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The increasing prevalence of diabetes mellitus has been accompanied by a rapid expansion in wearable continuous glucose monitoring (CGM) devices and insulin pumps. Systems combining these components in a "closed loop," where interstitial glucose measurement guides automated insulin delivery (AID, or closed loop) based on sophisticated algorithms, are increasingly common. While these devices' efficacy in achieving near-normoglycemia is contributing to increasing usage among patients with diabetes, the management of these patients in operative and procedural environments remains understudied with limited published guidance available, particularly regarding AID systems. With their growing prevalence, practical management advice is needed for their utilization, or for the rational temporary substitution of alternative diabetes monitoring and treatments, during surgical care. CGM devices monitor interstitial glucose in real time; however, there are potential limitations to use and accuracy in the perioperative period, and, at the present time, their use should not replace regular point-of-care glucose monitoring. Avoiding perioperative removal of CGMs when possible is important, as removal of these prescribed devices can result in prolonged interruptions in CGM-informed treatments during and after procedures, particularly AID system use. Standalone insulin pumps provide continuous subcutaneous insulin delivery without automated adjustments for glucose concentrations and can be continued during some procedures. The safe intraoperative use of AID devices in their hybrid closed-loop mode (AID mode) requires the CGM component of the system to continue to communicate valid blood glucose data, and thus introduces the additional need to ensure this portion of the system is functioning appropriately to enable intraprocedural use. AID devices revert to non-AID insulin therapy modes when paired CGMs are disconnected or when the closed-loop mode is intentionally disabled. For patients using insulin pumps, we describe procedural factors that may compromise CGM, insulin pump, and AID use, necessitating a proactive transition to an alternative insulin regimen. Procedure duration and invasiveness is an important factor as longer procedures increase the risk of stress hyperglycemia, tissue malperfusion, and device malfunction. Whether insulin pumps should be continued through procedures, or substituted by alternative insulin delivery methods, is a complex decision that requires all parties to understand potential risks and contingency plans relating to patient and procedural factors. Currently available CGMs and insulin pumps are reviewed, and practical recommendations for safe glycemic management during the phases of perioperative care are provided., Competing Interests: Conflicts of Interest: See Disclosures at the end of the article., (Copyright © 2024 International Anesthesia Research Society.)

Objective: To evaluate whether continuous glucose monitoring (CGM) could assist providers in intensifying glycemic management in hospitalized patients with type 2 diabetes., Research Design and Methods: At six academic hospitals, adults with type 2 diabetes hospitalized in a non-intensive care setting were randomly assigned to either standard therapy with glucose target 140-180 mg/dL (standard group) or intensive therapy with glucose target 90-130 mg/dL guided by CGM (intensive group). The primary outcome was mean glucose measured with CGM (blinded in standard group), and the key secondary outcome was CGM glucose <54 mg/dL., Results: For the 110 participants included in the primary analysis, mean ± SD age was 61 ± 12 years and mean HbA1c was 8.9 ± 2.3% (73.8 ± 1.6 mmol/mol). During the study, CGM-measured mean glucose was 170 mg/dL for the intensive group (n = 60) vs. 175 mg/dL for the standard group (n = 50; risk-adjusted difference -7 mg/dL, 95% CI -19 to 5; P = 0.25). Only 7% of the intensive group achieved the mean glucose target range of 90-130 mg/dL. CGM readings <54 mg/dL were infrequent (0.2% for intensive and 0.4% for standard; adjusted treatment group difference -0.1%, 95% CI -0.6 to 0.3). One severe hypoglycemia event occurred in the standard group., Conclusions: The study's glucose management approach using CGM did not improve glucose levels compared with standard glucose management in the non-intensive care unit hospital setting. A glucose target of 90-130 mg/dL may not be realistic in the current environment of insulin management in the hospital., (© 2024 by the American Diabetes Association.)

Objective: To examine the efficacy and safety of the tubeless Omnipod 5 automated insulin delivery (AID) system compared with pump therapy with a continuous glucose monitor (CGM) in adults with type 1 diabetes with suboptimal glycemic outcomes., Research Design and Methods: In this 13-week multicenter, parallel-group, randomized controlled trial performed in the U.S. and France, adults aged 18-70 years with type 1 diabetes and HbA1c 7-11% (53-97 mmol/mol) were randomly assigned (2:1) to intervention (tubeless AID) or control (pump therapy with CGM) following a 2-week standard therapy period. The primary outcome was a treatment group comparison of time in range (TIR) (70-180 mg/dL) during the trial period., Results: A total of 194 participants were randomized, with 132 assigned to the intervention and 62 to the control. TIR during the trial was 4.2h/day higher in the intervention compared with the control group (mean difference 17.5% [95% CI 14.0%, 21.1%]; P < 0.0001). The intervention group had a greater reduction in HbA1c from baseline compared with the control group (mean ± SD -1.24 ± 0.75% [-13.6 ± 8.2 mmol/mol] vs. -0.68 ± 0.93% [-7.4 ± 10.2 mmol/mol], respectively; P < 0.0001), accompanied by a significantly lower time <70 mg/dL (1.18 ± 0.86% vs. 1.75 ± 1.68%; P = 0.005) and >180 mg/dL (37.6 ± 11.4% vs. 54.5 ± 15.4%; P < 0.0001). All primary and secondary outcomes were met. No instances of diabetes-related ketoacidosis or severe hypoglycemia occurred in the intervention group., Conclusions: Use of the tubeless AID system led to improved glycemic outcomes compared with pump therapy with CGM among adults with type 1 diabetes, underscoring the clinical benefit of AID and bolstering recommendations to establish AID systems as preferred therapy for this population., (© 2024 by the American Diabetes Association.)

