Association between glycaemia risk index (GRI) and diabetic retinopathy in type 2 diabetes: A cohort study.

AIM: To investigate the association between a new composite metric, glycaemia risk index (GRI), and incident diabetic retinopathy (DR). METHODS: A total of 1204 adults with type 2 diabetes without DR at baseline were included between 2005 and 2019 from a single centre in Shanghai, China. GRI was obtained from continuous glucose monitoring data at baseline. Cox proportion hazard regression analysis was used to assess the association between GRI and the risk of incident DR. RESULTS: During a median follow-up of 8.4 years, 301 patients developed DR. The multivariable-adjusted hazard ratios (HRs) for incident DR across ascending GRI quartiles (≤14 [reference], 15 ~ 28, 29 ~ 47 and > 47) were 1.00, 1.05 (95% CI 0.74-1.48), 1.33 (95% confidence interval [CI] 0.96-1.84) and 1.53 (95% CI 1.11-2.11), respectively. For each 1-SD increase in GRI, the risk of DR was increased by 20% (HR 1.20, 95% CI 1.07-1.33) after adjustment for confounders. CONCLUSIONS: In patients with type 2 diabetes, higher GRI is associated with an increased risk of incident DR. GRI has the potential to be a valuable clinical measure, which needs to be further explored in future studies.

Fulminant type 1 diabetes: The clinical and continuous glucose monitoring characteristics in Chinese patients.

The purpose of the current study was to investigate the clinical characteristics of fulminant type 1 diabetes mellitus (FT1DM) in Chinese patients and to further determine their glycaemic profiles through continuous glucose monitoring (CGM). Thirty subjects who were diagnosed with FT1DM according to the 2012 JDS criteria were enrolled. Clinical characteristics were compared to those reported in Japanese FT1DM. All subjects received retrospective CGM for 3 days after being converted to subcutaneous insulin injection therapy. Chinese FT1DM patients presented with a shorter duration of symptoms (2.84 ± 2.42 days vs 4.4 ± 3.1 days, P < 0.01), worse islet function (fasting C-peptide, 0.09 ± 0.11 ng/mL vs 0.30 ± 0.21 ng/mL; 2-hour C-peptide, 0.13 ± 0.14 ng/mL vs 0.30 ± 0.30 ng/mL, both P < 0.01), lower prevalence of flu-like symptoms (46.7% vs 71.4%, P < 0.05), and a significantly higher GADA positive rate (23.3% vs 5.1%, P < 0.01) when compared with Japanese patients. The CGM results showed that the mean time in range (TIR) of FT1DM patients was 49.8 ± 22.1%, while mean amplitude of glycaemic excursion (MAGE) and standard deviations of sensor glucose (SDSG) were 7.58 ± 3.59 mmol/L and 3.19 ± 1.22 mmol/L, respectively, with nearly 1/3 participants coefficient of variation (CV) > 36% (all are male), suggesting a large glucose fluctuation. The female patients were further divided into pregnancy-related FT1DM (PF) and non-PF (NPF) subgroups (both n = 5), and we found that PF patients had a significantly higher TIR than NPF patients (77.0 ± 16.1% vs 41.0 ± 22.4%, P < 0.05). There were heterogeneities in the clinical characteristics of FT1DM patients, and the CGM results indicated a very low TIR and large glucose fluctuation which needs careful attention.

IMPROVED HBA1C, TOTAL DAILY INSULIN DOSE, AND TREATMENT SATISFACTION WITH INSULIN PUMP THERAPY COMPARED TO MULTIPLE DAILY INSULIN INJECTIONS IN PATIENTS WITH TYPE 2 DIABETES IRRESPECTIVE OF BASELINE C-PEPTIDE LEVELS.

OBJECTIVE: 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. METHODS: 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. RESULTS: 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. CONCLUSION: 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. ABBREVIATIONS: 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.

Continuous glucose control in the ICU: report of a 2013 round table meeting.

