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.

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.

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.

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.

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.

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.

Safety and Glycemic Outcomes During the MiniMedTM Advanced Hybrid Closed-Loop System Pivotal Trial in Children and Adolescents with Type 1 Diabetes

Background: During MiniMed™ advanced hybrid closed-loop (AHCL) use by adolescents and adults in the pivotal trial, glycated hemoglobin (A1C) was significantly reduced, time spent in range (TIR) was significantly increased, and there were no episodes of severe hypoglycemia or diabetic ketoacidosis (DKA). The present study investigated the same primary safety and effectiveness endpoints during AHCL use by a younger cohort with type 1 diabetes (T1D). Methods: An intention-to-treat population (N = 160, aged 7-17 years) with T1D was enrolled in a single-arm study at 13 investigational centers. There was a run-in period (∼25 days) using HCL or sensor-augmented pump with/without predictive low-glucose management, followed by a 3-month study period with AHCL activated at two glucose targets (GTs; 100 and 120 mg/dL) for ∼45 days each. The mean ± standard deviation values of A1C, TIR, mean sensor glucose (SG), coefficient of variation (CV) of SG, time at SG ranges, and insulin delivered between run-in and study were analyzed (Wilcoxon signed-rank test or t-test). Results: Compared with baseline, AHCL use was associated with reduced A1C from 7.9 ± 0.9% (N = 160) to 7.4 ± 0.7% (N = 136) (P < 0.001) and overall TIR increased from the run-in 59.4 ± 11.8% to 70.3 ± 6.5% by end of study (P < 0.001), without change in CV, time spent below range (TBR) <70 mg/dL, or TBR <54 mg/dL. Relative to longer active insulin time (AIT) settings (N = 52), an AIT of 2 h (N = 19) with the 100 mg/dL GT increased mean TIR to 73.4%, reduced TBR <70 mg/dL from 3.5% to 2.2%, and reduced time spent above range (TAR) >180 mg/dL from 28.7% to 24.4%. During AHCL use, there was no severe hypoglycemia or DKA. Conclusions: In children and adolescents with T1D, MiniMed AHCL system use was safe, A1C was lower, and TIR was increased. The lowest GT and shortest AIT were associated with the highest TIR and lowest TBR and TAR, all of which met consensus-recommended glycemic targets. ClinicalTrials.gov ID: NCT03959423.

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.

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.

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.

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.

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.

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.

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).

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.

Evaluation of Extended Infusion Set Performance in Adults with Type 1 Diabetes: Infusion Set Survival Rate and Glycemic Outcomes from a Pivotal Trial

Background: Standard insulin infusion sets (IISs) are to be replaced every 2 to 3 days to avoid complications and diabetic ketosis due to set failure. This pivotal trial evaluated the safety and performance of a new extended-wear infusion set (EIS) when used for 7 days by adults with type 1 diabetes (T1D). Methods: This single-arm, nonrandomized trial enrolled adults (18-80 years of age) with T1D, who used their own MiniMed™ 670G system with insulin lispro or insulin aspart and the EIS for up to 7 days, across 12 consecutive wears. Safety endpoints included incidence of serious adverse events (SAEs), serious adverse device effects (SADEs), unanticipated adverse device effects (UADEs), severe hypoglycemia (SevHypo), severe hyperglycemia (SevHyper), diabetic ketoacidosis (DKA), and skin infection. The EIS failure rate due to unexplained hyperglycemia (i.e., suspected occlusion), the overall EIS survival rate, glycemic control outcomes (i.e., A1C, mean sensor glucose and time spent in established glucose ranges), total daily insulin delivered, and satisfaction with the EIS were determined. Results: The intention to treat population (n = 259, 48% men, 45.0 ± 14.1 years) wore a total of 3041 EIS devices. No SADE, UADE, or DKA events was reported. Overall rates of SAEs, SevHypo, SevHyper, and skin infection were 3.8, 2.5, 104.1, and 20.1 events per 100 participant-years. The rate of EIS failure due to unexplained hyperglycemia at the end of day 7 was 0.1% (95% confidence interval [CI]: 0.03-0.51) and 0.4% (95% CI: 0.16-1.00) for insulin lispro and aspart use, respectively. Overall EIS survival rate at the end of day 7 was 77.8% (95% CI: 76.2-79.3), glycemic control did not change, and participants reported greater satisfaction with the EIS compared with standard IISs worn before the study (P < 0.001). Conclusions: This investigation demonstrates that the EIS, when worn for up to 7 days, was safe and rated with high satisfaction, without adversely affecting glycemic control in adults with T1D. Clinical Trial Registration number: NCT04113694 (https://clinicaltrials.gov/ct2/show/NCT04113694).

Improving the Patient Experience With Longer Wear Infusion Sets Symposium Report

Continuous subcutaneous insulin infusion (CSII) therapy is becoming increasingly popular. CSII provides convenient insulin delivery, precise dosing, easy adjustments for physical activity, stress, or illness, and integration with continuous glucose monitors in hybrid or other closed-loop systems. However, even as insulin pump hardware and software have advanced, technology for insulin infusion sets (IISs) has stayed relatively stagnant over time and is often referred to as the "Achilles heel" of CSII. To discuss barriers to insulin pump therapy and present information about advancements in, and results from clinical trials of extended wear IISs, Diabetes Technology Society virtually hosted the "Improving the Patient Experience with Longer Wear Infusion Sets Symposium" on December 1, 2021. The symposium featured experts in the field of IISs, including representatives from Steno Diabetes Center Copenhagen, University of California San Francisco, Stanford University, Medtronic Diabetes, and Science Consulting in Diabetes. The webinar's seven speakers covered (1) advancements in insulin pump therapy, (2) efficacy of longer wear infusion sets, and (3) innovations to reduce plastics and insulin waste.

