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The study was designed to determine the effect of TPT vs. standard care (SC) on change in A1C and T2DM remission at 90 day intervals, in addition to multiple secondary endpoints. The TPT intervention uses the Whole-Body Digital Twin Platform, with AI and Internet of Things, to integrate multi-dimensional data to give precision nutrition and health recommendations via the TPT app and by coaches. Baseline mean age, diabetes duration and A1C obtained in 319 pts were 45y (±9.7y) , 3.9y (±2.9y) and 9.0% (±1.9%) , respectively. Interim analysis of 262 pts (TPT n=199; SC n=63) who reached 180d showed 94.9% (189/199) of TPT pts had A1C < 6.5%, on no medications or metformin only; 83.9% (167/199) achieved diabetes remission based on ADA criteria. All 9 insulin-using pts stopped insulin before 90d. The Table shows significant improvement in secondary endpoints in TPT pts at baseline and 180d, including A1C (9.0% to 5.7%, P Disclosure P. Shamanna: None. M. Thajudeen: None. A. Keshavamurthy: None. F. R. Kaufman: Consultant; Twin Health, Employee; Senseonics. S. R. Joshi: Advisory Panel; AstraZeneca, Consultant; Biocon, Franco India, Glenmark Pharmaceuticals, Marico, Sanofi, Twinhealth, Zydus Cadila, Speaker’s Bureau; Abbott, Serdia Pharmaceuticals (India) Pvt. Ltd. L. Shah: None. J. Mohammed: None. M. Mohamed: None. T. Poon: None. M. Dharmalingam: None. B. Saboo: None. S. Damodharan: None. A. Vadavi: None.

Background: The PROMISE Clinical Trial, conducted to assess safety and accuracy of a 180-day implantable CGM System, had 43 subjects implanted with a modified sensor containing sacrificial boronic acid (SBA) to reduce the degradation of the boronic acid glucose-binding moieties. In-home use to 365 days was monitored in a 30 subject SBA sub-study. Methods: Accuracy of sensor glucose (SG) measurements produced by an algorithm emulator was compared to YSI model 2300 glucose obtained during in-clinic visits to 180 days. The sub-study compared SG to fingerstick blood glucose (BG, CONTOUR Next One BG meter) 4-7 times/day, from days 1-365 or until sensor retirement. SG values were paired within 5 mins after a BG values in the 30 sensors. MARD for 1-180 days was assessed with both YSI and BG reference methods. MARD by glucose ranges were compared for 1-180 days, 181-365 days and 1-365 days using BG as reference. Results: The MARD for SBA sensors for days 1-180 from in-clinic visits was 8.1% with YSI and 9.5% with BG as reference. The Table shows a comparison of MARD values by glucose ranges for the 3 time periods. Conclusions: There was ∼1.4 percentage point increase in overall MARD obtained when BG measurements were used as the reference value rather than YSI. The extension of the PROMISE Clinical Trial in a subset of subjects implanted with SBA sensors suggests accuracy can be maintained and extended to 365 days and across 40-400 mg/dl glucose ranges. Disclosure A.E.Jacquin: Employee; Senseonics, Other Relationship; BrainScope Company, Inc. L.Al-khawi: None. P.Sanchez: Employee; Senseonics. S.Mohanty: Employee; Senseonics. K.S.Tweden: Employee; Senseonics. F.R.Kaufman: Consultant; Twin Health, Employee; Senseonics.

Background: The Eversense CGM System sensor is implanted in the upper arm. It uses a fluorescent, boronic acid glucose-binding moiety to measure glucose. The glucose indicator is susceptible to oxidative de-boronation from reactive oxygen species (ROS) in the interstitial fluid, necessitating daily calibrations. To reduce calibration frequency, a ROS indicator was added to measure oxidative de-boronation. Figure 1 (a) shows the copolymerization of glucose and ROS indicators into a single hydrogel matrix with orthogonal excitation emission properties. The sensor uses a 380 nm LED for excitation of the glucose indicator and a 470 nm LED for excitation of the ROS indicator. Methods: The fluorescence of the indicators was characterized in vitro. In addition, sensors were implanted in subjects with type 1 diabetes in a 365-day clinical feasibility study to assess accuracy against fingerstick measurements. Results: Figure 1 (b) illustrates the relationship whereby ROS exposure increases the fluorescence of the ROS indicator and decreases the fluorescence of the glucose indicator. A MARD of 9.9% against fingerstick with one calibration per week was observed through 90 days. Conclusions: Early data suggests the multiple-analyte system should allow the next generation of long-term, implanted CGM systems to maintain accuracy with significantly reduced calibration requirements. Disclosure V.N.Velvadapu: None. J.M.Masciotti: Employee; Senseonics. A.D.Dehennis: Employee; Senseonics. P.Sanchez: Employee; Senseonics. K.S.Tweden: Employee; Senseonics. F.R.Kaufman: Consultant; Twin Health, Employee; Senseonics. S.Ioacara: Research Support; Senseonics.

Background: The PROMISE Clinical Study was conducted to determine the accuracy and safety of the next generation implantable CGM System. A subset of 43 subjects had a sensor implanted with modified chemistry referred to as sacrificial boronic acid (SBA) , to protect the boronic acid glucose-binding moieties from degradation. This post-hoc analysis investigated the effect of SBA on accuracy through 180 days using different calibration (cal) schemes. Methods: Data from the PROMISE Clinical Study from participants with SBA sensors was run through an algorithm emulator with cals of 1/day, 2/day, or using a dynamic cal scheme switching between 1-2/day, all starting on day 22 (day 1-21 had fixed 2 cals/day) . MARD was analyzed by glucose ranges and days of sensor wear through 180 days. Results: The Table shows the MARD by glucose ranges and cal frequency. MARD (%) by days of sensor wear demonstrated: 9.6, 9.4, 9.2 on days 1-30; 9.5, 8.6, 8.3 on days 31-60; 7.7, 7.4, 7.6 on days 61-90; 8.3, 8.0, 7.9 on days 91-120; 9.6, 8.8, 7.5 on days 121-150; and 7.0, 7.3, 6.9 on days 151-180, respectively, for 1 cal/day, dynamic cal, and 2 cals/day. Conclusions: The SBA sensor maintains an overall MARD less than 9.0% by glucose range and 9.6% by days of sensor wear through 180 days, whether it has a cal scheme of 1, dynamic, or 2 cal per day. By reducing sensor degradation with the SBA chemistry modification, the sensor maintains long-term accuracy with 1 cal/day. Disclosure A.E.Jacquin: Employee; Senseonics, Other Relationship; BrainScope Company, Inc. L.Al-khawi: None. S.Ghosh-dastidar: Employee; Senseonics. K.S.Tweden: Employee; Senseonics. F.R.Kaufman: Consultant; Twin Health, Employee; Senseonics.

Aims This real‐world study evaluated the changes in glycated haemoglobin (HbA1c) and continuous glucose monitoring (CGM) metrics associated with use of the implantable 180‐day Eversense CGM System (Eversense) in patients with type 1 diabetes. Materials and methods This was a prospective, multicentre, observational study among adult participants aged ≥18 years with type 1 diabetes across seven diabetes‐care centres in Italy who had Eversense inserted for the first time. HbA1c was measured at baseline and at 180 days. Changes in time in range [TIR (glucose 70–180 mg/dL)], time above range [TAR (glucose >180 mg/dL)], time below range [TBR (glucose

Previously, the safety and accuracy of the Eversense continuous glucose monitoring (CGM) system were characterized in three pivotal trials among individuals with type 1 diabetes (T1D) and type 2 diabetes (T2D) with a single 90- or 180-day sensor insertion-removal cycle. The Post-Market Clinical Follow-up (PMCF) registry is a prospective study evaluating the long-term safety and performance of the Eversense CGM system over multiple sensor insertion-removal cycles among adults with T1D and T2D. All patients who had a sensor subcutaneously implanted across 534 participating centers in Europe and South Africa from June 2016 to August 2018 were enrolled. Adverse events (AEs) were recorded at each visit and patients were instructed to inform their clinic if they experienced any AEs between visits. AEs were adjudicated for relatedness to the device, procedure, or drug (dexamethasone acetate). The primary safety endpoint was the rate of related serious adverse events (SAEs) through four sensor insertion-removal cycles. The registry enrolled 3023 patients. As of last follow-up, 5417 sensors had been inserted with a total of 1260 patient-years (PYs) of follow-up: 969 patients had used the system for at least 6 months and 173 patients had used the system for at least 1 year. No related SAEs were reported. The most frequently reported related AEs were sensor location site infection (0.96%; 2.46 events per 100 PYs), inability to remove the sensor upon first attempt (0.76%; 1.90 events per 100 PYs), and adhesive patch location site irritation (0.66%; 1.59 events per 100 PYs). One nonserious allergic reaction to lidocaine was reported, which resolved with administration of an antihistamine. The full intended sensor life was achieved by 91% of 90-day sensors and 75% of 180-day sensors. The PMCF registry provides real-world evidence that the Eversense CGM system is safe over multiple cycles of use.

Background: The Eversense® Continuous Glucose Monitoring (CGM) System, with the first 90-day implantable sensor, received FDA (Food and Drug Administration) approval in June 2018. No real-...