Achieving adequate glucose control in critically ill patients is a complex but important part of optimal patient management. Until relatively recently, intermittent measurements of blood glucose have been the only means of monitoring blood glucose levels. With growing interest in the possible beneficial effects of continuous over intermittent monitoring and the development of several continuous glucose monitoring (CGM) systems, a round table conference was convened to discuss and, where possible, reach consensus on the various aspects related to glucose monitoring and management using these systems. In this report, we discuss the advantages and limitations of the different types of devices available, the potential advantages of continuous over intermittent testing, the relative importance of trend and point accuracy, the standards necessary for reporting results in clinical trials and for recognition by official bodies, and the changes that may be needed in current glucose management protocols as a result of a move towards increased use of CGM. We close with a list of the research priorities in this field, which will be necessary if CGM is to become a routine part of daily practice in the management of critically ill patients.

The Myth of MARD (Mean Absolute Relative Difference): Limitations of MARD in the Clinical Assessment of Continuous Glucose Monitoring Data.

The mean absolute relative difference (MARD) is a numerical metric that has been adopted by the diabetes technology community as the main indicator that describes the accuracy of a glucose sensor at a single point in time. The appropriateness of this adoption is questionable because there is limited evidence that MARD has meaningful clinical relevance in the current era of sensor technology. The calculation may be simple, but evaluation of MARD can be very complex because it is substantially impacted by the design of the data collection in an accuracy study. Factors that can influence the overall MARD include participant demographics such as type of diabetes and age, site of sensor wear, and the percentage of collected values in each glycemic range during the study that is, in turn, a function of the study design. MARD is only one of several important statistical metrics such as bias and precision that are relevant to assessing accuracy of a sensor. Furthermore, these analytic metrics convey little information about the safety and effectiveness of sensor use with an automated insulin delivery system or a standalone device. There are no clinical studies in people with diabetes (PWD) proving that MARD can accurately differentiate between a safe and unsafe sensor or between a more and less clinically effective sensor. Moreover, there are alternatives to MARD that can do this in a clinically meaningful way, which include error grid analyses and clinical studies in PWD. This review attempts to demythologize the status of MARD for the diabetes community in an effort to shift the focus from MARD to using clinically relevant assessments.

Shining the Spotlight on Multiple Daily Insulin Therapy: Real-World Evidence of the InPen Smart Insulin Pen.

Objective: Connected insulin pens are creating opportunities for the millions of individuals with diabetes using multiple daily injections (MDI) therapy across the globe. Continuous glucose monitoring (CGM) data from connected insulin pens are revealing gaps and opportunities to significantly improve care for this population. In this article, we report real-world findings of the InPen™ smart insulin pen paired with CGM (InPen system), used by persons with type 1 diabetes (T1D) and type 2 diabetes (T2D). Methods: A retrospective cohort analysis was conducted with the real-world data collected from the InPen system of individuals (N = 3793 with T1D, N = 552 with T2D, and N = 808 unidentified) who used the system from January 01, 2020, to December 31, 2021. Diabetes management (e.g., missed and mistimed insulin dosing, mismatched food intake, and correction dose delivery) and glycemic outcomes were assessed. Results: In the overall and T1D populations, a dosing frequency of ≥3 doses per day and a missed dose frequency of <20% was associated with improved glycemia. In adults with T2D, missing <20% of doses was the significant factor determining improved glycemia. Conclusion: This analysis, integrating data from a smart insulin pen and CGM, provides insights into the impact of dosing behavior on glycemic outcomes and informs counseling strategies for the diabetes care team, through technologically advanced insulin management for those using MDI therapy.

A Peek Under the Hood: Explaining the MiniMed™ 780G Algorithm with Meal Detection Technology.

The MiniMed™ 780G system (780G) received Conformité Européenne mark in June 2020 and was, recently, approved by the U.S. Food and Drug Administration (April 2023). Clinical trials and real-world analyses have demonstrated MiniMed™ 780G system safety and effectiveness and that glycemic outcomes (i.e., time in range) improve with recommended settings use. In this publication, we will explain the iterative development of the 780G algorithm and how this technology has simplified diabetes management.