Withdrawn as duplicate: Corrigendum to: Continuous Glucose Monitoring: An Endocrine Society Clinical Practice Guideline

This corrigendum has been withdrawn due to a publisher error that caused it to be duplicated. The definitive version of this corrigendum is published under DOI https://doi.org/10.1210/clinem/dgab250.

Inequity in Adoption of Advanced Diabetes Technologies Among Medicare Fee-for-service Beneficiaries

CONTEXT

Health inequity is often associated with race-ethnicity.

OBJECTIVE

To determine the prevalence of insulin pump therapy and continuous glucose monitoring (CGM) among Medicare beneficiaries with type 1 diabetes (T1D) by race-ethnicity, and to compare diabetes-related technology users with nonusers.

DESIGN

The prevalence of technology use (pump, CGM) was determined by race-ethnicity for enrollees in coverage years (CY) 2017-2019 in the Medicare fee-for-service database. Using CY2019 data, technology users were compared with nonusers by race-ethnicity, sex, average age, Medicare eligibility criteria, and visit to an endocrinologist.

SETTING

Community.

PATIENTS OR OTHER PARTICIPANTS

Beneficiaries with T1D and at least 1 inpatient or 2 outpatient claims in a CY.

INTERVENTION(S)

Pump or CGM therapy, visit to an endocrinologist.

MAIN OUTCOME MEASURE(S)

Diabetes-related technology use by race-ethnicity groups.

RESULTS

Between 2017 and 2019, CGM and insulin pump use increased among all groups. Prevalence of insulin pump use was < 5% for Black and Other beneficiaries yet increased from 14% to 18% among White beneficiaries. In CY2019, 57% of White patients used a pump compared with 33.1% of Black and 30.3% of Other patients (P < 0.001). Black patients were more likely than White patients to be eligible because of disability/end-stage renal disease or to be Medicare/Medicaid eligible (both P < 0.001), whether using technology or not. Significant race-ethnicity differences (P < 0.001) existed between technology users and nonusers for all evaluated factors except visiting an endocrinologist.

CONCLUSIONS

Significant race-ethnicity associated differences existed in T1D management. The gap in diabetic technology adoption between Black and White beneficiaries grew between 2017 and 2019.

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.

Safety and Glycemic Outcomes During the MiniMed™ Advanced Hybrid Closed-Loop System Pivotal Trial in Adolescents and Adults with Type 1 Diabetes

Introduction: This trial assessed safety and effectiveness of an advanced hybrid closed-loop (AHCL) system with automated basal (Auto Basal) and automated bolus correction (Auto Correction) in adolescents and adults with type 1 diabetes (T1D). Materials and Methods: This multicenter single-arm study involved an intent-to-treat population of 157 individuals (39 adolescents aged 14-21 years and 118 adults aged ≥22-75 years) with T1D. Study participants used the MiniMed™ AHCL system during a baseline run-in period in which sensor-augmented pump +/- predictive low glucose management or Auto Basal was enabled for ∼14 days. Thereafter, Auto Basal and Auto Correction were enabled for a study phase (∼90 days), with glucose target set to 100 or 120 mg/dL for ∼45 days, followed by the other target for ∼45 days. Study endpoints included safety events and change in mean A1C, time in range (TIR, 70-180 mg/dL) and time below range (TBR, <70 mg/dL). Run-in and study phase values were compared using Wilcoxon signed-rank test or paired t-test. Results: Overall group time spent in closed loop averaged 94.9% ± 5.4% and involved only 1.2 ± 0.8 exits per week. Compared with run-in, AHCL reduced A1C from 7.5% ± 0.8% to 7.0% ± 0.5% (<0.001, Wilcoxon signed-rank test, n = 155), TIR increased from 68.8% ± 10.5% to 74.5% ± 6.9% (<0.001, Wilcoxon signed-rank test), and TBR reduced from 3.3% ± 2.9% to 2.3% ± 1.7% (<0.001, Wilcoxon signed-rank test). Similar benefits to glycemia were observed for each age group and were more pronounced for the nighttime (12 AM-6 AM). The 100 mg/dL target increased TIR to 75.4% (n = 155), which was further optimized at a lower active insulin time (AIT) setting (i.e., 2 h), without increasing TBR. There were no severe hypoglycemic or diabetic ketoacidosis events during the study phase. Conclusions: These findings show that the MiniMed AHCL system is safe and allows for achievement of recommended glycemic targets in adolescents and adults with T1D. Adjustments in target and AIT settings may further optimize glycemia and improve user experience. Clinical Trial Registration number: NCT03959423.

Improved technology satisfaction and sleep quality with Medtronic MiniMed® Advanced Hybrid Closed-Loop delivery compared to predictive low glucose suspend in people with Type 1 Diabetes in a randomized crossover trial

BACKGROUND

Automated insulin delivery aims to lower treatment burden and improve quality of life as well as glycemic outcomes.

METHODS

We present sub-study data from a dual-center, randomized, open-label, two-sequence crossover study in automated insulin delivery naïve users, comparing Medtronic MiniMed® Advanced Hybrid Closed-Loop (AHCL) to Sensor Augmented Pump therapy with Predictive Low Glucose Management (SAP + PLGM). At the end of each 4-week intervention, impacts on quality of life, sleep and treatment satisfaction were compared using seven age-appropriate validated questionnaires given to patients or caregivers.