Continuous glucose monitoring (CGM) systems offer real-time data to facilitate diabetes management. The novel Eversense CGM has been approved in Europe and the US. The unique characteristics are the fully implantable sensor and the sensor life up to 180 days.This expert review describes the results of clinical trials, and the accuracy and safety of the Eversense system. The overall MARD ranges from 8.5% to 9.4%, the 20/20% agreement rate ranges from 84% to 94%, and the percent of values in zones A and B on the Clarke Error Grid is 99.2%. No device-related serious adverse events have been described during pivotal trial studies. The most frequently reported device- or procedure-related adverse events are sensor adhesive patch location site irritation (0.66%), inability to remove the sensor upon first attempt (0.76%), and location site infection (0.96%). Mean A1c reduction is about 0.4% from pivotal trials and real-world studies.The Eversense system is novel and differentiated from transcutaneous CGM systems. The long life, the removable transmitter, and the on-body vibration alerts offer opportunities to properly manage diabetes with both MDI and insulin pump therapy.

Background: Use of continuous glucose monitoring (CGM) systems is being rapidly adopted as standard of care for insulin-requiring patients with diabetes. The PROMISE study (NCT03808376) evaluated the accuracy and safety of the next-generation implantable Eversense CGM system for up to 180 days. Methods: This was a prospective multicenter study involving 181 subjects with diabetes at 8 USA sites. All subjects were inserted with a primary sensor. Ninety-six subjects had a second sensor, either an identical sensor or a modified sensor (sacrificial boronic acid [SBA]), inserted in their other arm (53 and 43 subjects, respectively). Accuracy was evaluated by comparing CGM to YSI 2300 glucose analyzer (Yellow Springs Instrument [YSI]) values during 10 clinic visits (day 1–180). Confirmed event detection rates, calibration stability, sensor survival, and serious adverse events (SAEs) were evaluated. Results: For primary sensors, the percent CGM readings within 20%/20% of YSI values was 92.9%; overall mean absolute relative difference (MARD) was 9.1%. The confirmed alert detection rate at 70 mg/dL was 93% and at 180 mg/dL was 99%. The median percentage of time for one calibration per day was 56%. Sixty-five percent of the primary sensors survived to 180 days. For the SBA sensors, the percent CGM readings within 20%/20% of YSI values was 93.9%; overall MARD was 8.5%. The confirmed alert detection rate at 70 mg/dL was 94% and at 180 mg/dL was 99%. The median percentage of time for one calibration per day was 63%. Ninety percent of the SBA sensors survived to 180 days. No device- or insertion/removal procedure-related SAEs were reported. Conclusion: These data show the next-generation Eversense CGM system had sustained accuracy and safety up to 180 days, with an improved calibration scheme and survival, using the primary or SBA sensors.

Background: The prospective, multi-center PROMISE study evaluated the safety and accuracy of the next generation Eversense CGM System for up to 180 days in 181 adults with diabetes at 8 US clinical sites. Methods: Accuracy was evaluated by comparing CGM and reference values from Yellow Springs Instruments (YSI) during 10 clinic visits from day 1-180, which included hyperglycemia and hypoglycemia challenges. Eighty-five and 96 subjects had 1 and 2 sensors inserted in the arm, respectively, with 2 replaced sensors for 279 sensors (558 insertions/removals). The CGM prompts 2 calibrations/day to day 21, after which it primarily prompts 1 calibration/day. Results: The Table shows accuracy analyses based on 49,613 matched pairs over 180 days. Percent CGM readings within 15/15% and 20/20% of YSI values was 85.6% and 92.9%, respectively, and the MARD was 9.1%. MARDs across different glucose ranges from 40-400 mg/dL were ≤9.4% (Table). The confirmed hypoglycemia detection rates at 70mg/dL and 60 mg/dL were 93% and 87%, respectively. Hyperglycemia at 180mg/dL was detected in 99%. There were no device or insertion/removal procedure-related serious adverse events. Two mild skin infections occurred for a rate of 0.36% per procedure. Conclusion: These results indicate the next generation Eversense long-term implantable CGM System has sustained accuracy and safety up to 180 days with primarily one calibration/day. Disclosure S. K. Garg: Advisory Panel; Self; Eli Lilly and Company, Medtronic, Novo Nordisk Inc., Zealand Pharma A/S, Research Support; Self; Dexcom, Inc., Eli Lilly and Company, Medtronic. A. D. Dehennis: Employee; Self; Senseonics. K. Tweden: Employee; Self; Senseonics. F. R. Kaufman: Advisory Panel; Self; Virta Health Corp., Employee; Self; Senseonics, Stock/Shareholder; Self; Medtronic. D. R. Liljenquist: Research Support; Self; Abbott Diabetes, AbbVie Inc., Ascensia Diabetes Care, Dexcom, Inc., Drawbridge Health, Inc., Eyenuk, Inc., Jaeb Center for Health Research, Medtronic, Provention Bio, Inc., Senseonics. B. W. Bode: Advisory Panel; Self; Eli Lilly and Company, Consultant; Self; Bigfoot Biomedical, Inc., Companion Medical, Lexicon Pharmaceuticals, Inc., Medtronic, Novo Nordisk Inc., Zealand Pharma A/S, Research Support; Self; Abvance Therapeutics, Dexcom, Inc., Diasome Pharmaceuticals, Inc., Dompe, Eli Lilly and Company, Eyenuk, Inc., Insulet Corporation, Jaeb Center for Health Research, Medtronic, Nova Biomedical, Novo Nordisk, Provention Bio, Inc., REMD Biotherapeutics, Sanofi, Senseonics, Viacyte, Inc., vTv Therapeutics, Xeris Pharmaceuticals, Inc., Speaker’s Bureau; Self; AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Eli Lilly and Company, MannKind Corporation, Medtronic, Novo Nordisk, Sanofi, Stock/Shareholder; Self; AgaMatrix, Aseko, Inc., Glytec, LLC. M. P. Christiansen: Research Support; Self; Abbott Diabetes, Biolinq, Dexcom, Inc., Eli Lilly and Company, Medtronic, Merck & Co., Inc., Novo Nordisk A/S, Pfizer Inc., Viacyte, Inc. T. S. Bailey: Consultant; Self; Abbott Diabetes, LifeScan, Novo Nordisk, Sanofi, Research Support; Self; Abbott, Abbott Diabetes, Biolinq, Capillary Biomedical, Inc., Dexcom, Inc., Eli Lilly and Company, Kowa Research Institute, Inc., Lexicon Pharmaceuticals, Inc., Livongo, Medtronic, Medtrum Technologies, Novo Nordisk, REMD Biotherapeutics, Sanofi, Sanvita, Viacyte, Inc., vTv Therapeutics, Zealand Pharma A/S, Speaker’s Bureau; Self; BD, Medtronic, Sanofi. R. L. Brazg: Research Support; Self; Abbott Diabetes, Ascensia Diabetes Care, Lexicon Pharmaceuticals, Inc., Lilly Diabetes, Medtronic, Pfizer Inc., Roche Diagnostic USA, Senseonics. D. S. Denham: None. A. Chang: None. H. K. Akturk: Consultant; Self; American Diabetes Association, Research Support; Self; Dexcom, Inc., Eli Lilly and Company, IM Therapeutics, MannKind Corporation, REMD Biotherapeutics, Senseonics, Speaker’s Bureau; Self; American Diabetes Association. Funding Senseonics, Inc.

Background: Data from the first ∼200 adult real-world U.S. users of the implantable 90-day fluorescence-based glucose sensor, Eversense CGM System, showed 62.3% time in range (TIR, glucose 70-180mg/dL) and 4.1% time 1600) of users with Eversense. Methods: Sensor glucose (SG) data were analyzed for users who reached a 90-day wear period. Mean SG, variability measures (SD, CV), glucose management indicator (GMI), and CGM metrics for 18-24.9, 25-44.9, 45-64.9, ≥65 years of age subgroups were computed. Transmitter wear time was calculated in users with at least 30 wear days. Results: We evaluated 1656 users (997 with T1D, 261 with T2D, 408 unreported). Percent time in range (TIR), time below ranges (180 mg/dL and >250 mg/dL) improved with age, with 52.6% and 69.0% TIR in the youngest and oldest groups, respectively (Table). Transmitter wear time was 82% overall and improved to 87% in those ≥65 years. Percent users achieving goals for targets also improved with age. Conclusion: Glycemic outcomes improved with age in a large cohort using the implantable Eversense CGM System. Younger adults had favorable outcomes compared to data from the T1D Exchange. Overall, these data suggest that the implanted Eversense CGM system is a valuable tool for management of diabetes. Disclosure K. Tweden: Employee; Self; Senseonics. S. Ghosh-Dastidar: Employee; Self; Senseonics. A.D. Dehennis: Employee; Self; Senseonics. F. Kaufman: Advisory Panel; Self; Virta Health Corp. Employee; Self; Senseonics. Stock/Shareholder; Self; Medtronic.

A 3-month pivotal trial using the MiniMed™ 670G hybrid closed-loop (HCL) system in adolescent and adult patients with type 1 diabetes (T1D), relative to a 2-week baseline run-in period, resulted in increased sensor glucose (SG) values in target range (71–180 mg/dL), reduced HbA1c levels, and no events of diabetic ketoacidosis or severe hypoglycemia (Clinicaltrials.gov: NCT02463097). This brief report evaluated how prior continuous glucose monitoring (CGM) experience influenced glycemic outcomes, in the same pivotal trial. HbA1c levels and the percentage of SG values in low, high, and in-target ranges were analyzed from participants (n = 124) completing the Hybrid Closed-Loop Pivotal Trial in T1D. There were 78 individuals comprising the prior CGM group and 46 comprising the no prior CGM group. Compared to baseline, HbA1c was reduced from 7.4% ± 0.9% to 6.9% ± 0.7% for the prior CGM group and from 7.5% ± 0.9% to 6.8% ± 0.5% for the no prior CGM group. For those with prior CGM experience, the mean ...