Early Real-World Performance of the MiniMed™ 780G Advanced Hybrid Closed-Loop System and Recommended Settings Use in the United States.

Background: The MiniMed™ 780G system (MM780G) with Guardian™ 4 sensor includes a 100 mg/dL glucose target (GT) and automated insulin corrections up to every 5 min and was recently approved for use in the United States. In the present study, early real-world MM780G performance and the use of recommended system settings (100 mg/dL GT with an active insulin time of 2 h), by individuals with type 1 diabetes, were evaluated. Methods: CareLink™ personal data uploaded between the launch of the MM780G to August 22, 2023 were aggregated and underwent retrospective analysis (based on user consent) and if users had ≥10 days of continuous glucose monitoring (CGM) data. The 24-h day CGM metrics, including mean glucose, percentage of time spent in (%TIR), above (%TAR), and below (%TBR) target range (70-180 mg/dL), in addition to delivered insulin and closed-loop (CL) exits, were compared between an overall group (n = 7499) and individuals who used recommended settings (each, for >95% of the time). An analysis of the same metrics for MiniMed™ 770G system (MM770G) users (n = 3851) who upgraded to the MM780G was also conducted (paired t-test or Wilcoxon signed-rank test, P < 0.05 considered statistically significant). Results: For MM780G users, CGM use, and time in CL were >90% and all MM780G CGM metrics exceeded consensus-recommended goals. With recommended settings (22% of all users), mean %TIR and %TITR (70-140 mg/dL) were 81.4% and 56.4%, respectively. For individuals who upgraded from the MM770G, %TIR and %TITR increased from 73.2% to 78.3% and 45.8% to 52.6%, respectively, while %TAR reduced from 25.1% to 20.2% (P < 0.001, for all three). CL exits/week averaged <1, for all MM780G users. Conclusions: Early real-world MM780G use in the United States demonstrated a high percentage of time in range with low time above and below range. These outcomes are similar to those observed for real-world MM780G use in other countries.

Impact of Body Composition and Anemia on Accuracy of a Real-Time Continuous Glucose Monitor in Diabetes Patients on Continuous Ambulatory Peritoneal Dialysis.

Continuous glucose monitoring (CGM) is proposed as an alternative for glycemic assessment in peritoneal dialysis, but volume overload and anemia may affect sensor accuracy. This is an exploratory analysis of a study of Guardian Connect™ with Guardian Sensor™ 3 in 30 participants with diabetes on continuous ambulatory peritoneal dialysis (CAPD) (age [mean ± standard deviation] 64.7 ± 5.6 years, 23 men, body mass index [BMI] 25.4 ± 3.9 kg/m2, blood hemoglobin [Hb] 10.7 ± 1.3 g/dL). The mean absolute relative difference (MARD) was calculated between paired sensor and YSI 2300 STAT venous glucose readings (n = 941) during an 8-h in-clinic session with glucose challenge. Body composition was evaluated using bioimpedance. The overall MARD was 10.4% (95% confidence interval 9.6-11.7). There were no correlations between BMI, extracellular water, relative hydration index, and lean or fat mass with MARD. No correlations were observed between MARD and Hb (r = 0.016, P > 0.05). In summary, this real-time CGM demonstrated good accuracy in CAPD with minimal influence from body composition and anemia.

Advances in Automated Insulin Delivery with the Medtronic 780G: The Australian Experience.

