 to 23]. The Dexcom G6 CGM system detects glucose with very good accuracy during liquid solution challenges in normoglycemic individuals, however, our data suggest that in people without diabetes, sensor performance is influenced by different solutions.

Use of factory-calibrated real-time continuous glucose monitoring improves time in target and HbA1c in a multiethnic cohort of adolescents and young adults with type 1 diabetes: the MILLENNIALS study

OBJECTIVE International type 1 diabetes registries have shown that HbA1c levels are highest in young people with type 1 diabetes; however, improving their glycemic control remains a challenge. We propose that use of the factory-calibrated Dexcom G6 CGM system would improve glycemic control in this cohort. RESEARCH DESIGN AND METHODS We conducted a randomized crossover trial in young people with type 1 diabetes (16–24 years old) comparing the Dexcom G6 CGM system and self-monitoring of blood glucose (SMBG). Participants were assigned to the interventions in random order during two 8-week study periods. During SMBG, blinded continuous glucose monitoring (CGM) was worn by each participant for 10 days at the start, week 4, and week 7 of the control period. HbA1c measurements were drawn after enrollment and before and after each treatment period. The primary outcome was time in range 70–180 mg/dL. RESULTS Time in range was significantly higher during CGM compared with control (35.7 ± 13.5% vs. 24.6 ± 9.3%; mean difference 11.1% [95% CI 7.0–15.2]; P CONCLUSIONS CGM use in young people with type 1 diabetes improves time in target and HbA1c levels compared with SMBG.

900-P: Continuous Glucose Monitoring in Youth with Type 2 Diabetes: A Pilot and Feasibility Study

Objective: Real-time continuous glucose monitoring (CGM) is effective for diabetes management in T1D and adults with T2D, but has not been assessed in youth with T2D. The objective of this study was to assess the feasibility and acceptability of CGM use in youth with T2D. Methods: Youth (13- 21 years old) with T2D ≥ 6 months and A1c &amp;gt; 7%, on any FDA approved treatment regimen were included. After a blinded run-in period, participants were given a Dexcom G6 CGM system for 12 weeks. The use and acceptability of the real-time CGM were evaluated by sensor usage, surveys, and focus group qualitative data. Results: Youth (n=8) had median age 19.4 (IQR 15.5-20.6) years, were 75% female, 50% hispanic/latino ethnicity, 50% non-English speaking at home, and 91% had public insurance. Baseline A1c was 11.7 (±2.8)% with mean diabetes duration of 2.5 (IQR 1.4 - 5.1) years and 75% were on basal insulin. Of the 7 participants who have completed the CGM intervention, all reported CGM was a positive experience (50% very positive, 50% slightly positive), easy to use (50% very easy, 50% easy), and useful (83% useful, 17% useful). All participants desired to continue to use real-time CGM in the future. 85% were “extremely” likely to recommend real-time CGM to friends. 67% of participants self-reported eating fewer meals while using CGM. All participants used sensors for the duration of the study. Conclusion: Real-time CGM is feasible and acceptable for youth with type 2 diabetes. Larger randomized controlled trials are needed to assess effects on glycemic control, healthy lifestyle changes, and diabetes distress. Disclosure H. Chesser: None. S. Srinivasan: None. J. C. Wong: Advisory Panel; Self; Provention Bio, Inc., Research Support; Self; Dexcom, Inc., Tandem Diabetes Care.

622-P: Frequent Engagement with Retrospective Real-Time CGM Data Is Associated with Improved Glycemic Control

Real-time continuous glucose monitoring (CGM) systems allow users to take immediate action based on current glucose and its trajectory; retrospective review of CGM data permits behavior modification according to historic trends. Dexcom CGM Systems allow for data to be uploaded automatically into Dexcom CLARITY for retrospective review. CLARITY mobile app users can also engage with their recent data by setting goals for time in range (TIR; 70-180 mg/dL) and opting to receive push notifications when TIR goals are met. We evaluated the associations between CLARITY engagement and glycemic metrics. Anonymized data uploaded in September 2020 by a convenience sample of 25,000 US-based users of the G6 CGM System (Dexcom, Inc., San Diego, CA) were assessed. Users were stratified by those who engaged with CLARITY never, at least once, or every day in September 2020. Utilization was calculated as the number of sensor glucose values over the number of total possible sensor glucose values for days with ≥1 glucose value. CGM-derived glycemic metrics are shown in the Table. Increased CLARITY engagement was associated with lower mean glucose and higher TIR, mainly attributable to less hyperglycemia. Hypoglycemia exposure was consistently low and did not depend on the extent of CLARITY engagement. Frequent retrospective CGM data review may motivate behaviors that result in improved glycemic control.View largeDownload slideView largeDownload slide DisclosureJ. H. Van der linden: Employee; Self; Dexcom, Inc. S. Puhr: Employee; Self; Dexcom, Inc. J. Welsh: Employee; Self; Dexcom, Inc. T. C. Walker: Employee; Self; Dexcom, Inc.