Predictions based on continuous glucose monitoring (CGM) data are the basis for automatic suspension and resumption of insulin delivery by a predictive low-glucose management feature termed "suspend before low," which is part of the Medtronic MiniMedIn-clinic standardized increases in basal insulin delivery rates were used to induce nocturnal hypoglycemia in subjects (14-75 years) with type 1 diabetes wearing the MiniMed 640G system. The "suspend before low" feature was set at 65 mg/dL, and as a result, the predictive algorithm suspended insulin delivery when the forecasted glucose was predicted to be ≤85 mg/dL in 30 min (a 20 mg/dL safety buffer). Reference plasma glucose values (Yellow Springs Instruments [YSI], Yellow Springs, OH) were used to establish hypoglycemia and were defined as ≥2 consecutive values ≤65 mg/dL.Eighty subjects were screened. Among the 69 successful completers, 27 experienced a hypoglycemic event and 42 did not, a prevention rate of 60%. The mean (±standard deviation) YSI value at the time of pump suspension was 101 ± 18.5 mg/dL, and the mean duration of the 68 "suspend before low" events was 105 ± 27 min. At 120 min after the start of the pump suspension events, the mean YSI value was 102 ± 34.6 mg/dL.The MiniMed 640G "suspend before low" feature prevented 60% of induced predicted hypoglycemic events without significant rebound hyperglycemia.

The Eversense® Continuous Glucose Monitoring (CGM) System, with the first long-term, implantable glucose sensor, has been commercially available in Europe and South Africa since 2016 for adults with diabetes. The performance of the sensor over multiple, sequential 90- or 180-day cycles from either real-world experience or clinical studies has not been previously published. The Eversense Data Management System (DMS) was used to evaluate the accuracy of General Data Protection Regulation (GDPR)-compliant sensor glucose (SG) values against self-monitoring of blood glucose (SMBG) from June 2016 through August 2019 among patients with at least four sensor cycles from European and South African health care practices. Mean SG and associated measures of variability, glucose management indicator (GMI), and percent and time in various hypoglycemic, euglycemic, and hyperglycemic ranges were calculated for the 24-h time period over each cycle. In addition, transmitter wear time was evaluated across each sensor wear cycle. Among the 945 users included in the analysis, the mean absolute relative difference (standard deviation [SD]) using 152,206, 174,645, 206,024, and 172,587 calibration matched pairs against SMBG was 11.9% (3.6%), 11.5% (4.0%), 11.8% (4.7%), and 11.5% (4.1%) during the first four sensor cycles, respectively. Mean values of the CGM metrics over the first sensor cycle were 156.5 mg/dL for SG, 54.7 mg/dL for SD, 0.35 for coefficient of variation, and 7.04% for GMI. Percent SG at different glycemic ranges was as follows: 180–250 mg/dL was 22.8% (328 min), and >250 mg/dL was 8.1% (117 min). The median transmitter wear time over the first cycle was 83.2%. CGM metrics and wear time were similar over the subsequent three cycles. This real-world evaluation of adult patients with diabetes using the Eversense CGM System in the home setting demonstrated that the implantable sensor provides consistent stable accuracy and CGM metrics over multiple, sequential sensor cycles with no indication of degradation of sensor performance.

Background: The MiniMed™ 670G system is FDA-approved and CE-marked for patients with T1D aged ≥7 years. Glycemic outcomes of patients aged 2-75 years with T1D using the system at home for 3 months were evaluated and compared. Methods: Data from 151 children (n=46, 2-6 years and n=105, 7-13 years) enrolled at 9 sites; and 124 adolescents and adults (n=30, 14-21 years and n=94, 22-75 years) enrolled at 10 sites, during 2-week Manual Mode use (run-in phase) followed by 3-month Auto Mode use (study phase) were analyzed. Glycemic outcomes (HbA1c, time spent at sensor glucose [SG] ranges, SG, and SG variability, etc.) were compared across age groups. Results: Data from run-in and study phases are shown (Table). Across age groups there was a 0.4% to 0.5% decrease in HbA1c and a 5.5% to 8.8% increase in time in range. During the study phases of the pediatric (2-13 years) and older cohort (14-75 years) trials, there were no episodes of severe hypoglycemia or DKA, and no serious device-related adverse events. Conclusions: These findings indicate that 3-month MiniMed™ 670G Auto Mode use in patients as young as two years of age with T1D, similar to older cohorts using the system, can safely improve glycemic outcomes compared to 2-week open-loop Manual Mode. Disclosure T.S. Bailey: Advisory Panel; Self; Abbott. Consultant; Self; Capillary Biomedical, Inc., Eli Lilly and Company, Medtronic, Novo Nordisk Inc., Sanofi. Research Support; Self; Abbott, Ascensia Diabetes Care, Becton, Dickinson and Company, Boehringer Ingelheim Pharmaceuticals, Inc., Calibra Medical, Capillary Biomedical, Inc., Companion Medical, Dance Biopharm Holdings Inc., Dexcom, Inc., Diasome Pharmaceuticals, Inc., Eli Lilly and Company, GlySens Incorporated, Kowa Pharmaceutical Europe Co. Ltd., Lexicon Pharmaceuticals, Inc., Medtronic, Novo Nordisk Inc., POPS! Diabetes Care, POPS! Diabetes Care, Sanofi, Senseonics, vTv Therapeutics, Xeris Pharmaceuticals, Inc., Zealand Pharma A/S. Speaker's Bureau; Self; Abbott, MannKind Corporation, Medtronic, Novo Nordisk Inc., Sanofi US, Senseonics. B.W. Bode: Consultant; Self; ADOCIA, Lexicon Pharmaceuticals, Inc., Novo Nordisk Inc. Research Support; Self; Becton, Dickinson and Company, Dexcom, Inc., Diasome Pharmaceuticals, Inc., Eli Lilly and Company, Eyenuk Inc., Insulet Corporation, National Institutes of Health, Novo Nordisk Inc., Sanofi Research & Development, Senseonics, Xeris Pharmaceuticals, Inc. Speaker's Bureau; Self; AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Janssen Pharmaceuticals, Inc., Novo Nordisk Inc., Sanofi US, Senseonics. Stock/Shareholder; Self; AgaMatrix, Glytec, LLC. B.A. Buckingham: Advisory Panel; Self; ConvaTec Inc., Novo Nordisk Inc., Profusa, Inc. Consultant; Self; Medtronic MiniMed, Inc. Research Support; Self; Beta Bionics, ConvaTec Inc., Dexcom, Inc., Insulet Corporation, Medtronic MiniMed, Inc., Tandem Diabetes Care. Other Relationship; Self; Insulet Corporation, Tandem Diabetes Care. G.P. Forlenza: Advisory Panel; Self; Dexcom, Inc. Consultant; Self; Medtronic MiniMed, Inc., Tandem Diabetes Care. Research Support; Self; Dexcom, Inc., Insulet Corporation, Medtronic MiniMed, Inc., Tandem Diabetes Care. O. Pinhas-Hamiel: None. K.K. Kaiserman: Consultant; Self; Medtronic MiniMed, Inc. Research Support; Self; Medtronic MiniMed, Inc. Speaker's Bureau; Self; Medtronic MiniMed, Inc. D.R. Liljenquist: None. D.I. Shulman: None. M.A. Wood: None. X. Chen: None. J. Shin: Employee; Self; Medtronic. T.L. Cordero: Employee; Self; Medtronic. S.W. Lee: Employee; Self; Medtronic. F.R. Kaufman: Employee; Self; Medtronic.

Background: The Guardian Connect continuous glucose monitoring (CGM) system displays current and trending sensor glucose (SG) via smartphone; records insulin, carbohydrate and exercise; and sends predictive high and low SG alerts up to one hour in advance. When used with the Sugar.IQ diabetes assistant application, personalized insights based on behavior patterns (e.g., food log or insulin dose entry) and glycemic outcomes can be tracked with the Glycemic Assist feature. Methods: System data uploaded between June-November of 2018, by 1765 individuals with diabetes were analyzed. Time in target glucose range (TIR, 70-180 mg/dL) and the Glucose Management Indicator (GMI) were compared between those who used (N=530) or did not use Sugar.IQ. Both groups had ≥5 days of SG data and similar demographic and initial glucose profiles. Results: System users had a mean GMI of 7.1%, mean±SD SG of 157.0±49.1mg/dL (8.7±2.7mmol/L), and a mean TIR of 64.5%, over the data upload period. When predictive alerts were enabled, excursions were avoided after 31% of high SG alerts and 62% of low SG alerts. Those who accessed Sugar.IQ experienced a TIR increase of 2.7% (p=0.006) and a mean SG decrease of -3.0% (p Discussion: The Guardian Connect CGM system with Sugar.IQ may advance patient understanding of glucose trends, aid in behavioral change that improves therapy adherence, and lead to better glycemic outcomes. Disclosure S. Arunachalam: Employee; Self; Medtronic. Y. Zhong: None. S. Abraham: Employee; Self; Medtronic MiniMed, Inc. P. Agrawal: Employee; Self; Medtronic MiniMed, Inc. Stock/Shareholder; Self; Medtronic. R. Vigersky: Employee; Self; Medtronic MiniMed, Inc. T.L. Cordero: Employee; Self; Medtronic. F.R. Kaufman: Employee; Self; Medtronic.