Glucagon-like peptide-1 receptor agonist (GLP-1RA) medications have been shown to be effective in achieving optimal glucose control and reducing all-cause death, cardiovascular death, nonfatal myocardial infarction, hospitalization for heart failure, and end-stage kidney disease in individuals with type 1 (T1D) and type 2 diabetes (T2D). However, use of these medications has been associated with increased hypoglycaemia risk in patients treated with concomitant antihyperglycaemic medications. The risk is particularly high in patients with T1D due to their loss of glucagon counter-regulatory response. This article reviews the effect of GLP-1RA formulations on the development of hypoglycaemia in individuals with T1D and T2D treated with insulin therapy, discusses the benefits of continuous glucose monitoring with GLP-1RA treatment, and presents strategies for safely initiating GLP-1RA therapy in these individuals., (© 2024 John Wiley & Sons Ltd.)

Aim: The real-world benefits of continuous glucose monitoring (CGM) in the broad type 2 diabetes (T2D) population are not well studied. Our study evaluated the impact of CGM use on health care resource utilization over 12 months in adults with T2D., Materials and Methods: This retrospective cohort analysis used Optum's de-identified Market Clarity data of >79 million people to evaluate CGM use in people with T2D who were treated with non-insulin (NIT), basal insulin (BIT) and prandial insulin therapy (PIT). The primary outcomes were changes in all-cause hospitalizations, acute diabetes-related hospitalizations and acute diabetes-related emergency room visits during the 6- and 12-month post-index period following transition from blood glucose monitoring to CGM. A pre-specified subgroup analysis assessed glucose control and medication changes among people with T2D over 1 year., Results: The analysis included 74 679 adults with T2D (NIT; n = 25 269), (BIT; n = 16 264) and (PIT; n = 33 146). Significant reductions in all-cause hospitalizations, acute diabetes-related hospitalizations and acute diabetes-related emergency room visits were observed in the 6-month post-index period that were sustained during the 6-12 month post-index period (NIT, -10.1%, -31.0%, -30.7%; BIT, -13.9%, -47.6%, -28.2%; and PIT, -22.6%, -52.7%, -36.6%, respectively). A subgroup analysis of 6030 people showed mean glycated haemoglobin reductions at approximately 3 months, which were also sustained throughout the post-index period: NIT, -1.1 (0.05)%; BIT, -1.1 (0.06)%; and PIT, -0.9 (0.04)%, p < 0.0001., Conclusions: CGM use in real-life across different therapeutic regimens in adults with T2D was associated with reductions in health care resource utilization with improved glucose control over 1 year., (© 2024 The Author(s). Diabetes, Obesity and Metabolism published by John Wiley & Sons Ltd.)

Background : Connected insulin pens capture data on insulin dosing/timing and can integrate with continuous glucose monitoring (CGM) devices with essential insulin and glucose metrics combined into a single platform. Standardization of connected insulin pen reports is desirable to enhance clinical utility with a single report. Methods : An international expert panel was convened to develop a standardized connected insulin pen report incorporating insulin and glucose metrics into a single report containing clinically useful information. An extensive literature review and identification of examples of current connected insulin pen reports were performed serving as the basis for creation of a draft of a standardized connected insulin pen report. The expert panel participated in three virtual standardization meetings and online surveys. Results : The Ambulatory Glucose Profile (AGP) Report: Connected Insulin Pen brings all clinically relevant CGM-derived glucose and connected insulin pen metrics into a single simplified two-page report. The first page contains the time in ranges bar, summary of key insulin and glucose metrics, the AGP curve, and detailed basal (long-acting) insulin assessment. The second page contains the bolus (mealtime and correction) insulin assessment periods with information on meal timing, insulin-to-carbohydrate ratio, average bolus insulin dose, and number of days with bolus doses recorded. The report's second page contains daily glucose profiles with an overlay of the timing and amount of basal and bolus insulin administered. Conclusion : The AGP Report: Connected Insulin Pen is a standardized clinically useful report that should be considered by companies developing connected pen technology as part of their system reporting/output.

Objective: Since the introduction of continuous glucose monitoring (CGM) technology, developers have rigorously researched the feasibility of creating a noninvasive glucose monitoring device. In a recent pilot study, investigators reported a strong correlation between glucose values obtained from novel noninvasive monitoring device (GWave) values to venous and capillary glucose measurements. Research Design and Methods: We investigated whether the level of accuracy observed in the pilot study could be reproduced in a larger cohort, using a smaller third-generation manufacturable device (Gen III GWave) containing a standardized sensor chip that can be mass produced for commercial use. The evaluation assessed concordance with capillary blood glucose, reproducibility between two Gen III devices, and accuracy during insulin-induced hypoglycemia. Results: Assessment of samples from 75 subjects (type 2 diabetes, n  = 6; type 1 diabetes, n  = 28; nondiabetic pregnant subjects, n  = 10; and nondiabetic, n  = 31) showed that 97% of values were in Zone A with 3% in Zone B of the Clarke Error Grid, with a mean absolute relative difference of 6.7% from reference blood glucose. Comparison between two independent Gen III GWave devices demonstrated reproducibility between the sensors ( R 2 Our results show promise as potentially the first noninvasive technology. Future studies will focus on larger number of people in all glucose ranges. Real-time noninvasive blood glucose monitoring is possible using GWave technology. Conclusion: Our results show promise as potentially the first noninvasive technology. Future studies will focus on larger number of people in all glucose ranges. Real-time noninvasive blood glucose monitoring is possible using GWave technology.