RESULTS

59/60 people completed the study (mean age 23.3 ± 14.4yrs). Statistically significant differences favoring AHCL were demonstrated in several scales (data shown as mean ± SE). In adults (≥ 18yrs), technology satisfaction favored AHCL over PLGM as shown by a higher score in the DTSQs during AHCL (n = 28) vs SAP + PLGM (n = 29) (30.9 ± 0.7 vs 27.9 ± 0.7, p = 0.004) and DTSQc AHCL (n = 29) vs SAP + PLGM (n = 30) (11.7 ± 0.9 vs 9.2 ± 0.8, p = 0.032). Adolescents (aged 13-17yrs) also showed a higher DTSQc score during AHCL (n = 16) versus SAP + PLGM (n = 15) (14.8 ± 0.7 vs 12.1 ± 0.8, p = 0.024). The DTQ "change" score (n = 59) favored AHCL over SAP + PLGM (3.5 ± 0.0 vs 3.3 ± 0.0, p < 0.001). PSQI was completed in those > 16 years (n = 36) and demonstrated improved sleep quality during AHCL vs SAP + PLGM (4.8 ± 0.3 vs 5.7 ± 0.3, p = 0.048) with a total score > 5 indicating poor quality sleep.

CONCLUSION

These data suggest that AHCL compared to SAP + PLGM mode has the potential to increase treatment satisfaction and improve subjective sleep quality in adolescents and adults with T1D.

The Rising Cost of Insulin for Pump Users: How Policy Drives Prices

The price of insulin has increased dramatically over the past two decades. Medicare reimbursement for insulin is based on the route of administration via syringe (Part D) or via pump (Part B). Recently, the Centers for Medicare & Medicaid Services (CMS) announced a voluntary model for Part D enhanced plans that lower out-of-pocket costs to a co-pay of ≤$35/month. Meanwhile, the 21st Century Cures Act and manufacturer price increases raised the cost of insulin for pump users by 304% in less than 2 years. Because insulin is a life-saving necessity and unlike other Part B infused drugs, we call on CMS to determine drug reimbursement on a drug-by-drug basis and to develop a payment model that lowers out-of-pocket costs for patients using insulin delivered via pumps.

Evaluating Perioperative Glycemic Control of Non-cardiac Surgical Patients with Diabetes

INTRODUCTION

Hyperglycemia during the perioperative period has generally been accepted as a contributor of poor outcomes in patients with diabetes mellitus undergoing surgery. Although an optimal glycemic range has not been clearly established in the literature, a consensus among national medical organizations generally recommends serum glucose levels to be maintained less than 180 mg/dL during the perioperative period.

MATERIALS AND METHODS

The primary purpose of this evidence-based project was to identify the range of blood glucose values obtained from adult patients with diabetes mellitus undergoing non-cardiac surgery at a large military medical facility. The secondary purpose of this project was to assess the need for change in future practice. A retrospective review of the electronic medical record was conducted to identify adult surgical patients with diabetes scheduled for non-cardiac surgery. Preoperative and postoperative blood glucose values were obtained from the electronic medical record. The frequency of blood glucose values maintained within the recommended range of 140-180 mg/dL was recorded. Additional demographic data were collected to include age, height, weight, body mass index, length of surgery, and insulin/oral glycemic medications.

RESULTS

Of the 9,449 surgeries performed between January 1, 2013, and December 31, 2013, there were 762 (8%) adult non-cardiac surgical patients identified with either a diagnosis of diabetes or a blood glucose value reported during the perioperative period. The recommended blood glucose range of 140-180 mg/dL was achieved in 31.3% (179 of 572) of patients before surgery and 28.6% (71 of 248) after surgery. A blood glucose value was not recorded before or after surgery in 24.9% (190 of 762) of patients identified as having pre-diabetes or diabetes.

CONCLUSION

Diabetes is a frequent finding in surgical patients. Monitoring blood glucose values during the perioperative period may allow for early treatment and prevent complications related to poor glycemic control. The results of this project revealed 2 potential areas of improvement in the care of non-cardiac surgical patients with diabetes: (1) improving compliance with obtaining blood glucose values before and after surgery and (2) reducing the incidence of postoperative hyperglycemia (>180 mg/dL) which potentially could prevent avoidable complications related to poor glycemic control.

Advances in Insulin Pump Infusion Sets Symposium Report

Continuous subcutaneous insulin infusion (CSII) is becoming increasingly used for achieving target glycemic control as well as providing flexibility in lifestyle. In a widely used version of CSII, the insulin pump itself is attached to one end of an insulin infusion set (IIS), which delivers insulin via a thin flexible plastic tube to the patient's body via a cannula or needle that is inserted under the skin at the other end of the IIS. Despite the increased use of CSII by patients with diabetes, there have been few recent advances in IIS technology, especially when compared to the many recent advances made in insulin pump technology and in insulin pharmacokinetics. To discuss recent developments in, and future plans for IIS development, Diabetes Technology Society virtually hosted the Advances in Insulin Pump Infusion Sets Symposium on December 1, 2020. This symposium featured experts in the field of IISs, including representatives from Medtronic and ConvaTec (which are two manufacturers that are currently developing IISs), Stanford University, Steno Diabetes Center Copenhagen, and Science Consulting in Diabetes. The webinar's six speakers covered (1) patient burden, (2) extended wear technology, and (3) future directions in IIS development.

Improved Glycemic Outcomes With Medtronic MiniMed Advanced Hybrid Closed-Loop Delivery: Results From a Randomized Crossover Trial Comparing Automated Insulin Delivery With Predictive Low Glucose Suspend in People With Type 1 Diabetes

OBJECTIVE

To study the MiniMed Advanced Hybrid Closed-Loop (AHCL) system, which includes an algorithm with individualized basal target set points, automated correction bolus function, and improved Auto Mode stability.

RESEARCH DESIGN AND METHODS

This dual-center, randomized, open-label, two-sequence crossover study in automated-insulin-delivery-naive participants with type 1 diabetes (aged 7-80 years) compared AHCL to sensor-augmented pump therapy with predictive low glucose management (SAP + PLGM). Each study phase was 4 weeks, preceded by a 2- to 4-week run-in and separated by a 2-week washout.