Association between attendance at an American diabetes camp and improvements in glycaemic control and treatment satisfaction.

IntroductionFew studies have evaluated glycaemic control using continuous glucose monitoring (CGM) in individuals before and after attendance at a diabetes camp or by comparing control groups at home to control groups at camp.MethodsYouth (6–17 years) with T1D and receiving insulin therapy were enrolled at a week‐long diabetes camp. They participated in three clinic visits: at the start of a week at home, by initiating a Dexcom G6 CGM system; at the start of a week at camp, where the home week G6 was removed and a camp week G6 was inserted; and after camp, where the camp week G6 was removed. We administered Problem Areas in Diabetes (PAID) surveys at the second and third visits. Participants with <80% CGM data coverage or who did not complete all PAID surveys were excluded from analysis. We compared glycaemic control and PAID scores between the week at home and week at camp.ResultsOf 76 enrolled campers, 69 completed the study and 52 had results that qualified for analysis. The mean participant age was 12.5 ± 2.2 years. Camp was associated with significantly improved treatment satisfaction, time in desired glucose range and insulin sensitivity. Time in hyperglycaemia and basal insulin requirements decreased significantly.ConclusionsDiabetes camp is associated with significant improvements in diabetes treatment satisfaction and glycaemic control compared to home care.

Should Target Glucose Values Be Increased to Avoid Severe Hypoglycemia? Real-World Data Say “No.”

Early studies such as the Diabetes Control and Complications Trial showed a strong inverse relationship between A1C and the risk of severe hypoglycemia in type 1 diabetes. This risk has historically limited insulin therapy intensification efforts, and some treatment guidelines (e.g., Rosenzweig et al., J Clin Endocrinol Metab 105:969, 2020) suggest that A1C values <7% confer an increased risk of hypoglycemia. Nowadays, real-time continuous glucose monitoring (CGM) systems can flatten and attenuate the relationship between overall glucose control and hypoglycemia (Oliver et al., Diabetes Care 43:53, 2020). The glucose management indicator (GMI) is an estimate of A1C derived from the CGM system’s mean estimated glucose value (EGV) (Bergenstal et al., Diabetes Care 41:2275, 2018). We analyzed real-world evidence of the relationship between the GMI and exposure to hypoglycemia. Data were from an anonymized convenience sample of US-based users of the G6 CGM system (Dexcom, Inc., San Diego, CA) who used a mobile device to upload EGVs in the third quarter of 2020. Only data from people who had uploaded ≥80% of possible values were included. Each person’s GMI was calculated as GMI = 3.31 + (0.02392 × mean EGV [mg/dL]). Each person’s exposure to hypoglycemia was estimated as the percentage of EGVs <70 mg/dL or <54 mg/dL (%<70 and %<54, respectively). Patients were grouped into 6 categories according to GMI values <6.5%, 6.5 to 6.9%, 7.0 to 7.4%, 7.5 to 7.9%, 8.0 to 8.4%, and ≥8.5%. Mean %<70 mg/dL and %<54 mg/dL were both inversely correlated with GMI, decreasing monotonically as the GMI category increased. GMI category, %<70, and %<54 are as follows: (<6.5%: 5.27%, 1.13%); (6.5 to 6.9%: 2.84%, 0.59%); (7.0 to 7.4%: 1.95%, 0.41%); (7.5 to 7.9%: 1.46%, 0.31%); (8.0 to 8.4%: 1.14%, 0.25%); (≥8.5%: 0.69%, 0.17%). However, in all GMI categories except for the “<6.5%” category, the extent of hypoglycemic exposure was below the consensus targets proposed by Battelino et al. (Diabetes Care 42:1593, 2019) of <4% for EGVs <70 mg/dL and <1% for EGVs <54 mg/dL. The approach of elevating A1C targets to reduce hypoglycemia risk is not supported by real-world evidence for CGM users who have GMI or A1C values ≥6.5%. CGM users can safely strive for A1C values <7.0%.