Objective: To compare postprandial glucose excursions following a bolus with inhaled technosphere insulin (TI) or subcutaneous rapid-acting analog (RAA) insulin., Research Design and Methods: A meal challenge was completed by 122 adults with type 1 diabetes who were using multiple daily injections (MDI), a nonautomated pump, or automated insulin delivery (AID) and who were randomized to bolus with their usual RAA insulin (n = 61) or TI (n = 61)., Results: The primary outcome, the treatment group difference in area under the curve for glucose >180 mg/dL over 2 h, was less with TI versus RAA (adjusted difference -12 mg/dL, 95% CI -22 to -2, P = 0.02). With TI, the glucose excursion was smaller (P = 0.01), peak glucose lower (P = 0.01), and time to peak glucose shorter (P = 0.006). Blood glucose <70 mg/dL occurred in one participant in each group., Conclusions: Postmeal glucose excursion was smaller with TI than with RAA insulin in a cohort that included both AID and MDI users., (© 2024 by the American Diabetes Association.)

Aims/hypothesis: Previous studies have shown that individuals with similar mean glucose levels (MG) or percentage of time in range (TIR) may have different HbA 1c values. The aim of this study was to further elucidate how MG and TIR are associated with HbA 1c ., Methods: Data from the randomised clinical GOLD trial (n=144) and the follow-up SILVER trial (n=98) of adults with type 1 diabetes followed for 2.5 years were analysed. A total of 596 paired HbA 1c /continuous glucose monitoring measurements were included. Linear mixed-effects models were used to account for intra-individual correlations in repeated-measures data., Results: In the GOLD trial, the mean age of the participants (± SD) was 44±13 years, 63 (44%) were female, and the mean HbA 1c (± SD) was 72±9.8 mmol/mol (8.7±0.9%). When correlating MG with HbA 1c , MG explained 63% of the variation in HbA 1c (r=0.79, p<0.001). The variation in HbA 1c explained by MG increased to 88% (r=0.94, p value for improvement of fit <0.001) when accounting for person-to-person variation in the MG-HbA 1c relationship. Time below range (TBR; <3.9 mmol/l), time above range (TAR) level 2 (>13.9 mmol/l) and glycaemic variability had little or no effect on the association. For a given MG and TIR, the HbA 1c of 10% of individuals deviated by >8 mmol/mol (0.8%) from their estimated HbA 1c based on the overall association between MG and TIR with HbA 1c . TBR and TAR level 2 significantly influenced the association between TIR and HbA 1c . At a given TIR, each 1% increase in TBR was related to a 0.6 mmol/mol lower HbA 1c (95% CI 0.4, 0.9; p<0.001), and each 2% increase in TAR level 2 was related to a 0.4 mmol/mol higher HbA 1c (95% CI 0.1, 0.6; p=0.003). However, neither TIR, TBR nor TAR level 2 were significantly associated with HbA 1c when accounting for MG., Conclusions/interpretation: Inter-individual variations exist between MG and HbA 1c , as well as between TIR and HbA 1c , with clinically important deviations in relatively large groups of individuals with type 1 diabetes. These results may provide important information to both healthcare providers and individuals with diabetes in terms of prognosis and when making diabetes management decisions., (© 2024. The Author(s).)

Background: The role of glycemic control and its variability on the rate of kidney function decline after the onset of diabetic kidney disease (DKD) remains unclear., Methods: The association between baseline glycated hemoglobin (HbA1c) and rates of estimated glomerular filtration rate (eGFR) loss during follow-up was examined by mixed-effects linear regression in 530 individuals with type 1 diabetes and early-to-moderate DKD from the Preventing Early Renal Loss (PERL) trial and 2378 individuals with type 2 diabetes and established DKD from the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial. The benefit of intensive vs standard glycemic control in slowing eGFR decline was examined in ACCORD. The associations between continuous glucose monitoring-derived short-term glycemic variability indices and rate of eGFR decline were also evaluated in PERL., Results: A higher baseline HbA1c was associated with a more negative eGFR slope in both PERL and ACCORD (-0.87 and -0.27 mL/min/1.73 m2/year per Hba1c unit increment, P < .0001 and P = .0002, respectively). In both studies, the strength of this association progressively increased with increasing levels of albuminuria (P for interaction <.05). Consistent with this, the benefit of intensive glycemic control on eGFR decline was greater in ACCORD participants with severe rather than moderate albuminuria (+1.13 vs + 0.26 mL/min/1.73 m2/year, P = .01). No independent associations were found in PERL between short-term glycemic variability indices and rate of eGFR decline., Conclusion: In both type 1 and type 2 diabetes, poor glycemic control is associated with a more rapid rate of glomerular filtration rate decline after DKD onset, especially in persons with severe albuminuria., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Endocrine Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