Aim: To assess the real-world performance of MiniMed™ 780G for Australians with type 1 diabetes (T1D) following advanced hybrid closed loop (AHCL) activation and to evaluate the effect of changing from MiniMed 670/770G to 780G. Methods: We analyzed deidentified Carelink™ continuous glucose monitoring (CGM) data from Australian users from January 2020 to December 2022, including the proportion attaining three major consensus targets: Glucose management indicator (GMI <7.0%), time in range (TIR 70-180 mg/dL >70%), and time below range (TBR 70 mg/dL <4%). Results: Comparing 670/770G users (n = 5676) for mean ± standard deviation 364 ± 244 days with 780G users (n = 3566) for 146 ± 145 days, the latter achieved a higher TIR (72.6% ± 10.6% vs. 67.3% ± 11.4%; P < 0.001), lower time above range (TAR) (25.5% ± 10.9% vs. 30.6% ± 11.7%; P < 0.001), and lower GMI (6.9% ± 0.4% vs. 7.2% ± 0.4%; P < 0.001) without compromising TBR (1.9% ± 1.8% vs. 2.0% ± 1.8%; P = 0.0015). Of 1051 670/770G users transitioning to 780G, TIR increased (70.0% ± 10.7% to 74.0% ± 10.2%; P < 0.001), TAR decreased (28.1% ± 10.9% to 24.0% ± 10.7%; P < 0.001), and TBR was unchanged. The percentage of users attaining all three CGM targets was higher in 780G users (50.1% vs. 29.5%; P < 0.001). CGM metrics were stable at 12 months post-transition. Conclusion: Real-world data from Australia shows that a higher proportion of MiniMed 780G users meet clinical targets for CGM consensus metrics compared to MiniMed 670/770G users and glucose control was sustained over 12 months.

A Review of Precision Insulin Management With Smart Insulin Pens: Opening Up the Digital Door to People on Insulin Injection Therapy.

Although advances in insulin therapy and delivery have been made, global evidence indicates sub-optimal glycemic management in people on insulin therapy with either type 1 diabetes (T1D) or type 2 diabetes (T2D). In this review, we discuss connected insulin pens that include tracking insulin pens (TIPs) and smart insulin pens (SIPs) and caps, as approaches to improving mean glucose or time in range while minimizing exposure to hypoglycemia or time below range (TBR) in people with diabetes (PwD) on multiple daily injection (MDI) therapy. We discuss various factors offered by SIPs that can facilitate precision insulin management, that is, delivering the right dose at the right time. These factors include the automatic recording of insulin dose size and delivery time; differentiating prime from therapy doses; active insulin tracking; dose calculators that provide individualized dosing recommendations; alerts for missed doses (ie, rapid-acting or long-acting insulin), insulin temperature, and insulin age monitoring; and integrated data reports for the clinical care team. A data-driven approach to care is critical to precision insulin management and includes helping PwD make informed choices regarding their preferred method of insulin delivery and ensuring insulin delivery technology tools are configured for their personal therapy plan. The data-driven approach involves developing a plan for ongoing collaborative use of the resulting data with their care team that may include adjusting insulin regimen and optimizing the care plan on a timely basis. We conclude with a list of practice protocols that are needed to support data-driven precision insulin management. This review includes a summary of research including various stages of connected insulin pens and caps.

Racial/Ethnic Inequities in Use of Diabetes Technologies Among Medicare Advantage Beneficiaries With Type 1 Diabetes.

CONTEXT: Racial/ethnic inequities have been observed in diabetes care. OBJECTIVE: To measure changes in prevalence of continuous glucose monitoring (CGM) and insulin pump therapy among Medicare Advantage beneficiaries with type 1 diabetes by race/ethnicity and to determine the impact of socioeconomic factors on racial/ethnic inequities. DESIGN: The prevalence of CGM and pump use was assessed by race/ethnicity for Medicare Advantage beneficiaries annually from 2017 through 2020. Models predicting technology use by year, race/ethnicity, age, sex, endocrinology visits, and measures of socioeconomic status were fit. SETTING: Community. PATIENTS OR OTHER PARTICIPANTS: Beneficiaries with type 1 diabetes and 2 or more claims with a diabetes diagnosis in the coverage year. INTERVENTION(S): Insulin pump or CGM therapy. MAIN OUTCOME MEASURE(S): Use of diabetes technology by racial/ethnic group. RESULTS: Technology use increased from 2017 through 2020 in all racial/ethnic groups. The absolute difference in use between White and Black beneficiaries from 2017 to 2020 remained stable for insulin pumps (10.7% to 10.8%) and increased for CGM (2.6% to 11.1%). The differences in pump use from 2017 to 2020 narrowed between White and Hispanic beneficiaries (12.3% to 11.4%) and White and Asian beneficiaries (9.7% to 6.6%), whereas the opposite occurred for CGM use (3.0% to 15.5% for White vs Hispanic beneficiaries; 1.5% to 8.0% for White vs Asian beneficiaries). Racial/ethnic inequities persisted (P < .0001) after adjusting for other characteristics. CONCLUSIONS: Differences in diabetes technology use between racial/ethnic groups often persisted from 2017 through 2020 and could not be explained by demographics, socioeconomic status, or endocrinology visits.