Change in Hemoglobin A1c and Quality of Life with Real-Time Continuous Glucose Monitoring Use by People with Insulin-Treated Diabetes in the Landmark Study.

Background: Initiating continuous glucose monitoring (CGM) can affect hemoglobin A1c (HbA1c) levels and patients' relationship with their diabetes. We used real-world HbA1c data to quantify short-term changes in glycemia and validated psychosocial questionnaires to assess changes in quality-of-life indicators in people during their first few months of CGM use.Methods: Eligibility was assessed during calls to Dexcom sales regarding its G6 CGM System. Eligibility criteria included ages 25–65 years, type 1 (T1D) or type 2 diabetes (T2D) on intensive insulin therapy (IIT), and no prior CGM use. Participants used a web-based portal to complete the 17-item Diabetes Distress Scale (DDS) and the 14-item Hypoglycemia Attitudes and Behavior Scale (HABS); provided validated HbA1c measurements; and shared their CGM data pre- and 3–5 months post-CGM initiation. Satisfaction and ease of use with the G6 System were also assessed.Results: Data were available from 248 patients (182 with T1D, 66 with T2D; 57% male, 88% non-Hispanic white). Mean (standard deviation) HbA1c fell significantly from 8.2% (1.9%) at baseline to 7.1% (1.1%) at the end of the study (P < 0.001); more than half (54.4%) of those with initial HbA1c values >7% experienced absolute HbA1c reductions of >1%. Significant reductions in diabetes distress (DDS) and hypoglycemic concerns (HABS) were observed (P < 0.001). Most (93%) participants were satisfied or very satisfied with the G6 System and 73% found it very easy to use.Conclusions: The first 3 months of CGM use was correlated with improvements in psychosocial outcomes and improved HbA1c levels for people with T1D or T2D who use IIT.

Real-World Evidence and Glycemic Improvement Using Dexcom G6 Features.

Background: Optional features of continuous glucose monitoring (CGM) systems empower patients and caregivers to understand and manage diabetes in new ways. We examined associations between use of optional features, demographics, and glycemic outcomes.Methods: Retrospective cohort studies were performed with data from US-based users of the G6 CGM System (Dexcom, Inc.). For all cohorts, data included sensor glucose values (SGVs). In separate cohorts, use of alert features (for hyperglycemia, existing hypoglycemia, and impending hypoglycemia), remote data sharing feature (Share), software for retrospective pattern analysis (CLARITY), “virtual assistant” feature that announces the current SGV and trend in response to a spoken request were assessed. Descriptive statistics were used to summarize feature set utilization patterns and relate them to glycemic outcomes.Results: Most individual features were consistently adopted by high proportions of G6 users. Threshold SGVs chosen for activating hyperglycemia and hypoglycemia alerts varied with age and were higher among the youngest and oldest patients. Use of the Share feature was more common among young patients and those with type 1 diabetes. Individuals who used more of the alert and notification features had more favorable glycemic outcomes, including time in range (TIR), than those who used fewer. More extensive engagement with CLARITY notifications was associated with higher TIR. Frequent use of the virtual assistant feature was associated with higher TIR and lower mean SGV.Conclusions: Optional features of the G6 CGM system are acceptable to and appear to benefit patients who use them. Different levels of engagement suggest that demographics and personal circumstances play a role in how patients and caregivers use CGM features to help manage diabetes.

Performance of the Dexcom G6 Continuous Glucose Monitoring System in Pregnant Women with Diabetes.