The annual Virtual Hospital Diabetes Meeting was hosted by the Diabetes Technology Society on April 14 and 15, 2023, with the goal of reviewing the progress made in the hospital use of continuous glucose monitors (CGMs). Meeting topics included (1) Nursing Issues, Protocols, Order Sets, and Staff Education for Using CGMs, (2) Implementing CGM Programs for Use in the Wards, (3) Quality Metrics and Financial Implications of CGMs in the Hospital, (4) CGMs in the Critical Care Setting, (5) Special Situations: Labor/Delivery and Hemodialysis, (6) Research Session on CGMs in the Hospital, (7) Starting a CGM on Hospitalized Patients, (8) Automated Insulin Delivery Systems in the Hospital, (9) CGMs in Children, (10) Data Integration of CGMs for Inpatient Use and Telemetry, (11) Accuracy of CGMs/Comparison with Point-of-care Blood Glucose Testing, and (12) Discharge Planning with CGMs. Outcome data as well as shared collective real-life experiences were reviewed, and expert recommendations for CGM implementation were formulated.

Objective: In chronic kidney disease, glycated albumin and fructosamine have been postulated to be better biomarkers of glycemic control than HbA 1c . We evaluated the accuracy, variability, and covariate bias of three biomarkers (HbA 1c , glycated albumin, and fructosamine) compared with continuous glucose monitoring (CGM)-derived measurement of glycemia across estimated glomerular filtration rate (eGFR) in type 2 diabetes., Research Design and Methods: A prospective cohort study was conducted of 104 participants with type 2 diabetes, 80 with eGFR <60 mL/min/1.73 m 2 (not treated with dialysis) and 24 frequency-matched control subjects with eGFR ≥60 mL/min/1.73 m 2 . Participants wore a blinded CGM for two 6-day periods separated by 2 weeks, with blood and urine collected at the end of each CGM period. HbA 1c , glycated albumin, and fructosamine were measured by high-performance liquid chromatographic, enzymatic, and colorimetric nitroblue tetrazolium methods, respectively., Results: Within-person biomarker values were strongly correlated between the two CGM periods ( r = 0.92-0.95), although no marker fully captured the within-person variability of mean CGM glucose. All markers were similarly correlated with mean CGM glucose ( r = 0.71-77). Compared with mean CGM glucose, glycated albumin and fructosamine were significantly biased by age, BMI, serum iron concentration, transferrin saturation, and albuminuria; HbA 1c was underestimated in those with albuminuria., Conclusions: Glycated albumin and fructosamine were not less variable than HbA 1c at a given mean CGM glucose level, with several additional sources of bias. These results support measuring HbA 1c to monitor trends in glycemia among patients with eGFR <60 mL/min/1.73 m 2 . Direct measurements of glucose are necessary to capture short-term variability., (© 2020 by the American Diabetes Association.)

Importance: Continuous glucose monitoring (CGM) provides real-time assessment of glucose levels and may be beneficial in reducing hypoglycemia in older adults with type 1 diabetes., Objective: To determine whether CGM is effective in reducing hypoglycemia compared with standard blood glucose monitoring (BGM) in older adults with type 1 diabetes., Design, Setting, and Participants: Randomized clinical trial conducted at 22 endocrinology practices in the United States among 203 adults at least 60 years of age with type 1 diabetes., Interventions: Participants were randomly assigned in a 1:1 ratio to use CGM (n = 103) or standard BGM (n = 100)., Main Outcomes and Measures: The primary outcome was CGM-measured percentage of time that sensor glucose values were less than 70 mg/dL during 6 months of follow-up. There were 31 prespecified secondary outcomes, including additional CGM metrics for hypoglycemia, hyperglycemia, and glucose control; hemoglobin A1c (HbA1c); and cognition and patient-reported outcomes, with adjustment for multiple comparisons to control for false-discovery rate., Results: Of the 203 participants (median age, 68 [interquartile range {IQR}, 65-71] years; median type 1 diabetes duration, 36 [IQR, 25-48] years; 52% female; 53% insulin pump use; mean HbA1c, 7.5% [SD, 0.9%]), 83% used CGM at least 6 days per week during month 6. Median time with glucose levels less than 70 mg/dL was 5.1% (73 minutes per day) at baseline and 2.7% (39 minutes per day) during follow-up in the CGM group vs 4.7% (68 minutes per day) and 4.9% (70 minutes per day), respectively, in the standard BGM group (adjusted treatment difference, -1.9% (-27 minutes per day); 95% CI, -2.8% to -1.1% [-40 to -16 minutes per day]; P <.001). Of the 31 prespecified secondary end points, there were statistically significant differences for all 9 CGM metrics, 6 of 7 HbA1c outcomes, and none of the 15 cognitive and patient-reported outcomes. Mean HbA1c decreased in the CGM group compared with the standard BGM group (adjusted group difference, -0.3%; 95% CI, -0.4% to -0.1%; P <.001). The most commonly reported adverse events using CGM and standard BGM, respectively, were severe hypoglycemia (1 and 10), fractures (5 and 1), falls (4 and 3), and emergency department visits (6 and 8)., Conclusions and Relevance: Among adults aged 60 years or older with type 1 diabetes, continuous glucose monitoring compared with standard blood glucose monitoring resulted in a small but statistically significant improvement in hypoglycemia over 6 months. Further research is needed to understand the long-term clinical benefit., Trial Registration: ClinicalTrials.gov Identifier: NCT03240432.