RESULTS

The study was completed by 59 of 60 people (mean age 23.3 ± 14.4 years). Time in target range (TIR) 3.9-10 mmol/L (70-180 mg/dL) favored AHCL over SAP + PLGM (70.4 ± 8.1% vs. 57.9 ± 11.7%) by 12.5 ± 8.5% (P < 0.001), with greater improvement overnight (18.8 ± 12.9%, P < 0.001). All age-groups (children [7-13 years], adolescents [14-21 years], and adults [>22 years]) demonstrated improvement, with adolescents showing the largest improvement (14.4 ± 8.4%). Mean sensor glucose (SG) at run-in was 9.3 ± 0.9 mmol/L (167 ± 16.2 mg/dL) and improved with AHCL (8.5 ± 0.7 mmol/L [153 ± 12.6 mg/dL], P < 0.001), but deteriorated during PLGM (9.5 ± 1.1 mmol/L [17 ± 19.8 mg/dL], P < 0.001). TIR was optimal when the algorithm set point was 5.6 mmol/L (100 mg/dL) compared with 6.7 mmol/L (120 mg/dL), 72.0 ± 7.9% vs. 64.6 ± 6.9%, respectively, with no additional hypoglycemia. Auto Mode was active 96.4 ± 4.0% of the time. The percentage of hypoglycemia at baseline (<3.9 mmol/L [70 mg/dL] and ≤3.0 mmol/L [54 mg/dL]) was 3.1 ± 2.1% and 0.5 ± 0.6%, respectively. During AHCL, the percentage time at <3.9 mmol/L (70 mg/dL) improved to 2.1 ± 1.4% (P = 0.034) and was statistically but not clinically reduced for ≤3.0 mmol/L (54 mg/dL) (0.5 ± 0.5%; P = 0.025). There was one episode of mild diabetic ketoacidosis attributed to an infusion set failure in combination with an intercurrent illness, which occurred during the SAP + PLGM arm.

CONCLUSIONS

AHCL with automated correction bolus demonstrated significant improvement in glucose control compared with SAP + PLGM. A lower algorithm SG set point during AHCL resulted in greater TIR, with no increase in hypoglycemia.

The Effectiveness of Virtual Training on the MiniMed™ 670G System in People with Type 1 Diabetes During the COVID-19 Pandemic

Background: The coronavirus disease 2019 (COVID-19) pandemic has challenged the ability to do face-to-face training on advanced diabetes management technologies. In the United States, Medtronic Diabetes shifted from occasional to 100% virtual training on all diabetes devices in mid-March 2020. We studied the outcomes of virtual training on the MiniMed™ 670 G hybrid closed-loop system in type 1 diabetes. Methods: From March 20, 2020, to April 22, 2020 (intra-COVID-19), virtual training on the MiniMed 670 G system was completed using Zoom with satisfaction captured through online post-training surveys. Training efficiency was measuring by the days between the date of product shipment and the date of the first and final trainings. Patient satisfaction with training on the MiniMed 670 G was determined by Net Promotor Score^® (NPS^®). Uploads from CareLink™ Personal and CareLink Professional and calls to the Medtronic 24-h technical support team requesting educational/software assistance and/or help with health care provider telehealth visits were recorded. Continuous glucose monitoring (CGM) results were measured using the CareLink Personal database. All results except for the Zoom satisfaction survey were compared with data from January 20, 2020, to February 22, 2020, (Pre-COVID-19) when training was performed in-person. Results: The CGM metrics were comparable between pre- and intra-COVID-19 training. The Zoom video conferencing application had 98% satisfaction. The NPS rose from 78 to 84. The time between the pump shipment and the first and last (automode) training was significantly reduced from 14 ± 7 days to 11 ± 5 days (P < 0.001) and from 19 ± 7 days to 15 ± 15 days (P < 0.01), respectively. There was a decrease in the calls for educational assistance to the technical support team but an increase in requests for login and software installation support. Conclusions: Virtual training of individuals with diabetes on the MiniMed 670 G system resulted in high satisfaction and short-term glycemic results comparable with in-person training.

The dawn phenomenon across the glycemic continuum: Implications for defining dysglycemia

AIMS

To investigate the frequency of dawn phenomenon (DP) and its relationship with time in range (TIR) and glycemic variability (GV) using continuous glucose monitoring (CGM).

METHODS

781 subjects of a multicenter CGM study in China were included: those with normal glucose tolerance (NGT n = 360); impaired glucose regulation (IGR n = 173); newly diagnosed type 2 diabetes mellitus (T2D n = 248). Analysis of the magnitude of DP (ΔG) was conducted with the primary definition of 1.11 mmol/L and a secondary definition of 0.56 mmol/L.

RESULTS

The frequency of DP was 8.9%, 30.1% and 52.4% in NGT, IGR and T2D group, respectively, using the primary definition. In all three groups, TIR was lower (all P < 0.05), coefficient of variation (CV) was higher in DP subgroup (all P < 0.05). In DP subgroup of T2D, TIR was 7.0% (1.68 h) lower and CV was 3.0% higher, and HbA_1c was 0.6% (7 mmol/mol) higher using the primary definition (all P < 0.05).

CONCLUSIONS

DP was present in a high percent of subjects with NGT and IGR. In newly diagnosed T2D group, the presence of DP was associated with poorer overall glycemic control.

TIR generated by continuous glucose monitoring is associated with peripheral nerve function in type 2 diabetes

AIMS

Continuous glucose monitoring (CGM)-derived time-in-range (TIR) of 3.9-10 mmol/L is associated with diabetic retinopathy in type 2 diabetes (T2DM), but its relationship to peripheral nerve function has not been previously investigated. To explore the association between the TIR and nerve conduction study parameters in patients with T2DM, we performed a cross-sectional analysis.

METHODS

A total of 740 patients with T2DM were enrolled in this study. All of the participants were divided into tertiles according to the TIR (TIR low: ≤53%; TIR medium: 54-76%; TIR high: ≥77%). Composite Z-scores of nerve conduction velocity (CV), latency, and amplitude were calculated. The linear correlation between the TIR and composite nerve function Z-score was evaluated and risk assessment was analysed using binary logistic regression.