Background: The aim of this study was to determine the performance of the Dexcom G6 continuous glucose monitoring (CGM) system across three sensor wear sites in pregnant women with diabetes in the second or third trimesters.Methods: Participants with type 1 (T1D), type 2 (T2D), or gestational (GDM) diabetes mellitus were enrolled at three sites. Each wore two G6 sensors on the abdomen, upper buttock, and/or posterior upper arm for 10 days and underwent a 6-h clinic session between days 3 and 7 of sensor wear, during which YSI reference blood glucose values were obtained every 30 min. No intentional glucose manipulations were performed. Accuracy metrics included the proportion of CGM values that were within ±20% of paired reference values >100 mg/dL or ±20 mg/dL of YSI values ≤100 mg/dL (hereafter referred to as %20/20), as well as the analogous %15/15, %30/30, and %40/40. The mean absolute relative difference (MARD) between CGM-YSI pairs was also calculated.Results: Thirty-two participants with T1D (n = 20), T2D (n = 3), or GDM (n = 9) were enrolled: 19 were in the second trimester and 13 were in the third trimester of pregnancy. Compared with the reference, 92.5% of CGM values were within ±20%/20 mg/dL. The overall MARD and that of sensors worn on the abdomen, upper buttock, and posterior upper arm was 10.3%, 11.5%, 11.2%, and 8.7%, respectively. There were no device-related adverse events. Skin reactions at the insertion sites were absent or minor.Conclusions: The Dexcom G6 CGM system is accurate and safe in pregnant women with diabetes.

Use of Factory-Calibrated Real-time Continuous Glucose Monitoring Improves Time in Target and HbA1c in a Multiethnic Cohort of Adolescents and Young Adults With Type 1 Diabetes: The MILLENNIALS Study.

International type 1 diabetes registries have shown that HbA1c levels are highest in young people with type 1 diabetes; however, improving their glycemic control remains a challenge. We propose that use of the factory-calibrated Dexcom G6 CGM system would improve glycemic control in this cohort. We conducted a randomized crossover trial in young people with type 1 diabetes (16-24 years old) comparing the Dexcom G6 CGM system and self-monitoring of blood glucose (SMBG). Participants were assigned to the interventions in random order during two 8-week study periods. During SMBG, blinded continuous glucose monitoring (CGM) was worn by each participant for 10 days at the start, week 4, and week 7 of the control period. HbA1c measurements were drawn after enrollment and before and after each treatment period. The primary outcome was time in range 70-180 mg/dL. Time in range was significantly higher during CGM compared with control (35.7 ± 13.5% vs. 24.6 ± 9.3%; mean difference 11.1% [95% CI 7.0-15.2]; P < 0.001). CGM use reduced mean sensor glucose (219.7 ± 37.6 mg/dL vs. 251.9 ± 36.3 mg/dL; mean difference -32.2 mg/dL [95% CI -44.5 to -20.0]; P < 0.001) and time above range (61.7 ± 15.1% vs. 73.6 ± 10.4%; mean difference 11.9% [95% CI -16.4 to -7.4]; P < 0.001). HbA1c level was reduced by 0.76% (95% CI -1.1 to -0.4) (-8.5 mmol/mol [95% CI -12.4 to -4.6]; P < 0.001). Times spent below range (<70 mg/dL and <54 mg/dL) were low and comparable during both study periods. Sensor wear was 84% during the CGM period. CGM use in young people with type 1 diabetes improves time in target and HbA1c levels compared with SMBG.

266-OR: Rebound Hyperglycemia in Real-World Data and Its Mitigation with a CGM-Based Predictive Alert

Symptomatic hypoglycemia is an incentive for carbohydrate intake which, in excess, can lead to rebound hyperglycemia (RH) and contribute to high glycemic variability. We examined whether an optional "urgent low soon" (ULS) alert triggered by impending hypoglycemia could mitigate RH in the real world. Sensor glucose values (SGVs) were from the G5 and G6 continuous glucose monitoring (CGM) systems (Dexcom). G5 does not offer the ULS feature; all G6 usage was with the ULS alert enabled. An RH event was defined as any series of SGVs &amp;gt;180 mg/dL preceded within 2 hours by a low SGV (&amp;lt;70 or &amp;lt;55 mg/dL). Event severity was defined as the area under the curve (AUC) for consecutive SGVs &amp;gt;180 mg/dL. Data from a convenience sample of 24,518 anonymized G5 users who transitioned to G6 and uploaded ≥30 days of data from each system in 2018 were analyzed. RH events preceded by an SGV &amp;lt;70 mg/dL and those preceded by an SGV &amp;lt;55 mg/dL were analyzed separately. For both types of RH events, the transition from G5 to G6 and its predictive alert was associated with favorable and statistically significant reductions in the mean (SD) frequency, severity, and duration RH events (Table). The ULS alert in the G6 CGM system, intended to reduce hypoglycemia, mitigates RH events in users who transition from a system without predictive alerts and may contribute to other metrics of improved glycemic control. Disclosure G. Acciaroli: Employee; Self; Dexcom, Inc. A. Parker: Employee; Self; Dexcom, Inc. Stock/Shareholder; Self; Dexcom, Inc. J. Welsh: Employee; Self; CSL Behring. S. Puhr: Employee; Self; Dexcom, Inc. T.C. Walker: Employee; Self; Dexcom, Inc. H.K. Akturk: Advisory Panel; Self; Sanofi US. Research Support; Self; Eli Lilly and Company, REMD Biotherapeutics, Senseonics.