In this study, we investigated which predictors from people with type 1 diabetes at initiation of intensive treatment that increase the risk of not achieving glycemic target. Data from a clinical trial with type 1 diabetes people (n=460) were used in a logistic regression model to analyze the effect of the predictors on achievement of glycemic target. Results indicate that age, smoking, glycated hemoglobin, 1,5-anhydroglucitol and fluctuation from continuous glucose monitoring are predictors of achievement of glycemic target, which can be used in an algorithm to predict people who fail to achieve glycemic target.

​OBJECTIVE: Compared with hemoglobin A1c (HbA1c), continuous glucose monitoring (CGM) may better capture risk of diabetes complications in patients with chronic kidney disease (CKD), including diabetic peripheral neuropathy (DPN). We hypothesized that glucose time in range (TIR), measured by CGM, is associated with DPN symptoms among participants with type 2 diabetes mellitus (type 2 DM) and moderate-to-severe CKD. ​RESEARCH DESIGN AND METHODS: We enrolled 105 people with type 2 DM treated with insulin or sulfonylurea, 81 participants with CKD (estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m 2 ) and 24 matched control participants with eGFR ≥60 mL/min/1.73 m 2 . Each participant wore a CGM for two 6-day periods. Calculated glycemic measures included TIR (glucose 70-180 mg/dL) and glucose management indicator (GMI). DPN symptoms were assessed using the Michigan Neuropathy Screening Instrument (MNSI) questionnaire, with a positive MNSI score defined as ≥2 symptoms. ​RESULTS: Participants with CKD had a mean age of 68 years, diabetes duration 20 years, eGFR 38 mL/min/1.73 m 2 and HbA1c 7.8%, 61 mmol/mol. Sixty-two participants reported ≥2 DPN symptoms, 51 (63%) with CKD and 11 (46%) controls. Less TIR and higher GMI were associated with higher risk of MNSI questionnaire score ≥2 (OR 1.25 (95% CI 1.02 to 1.52) per 10% lower TIR, and OR 1.79 (95% CI 1.05 to 3.04) per 1% higher GMI, adjusting for age, gender and race). Similar results were observed when analyses were restricted to participants with CKD. In contrast, there was no significant association of HbA1c with DPN symptoms. ​CONCLUSIONS: Symptoms of DPN were common among participants with long-standing type 2 DM and CKD. Lower TIR and higher GMI were associated with DPN symptoms., Competing Interests: Competing interests: IBH reports receiving research support from Medtronic Diabetes and consulting for Abbott Diabetes Care, Roche, Bigfoot and Becton Dickinson. IHdB reports consulting for Ironwood and Boehringer-Ingelheim., (© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Improvements in sensor accuracy, greater convenience and ease of use, and expanding reimbursement have led to growing adoption of continuous glucose monitoring (CGM). However, successful utilization of CGM technology in routine clinical practice remains relatively low. This may be due in part to the lack of clear and agreed-upon glycemic targets that both diabetes teams and people with diabetes can work toward. Although unified recommendations for use of key CGM metrics have been established in three separate peer-reviewed articles, formal adoption by diabetes professional organizations and guidance in the practical application of these metrics in clinical practice have been lacking. In February 2019, the Advanced Technologies & Treatments for Diabetes (ATTD) Congress convened an international panel of physicians, researchers, and individuals with diabetes who are expert in CGM technologies to address this issue. This article summarizes the ATTD consensus recommendations for relevant aspects of CGM data utilization and reporting among the various diabetes populations., (© 2019 by the American Diabetes Association.)

Background and Objectives: Among people with diabetes mellitus, CKD may promote hypoglycemia through altered clearance of glucose-lowering medications, decreased kidney gluconeogenesis, and blunted counter-regulatory response. We conducted a prospective observational study of hypoglycemia among 105 individuals with type 2 diabetes treated with insulin or a sulfonylurea using continuous glucose monitors., Design, Setting, Participants & Measurements: We enrolled 81 participants with CKD, defined as eGFR<60 ml/min per 1.73 m 2 , and 24 control participants with eGFR≥60 ml/min per 1.73 m 2 frequency-matched on age, duration of diabetes, hemoglobin A1c, and glucose-lowering medications. Each participant wore a continuous glucose monitor for two 6-day periods. We examined rates of sustained level 1 hypoglycemia (<70 mg/dl) and level 2 hypoglycemia (<54 mg/dl) among participants with CKD. We then tested differences compared with control participants as well as a second control population ( n =73) using Poisson and linear regression, adjusting for age, sex, and race., Results: Over 890 total days of continuous glucose monitoring, participants with CKD were observed to have 255 episodes of level 1 hypoglycemia, of which 68 episodes reached level 2 hypoglycemia. Median rate of hypoglycemic episodes was 5.3 (interquartile range, 0.0-11.7) per 30 days and mean time spent in hypoglycemia was 28 (SD 37) minutes per day. Hemoglobin A1c and the glucose management indicator were the main clinical correlates of time in hypoglycemia (adjusted differences 6 [95% confidence interval, 2 to 10] and 13 [95% confidence interval, 7 to 20] fewer minutes per day per 1% higher hemoglobin A1c or glucose management indicator, respectively). Compared with control populations, participants with CKD were not observed to have significant differences in time in hypoglycemia (adjusted differences 4 [95% confidence interval, -12 to 20] and -12 [95% confidence interval, -29 to 5] minutes per day)., Conclusions: Among people with type 2 diabetes and moderate to severe CKD, hypoglycemia was common, particularly with tighter glycemic control, but not significantly different from groups with similar clinical characteristics and preserved eGFR., (Copyright © 2019 by the American Society of Nephrology.)