Background: Forgetting a premeal bolus can lead to hyperglycemia in patients with type 1 diabetes (T1D). A prototype e-HCL system was designed to automatically deliver basal insulin and correction boluses based on sensor glucose (SG) values. The effect of the system on hyperglycemia due to unannounced medium-sized meals was assessed. Methods: Twelve subjects with T1D aged 15-25 years (median 17 years) underwent a 1-week hotel phase of e-HCL Auto Mode use, followed by a 3-week unsupervised at-home phase of use. On the third day of the hotel phase, a ∼40gm-carbohydrate (carb) dinner was consumed without a premeal bolus. Five hours of postprandial data were analyzed and compared to data captured after 40gm-carb meals eaten during the at-home phase, but accompanied by a premeal bolus. Results: Meals without a premeal bolus resulted in postprandial SG levels statistically similar to those observed for meals accompanied by a premeal bolus (Table). Conclusion: These data suggest that e-HCL can handle unannounced medium-sized meals to a similar extent as meals of equal size accompanied by premeal boluses. This may improve overall glycemic control of patients who underestimate or frequently forget to administer premeal boluses. Disclosure A. Roy: Employee; Self; Medtronic MiniMed, Inc. B. Grosman: Employee; Self; Medtronic. N. Parikh: None. D. Wu: None. L.J. Lintereur: Employee; Self; Medtronic MiniMed, Inc. N. Kurtz: Employee; Self; Medtronic MiniMed, Inc. F.R. Kaufman: Employee; Self; Medtronic.

Background: The MiniMed™ 670G system targets glucose levels to 120mg/dL (6.7mmol/L) and has a temporary target (TT) of 150mg/dL (8.3mmol/L) that can be set from 2-12 hours. An exploratory analysis of glycemic outcomes and TT use during the 3-month MiniMed™ 670G system pivotal trials was conducted. Methods: Data from 151 children (n=46, 2-6 years and n=105, 7-13 years) and 124 adolescents and adults (n=30, 14-21 years and n=94, 22-75 years) during 2-week Manual Mode use (run-in), followed by 3-month Auto Mode use (study), were analyzed by percentage of TT use. Results: The median (IQR) of TT use for those 2-6 years was 4.1% (0.6-16.3%); for 7-13 years was 0.4% (0-2.1%) and ≥14 years was 0.4% (0-1.2%). Glycemic outcomes for the 2-6 years are shown by percentage of TT use ( Conclusions: Improved glycemia was observed in the 2-6 years group regardless of TT use during study phase, compared to baseline run-in. The higher glucose target was used more often in the youngest cohort, suggesting the TT feature is important for young children with T1D using automated insulin delivery. Disclosure J. Shin: Employee; Self; Medtronic. X. Chen: None. T.L. Cordero: Employee; Self; Medtronic. S.W. Lee: Employee; Self; Medtronic. F.R. Kaufman: Employee; Self; Medtronic.

Background: Automated insulin delivery, or closed-loop (CL), systems are emerging as a management tool for individuals with T1D. The MiniMed™ 670G system is a single hormone hybrid closed-loop (HCL) system that adjusts basal insulin delivery based on sensor glucose (SG)levels and is already used in clinical practice. An enhanced HCL system (e-HCL) prototype with an automated correction bolus feature was developed and evaluated in a small feasibility study. Methods: Subjects (n=12) aged a mean±SD of 17.6±2.9 years with T1D and an A1C of 7.3±0.7% (56.5±7.7 mmol/mol) completed a 6-day run-in period with the e-HCL system in open-loop (OL) (i.e., Auto Mode OFF and Suspend before low ON). Thereafter, a supervised hotel period (6 days/5 nights) with CL challenges (missed meal bolus, late meal bolus, and physical activity) was completed, and followed by a 3-week at-home period with Auto Mode and automated correction boluses ON, without restrictions. Glycemic control was compared between the OL run-in period and CL period. Results: During the at-home period, subjects spent 93±4% of the time in Auto Mode. Time within target glucose range of 70-180 mg/dL (3.9-10.0 mmol/L) increased from 68.8±10.5% to 74±6.1%, time >180 mg/dL reduced from 27.1±11.9% to 23.7±8.8%, and time Conclusions: Incorporating automated correction boluses to an HCL system was safe and effective in controlling day and night glucose levels, during a 3-week at-home period. Disclosure R. Nimri: Employee; Self; DreaMed Diabetes. Research Support; Self; Dexcom, Inc., Glooko, Inc., Insulet Corporation, JDRF, Medtronic, National Institutes of Health. Speaker's Bureau; Self; Lilly Diabetes. Stock/Shareholder; Self; DreaMed Diabetes. B. Grosman: Employee; Self; Medtronic. N. Kurtz: Employee; Self; Medtronic MiniMed, Inc. A. Roy: Employee; Self; Medtronic MiniMed, Inc. J. Nir: None. N. Loewenthal: None. F.R. Kaufman: Employee; Self; Medtronic. M. Phillip: Consultant; Self; Qulab Medical, RSP Systems A/S. Research Support; Self; Bristol-Myers Squibb Company, Dexcom, Inc., JDRF, Lexicon Pharmaceuticals, Inc., Merck & Co., Inc., OPKO. Stock/Shareholder; Self; DreaMed Diabetes, Ltd., NG Solutions Ltd., Nutriteen Professional Ltd. Other Relationship; Self; AstraZeneca, Eli Lilly and Company, Insulet Corporation, Medtronic MiniMed, Inc., Novo Nordisk A/S, Pfizer Inc., Sanofi-Aventis.

Objective: To evaluate the safety of in-home use of the MiniMed™ 670G system with SmartGuard™ technology in children with type 1 diabetes (T1D). Methods: Participants (N = 105, ages 7–13 years, mean age 10.8 ± 1.8 years) were enrolled at nine centers (eight in the United States and one in Israel) and completed a 2-week baseline run-in phase in Manual Mode followed by a 3-month study phase with Auto Mode enabled. Sensor glucose (SG), glycated hemoglobin (HbA1c), percentage of SG values across glucose ranges, and SG variability, during the run-in and study phases were compared. Participants underwent frequent sample testing with i-STAT® venous reference measurement during a hotel period (6 days/5 nights) to evaluate the system's continuous glucose monitoring performance. Results: Auto Mode was used a median of 81% of the time. From baseline to end of study, overall SG dropped by 6.9 ± 17.2 mg/dL (P

Background: Automated insulin management features of the MiniMed® 640G sensor-augmented pump system include suspension in response to predicted low sensor glucose (SG) values (“suspend before low”), suspension in response to existing low SG values (“suspend on low”), and automatic restarting of basal insulin delivery upon SG recovery. The effectiveness of these features was evaluated using CareLink® software data. Methods: Anonymized data from MiniMed 640G system users (n = 4818), MiniMed 530G system users (n = 39,219), and MiniMed Paradigm® Veo™ system users (n = 43,193) who voluntarily uploaded pump and sensor data were retrospectively analyzed. Comparisons were made between days in which system features were enabled at any time and those in which they were not. Comparisons were also made between pump suspension events for which insulin delivery was automatically or manually resumed and between glycemic parameters of users who switched from the MiniMed Paradigm Veo system to the MiniMed 640G sy...

The Medtronic predictive low-glucose management (PLGM) algorithm automatically stops insulin delivery when sensor glucose (SG) is predicted to reach or fall below a preset low-glucose value within the next 30 min, and resumes delivery after hypoglycemia recovery. The present study evaluated the PLGM algorithm performance of the MiniMed™ 670G system SmartGuard™ "suspend before low" feature in children aged 7-13 years with type 1 diabetes (T1D).Participants (N = 105, mean ± standard deviation of 10.8 ± 1.8 years) underwent an overnight in-clinic evaluation of the "suspend before low" feature with a preset low limit of 65 mg/dL. After exercise, frequent sample testing (FST) was conducted every 5 min if values were70 mg/dL; every 15 min if 70-80 mg/dL; and every 30 min if80 mg/dL. First-day performance of the Guardian™ Sensor 3 glucose sensor and continuous glucose monitoring system was also evaluated.Activation of the "suspend before low" feature occurred in 79 of the 105 participants, 79.7% (63/79) did not result in SG falling below 65 mg/dL. Mean glucose at activation was 102 ± 19 mg/dL and the initial insulin suspension duration was 87.5 ± 32.7 min. Four hours after insulin resumption, mean reference glucose was 130 ± 42 mg/dL. Mean absolute relative difference between the FST reference glucose and SG values on the first day of sensor wear was 11.4%. For the 26 participants in whom the "suspend before low" feature did not activate, none involved a reference glucose value ≤65 mg/dL, suggesting that the PLGM algorithm performed as intended.In children aged 7-13 years with T1D, the "suspend before low" feature of the MiniMed 670G system demonstrated a hypoglycemia prevention rate of nearly 80% after exercise and did not involve rebound hyperglycemia. There were no events of severe hypoglycemia during the evaluation.