Glycemic Outcomes During Real-World Hybrid Closed-Loop System Use by Individuals With Type 1 Diabetes in the United States.

BACKGROUND: Glycemic outcomes during real-world hybrid closed-loop (HCL) system use by individuals with type 1 diabetes, in the United States, were retrospectively analyzed. METHODS: Hybrid closed-loop system data voluntarily uploaded to Carelink™ personal software from March 2017 to November 2020 by individuals (aged ≥7 years) using the MiniMed™ 670G system and having ≥10 days of continuous glucose monitoring data after initiating Auto Mode were assessed. Glycemic outcomes including the mean glucose management indicator (GMI), sensor glucose (SG), percentage of time spent in (TIR), below (TBR), and above (TAR) target range (70-180 mg/dL) were analyzed. Outcomes were also analyzed in a subgroup of users per baseline GMI of <7% versus >8%. RESULTS: The overall cohort (N = 123 355 users, with a mean of 87.9% of time in Auto Mode) had a GMI of 7.0% ± 0.4%, TIR of 70.4% ± 11.2%, TBR <70 mg/dL of 2.2% ± 2.1% and TAR>180 mg/dL of 27.5% ± 11.6%, post-Auto Mode initiation. Compared with pre-Auto Mode initiation, users (N = 52 941, 88.6% of time in Auto Mode) had a GMI that decreased from 7.3% ± 0.6% to 7.1% ± 0.5% (P < .001), TIR that increased from 61.5% ± 15.1% to 68.1% ± 11.9% (P < .001), TAR>180 mg/dL that decreased from 36.3% ± 15.7% to 29.8% ± 12.2% (P < .001) and TBR<70 mg/dL that decreased from 2.11 ± 2.4 to 2.07% ± 2.25% (P = .002). While all metrics statistically improved for the baseline GMI >8.0% group, the baseline GMI <7.0% group had unchanged TIR (77.4% ± 7.4% to 77.5% ± 8.0%, P = .456) and TAR>180 mg/dL that increased (19.2 ± 6.7 to 19.6 ± 7.9%, p < 0.001). CONCLUSION: Real-world HCL system use in the U.S. demonstrated overall glycemic control that trended similarly with the system pivotal trial outcomes and previous real-world system use analyses.

Using Continuous Glucose Monitoring Values for Bolus Size Calculation in Smart Multiple Daily Injection Systems: No Negative Impact on Post-bolus Glycemic Outcomes Found in Real-World Data.

BACKGROUND: Recent evidence shows that it may be safe to estimate bolus sizes based on continuous glucose monitoring (CGM) rather than blood glucose (BG) values using glycemic trend-adjusted bolus calculators. Users may already be doing this in the real world, though it is unclear whether this is safe or effective for calculators not employing trend adjustment. METHODS: We assessed real-world data from a smart multiple daily injections (MDIs) device users with a CGM system, hypothesizing that four-hour post-bolus outcomes using CGM values are not inferior to those using BG values. Our data set included 184 users and spanned 18 months with 79 000 bolus observations. We tested differences using logistic regression predicting CGM or BG value usage based on outcomes and confirmed initial results using a mixed model regression accounting for within-subject correlations. RESULTS: Comparing four-hour outcomes for bolus events using CGM and BG values revealed no differences using our initial approach (P > .183). This finding was confirmed by our mixed model regression approach in all cases (P > .199), except for times below range outcomes. Higher times below range were predictive of lower odds of CGM-based bolus calculations (OR = 0.987, P < .0001 and OR = 0.987, P = .0276, for time below 70 and 54 mg/dL, respectively). CONCLUSIONS: We found no differences in four-hour post-bolus glycemic outcomes when using CGM or BG except for time below range, which showed evidence of being lower for CGM. Though preliminary, our results confirm prior findings showing non-inferiority of using CGM values for bolus calculation compared with BG usage in the real world.