RESULTS

The composite Z-score of the CV and amplitude increased with higher TIR and the composite Z-score of latency significantly decreased as the TIR tertiles increased (all P trend < 0.05). After adjusting for age, diabetes duration, height, weight and other confounding factors, higher TIR was associated with a higher composite Z-score of CV (β = 0.230, P < 0.001), amplitude (β = 0.099, P = 0.010), and lower composite Z-score of latency (β = -0.172, P < 0.001). The risk of TIR tertiles and low composite Z-score of CV remained significant even after adjustment of HbA1c (TIR medium: OR = 0.48, P = 0.001; TIR high: OR = 0.41, P < 0.001).

CONCLUSIONS

Higher TIR tertiles were independently associated with better peripheral nerve function. CGM-derived TIR may be a promising approach to screen patients for further assessment of possible diabetic peripheral neuropathy.

The Effect of Acarbose on Glycemic Variability in Patients with Type 2 Diabetes Mellitus Using Premixed Insulin Compared to Metformin (AIM): An Open-Label Randomized Trial

Background: Acarbose (ACA) can effectively reduce the postprandial blood glucose and has similar antidiabetic effects as metformin (MET). To our knowledge, few studies have compared the effect of ACA or MET on glucose fluctuations. In the present study, we explored the effect of ACA or MET combined with premixed insulin (INS) on glycemic control and glycemic variability (GV). Methods: This was an open-label randomized trial that was conducted in type 2 diabetic patients taking premixed insulin. The patients were assigned to 12 weeks of MET (n = 62) or ACA (n = 62) treatment combined with INS. The main outcomes were changes in GV and glycosylated hemoglobin A1c (HbA1c) compared with baseline. Results: Compared with baseline, several GV indices (standard deviation [SD], mean amplitude of glycemic excursions [MAGE]) and blood glucose control indices (mean glucose [MG], time in range [TIR] and HbA1c) were both significantly improved in INS+ACA and INS+MET after 12-week therapy. However, coefficient of variation (CV) was significantly reduced in INS+ACA but not in INS+MET. Moreover, compared with INS+MET, INS+ACA led to a more pronounced percentage change from baseline in CV (26.3% [1.7%-44.6%] vs. 11.9% [-7.0% to 29.9%], P = 0.022), MAGE (40.5% [20.1%-60.5%] vs. 25.2% [-2.1% to 43.4%], P = 0.007) and SD (38.6% [25.2%-57.9%] vs. 30.1% [10.8%-46.5%], P = 0.041). Conclusion: Both MET and ACE combined with INS effectively reduced blood glucose. Compared with MET, ACA combined with INS reduced GV.

Time in Range Is Associated with Carotid Intima-Media Thickness in Type 2 Diabetes

Background: Time in range (TIR) is an emerging metric of glycemic control and is reported to be associated with microvascular complications of diabetes. We sought to investigate the association of TIR obtained from continuous glucose monitoring (CGM) with carotid intima-media thickness (CIMT) as a surrogate marker of cardiovascular disease (CVD). Methods: Data from 2215 patients with type 2 diabetes were cross-sectionally analyzed. TIR of 3.9-10.0 mmol/L was evaluated with CGM. CIMT was measured using high-resolution B-mode ultrasonography and abnormal CIMT was defined as a mean CIMT ≥1.0 mm. Logistic regression models were used to examine the independent association of TIR with CIMT. Results: Compared with patients with normal CIMT, those with abnormal CIMT had significantly lower TIR (P < 0.001). The prevalence of abnormal CIMT progressively decreased across the categories of increasing TIR (P for trend <0.001). In a fully adjusted model controlling for traditional risk factor of CVD, each 10% increase in TIR was associated with 6.4% lower risk of abnormal CIMT. Stratifying the data by sex revealed that TIR was significantly associated with CIMT in males but not in females. In a subset of patients (n = 612) with complete data on diabetic retinopathy and albuminuria, we found that the relationship between TIR and CIMT remained to be significant, regardless of the status of microvascular complications. Conclusions: TIR is associated with CIMT in a large sample of patients with type 2 diabetes, suggesting a link between TIR and macrovascular disease.

Role of Composite Glycemic Indices: A Comparison of the Comprehensive Glucose Pentagon Across Diabetes Types and HbA1c Levels

Background: Complex changes of glycemia that occur in diabetes are not fully captured by any single measure. The Comprehensive Glucose Pentagon (CGP) measures multiple aspects of glycemia to generate the prognostic glycemic risk (PGR), which constitutes the relative risk of hypoglycemia combined with long-term complications. We compare the components of CGP and PGR across type 1 and type 2 diabetes. Methods: Participants: n = 60 type 1 and n = 100 type 2 who underwent continuous glucose monitoring (CGM). Mean glucose, coefficient of variation (%CV), intensity of hypoglycemia (INT_hypo), intensity of hyperglycemia (INT_hyper), time out-of-range (TOR <3.9 and >10 mmol/L), and PGR were calculated. PGR (median, interquartile ranges [IQR]) for diabetes types, and HbA1c classes were compared. Results: While HbA1c was lower in type 1 (type 1 vs. type 2: 8.0 ± 1.6 vs. 8.6 ± 1.7, P = 0.02), CGM-derived mean glucoses were similar across both groups (P > 0.05). TOR, %CV, INT_hypo, and INT_hyper were all higher in type 1 [type 1 vs. type 2: 665 (500, 863) vs. 535 (284, 823) min/day; 39% (33, 46) vs. 29% (24, 34); 905 (205, 2951) vs. 18 (0, 349) mg/dL × min²; 42,906 (23,482, 82,120) vs. 30,166 (10,276, 57,183) mg/dL × min², respectively, all P < 0.05]. Across each HbA1c class, the PGR remained consistently and significantly higher in type 1. While mean glucose remained the same across HbA1c classes, %CV, TOR, INT_hyper, and INT_hypo were significantly higher for type 1. Even within the same HbA1c class, the variation (IQR) of each parameter in type 1 was wider. The PGR increased across diabetes groups; type 2 on orals versus type 2 on insulin versus type 1 (PGR: 1.6 vs. 2.2 vs. 2.9, respectively, P < 0.05). Conclusion: Composite indices such as the CGP capture significant differences in glycemia independent of HbA1c and mean glucose. The use of such indices must be explored in both the clinical and research settings.