Two types of continuous glucose monitoring (CGM) systems are now available: real-time CGM (rtCGM) and intermittently scanned (isCGM). Current rtCGM systems automatically transmit a continuous stream of glucose data to the user, provide alerts and active alarms, and transmit glucose data (trend and numerical) in real time to a receiver, smart watch, or smartphone. The current isCGM system provides the same type of glucose data but requires the user to purposely scan the sensor to obtain information, and it does not have alerts and alarms. Both CGM technologies have significant advantages over self-monitoring of blood glucose; however, differences in the features and capabilities of the two approaches must be considered when guiding patient selection of the system that meets their individual needs., (© 2018 by the American Diabetes Association.)

Achievement of well-controlled blood glucose is essential for preventing complications in patients with type 1 diabetes. Since the inception of continuous subcutaneous insulin infusion, the aim has been to develop an artificial pancreas, with the ability to use an automated algorithm to deliver one or more hormones in response to blood glucose with the intent to keep blood sugar as close to a prespecified target as possible. Development and rapid improvement of continuous glucose sensor technology has recently allowed swift progress toward a fully closed-loop insulin delivery system. In 2017, Medtronic began marketing the 670G insulin pump with Guardian 3 sensor. When in auto mode, this is a hybrid closed-loop insulin delivery system that automatically adjusts basal insulin delivery every 5 min based on sensor glucose to maintain blood glucose levels as close to a specific target as possible. Patients receive prandial insulin by entering carbohydrate amount into the bolus calculator. Early studies show improvement in HbA1c in both adults and adolescents with this technology. Initial safety trials showed no occurrence of diabetic ketoacidosis or hypoglycemia. The utility of this device is limited by blood glucose targets of 120 and 150 mg/dL that are unacceptably high for some patients. Notwithstanding recent advances, we are far from a system that is able to replicate islet function in the form of a fully automated, multihormonal blood glucose control device.

Background: To evaluate the effects of continuous glucose monitoring (CGM) on nocturnal and daytime hypoglycemia in persons with type 1 diabetes treated with multiple daily insulin injections (MDI); we also evaluated factors related to differences in hypoglycemia confidence in this population., Methods: Evaluations were performed from the GOLD randomized trial, an open-label multicenter crossover randomized clinical trial (n = 161) over 69 weeks comparing CGM to self-measurement of blood glucose (SMBG) in persons with type 1 diabetes treated with MDI. Masked CGM and the hypoglycemia confidence questionnaire were used for evaluations., Results: Time with nocturnal hypoglycemia, glucose levels <70 mg/dL was reduced by 48% (10.2 vs. 19.6 min each night, P < 0.001) and glucose levels <54 mg/dL by 65%. (3.1 vs. 8.9 min, P < 0.001). For the corresponding glucose cutoffs, daytime hypoglycemia was reduced by 40% (29 vs. 49 min, P < 0.001) and 54% (8 vs. 18 min., P < 0.001), respectively. Compared with SMBG, CGM use improved hypoglycemia-related confidence in social situations (P = 0.016) and confidence in more broadly avoiding serious problems due to hypoglycemia (P = 0.0020). Persons also reported greater confidence in detecting and responding to decreasing blood glucose levels (thereby avoiding hypoglycemia) during CGM use (P = 0.0033) and indicated greater conviction that they could more freely live their lives despite the risk of hypoglycemia (P = 0.022)., Conclusion: CGM reduced time in both nocturnal and daytime hypoglycemia in persons with type 1 diabetes treated with MDI and improved hypoglycemia-related confidence, especially in social situations, thus contributing to greater well-being and quality of life., Trial Registration: ClinicalTrials.gov , number NCT02092051.

Purpose of Review: Diabetes is the leading cause of kidney disease globally. Diabetic kidney disease (DKD) is a heterogeneous disorder manifested as albuminuria and/or decreasing GFR. Hyperglycemic burden is the major contributor to the development of DKD. In this article, we review the evidence for the contribution of glycemic variability and the pitfalls associated with use of hemoglobin A1c (A1C), the gold standard for assessment of glucose control, in the setting of DKD., Recent Findings: Glycemic variability, characterized by swings in blood glucose levels, can result in generation of mitochondrial reactive oxygen species, a putative inciting factor for hyperglycemia-induced alterations in intracellular metabolic pathways. While there is indirect evidence supporting the role of glycemic variability in the pathogenesis of DKD, definitive data are lacking. A1C has many limitations and is a particularly suboptimal measure in patients with kidney disease, because its accuracy is compromised by variables affecting RBC survival and other factors. Continuous glucose monitoring (CGM) technology has the potential to enable us to use glucose as a more important clinical tool, for a more definitive understanding of glucose variability and its role in DKD. Glycemic variability may be a factor in the development of DKD, but definitive evidence is lacking. Currently, all available glycemic biomarkers, including A1C, have limitations and in the setting of DKD and should be used cautiously. Emerging data suggest that personal and professional CGM will play an important role in managing diabetes in patients with DKD, where risk of hypoglycemia is high.