This study evaluated the safety and performance of the Guardian™ continuous glucose monitoring (CGM) system in children and adolescents with type 1 diabetes (T1D).Subjects 2-18 years of age (mean ± standard deviation [SD] 13.1 ± 3.9 years) with T1D and duration of diagnosis ≥1 year were enrolled at 11 sites in the United States and wore two Guardian Sensor 3 sensors in the abdomen and/or buttock. Sensors were connected to a transmitter paired with either a Guardian Connect system (i.e., mobile device with software application allowing display of sensor glucose [SG] values) or a Guardian Link 3 transmitter used as a Glucose Sensor Recorder (GSR). There were 145 participants who underwent a 6-h in-clinic frequent sample testing (FST) on day 1 (n = 54), day 3 (n = 48), or day 7 (n = 43) postsensor insertion. During FST, SG values were compared with a Yellow Springs Instrument (YSI) plasma reference every 5-15 min (n = 124, 7-18 years of age; n = 2, 2-6 years of age), or to a self-monitoring of blood glucose (SMBG) reference every 5-30 min (n = 19, 2-6 years of age).The overall mean absolute relative difference (ARD ± SD) between SG and reference values (YSI or SMBG) when calibrating approximately every 12 h, was 10.9% ± 10.7% (3102 paired points) for sensors communicating with the Guardian Connect system and 11.1% ± 10.6% (2624 paired points) for sensors connected to the GSR. The overall percentage of SG values within ±20% of reference values80 mg/dL or within 20 mg/dL of reference values ≤80 mg/dL was 87.8% for the Guardian Connect system and 86.7% for the GSR, respectively. There was one device-related adverse event of contact dermatitis, but no serious device-related adverse events.The Guardian CGM system demonstrated good accuracy in children and adolescents. These findings support its use in sensor-integrated insulin pump platforms, as well as a standalone technology, for managing diabetes in pediatric populations.

To assess glycemic outcomes during non-adjunctive use of a Medtronic continuous glucose monitoring system, CareLink™ personal software data were analyzed after insulin bolus delivery to correct hyperglycemia. Voluntarily uploaded data captured between January 1, 2015-August 12, 2016, from European users of the MiniMed™ Veo™ insulin pump with SmartGuard™ technology, were de-identified and analyzed. Non-adjunctive sensor glucose (SG) values were defined as manually-entered self-monitored blood glucose (SMBG) values that were within ±5mg/dL of the preceding SG value. Non-adjunct vs. adjunct performance of the system in frequent non-adjunct users (at least, 10% non-adjunct use) was evaluated based on the frequency of post-corrective bolus hypoglycemia (nadir) and hyperglycemia (peak) over the 4 hours following insulin bolus delivery. All statistics were conducted per patient and analyzed using Wilcoxon signed rank test. Among 23,784 total users, 5,851 were identified as frequent non-adjunct users. Of the over 1.7 million corrective boluses evaluated, 32% met the non-adjunctive criteria. Outcomes results are presented in the Table below. The frequency and severity of hypoglycemia and hyperglycemia, although lower statistically with non-adjunctive vs. adjunctive corrective bolus delivery, showed likely clinical equivalency. Disclosure B. Jiang: None. S. Soleymani: Employee; Self; Medtronic MiniMed, Inc. R. Vigersky: Employee; Self; Medtronic MiniMed, Inc.. A. Sullivan: None. Y. Zhong: None. P. Agrawal: None. F.R. Kaufman: Employee; Self; Medtronic.

The Medtronic MiniMed™ 670G hybrid closed-loop system was designed to automatically adjust basal insulin delivery every 5 minutes based on sensor glucose (SG) values. Its safety and effectiveness have been recently investigated in a multi-center pivotal trial conducted in 1T1D children aged 7-13 years. During the 2 week run-in phase, participants used the system in Manual Mode. This was followed by a 3-month at-home study phase in which the Auto Mode feature was enabled. The SG data and the amount of insulin delivered were analyzed during the overnight period (11:00 p.m.-7:00 a.m.). Figure-1 (top panel) shows overnight SG tracings from the run-in phase and study phase, and that the median [IQR] reduced significantly from run-in (142 [71]mg/dL) to study phase (126 [34]mg/dL), by 7:00 a.m. This was mainly achieved by the system transferring variability from SG to insulin infusion rate (bottom panel). During the nighttime period, the system suspended insulin for an average 1.3 hours and delivered insulin at the maximum allowable limit for an average 3.6 hours. The remainder of the time, it delivered insulin between 1-99% of the maximum allowable limit. These data suggest that greater variability of basal insulin delivery, such as that achieved with MiniMed™ 670G system automation, compared to fixed pre-set basal rates, improves nighttime glucose control in children. Disclosure A. Roy: Employee; Self; Medtronic MiniMed, Inc. B. Grosman: Employee; Self; Medtronic. N. Parikh: Employee; Self; Medtronic. D. Wu: None. S.W. Lee: Employee; Self; Medtronic. F.R. Kaufman: Employee; Self; Medtronic.

In-home use of the MiniMed™ 670G system with SmartGuard™ technology for 3 months improved A1C, 24-hour, and overnight (10PM-7AM) glycemia in T1D patients ≥14 years.1 Recently, the system was shown to improve A1C and time in target range (TIR) (>70-180mg/dL, 3.9-10mmol/L) during 24-h and overnight periods in T1D children aged 7-13 years. Effect of the system on insulin delivery and early morning glycemia was also examined. During a 2 week run-in phase in Manual Mode and a 3-month study phase using HCL Auto Mode; 24-hour, 10PM-7AM, and 3AM-7AM insulin delivery (programmed hourly basal rates during Manual Mode, variable basal from 0 units to an individualized daily maximum every 5min during Auto Mode); time in sensor glucose (SG) ranges; and SG SD were examined in 1T1D children (mean±SD age 10.8±1.8 years). The table shows Auto Mode use across periods. Total insulin delivered increased from baseline run-in (1990 patient-days) through study phase (10,602 patient-days); SG, TIR, and SG SD improved. During the study phase, there was no severe hypoglycemia, DKA, or serious device-related AEs. The ability of the MiniMed™ 670G system to automate basal insulin delivery and safely improve 24-hour and overnight glycemic control in children was comparable to that observed in patients 14-75 years, over 3 months. Improved early morning glycemia further indicates that patients ≥7 years can benefit from this HCL therapy. Disclosure G.P. Forlenza: Advisory Panel; Self; Dexcom, Inc.. Research Support; Self; Medtronic, Tandem Diabetes Care, Inc., Insulet Corporation, Dexcom, Inc., Novo Nordisk Inc., Bigfoot Biomedical. D.I. Shulman: Other Relationship; Self; Novo Nordisk Inc.. Research Support; Self; Medtronic MiniMed, Inc.. Board Member; Self; Pediatric Endocrine Society. Research Support; Self; Versartis, Inc. M.A. Wood: Research Support; Self; Medtronic MiniMed, Inc. T.S. Bailey: Research Support; Self; Abbott. Consultant; Self; Abbott. Speaker's Bureau; Self; Abbott. Research Support; Self; Ambra BioScience, Ascensia Diabetes Care, Becton, Dickinson and Company. Consultant; Self; Becton, Dickinson and Company. Research Support; Self; Boehringer Ingelheim Pharmaceuticals, Inc., Calibra Medical. Consultant; Self; Calibra Medical. Research Support; Self; Companion Medical, Dexcom, Inc., Glooko, Inc., GlySens Incorporated, Lexicon Pharmaceuticals, Inc., Eli Lilly and Company. Consultant; Self; Eli Lilly and Company. Speaker's Bureau; Self; Eli Lilly and Company. Research Support; Self; Medtronic MiniMed, Inc.. Consultant; Self; Medtronic MiniMed, Inc.. Speaker's Bureau; Self; Medtronic MiniMed, Inc.. Research Support; Self; Novo Nordisk Inc.. Consultant; Self; Novo Nordisk Inc.. Speaker's Bureau; Self; Novo Nordisk Inc.. Research Support; Self; Sanofi. Consultant; Self; Sanofi. Speaker's Bureau; Self; Sanofi. Research Support; Self; Senseonics. Consultant; Self; Intarcia Therapeutics, Inc.. Research Support; Self; Versartis, Inc., Xeris Pharmaceuticals, Inc., MannKind Corporation. B.W. Bode: Research Support; Self; Abbott. Advisory Panel; Self; ADOCIA. Research Support; Self; Boehringer Ingelheim Pharmaceuticals, Inc.. Consultant; Self; Janssen Pharmaceuticals, Inc.. Research Support; Self; GlaxoSmithKline plc., Lexicon Pharmaceuticals, Inc., Medtronic MiniMed, Inc., Novo Nordisk Inc., Diasome Pharmaceuticals, Inc., Sanofi US, Eli Lilly and Company, MannKind Corporation, Dexcom, Inc., OmniPod, Senseonics. B. Buckingham: Advisory Panel; Self; Novo Nordisk Inc., ConvaTec Inc.. Research Support; Self; Medtronic, Insulet Corporation, Dexcom, Inc., Tandem Diabetes Care, Inc.. Consultant; Self; Tandem Diabetes Care, Inc., Becton, Dickinson and Company. S. Huang: Employee; Self; Medtronic. J. Shin: Employee; Self; Medtronic. S.W. Lee: Employee; Self; Medtronic. T.L. Cordero: Employee; Self; Medtronic. F.R. Kaufman: Employee; Self; Medtronic.

Background: Cognitive computing technology providing personalized insights based on correlations between behavior patterns and glycemic outcomes was leveraged to create an interactive mobile assistant for T1D patients. Method: Medtronic MiniMed™ Connect users (N=256) were invited to take part in a 90-day Sugar.IQ app pilot program that began April 11, 2017. The percentage of time in target range (TIR, 70-180 mg/dL), 180mg/dL, and excursions (periods >20 minutes and 180mg/dL) were collected 30 days before Sugar.IQ onboarding, and compared to those 90 days later (August 2017). Insights delivered to users and user feedback were also analyzed. Results: There were 11,356 sensor-wear days; 10,761 unique Sugar.IQ usage sessions collected; and 4,688 insights delivered (1 every 3 days). Insights included 655 and 699 identifying behaviors associated with more time 180mg/dL, respectively. The Sugar.IQ app was used 2.1 times/day. Compared to baseline, TIR was 33 minutes longer per day (P2 hours reduced by 1.3 per month (P Conclusion: Timely and personalized insights, such as those provided during the Sugar.IQ pilot, may advance patient understanding of glucose trends, aid in behavioral change that improves therapy adherence, and lead to better outcomes. Disclosure Y. Zhong: None. S. Arunachalam: None. P. Agrawal: None. H. Neemuchwala: None. T.L. Cordero: Employee; Self; Medtronic. F.R. Kaufman: Employee; Self; Medtronic.