Potential cost savings in the United States from a reduction in sensor-detected severe hypoglycemia among users of the InPen smart insulin pen system.

BACKGROUND: Severe hypoglycemia is a significant barrier to optimizing insulin therapy in both type 1 and type 2 diabetes and places a burden on the US health care system because of the high costs of hypoglycemia-related health care utilization. OBJECTIVE: To compare the frequency of sensor-detected severe hypoglycemic events (SHEs) among a population of continuous glucose monitoring (CGM) users on insulin therapy after initiation of the InPen smart insulin pen (SIP) system and to estimate the potential hypoglycemia-related medical cost savings across a population of SIP users. METHODS: SIP users of all ages with type 1 or type 2 diabetes were required to have at least 90 days of SIP use with a connected CGM device. The last 14 days of sensor glucose (SG) data within the 30-day period prior to the start of SIP use ("pre-SIP") and the last 14 days of SG data, along with the requirement of at least 1 bolus entry per day within the 61- to 90-day period after SIP start ("post-SIP"), were analyzed. Sensor-detected SHEs (defined as ≥10 minutes of consecutive SG readings at <54 mg/dL) were determined. Once factored, the expected medical intervention rates and associated costs were calculated. Intervention rates and costs were obtained from the literature. RESULTS: There were 1,681 SIP + CGM users from March 1, 2018, to April 30, 2021. The mean number of sensor-detected SHEs per week declined from 0.67 in the pre-SIP period to 0.58 in the post-SIP period (P = 0.008), which represented a 13% reduction. Assuming a range of 5%-25% of all sensor-detected SHEs resulted in a clinical event, the estimated cost reduction associated with reduced SHEs was $12-$59 and $110-$551 per SIP user per month and per year, respectively. For those aged at least 65 years, there were 166 SIP+CGM users and the reduction in the mean number of sensor-detected SHEs per week between the pre-SIP and post-SIP periods was 31%. CONCLUSIONS: Use of the SIP system with a connected CGM is associated with reduced sensor-detected severe hypoglycemia, which may result in significant cost savings. DISCLOSURES: Albert Chien, Glen Im, Kael Wherry, Janice MacLeod, and Robert A Vigersky are employees of Medtronic; Sneha Thanasekaran and Angela Gaetano were affiliated with Medtronic while doing this research. The submitted work did not involve study subject recruitment, enrollment, or participation in a trial and did not fall under human subject protection requirements (per the Department of Health and Human Services CFR Part 46) necessitating Internal Review Board approval or exemption.

An Assessment of Clinical Continuous Glucose Monitoring Targets for Older and High-Risk People Living with Type 1 Diabetes.