Background: High levels of glycemic variability are still observed in most patients with diabetes with severe insulin deficiency. Glycemic variability may be an important risk factor for acute and chronic complications. Despite its clinical importance, there is no consensus on the optimum method for characterizing glycemic variability., Method: We developed a simple new metric, the glycemic variability percentage (GVP), to assess glycemic variability by analyzing the length of the continuous glucose monitoring (CGM) temporal trace normalized to the duration under evaluation. The GVP is similar to other recently proposed glycemic variability metrics, the distance traveled, and the mean absolute glucose (MAG) change. We compared results from distance traveled, MAG, GVP, standard deviation (SD), and coefficient of variation (CV) applied to simulated CGM traces accentuating the difference between amplitude and frequency of oscillations. The GVP metric was also applied to data from clinical studies for the Dexcom G4 Platinum CGM in subjects without diabetes, with type 2 diabetes, and with type 1 diabetes (adults, adolescents, and children)., Results: In contrast to other metrics, such as CV and SD, the distance traveled, MAG, and GVP all captured both the amplitude and frequency of glucose oscillations. The GVP metric was also able to differentiate between diabetic and nondiabetic subjects and between subjects with diabetes with low, moderate, and high glycemic variability based on interquartile analysis., Conclusion: A new metric for the assessment of glycemic variability has been shown to capture glycemic variability due to fluctuations in both the amplitude and frequency of glucose given by CGM data.

Background: The problem of glycemic variability has been widely acknowledged in patients with diabetes with severe insulin deficiency. In a companion article, we proposed a novel metric, the glycemic variability percentage (GVP), for assessing glycemic variability that accounts for both the amplitude and frequency of glycemic fluctuations., Method: We applied the new metric, the GVP, to a previously reported case of a subject using an earlier generation continuous glucose monitoring (CGM) device, in which successive periods of use were associated with an apparent decrease in glycemic variability. Results were compared with histogram distributions for the rate of change of glucose as well. The GVP was also applied to data from a published study of a bihormonal artificial pancreas system comparing results from open loop and closed loop in adolescents and in adults., Results: The GVP was able to quantify the changes in glycemic variability during successive periods of CGM use. Application of the GVP to a published study of a bihormonal artificial pancreas found an increase in glycemic variability compared with other accepted metrics which suggested a decrease in glycemic variability., Conclusion: The GVP may be a clinically useful tool in characterizing the change in glycemic variability in subjects using CGM devices. Compared with metrics, such as the standard deviation, that focus solely on the amplitude of oscillations, the GVP, which measures both frequency and amplitude, may also be a more useful tool in assessing the true level of glycemic variability in artificial pancreas studies.

Decreasing glycated hemoglobin (A1C) is the primary goal of current diabetes management due to intervention studies in type 1 and type 2 diabetes associating levels <7.0% (53 mmol/mol) with lower complication risk. Strategic self-monitoring of blood glucose (SMBG) is also recommended to achieve greater time in range, with fewer extremes of hypo- or hyperglycemia. Unlike A1C, SMBG can distinguish among fasting, prandial, and postprandial hyperglycemia; uncover glycemic variability, including potentially dangerous hypoglycemia; and provide feedback to patients about the effects of behavior and medication on glycemic control. However, it has the drawback of capturing only static glucose readings and users are often dependent on time-pressed clinicians to interpret numerous data points. A novel flash continuous glucose monitoring (FCGM) device used for a single 2-week period with a readily interpretable data report know as the ambulatory glucose profile (AGP) has the potential to overcome limitations of conventional technologies, with less cost and greater convenience. This review summarizes the rationale for using intermittent FCGM as a supplement to A1C in primary care, and provides a stepwise approach to interpreting the AGP visual display for efficient individualized therapy.

Objective: Recent consensus statements strongly advocate downloading and interpreting continuous glucose data for diabetes management in patients with type 1 or 2 diabetes. Supplementing periodic glycated hemoglobin (A1C) testing with intermittent continuous glucose monitoring (CGM) using a standardized report form known as the ambulatory glucose profile (AGP) is an evolving standard of care. The rationale for this approach and its implementation with a recently approved novel monitoring technology are explored., Methods: Search of the medical literature, professional guidelines, and real-world evidence guided this introduction of an integrative practice framework that uses AGP in conjunction with intermittent flash continuous glucose monitoring (FCGM) as a supplement to A1C testing., Results: The combination of intermittent continuous glucose pattern analysis, standardized glucose metrics, and a readily interpretable data report has the potential to practically extend the recognized benefits of CGM to more patients and clarify the relationship between A1C and average glucose levels in individual cases., Conclusion: Novel FCGM technologies portend greater use of continuous forms of glucose monitoring and wider adoption of AGP report analysis. Additional formal and empirical evidence is needed to more fully characterize best practice., Abbreviations: A1C = glycated hemoglobin; AGP = ambulatory glucose profile; CGM = continuous glucose monitoring; FCGM = flash continuous glucose monitoring; IQR = interquartile range; SMBG = self-monitoring of blood glucose.