The Medtronic MiniMed™ 670G hybrid closed-loop system with SmartGuard™ technology, which automatically adjusts basal insulin delivery, was released for commercial use in the U.S. in March 2017. Data from the first 13,9patients to use the system are reported. MiniMed™ 670G data from patients who voluntarily uploaded to CareLink™ Personal software, from 3/17/17 to 12/14/17, were de-identified and analyzed if there were ≥7 days of sensor wear. Comparisons of glycemic metrics between 258,415 patient-days in the initial open-loop Manual Mode and 724,220 patient-days after starting closed-loop Auto Mode were made. Data were compared for patients 7-13 years, 14-21 years, 22-60 years, and ≥60 years. The Table shows glycemic metrics, including time in target range (TIR, 70-180mg/dL), during Manual Mode and after Auto Mode start for all users and by age group. Children and teens had lower baseline TIR and more hyperglycemia in Manual Mode vs. adults, but a similar magnitude of improvement when in Auto Mode. Older adults had the most optimal glycemia with Auto Mode. TIR was higher in patients with greater time in Auto Mode. For those in Auto Mode 50-59% of the time, mean TIR was 65%; for Auto Mode 60-80% of the time, TIR was 68%; and for Auto Mode >80% of the time, TIR was 74%. Overall, data from the commercial launch of the MiniMed™ 670G system mirrored the pivotal trial1 results for all ages and showed an increase in TIR with less hypoglycemia and hyperglycemia. All Patients7-13 years14-21 years22-60 years≥ 60 yearsManual ModeAfter Auto Mode startManual ModeAfter Auto Mode startManual ModeAfter Auto Mode startManual ModeAfter Auto Mode startManual ModeAfter Auto Mode startPatients, N13,906479126293781946Auto Mode Use, %-80.05%-77.58%-66.07%-80.89%-84.95%Mean SG, mg/dL163.53154.87183.44163.44179.55166.98161.50153.55156.91150.38SD SG, mg/dL54.2251.0463.1560.5563.0560.2953.3550.0649.9447.22Percentage of time in SG range, mg/dL18034.24%26.60%45.98%33.11%44.09%35.11%33.11%25.75%29.52%22.98%>2509.58%6.18%17.22%10.37%16.49%11.42%8.79%5.53%6.69%4.55%>3003.22%1.86%6.94%3.73%6.57%4.34%2.82%1.53%1.91%1.20% Disclosure P. Agrawal: None. M. Stone: None. S. Gopalakrishnan: Employee; Self; Medtronic. C. Fogel: Employee; Self; Medtronic. S.W. Lee: Employee; Self; Medtronic. F.R. Kaufman: Employee; Self; Medtronic.

The Medtronic MiniMed™ 670G hybrid closed-loop system with SmartGuard™ technology was released for commercial use in the U.S. in March 2017. Sensor glucose (SG) and device utilization data from the initial open-loop Manual Mode and closed-loop Auto Mode periods were analyzed for the first 1052 patients and compared to those from the MiniMed™ 670G system pivotal trial1. De-identified data voluntarily uploaded to CareLink™ Personal software, from 3/17/17 to 11/11/17, were evaluated monthly, for 3 months. Data for 12,758 patient-days in Manual Mode and 142,065 patient-days after Auto Mode start were compared to results of the MiniMed™ 670G pivotal trial (124 patients aged 14-75 years) conducted from 6/2/15 to 3/7/16. The percentage of time in Auto Mode, after initiation, was >85% over the 3 months for the entire commercial cohort. The SG values across glucose ranges were comparable to pivotal trial data (Table). These findings indicate that outcomes data for the first 1052 patients using the commercial MiniMed™ 670G system mirrored the pivotal trial outcomes. Further, the increased time in target range and decreased hypoglycemia and hyperglycemia were sustained over 3 months. Pivotal TrialCommercial LaunchManual ModeAuto ModeManual ModeAuto Mode Month 1Auto Mode Month 2Auto Mode Month 3Patients, N1241241052105210521052Auto Mode Use, %-87.20-88.6086.7885.96Mean SG, mg/dL150.2150.78157.02149.84150.30150.75Percentage of time in SG range, mg/dL18027.424.4529.9622.9323.4323.70>2506.945.587.494.504.865.14 1. Garg SK, Weinzimer SA, Tamborlane WV, et al. Glucose outcomes with the in-home use of a hybrid closed-loop insulin delivery system in adolescents and adults with type 1 diabetes. Diabetes Technol Ther. 2017;19:155-163. Disclosure P. Agrawal: None. M. Stone: None. S. Gopalakrishnan: Employee; Self; Medtronic. C. Fogel: Employee; Self; Medtronic. S.W. Lee: Employee; Self; Medtronic. F.R. Kaufman: Employee; Self; Medtronic.

The Medtronic MiniMed™ 670G hybrid closed-loop (HCL) system was investigated in a multi-center pivotal trial conducted in 1T1D children aged 7-13 years. A 3-month at-home study phase with Auto Mode enabled followed the 2 week run-in phase in Manual Mode. The system improved overall glycemic control and minimized the percentage of time in hypoglycemia (≤70mg/dL, 3.9mmol/L). Several aspects of the postprandial response and sensor glucose (SG) values, during the run-in and study were compared. The maximum increase in SG (mg/dL) per 50 grams of carbohydrate (carb) in postprandial responses >3h; settling time, defined as the minutes for the postprandial response to settle back to Disclosure B. Grosman: Employee; Self; Medtronic. A. Roy: Employee; Self; Medtronic MiniMed, Inc.. D. Wu: None. N. Parikh: Employee; Self; Medtronic. S.W. Lee: Employee; Self; Medtronic. F.R. Kaufman: Employee; Self; Medtronic.

Glycated hemoglobin (A1C) is considered a “gold standard” measure of glycemic control in patients with diabetes and is correlated with a lower risk of diabetes complications and cost savings. This retrospective claims-analysis assessed the impact of A1C reduction on healthcare costs in patients with uncontrolled Type 1 and Type 2 diabetes. Using a large repository of US health plan administrative data linked to A1C values, patients with a diabetes diagnosis and at least two A1C values between 1 January 2009 and 31 December 2014 were selected to identify changes in A1C and associated changes in healthcare expenditure. We used all medical and pharmacy claims to calculate direct healthcare costs from 1 year prior to the index A1C to 2 years after the index A1C. A propensity score method was used to match patients with decreased A1C to patients whose A1C did not decrease, based on potentially confounding variables. Then, a generalized linear model regression was used to estimate the difference-in-difference (DD) effect on costs between the two groups. Of the 3,197 patients who had a first A1C ≥ 9%, 2,273 patients (71%) had a decrease in A1C (Decreasers) and 924 patients (27%) had an increase in A1C (Non-decreasers). After matching, we compared 912 Decreasers to 912 Non-decreasers. Patients in the former group had average annual healthcare costs that were 24% lower during the first year of follow-up and 17% lower during the second year of follow-up, compared to patients whose A1C did not decrease. This reflected a savings of US$2503 and US$1690, respectively. For both time periods, the outpatient category was the largest contributor to cost savings. In our analysis, A1C reduction among patients with T1DM and T2DM was associated with slower growth in healthcare costs within 1–2 years. These findings suggest that programs aimed at reducing A1C over a short timeframe may lead to substantial savings and may be worth pursuing by health plans and other payers.

Fasting C-peptide levels are used to differentiate type 1 from type 2 diabetes (T2D), thereby determining eligibility for coverage of continuous subcutaneous insulin infusion (CSII) for patients with T2D.A total of 168 patients (74 female/94 male, aged 55.5 ± 9.7 years) were randomized to CSII, and 163 patients (77 female/86 male, aged 56.4 ± 9.5 years) were randomized to multiple daily injections (MDI) of insulin and grouped by baseline C-peptide level: group A (≤183 pmol/L [≤0.55 ng/mL]); group B (183 pmol/L [0.55 ng/mL]). At 6 months, the MDI group crossed over to CSII. Within- and between-group comparisons were recorded at 6 and 12 months in the entire group and separately for those patients aged ≥65 years.CSII reduced hemoglobin A1c (A1c) equally in groups A ( P = .0006, P = .0022) and B ( P.0001, P.0001) at 6 and 12 months, respectively. There was an increase in weight in group A versus group B at 6 months but not 12 months ( P.03). CSII therapy reduced total daily dose (TDD) of insulin and improved treatment satisfaction similarly in groups A and B. The results for patients aged ≥65 years displayed a similar trend as the entire group.A1c, TDD of insulin, and treatment satisfaction improved for T2D patients using CSII versus MDI therapy, irrespective of baseline C-peptide level. A subgroup of patients aged ≥65 years displayed a similar trend. These results support abandoning C-peptide as a criterion for reimbursing CSII therapy in patients with diabetes.A1c = hemoglobin A1c; CMS = Centers for Medicare and Medicaid Services; CSII = continuous subcutaneous insulin infusion; DTSQ = Diabetes Treatment Satisfaction Questionnaire; MDI = multiple daily injections; RCT = randomized controlled trials; T1D = type 1 diabetes; T2D = type 2 diabetes; TDD = total daily dose.