Aim: To assess relationships between continuous glucose monitoring (CGM) time in range (TIR), 70-180 mg/dL, time below range (TBR), <70 mg/dL, time above range (TAR), >180 mg/dL, and glucose coefficient of variation (CV) in relation to currently recommended clinical CGM targets for older people, which recommend reduced TIR and TBR targets relative to the general type 1 diabetes population. Methods: We conducted a post hoc analysis using the JDRF Australia Adult Hybrid Closed Loop trial database examining correlations in 120 adults with type 1 diabetes of 3 weeks masked CGM (Guardian Sensor 3; Medtronic) metrics (n = 61 on multiple daily injections, 59 on non-CGM augmented pumps) using manual insulin dosing at baseline and at 26-weeks, with 50% randomized to automated insulin dosing (AID). Results: Correlations between baseline TIR and TAR were strong (r = -0.966; P < 0.0001), weak for TBR (r = 0.363; P < 0.0001), and glucose CV (r = 0.037; P = 0.687) while moderate between CV and TBR (r = 0.726; P < 0.0001). Associations were similar for participants aged >60 years (n = 15) versus younger subjects. Correlations of changes in (Δ) TIR with ΔTAR over 26 weeks were strong (r = -0.945; P < 0.001) and correlations for ΔTBR were weak (r = 0.025; P = 0.802). ΔCV did not significantly correlate with ΔTAR (r = -0.064; P = 0.526) but did with ΔTBR (r = 0.770; P = <0.001). Conclusions: Changes in TIR are not associated with changes in TBR. Thus, we recommend that for older AID users whilst TBR targets should be prioritized to reduce hypoglycemia-related risk, TBR should be addressed independently of TIR. Clinical Trial Registratrion number: (ACTRN12617000520336).

Safety Event Outcomes and Glycemic Control with a Hybrid Closed-Loop System Used by Chinese Adolescents and Adults with Type 1 Diabetes Mellitus.

Background: While evidence supports glycemic control benefits for individuals with type 1 diabetes mellitus (T1DM) using hybrid closed-loop (HCL) systems, HCL automated insulin delivery therapy in China has not been assessed. This study evaluated safety events and effectiveness during HCL system use by Chinese adolescents and adults with T1DM. Methods: Sixty-two participants (n = 12 adolescents with a mean ± standard deviation [SD] of 15.5 ± 1.1 years and n = 50 adults [mean ± SD of 37.6 ± 11.1 years]) with T1DM and baseline A1C of 7.1% ± 1.0% underwent a run-in period (∼2 weeks) using open-loop Manual Mode (sensor-augmented pump) insulin delivery with the MiniMed™ 770G system with the Guardian™ Sensor (3) glucose sensor, followed by a study period (4 weeks) with HCL Auto Mode enabled. Analyses compared continuous glucose monitoring data and insulin delivered during the run-in versus study period (Wilcoxon signed-rank test or t-test). Safety events included rates of severe hypoglycemia and diabetic ketoacidosis (DKA). Results: Compared to baseline run-in, overall Auto Mode use increased time in range (TIR, 70-180 mg/dL) from 75.3% to 80.9% (P < 0.001) and reduced time below range (TBR, <70 mg/dL) from 4.7% to 2.2% (P < 0.001). Subgroup analysis demonstrated that participants (n = 29) with baseline A1C <7.0% had TBR that reduced from 5.6% to 2.0%, while participants (n = 21) with baseline A1C ≥7.5% had time above range (TAR, >180 mg/dL) that reduced from 31.6% to 20.8%. Auto Mode use also increased the percentage achieving combined recommendations for time at sensor glucose ranges (i.e., TIR of >70%, TBR of <4% and TAR of <25%) from 24.2% at baseline to 77.4% at study end. Total daily insulin dose reduced from 42.8 ± 19.8 to 40.7 ± 18.9 U (P = 0.013). There were no severe hypoglycemic, DKA, or serious adverse events. Conclusions: Chinese adolescents and adults, some of whom met target A1C at baseline, safely achieved significantly improved glycemia with 1 month of MiniMed 770G system use when compared to open-loop insulin delivery. ClinicalTrials.gov ID: NCT04663295.

Glycemic Outcomes During Early Use of the MiniMed™ 780G Advanced Hybrid Closed-Loop System with Guardian™ 4 Sensor.