The Relationship of Hemoglobin A1C to Time-in-Range in Patients with Diabetes

BACKGROUND

There has been recent recognition of the limitations of hemoglobin A1C (HbA1C) in describing both short- and long-term glycemic control. Continuous glucose monitoring (CGM) provides robust data about short-term glycemic control and provides metrics such as percent time-in-range (%TIR) that are now routinely reported to describe the change in glycemic control after an intervention in a clinical study or a change in therapy in a patient's care. Recent studies have shown that %TIR may have similar associations with diabetes microvascular complications as does HbA1C. The relationship of %TIR to the long-standing metric of overall glycemic control has not been clearly defined to date.

METHODS

Articles that report paired HbA1C and %TIR metrics (n = 1137) or HbA1C and frequent self-monitoring of blood glucose (SMBG) (n = 1440) across a wide range of HbA1Cs, technologies, and subject demographics were reviewed to determine the correlation of these metrics.

RESULTS

Selected paired HbA1C and %TIR data from 18 articles were evaluated by linear regression analysis and Pearson's correlation coefficient. There was an excellent correlation between the two (R = -0.84; R² = 0.71). This relationship did not change after excluding one study that used SMBG or six studies with ≤7 days of CGM. For every absolute 10% change in %TIR, there was a 0.8% (9 mmol/mol) change in HbA1C.

CONCLUSIONS

There is a good correlation between HbA1C and %TIR that may permit the transition to %TIR as the preferred metric for determining the outcome of clinical studies, predicting of the risk of diabetes complications, and assessing of an individual patient's glycemic control.

Going beyond HbA1c to understand the benefits of advanced diabetes therapies

The gold standard for monitoring overall glycemia is HbA1c. However, HbA1c has several important limitations, giving more weight to the prior 2 to 3 months rather than short-term glycemic control. In addition, the level of the HbA1c does not reflect the important interpersonal differences in its relationship with mean glucose, and HbA1c is affected by many common clinical conditions (anemia, uremia) that can interfere with the accuracy of its measurement in the laboratory. The development and refinement of continuous glucose monitoring (CGM), a glucose- and patient-centric technology, over the past two decades have permitted the creation of new single and composite metrics, such as the percentage of time in range and the glucose pentagon, respectively, which provide clinically relevant insights into short-term glycemic control. In addition, CGM creates new outcome metrics for clinical management and investigational studies (percentage of time in hypoglycemia, percentage of time in target range) that can accurately and meaningfully report the effects of an intervention, whether that is a drug, a device, or a psychosocial program, and CGM provides the key input to drive algorithm-based insulin delivery. Finally, CGM linked with artificial intelligence permits real-time feedback to patients about modifiable patterns of glycemic excursions.

Association of Time in Range, as Assessed by Continuous Glucose Monitoring, With Diabetic Retinopathy in Type 2 Diabetes

OBJECTIVE

Continuous glucose monitoring (CGM) has provided new measures of glycemic control that link to diabetes complications. This study investigated the association between the time in range (TIR) assessed by CGM and diabetic retinopathy (DR).

RESEARCH DESIGN AND METHODS

A total of 3,262 patients with type 2 diabetes were recruited. TIR was defined as the percentage of time spent within the glucose range of 3.9-10.0 mmol/L during a 24-h period. Measures of glycemic variability (GV) were assessed as well. DR was determined by using fundus photography and graded as 1) non-DR; 2) mild nonproliferative DR (NPDR); 3) moderate NPDR; or 4) vision-threatening DR (VTDR).

RESULTS

The overall prevalence of DR was 23.9% (mild NPDR 10.9%, moderate NPDR 6.1%, VTDR 6.9%). Patients with more advanced DR had significantly less TIR and higher measures of GV (all P for trend <0.01). The prevalence of DR on the basis of severity decreased with ascending TIR quartiles (all P for trend <0.001), and the severity of DR was inversely correlated with TIR quartiles (r = -0.147; P < 0.001). Multinomial logistic regression revealed significant associations between TIR and all stages of DR (mild NPDR, P = 0.018; moderate NPDR, P = 0.014; VTDR, P = 0.019) after controlling for age, sex, BMI, diabetes duration, blood pressure, lipid profile, and HbA_1c. Further adjustment of GV metrics partially attenuated these associations, although the link between TIR and the presence of any DR remained significant.

CONCLUSIONS

TIR assessed by CGM is associated with DR in type 2 diabetes.

The Development of New Composite Metrics for the Comprehensive Analytic and Visual Assessment of Hypoglycemia Using the Hypo-Triad

BACKGROUND

Quantifying hypoglycemia has traditionally been limited to using the frequency of hypoglycemic events during a given time interval using data from blood glucose (BG) testing. However, continuous glucose monitoring (CGM) captures three parameters-a Hypo-Triad-unavailable with BG monitoring that can be used to better characterize hypoglycemia: area under the curve (AUC), time (duration of hypoglycemia), and frequency of daily episodes below a specified threshold.

METHODS

We developed two new analytic metrics to enhance the traditional Hypo-Triad of CGM-derived data to more effectively capture the intensity of hypoglycemia (IntHypo) and overall hypoglycemic environment called the "hypoglycemia risk volume" (HypoRV). We reanalyzed the CGM data from the ASPIRE In-Home study, a randomized, controlled trial of a sensor-integrated pump system with a low glucose threshold suspend feature (SIP+TS), using these new metrics and compared them to standard metrics of hypoglycemia.