Simulations using mathematical models are important for studying, developing, and improving therapies for people with type 1 diabetes.The Medtronic CareLinkA total of 2087 virtual patients were developed. The time percentage between 70 and 180 mg/dL of the CareLink uploads and the simulated virtual patients was 72.4% (18.6) and 74.1% (16.9), respectively. The time percentage70 mg/dL of the real continuous glucose monitoring from CareLink uploads and the simulated virtual patients was 1% (2.4) and 1.7% (4.1), respectively. A simulation study with the virtual patients predicted the glycemic distribution after 2 h of insulin suspension as reported in the ASPIRE (Automation to Simulate Pancreatic Insulin Response) clinical trial. The 3 months outcomes of Medtronic's hybrid closed-loop 670G system pivotal trial were also predicted in a simulation study. The time percentage70 mg/dL was 3.4% and 3.1%, and the time percentage between 71 and 180 mg/dL was 73.8% and 77.7% for 93 pivotal study adults (18 years) and 90 adult (28 years) virtual patients, respectively.The Medtronic CareLink database was utilized to generate a large number of virtual patients with a variety of insulin sensitivities, pharmacokinetics, and meal absorption rates. This new simulation model can be potentially used to evaluate and prognosticate the outcomes of studies of artificial pancreas algorithms and systems.

BACKGROUND. Neutrophils and their inflammatory mediators are key pathogenic components in multiple autoimmune diseases, while their role in human type 1 diabetes (T1D), a disease that progresses sequentially through identifiable stages prior to the clinical onset, is not well understood. We previously reported that the number of circulating neutrophils is reduced in patients with T1D and in presymptomatic at-risk subjects. The aim of the present work was to identify possible changes in circulating and pancreas-residing neutrophils throughout the disease course to better elucidate neutrophil involvement in human T1D. METHODS. Data collected from 389 subjects at risk of developing T1D, and enrolled in 4 distinct studies performed by TrialNet, were analyzed with comprehensive statistical approaches to determine whether the number of circulating neutrophils correlates with pancreas function. To obtain a broad analysis of pancreas-infiltrating neutrophils throughout all disease stages, pancreas sections collected worldwide from 4 different cohorts (i.e., nPOD, DiViD, Siena, and Exeter) were analyzed by immunohistochemistry and immunofluorescence. Finally, circulating neutrophils were purified from unrelated nondiabetic subjects and donors at various T1D stages and their transcriptomic signature was determined by RNA sequencing. RESULTS. Here, we show that the decline in β cell function is greatest in individuals with the lowest peripheral neutrophil numbers. Neutrophils infiltrate the pancreas prior to the onset of symptoms and they continue to do so as the disease progresses. Of interest, a fraction of these pancreas-infiltrating neutrophils also extrudes neutrophil extracellular traps (NETs), suggesting a tissue-specific pathogenic role. Whole-transcriptome analysis of purified blood neutrophils revealed a unique molecular signature that is distinguished by an overabundance of IFN-associated genes; despite being healthy, said signature is already present in T1D-autoantibody-negative at-risk subjects. CONCLUSIONS. These results reveal an unexpected abnormality in neutrophil disposition both in the circulation and in the pancreas of presymptomatic and symptomatic T1D subjects, implying that targeting neutrophils might represent a previously unrecognized therapeutic modality. FUNDING. Juvenile Diabetes Research Foundation (JDRF), NIH, Diabetes UK.

Background: Hypoglycemia varies between patients with type 1 diabetes and is the main obstacle to therapy intensification. We investigated known and potential risk factors for hypoglycemia in subjects with type 1 diabetes. Method: In the ASPIRE In-Home study (NCT01497938), a randomized trial of the threshold suspend (TS) feature of sensor-augmented insulin pump (SAP) therapy, subjects’ propensity to nocturnal hypoglycemia (NH) was established in a 2-week run-in phase and assessed in a 3-month study phase via continuous glucose monitoring. Categorical variables were tested for association with NH rates in both phases. Results: Elevated rates of NH were significantly associated with baseline A1C ≤7%, with bolus insulin deliveries unassisted by the bolus estimation calculator, and with assignment to the control group during the study phase. Conclusions: Routine use of the TS feature and the bolus estimation calculator are strategies that may reduce the risk of NH.

A 3-month pivotal trial using the MiniMed™ 670G hybrid closed-loop (HCL) system in adolescent and adult patients with type 1 diabetes (T1D), relative to a 2-week baseline run-in period, resulted in increased sensor glucose (SG) values in target range (71-180 mg/dL), reduced HbA1c levels, and no events of diabetic ketoacidosis or severe hypoglycemia ( Clinicaltrials.gov : NCT02463097). This brief report evaluated how prior continuous glucose monitoring (CGM) experience influenced glycemic outcomes, in the same pivotal trial. HbA1c levels and the percentage of SG values in low, high, and in-target ranges were analyzed from participants (n = 124) completing the Hybrid Closed-Loop Pivotal Trial in T1D. There were 78 individuals comprising the prior CGM group and 46 comprising the no prior CGM group. Compared to baseline, HbA1c was reduced from 7.4% ± 0.9% to 6.9% ± 0.7% for the prior CGM group and from 7.5% ± 0.9% to 6.8% ± 0.5% for the no prior CGM group. For those with prior CGM experience, the mean percentage of in-target SG values increased from 66.9% ± 12.5% to 72.6% ± 9.1%, and for those with no prior CGM experience it increased from 66.6% ± 11.7% to 71.5% ± 8.5%. Similar improvement in glucose values in the low and high ranges, relative to baseline, was observed for both groups. Resulting outcomes, from baseline to study end, did not differ between each group. These findings suggest that individuals without prior CGM experience, and those already using CGM, will benefit similarly with use of the FDA-approved MiniMed 670G HCL system therapy.

It is estimated that one in 10 people in the US have a diagnosis of diabetes. Type 2 diabetes accounts for 95% of all cases in the US, with annual costs estimated to be $246 billion per year. This study investigated the impact of a glucose-measuring intervention to the burden of type 2 diabetes.This analysis seeks to understand how professional continuous glucose monitoring (professional CGM) impacts clinical and economic outcomes when compared to patients who are not prescribed professional CGM.This study utilized a large healthcare claims and lab dataset from the US, and identified a cohort of patients who were prescribed professional CGM as identified by CPT codes 95250 and 95251. It calculated economic and clinical outcomes 1 year before and 1 year after the use of professional CGM, using a generalized linear model.Patients who utilized professional CGM saw an improvement in hemoglobin A1C. The "difference-in-difference" calculation for A1C was shown to be -0.44%. There was no statistically significant difference in growth of total annual costs for people who used professional CGM compared to those who did not ($1,270, p = .08). Patients using professional CGM more than once per year had a -$3,376 difference in the growth of total costs (p = .05). Patients who used professional CGM while changing their diabetes treatment regimen also had a difference of -$3,327 in growth of total costs (p = .0023).Significant clinical benefits were observed for patients who used professional CGM. Economic benefits were observed for patients who utilized professional CGM more than once within a 1-year period or who used it during a change of diabetes therapy. This suggests that professional CGM may help decrease rising trends in healthcare costs for people with type 2 diabetes, while also improving clinical outcomes.

This study evaluated the accuracy and performance of a fourth-generation subcutaneous glucose sensor (GuardianEighty-eight subjects (14-75 years of age, mean ± standard deviation [SD] of 42.0 ± 19.1 years) with type 1 or type 2 diabetes participated in the study. Subjects wore two sensors in the abdomen that were paired with either a MiniMedThe overall mean absolute relative difference (MARD ± SD) between abdomen sensor glucose (SG) and YSI reference values was 9.6% ± 9.0% and 9.4% ± 9.8% for the MiniMed 640G insulin pump and Guardian Connect system, respectively; and 8.7% ± 8.0% between arm SG and YSI reference values. The percentage of SG values within 20% agreement of the YSI reference value (for YSI80 mg/dL) was 90.7% with the MiniMed 640G insulin pump, 91.8% with the Guardian Connect system, and 93.1% for GSR-connected arm sensors. Mean functional sensor life, when calibrating 3-4 times/day, was 145.9 ± 39.3 h for sensors paired with the MiniMed 640G insulin pump, 146.1 ± 41.6 h for sensors paired with the Guardian Connect system, and 147.6 ± 40.4 h for sensors connected to the GSR. Responses to survey questions regarding sensor comfort and ease of use were favorable.The Guardian Sensor 3 glucose sensor, whether located in abdomen or the arm, provided accurate glucose readings when compared with the YSI reference and demonstrated functional life commensurate with the intended 7-day use. ClinicalTrials.gov : NCT02246582.

Among children and adolescents with type 1 diabetes mellitus, the use of insulin pump therapy has increased since its introduction in the early 1980s. Optimal management of type 1 diabetes mellitus depends on sufficient understanding by patients, their families, and healthcare providers on how to use pump technology. The goal for the use of insulin pump therapy should be to advance proficiency over time from the basics taught at the initiation of pump therapy to utilizing advanced settings to obtain optimal glycemic control. However, this goal is often not met, and appropriate understanding of the full features of pump technology can be lacking. The objective of this review is to provide an expert perspective on the advanced features and use of insulin pump therapy, including practical guidelines for the successful use of insulin pump technology, and other considerations specific to patients and healthcare providers.