Background: Safety and significant improvement in overall glycated hemoglobin (A1C) and percentage of time spent in (TIR), below (TBR), and above (TAR) glucose range were demonstrated in the pivotal trial of adolescents and adults using the MiniMed™ advanced hybrid closed-loop (AHCL) system with the adjunctive, calibration-required Guardian™ Sensor 3. The present study evaluated early outcomes of continued access study (CAS) participants who transitioned from the pivotal trial investigational system to the approved MiniMed™ 780G system with the non-adjunctive, calibration-free Guardian™ 4 Sensor (MM780G+G4S). Study data were presented alongside those of real-world MM780G+G4S users from Europe, the Middle East, and Africa. Methods: The CAS participants (N = 109, aged 7-17 years and N = 67, aged >17 years) used the MM780G+G4S for 3 months and data of real-world MM780G+G4S system users (N = 10,204 aged ≤15 years and N = 26,099 aged >15 years) were uploaded from September 22, 2021 to December 02, 2022. At least 10 days of real-world continuous glucose monitoring (CGM) data were required for analyses. Glycemic metrics, delivered insulin and system use/interactions underwent descriptive analyses. Results: Time in AHCL and CGM use were >90% for all groups. AHCL exits averaged 0.1/day and there were few blood glucose measurements (BGMs) (0.8/day-1.0/day). Adults in both cohorts met most consensus recommendations for glycemic targets. Pediatric groups met recommendations for %TIR and %TBR, although not those for mean glucose variability and %TAR, possibly due to low use of recommended glucose target (100 mg/dL) and active insulin time (2 h) settings (28.4% in the CAS cohort and 9.4% in the real-world cohort). The CAS pediatric and adult A1C were 7.2% ± 0.7% and 6.8% ± 0.7%, respectively, and there were no serious adverse events. Conclusions: Early clinical use of the MM780G+G4S was safe and involved minimal BGMs and AHCL exits. Consistent with real-world pediatric and adult use, outcomes were associated with achievement of recommended glycemic targets. Clinical Trial Registration number: NCT03959423.

Improved Glycemia with Hybrid Closed-Loop Versus Continuous Subcutaneous Insulin Infusion Therapy: Results from a Randomized Controlled Trial.

Objective: To evaluate safety and effectiveness of MiniMed™ 670G hybrid closed loop (HCL) in comparison with continuous subcutaneous insulin infusion (CSII) therapy for 6 months in persons with type 1 diabetes (T1D). Methods: Adults (aged 18-80 years), adolescents, and children (aged 2-17 years) with T1D who were using CSII therapy were enrolled and randomized (1:1) to 6 months of HCL intervention (n = 151, mean age of 39.9 ± 19.8 years) or CSII without continuous glucose monitoring (n = 151, 35.7 ± 18.4 years). Primary effectiveness endpoints included change in A1C for Group 1 (baseline A1C >8.0%), from baseline to the end of study, and difference in the end of study percentage of time spent below 70 mg/dL (%TBR <70 mg/dL) for Group 2 (baseline A1C ≤8.0%), to show superiority of HCL intervention versus control. Secondary effectiveness endpoints were change in A1C and %TBR <70 mg/dL for Group 2 and Group 1, respectively, to show noninferiority of HCL intervention versus control. Primary safety endpoints were rates of severe hypoglycemia and diabetic ketoacidosis (DKA). Results: Change in A1C and difference in %TBR <70 mg/dL for the overall group were significantly improved, in favor of HCL intervention. In addition, a significant mean (95% confidence interval) change in A1C was observed for both Group 1 (-0.8% [-1.1% to -0.4%], P < 0.0001) and Group 2 (-0.3% [-0.5% to -0.1%], P < 0.0001), in favor of HCL intervention. The same was observed for difference in %TBR <70 mg/dL for Group 1 (-2.2% [-3.6% to -0.9%]) and Group 2 (-4.9% [-6.3% to -3.6%]) (P < 0.0001 for both). There was one DKA event during run-in and six severe hypoglycemic events: two during run-in and four during study (HCL: n = 0 and CSII: n = 4 [6.08 per 100 patient-years]). Conclusions: This RCT demonstrates that the MiniMed 670G HCL safely and significantly improved A1C and %TBR <70 mg/dL compared with CSII control in persons with T1D, irrespective of baseline A1C level.