RESULTS

IntHypo and HypoRV provide additional insights into the benefit of a SIP+TS system on glycemic exposure when compared to the standard reporting methods. In addition, the visual display of these parameters provides a unique and intuitive way to understand the impact of a diabetes intervention on a cohort of subjects as well as on individual patients.

CONCLUSION

The IntHypo and HypoRV are new and enhanced ways of analyzing CGM-derived data in diabetes intervention studies which could lead to new insights in diabetes management. They require validation using existing, ongoing, or planned studies to determine whether they are superior to existing metrics.

The Comprehensive Glucose Pentagon: A Glucose-Centric Composite Metric for Assessing Glycemic Control in Persons With Diabetes

BACKGROUND

Composite metrics have the potential to provide more complete and clinically useful information about glycemic control than traditional individual metrics such as hemoglobin A1C, %/time/area under curve of hypoglycemia and hyperglycemia.

METHODS

Using five key metrics that are derived from continuous glucose monitoring, we developed a new, multicomponent composite metric, the Comprehensive Glucose Pentagon (CGP) that demonstrates glycemic control both numerically and visually. Two of its axes are composite metrics-the intensity of hypoglycemia and intensity of hyperglycemia. This approach eliminates the use of the surrogate marker, hemoglobin A1C (A1C), and replaces it with glucose-centric metrics.

RESULTS

We reanalyzed the data from two randomized control trials, the STAR 3 and ASPIRE In-Home studies using the CGP. It provided new insights into the effect of sensor-augmented pumping (SAP) in the STAR 3 trial and sensor-integrated pumping with low-glucose threshold suspend (SIP+TS) in the ASPIRE In-Home trial.

CONCLUSIONS

The CGP has the potential to enable health care providers, investigators and patients to better understand the components of glycemic control and the effect of various interventions on the individual elements of that control. This can be done on a daily, weekly, or monthly basis. It also allows direct comparison of the effects on different interventions among clinical trials which is not possible using A1C alone. This new composite metric approach requires validation to determine if it provides a better predictor of long-term outcomes than A1C and/or better predictor of severe hypoglycemia than the low blood glucose index (LBGI).

The Cost-Effectiveness of Real-Time Continuous Glucose Monitoring (RT-CGM) in Type 2 Diabetes

BACKGROUND

This analysis models the cost-effectiveness of real-time continuous glucose monitoring (RT-CGM) using evidence from a randomized controlled trial (RCT) that demonstrated RT-CGM reduced A1C, for up to 9 months after using the technology, among patients with type 2 diabetes not on prandial insulin. RT-CGM was offered short-term and intermittently as a self-care tool to inform patients' behavior.

METHOD

The analyses projected lifetime clinical and economic outcomes for RT-CGM versus self-monitoring of blood glucose by fingerstick only. The base-case analysis was consistent with the RCT (RT-CGM for 2 weeks on/1 week off over 3 months). A scenario analysis simulated outcomes of an RT-CGM "refresher" after the active intervention of the RCT. Analyses used the IMS CORE Diabetes Model and were conducted from a US third-party payer perspective, including direct costs obtained from published sources and inflated to 2011 US dollars. Costs and health outcomes were discounted at 3% per annum.

RESULTS

Life expectancy (LE) and quality-adjusted life expectancy (QALE) from RT-CGM were 0.10 and 0.07, with a cost of $653/patient over a lifetime. Incremental LE and QALE from a "refresher" were 0.14 and 0.10, with a cost of $1312/patient over a lifetime, and incremental cost-effectiveness ratios were $9319 and $13 030 per LY and QALY gained.

CONCLUSIONS

RT-CGM, as a self-care tool, is a cost-effective disease management option in the US for people with type 2 diabetes not on prandial insulin. Repeated use of RT-CGM may result in additional cost-effectiveness.

Development of the Diabetes Technology Society Blood Glucose Monitor System Surveillance Protocol

BACKGROUND

Inaccurate blood glucsoe monitoring systems (BGMSs) can lead to adverse health effects. The Diabetes Technology Society (DTS) Surveillance Program for cleared BGMSs is intended to protect people with diabetes from inaccurate, unreliable BGMS products that are currently on the market in the United States. The Surveillance Program will provide an independent assessment of the analytical performance of cleared BGMSs.

METHODS

The DTS BGMS Surveillance Program Steering Committee included experts in glucose monitoring, surveillance testing, and regulatory science. Over one year, the committee engaged in meetings and teleconferences aiming to describe how to conduct BGMS surveillance studies in a scientifically sound manner that is in compliance with good clinical practice and all relevant regulations.

RESULTS

A clinical surveillance protocol was created that contains performance targets and analytical accuracy-testing studies with marketed BGMS products conducted by qualified clinical and laboratory sites. This protocol entitled "Protocol for the Diabetes Technology Society Blood Glucose Monitor System Surveillance Program" is attached as supplementary material.

CONCLUSION

This program is needed because currently once a BGMS product has been cleared for use by the FDA, no systematic postmarket Surveillance Program exists that can monitor analytical performance and detect potential problems. This protocol will allow identification of inaccurate and unreliable BGMSs currently available on the US market. The DTS Surveillance Program will provide BGMS manufacturers a benchmark to understand the postmarket analytical performance of their products. Furthermore, patients, health care professionals, payers, and regulatory agencies will be able to use the results of the study to make informed decisions to, respectively, select, prescribe, finance, and regulate BGMSs on the market.

Impact of CMS Competitive Bidding Program on Medicare Beneficiary Safety and Access to Diabetes Testing Supplies: A Retrospective, Longitudinal Analysis

OBJECTIVE

In 2011, the Centers for Medicare & Medicaid Services (CMS) launched the Competitive Bidding Program (CBP) in nine markets for diabetes supplies. The intent was to lower costs to consumers. Medicare claims data (2009-2012) were used to confirm the CMS report (2012) that there were no disruptions in acquisition caused by CBP and no changes in health outcomes.