Background: The safety and effectiveness of the in-home use of a hybrid closed-loop (HCL) system that automatically increases, decreases, and suspends insulin delivery in response to continuous glucose monitoring were investigated. Methods: Adolescents (n = 30, ages 14–21 years) and adults (n = 94, ages 22–75 years) with type 1 diabetes participated in a multicenter (nine sites in the United States, one site in Israel) pivotal trial. The Medtronic MiniMed® 670G system was used during a 2-week run-in phase without HCL control, or Auto Mode, enabled (Manual Mode) and, thereafter, with Auto Mode enabled during a 3-month study phase. A supervised hotel stay (6 days/5 nights) that included a 24-h frequent blood sample testing with a reference measurement (i-STAT) occurred during the study phase. Results: Adolescents (mean ± standard deviation [SD] 16.5 ± 2.29 years of age and 7.7 ± 4.15 years of diabetes) used the system for a median 75.8% (interquartile range [IQR] 68.0%–88.4%) of the time (2977 patient-days). Adults (mean ± SD 44.6 ± 12.79 years of age and 26.4 ± 12.43 years of diabetes) used the system for a median 88.0% (IQR 77.6%–92.7%) of the time (9412 patient-days). From baseline run-in to the end of study phase, adolescent and adult HbA1c levels decreased from 7.7% ± 0.8% to 7.1% ± 0.6% (P

Predictive low glucose management (PLGM) may help prevent hypoglycemia by stopping insulin pump delivery based on predicted sensor glucose values.Hypoglycemic challenges were simulated using the Food and Drug Administration-accepted glucose simulator with 100 virtual patients. PLGM was then tested with a system composed of a Paradigm(®) insulin pump (Medtronic, Northridge, CA), an Enlite™ glucose sensor (Medtronic), and a BlackBerry(®) (Waterloo, ON, Canada)-based controller. Subjects (n=22) on continuous subcutaneous insulin infusion (five females, 17 males; median [range] age, 15 [range, 14-20] years; median [range] diabetes duration, 7 [2-14] years; median [range] glycated hemoglobin, 8.0% [6.7-10.4%]) exercised until the PLGM system suspended insulin delivery or until the reference blood glucose value (HemoCue(®); HemoCue GmbH, Großostheim, Germany) reached the predictive suspension threshold setting.PLGM reduced hypoglycemia (70 mg/dL) in silico by 26.7% compared with no insulin suspension, as opposed to a 5.3% reduction in hypoglycemia with use of low glucose suspend (LGS). The median duration of hypoglycemia (time spent70 mg/dL) with PLGM was significantly less than with LGS (58 min vs. 101 min, respectively; P0.001). In the clinical trial the hypoglycemic threshold during exercise was reached in 73% of the patients, and hypoglycemia was prevented in 80% of the successful experiments. The mean (±SD) sensor glucose at predictive suspension was 92±7 mg/dL, resulting in a postsuspension nadir (by HemoCue) of 77±22 mg/dL. The suspension lasted for 90±35 (range, 30-120) min, resulting in a sensor glucose level at insulin resumption of 97±19 mg/dL.In silico modeling and early feasibility data demonstrate that PLGM may further reduce the severity of hypoglycemia beyond that already established for algorithms that use a threshold-based suspension.

The ASPIRE in-clinic study established that automatic suspension of insulin with the threshold suspend (TS) feature reduces the duration of induced hypoglycemia. The study's crossover design allowed the effects of antecedent hypoglycemia to be studied.The study enrolled 50 subjects who exercised until plasma glucose (YSI glucose and lactate analyzer; YSI, Inc., Yellow Springs, OH) reached ≤85 mg/dL. Hypoglycemia was evaluated after the YSI value reached70 mg/dL. In TS experiments, insulin was stopped for 2 h once a sensor glucose (SG) value of ≤70 mg/dL was detected; in control experiments, basal insulin delivery continued. Subjects were randomly assigned to Group A (TS in Period 1; control in Period 2) or Group B (control in Period 1; TS in Period 2). Experiments were separated by 3-10 days.Hypoglycemia was 63.7 min shorter in Period 1 TS experiments (no preceding control experiment) than in Period 2 TS experiments (one or more preceding control experiment(s)) (P0.01). The number of experiments prior to a successful TS experiment was lower for Period 1 than for Period 2 (0.36 ± 0.64 vs. 1.57 ± 0.84; P0.001), as was the cumulative duration of antecedent hypoglycemia (16.6 min vs. 204.6 min; P0.001). The between-groups difference in hypoglycemia duration was not attributable to differences in SG rates of change, the duration of exercise, or area under the curve of70 mg/dL × min in the 2 days before the successful experiment (all P0.3).The TS feature's ability to mitigate hypoglycemia was decreased by an episode or episodes of prolonged antecedent hypoglycemia, suggesting hypoglycemia begets hypoglycemia. The effect of antecedent hypoglycemia should be taken into consideration in the design of future experiments assessing strategies to reduce hypoglycemia.

The threshold-suspend feature of sensor-augmented insulin pumps is designed to minimize the risk of hypoglycemia by interrupting insulin delivery at a preset sensor glucose value. We evaluated sensor-augmented insulin-pump therapy with and without the threshold-suspend feature in patients with nocturnal hypoglycemia.We randomly assigned patients with type 1 diabetes and documented nocturnal hypoglycemia to receive sensor-augmented insulin-pump therapy with or without the threshold-suspend feature for 3 months. The primary safety outcome was the change in the glycated hemoglobin level. The primary efficacy outcome was the area under the curve (AUC) for nocturnal hypoglycemic events. Two-hour threshold-suspend events were analyzed with respect to subsequent sensor glucose values.A total of 247 patients were randomly assigned to receive sensor-augmented insulin-pump therapy with the threshold-suspend feature (threshold-suspend group, 121 patients) or standard sensor-augmented insulin-pump therapy (control group, 126 patients). The changes in glycated hemoglobin values were similar in the two groups. The mean AUC for nocturnal hypoglycemic events was 37.5% lower in the threshold-suspend group than in the control group (980 ± 1200 mg per deciliter [54.4 ± 66.6 mmol per liter] × minutes vs. 1568 ± 1995 mg per deciliter [87.0 ± 110.7 mmol per liter] × minutes, P0.001). Nocturnal hypoglycemic events occurred 31.8% less frequently in the threshold-suspend group than in the control group (1.5 ± 1.0 vs. 2.2 ± 1.3 per patient-week, P0.001). The percentages of nocturnal sensor glucose values of less than 50 mg per deciliter (2.8 mmol per liter), 50 to less than 60 mg per deciliter (3.3 mmol per liter), and 60 to less than 70 mg per deciliter (3.9 mmol per liter) were significantly reduced in the threshold-suspend group (P0.001 for each range). After 1438 instances at night in which the pump was stopped for 2 hours, the mean sensor glucose value was 92.6 ± 40.7 mg per deciliter (5.1 ± 2.3 mmol per liter). Four patients (all in the control group) had a severe hypoglycemic event; no patients had diabetic ketoacidosis.This study showed that over a 3-month period the use of sensor-augmented insulin-pump therapy with the threshold-suspend feature reduced nocturnal hypoglycemia, without increasing glycated hemoglobin values. (Funded by Medtronic MiniMed; ASPIRE ClinicalTrials.gov number, NCT01497938.).

In insulin pump therapy, optimization of bolus and basal insulin dose settings is a challenge. We introduce a new algorithm that provides individualized basal rates and new carbohydrate ratio and correction factor recommendations. The algorithm utilizes a mathematical model of blood glucose (BG) as a function of carbohydrate intake and delivered insulin, which includes individualized parameters derived from sensor BG and insulin delivery data downloaded from a patient's pump.A mathematical model of BG as a function of carbohydrate intake and delivered insulin was developed. The model includes fixed parameters and several individualized parameters derived from the subject's BG measurements and pump data. Performance of the new algorithm was assessed using n = 4 diabetic canine experiments over a 32 h duration. In addition, 10 in silico adults from the University of Virginia/Padova type 1 diabetes mellitus metabolic simulator were tested.The percentage of time in glucose range 80-180 mg/dl was 86%, 85%, 61%, and 30% using model-based therapy and [78%, 100%] (brackets denote multiple experiments conducted under the same therapy and animal model), [75%, 67%], 47%, and 86% for the control experiments for dogs 1 to 4, respectively. The BG measurements obtained in the simulation using our individualized algorithm were in 61-231 mg/dl min-max envelope, whereas use of the simulator's default treatment resulted in BG measurements 90-210 mg/dl min-max envelope.The study results demonstrate the potential of this method, which could serve as a platform for improving, facilitating, and standardizing insulin pump therapy based on a single download of data.

Background: Automated insulin management features of the MiniMed® 640G sensor-augmented pump system include suspension in response to predicted low sensor glucose (SG) values (“suspend before low”), suspension in response to existing low SG values (“suspend on low”), and automatic restarting of basal insulin delivery upon SG recovery. The effectiveness of these features was evaluated using CareLink® software data. Methods: Anonymized data from MiniMed 640G system users (n = 4818), MiniMed 530G system users (n = 39,219), and MiniMed Paradigm® Veo™ system users (n = 43,193) who voluntarily uploaded pump and sensor data were retrospectively analyzed. Comparisons were made between days in which system features were enabled at any time and those in which they were not. Comparisons were also made between pump suspension events for which insulin delivery was automatically or manually resumed and between glycemic parameters of users who switched from the MiniMed Paradigm Veo system to the MiniMed 640G system. Results: Days in which the MiniMed 640G “suspend before low” feature was enabled had lower percentages of SG readings ≤70 mg/dL (3.9 mmol/L) or ≥240 mg/dL (13.3 mmol/L) than days when it was not enabled (P