870-P: A1C Reductions and Improved Patient-Reported Outcomes following CGM Initiation in Insulin-Managed T2D

Initiating therapeutic continuous glucose monitoring (CGM) can affect A1C levels and patients’ relationship to their diabetes. We used real-world A1C data to quantify short-term glycemic changes in people with T2D new to CGM. Eligibility was assessed during calls to Dexcom regarding its G6 CGM system. Criteria included ages 25-65 years, use of intensive insulin therapy (IIT), no prior CGM use, coverage with a non-government health plan, willingness to provide validated A1C values and survey responses at baseline and at ∼12 weeks after CGM initiation, and willingness to share CGM data via CLARITY (Dexcom). Patient-reported outcome (PRO) surveys included the diabetes distress scale (DDS), hypoglycemic attitudes and behavior scale (HABS), and diabetes quality of life short inventory (DQOL). G6 satisfaction and ease of use were also assessed. Data from 39 participants were available for this interim analysis. Compared to baseline, the ∼12-week data showed a mean 1.5 percentage point reduction in A1C (Figure). Nineteen (49%) of the participants had at least a 1 percentage point A1C reduction. PRO scores improved by 31% for the DDS, by 22% for the HABS, and by 24% for the DQOL. Most participants found the G6 system satisfactory or very satisfactory (95%) and very easy to use (85%). Patients with T2D using IIT may experience significant glycemic and psychosocial benefits within 12 weeks of starting G6 CGM. Disclosure A. Noar: Employee; Self; Dexcom, Inc., Tandem Diabetes Care. J. Welsh: Employee; Self; CSL Behring. D.A. Price: Employee; Self; Dexcom, Inc.

76-LB: Differences in Time-In-Range, Glycemic Variability, and the Glucose Management Indicator in Pregnant Women with Type 1 (T1D), Type 2 (T2D), and Gestational Diabetes (GDM)

Glycemic control varies among different cohorts of pregnant women with diabetes. Most studies examining differences between groups using continuous glucose monitoring (CGM) data were performed with older CGM systems worn for 2-7 days. We examined differences in glycemic control and glycemic variability (GV) between pregnant women (n=32) with T1D (n=20), T2D (n=3), or GDM (n=9) in the 2nd and 3rd trimesters using the Dexcom G6 CGM system, worn for 10 days as part of a pregnancy CGM accuracy trial. Pair-wise comparisons were made between groups and group heterogeneity testing was performed. No adjustments were made for multiple comparisons analyses. Most women required insulin therapy (26/32, 81%). The baseline HbA1C levels were similar between groups (Table). The glucose management indicator (GMI) was numerically similar to HbA1C for the T1D and GDM cohorts. Time spent &amp;gt;140 mg/dL (p=0.009) was highest and time in range (63-140 mg/dL) was lowest (p=0.001) in women with T1D compared to the other groups. The coefficient of variation (CV) and mean amplitude of glycemic excursions (MAGE) were highest in the T1D group, lowest in the GDM group, and intermediate in the T2D group (p&amp;lt;0.0001 for each). Glycemic control was better and GV was lower for pregnant women with T2D and GDM compared to women with T1D. CGM use in pregnancy helps elucidate GV. Disclosure S. Polsky: None. C.J. Levy: Consultant; Self; Dexcom, Inc. Employee; Spouse/Partner; Allergan plc. Research Support; Self; Abbott, Dexcom, Inc., Insulet Corporation. X. Zhang: Employee; Self; Dexcom, Inc. S. Shah: Employee; Self; Dexcom, Inc. G. Haroush: None. K. Nelson: None. G. O’Malley: Research Support; Self; Abbott, Dexcom, Inc. S.J. Ogyaadu: None. S.J. Brackett: None. C. Levister: None. K.N. Castorino: Research Support; Self; Abbott, Dexcom, Inc., Medtronic, Mylan, Novo Nordisk Inc. Funding Dexcom, Inc.