RESEARCH DESIGN AND METHODS

The study population consisted of insulin users: 43,939 beneficiaries in the nine test markets (TEST) and 485,688 beneficiaries in the nontest markets (NONTEST). TEST and NONTEST were subdivided: those with full self-monitoring of blood glucose (SMBG) supply acquisition (full SMBG) according to prescription and those with partial/no acquisition (partial/no SMBG). Propensity score-matched analysis was performed to reduce selection bias. Outcomes were impact of partial/no SMBG acquisition on mortality, inpatient admissions, and inpatient costs.

RESULTS

Survival was negatively associated with partial/no SMBG acquisition in both cohorts (P < 0.0001). Coterminous with CBP (2010-2011), there was a 23.0% (P < 0.0001) increase in partial/no SMBG acquisition in TEST vs. 1.7% (P = 0.0002) in NONTEST. Propensity score-matched analysis showed beneficiary migration from full to partial/no SMBG acquisition in 2011 (1,163 TEST vs. 605 NONTEST) was associated with more deaths within the TEST cohort (102 vs. 60), with higher inpatient hospital admissions and associated costs.

CONCLUSIONS

SMBG supply acquisition was disrupted in the TEST population, leading to increased migration to partial/no SMBG acquisition with associated increases in mortality, inpatient admissions, and costs. Based on our findings, more effective monitoring protocols are needed to protect beneficiary safety.

The benefits, limitations, and cost-effectiveness of advanced technologies in the management of patients with diabetes mellitus

Hypoglycemia mitigation is critical for appropriately managing patients with diabetes. Advanced technologies are becoming more prevalent in diabetes management, but their benefits have been primarily judged on the basis of hemoglobin A1c. A critical appraisal of the effectiveness and limitations of advanced technologies in reducing both A1c and hypoglycemia rates has not been previously performed. The cost of hypoglycemia was estimated using literature rates of hypoglycemia events resulting in hospitalizations. A literature search was conducted on the effect on A1c and hypoglycemia of advanced technologies. The cost-effectiveness of continuous subcutaneous insulin infusion (CSII) and real-time continuous glucose monitors (RT-CGM) was reviewed. Severe hypoglycemia in insulin-using patients with diabetes costs $4.9-$12.7 billion. CSII reduces A1c in some but not all studies. CSII improves hypoglycemia in patients with high baseline rates. Bolus calculators improve A1c and improve the fear of hypoglycemia but not hypoglycemia rates. RT-CGM alone and when combined with CSII improve A1c with a neutral effect on hypoglycemia rates. Low-glucose threshold suspend systems reduce hypoglycemia with a neutral effect on A1c, and low-glucose predictive suspend systems reduce hypoglycemia with a small increase in plasma glucose levels. In short-term studies, artificial pancreas systems reduce both hypoglycemia rates and plasma glucose levels. CSII and RT-CGM are cost-effective technologies, but their wide adoption is limited by cost, psychosocial, and educational factors. Most currently available technologies improve A1c with a neutral or improved rate of hypoglycemia. Advanced technologies appear to be cost-effective in diabetes management, especially when including the underlying cost of hypoglycemia.

Escaping the Hemoglobin A1c-Centric World in Evaluating Diabetes Mellitus Interventions

Any intervention in patients with diabetes must consider its effect on both the incidence of hypoglycemia and hemoglobin A1c. Yet, there is no single metric that expresses these key factors simultaneously. Such a composite metric would permit clinicians, regulators, manufacturers, payers, and researchers to more easily evaluate the merits of an intervention as well as enable the comparison of qualitatively different interventions. This article proposes a composite metric, the hypoglycemia-A1c score (HAS), as the basis for a more comprehensive approach for the stakeholders in diabetes treatment to better understand how an intervention affects diabetes management. The article also demonstrates how additional parameters such as effects on weight, quality of life, and costs could be included in such a scoring system.

The clinical endocrinology workforce: current status and future projections of supply and demand

CONTEXT

Many changes in health care delivery, health legislation, and the physician workforce that affect the supply and demand for endocrinology services have occurred since the first published workforce study of adult endocrinologists in 2003.

OBJECTIVE

The objective of the study was to assess the current adult endocrinology workforce data and provide the first analysis of the pediatric endocrinology workforce and to project the supply of and demand for endocrinologists through 2025.

DESIGN

A workforce model was developed from an analysis of proprietary and publicly available databases, consultation with a technical expert panel, and the results of an online survey of board-certified endocrinologists.

PARTICIPANTS

The Endocrine Society commissioned The Lewin Group to estimate current supply and to project gaps between supply and demand for endocrinologists. A technical expert panel of senior endocrinologists provided context, clinical information, and direction.

MAIN OUTCOME MEASURES

The following were measured: 1) the current adult and pediatric endocrinology workforce and the supply of and demand for endocrinologists through 2025 and 2) the number of additional entrants into the endocrinology work pool that would be required to close the gap between supply and demand.

RESULTS

Currently there is a shortage of approximately 1500 adult and 100 pediatric full-time equivalent endocrinologists. The gap for adult endocrinologists will expand to 2700 without an increase in the number of fellows trained. An increase in the prevalence of diabetes mellitus further expands the demand for adult endocrinologists. The gap can be closed in 5 and 10 years by increasing the number of fellowship positions by 14.4% and 5.5% per year, respectively. The gap between supply and demand for pediatric endocrinologists will close by 2016, and thereafter an excess supply over demand will develop at the current rate of new entrants into the work force.

CONCLUSIONS

There are insufficient adult endocrinologists to satisfy current and future demand. A number of proactive strategies need to be instituted to mitigate this gap.