Thanks to significant improvements in the precision, accuracy, and usability of continuous glucose monitoring (CGM), its relevance in both ambulatory diabetes care and clinical research is increasing. In this study, we address the latter perspective and derive provisional reporting recommendations. CGM systems have been available since around the year 2000 and used primarily in people with type 1 diabetes. In contrast to self-measured glucose, CGM can provide continuous real-time measurement of glucose levels, alerts for hypoglycemia and hyperglycemia, and a detailed assessment of glycemic variability. Through a broad spectrum of derived glucose data, CGM should be a useful tool for clinical evaluation of new glucose-lowering medications and strategies. It is the only technology that can measure hyperglycemic and hypoglycemic exposure in ambulatory care, or provide data for comprehensive assessment of glucose variability. Other advantages of current CGM systems include the opportunity for improved self-management of glycemic control, with particular relevance to those at higher risk of or from hypoglycemia. We therefore summarize the current status and limitations of CGM from the perspective of clinical trials and derive suggested recommendations for how these should facilitate optimal CGM use and reporting of data in clinical research.

Background: The potential clinical benefits of continuous glucose monitoring (CGM) have been recognized for many years, but CGM is used by a small fraction of patients with diabetes. One obstacle to greater use of the technology is the lack of simplified tools for assessing glycemic control from CGM data without complicated visual displays of data., Methods: We developed a simple new metric, the personal glycemic state (PGS), to assess glycemic control solely from continuous glucose monitoring data. PGS is a composite index that assesses four domains of glycemic control: mean glucose, glycemic variability, time in range and frequency and severity of hypoglycemia. The metric was applied to data from six clinical studies for the G4 Platinum continuous glucose monitoring system (Dexcom, San Diego, CA). The PGS was also applied to data from a study of artificial pancreas comparing results from open loop and closed loop in adolescents and in adults., Results: The new metric for glycemic control, PGS, was able to characterize the quality of glycemic control in a wide range of study subjects with various mean glucose, minimal, moderate, and excessive glycemic variability and subjects on open loop versus closed loop control., Conclusion: A new composite metric for the assessment of glycemic control based on CGM data has been defined for use in assessing glycemic control in clinical practice and research settings. The new metric may help rapidly identify problems in glycemic control and may assist with optimizing diabetes therapy during time-constrained physician office visits.

Objective: To determine the safety and efficacy of a change in blood glucose (BG) control protocol from a single target to 2 targets based on diabetes mellitus (DM) status and glycated hemoglobin A1C (A1C) in a cohort of critically ill patients., Methods: This investigation includes 1,979 patients admitted to a single intensive care unit (ICU) between September 16, 2013 and September 15, 2015. The BG target was 90 to 120 mg/dL in the PRE era and 80 to 140 mg/dL for patients without diabetes (NON) and with DM with A1C <7% and 110 to 160 mg/dL for DM with A1C ≥7% (TIGHT and LOOSE protocols) in the POST era. The primary efficacy outcome was the observed:expected (O:E) mortality ratio., Results: Among NON, the mean BG was slightly lower in the POST era: 118 (106-132) versus 115 (101-120) mg/dL (P = .0003). Among DM, the mean BG was 139 (123-160) mg/dL in the PRE era versus 136 (119-149) and 159 (138-171) mg/dL for TIGHT and LOOSE in the POST era (P = .0668 and .0001, respectively). Overall, 11.0% and 11.8% of patients had at least 1 BG level <70 mg/dL in the 2 eras (P = .68). The O:E mortality ratios for NON and DM for the PRE and POST eras were 0.75 versus 0.74 (P = .51) and 0.69 versus 0.52 (P<.001) respectively, and among DM with A1C ≥7% were 0.74 versus 0.52 (P = .004)., Conclusion: This hypothesis-generating investigation suggests the need for additional prospective interventional studies assessing the outcomes of patients randomized to personalized glucose targets., Abbreviations: APACHE = Acute Physiology and Chronic Health Evaluation A1C = glycated hemoglobin A1C BG = blood glucose CV = co-efficient of variation DM = diabetes mellitus ICU = intensive care unit LOS = length of stay NON = patients without DM O:E = observed: expected.

Background: Real-time continuous glucose monitoring (RTCGM) may help in the management of individuals with type 1 diabetes mellitus (T1DM); however, the evidence supporting its use is unclear. The available meta-analyses on this topic use aggregate data which weaken inference., Objective: Individual patient data were obtained from randomized controlled trials (RCTs) to conduct a meta-analysis and synthesize evidence about the effect of RTCGM on glycosylated haemoglobin (HbA1c), hypoglycaemic events and time spent in hypoglycaemia in T1DM., Methods: We searched MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials and Database of Systematic Reviews, and Scopus through January 2015. We included RCTs that enrolled individuals with T1DM and compared RTCGM vs control group. A two-step regression model was used to pool individual patient data., Results: We included 11 RCTs at moderate risk of bias. Meta-analysis suggests that the use of RTCGM is associated with a statistically significant but modest reduction in HbA1c (-0·276; 95% confidence interval -0·465 to -0·087). The improvements in HbA1c were primarily seen in individuals over age 15 years. We were unable to identify a statistically significant difference in time spent in hypoglycaemia or the number of hypoglycaemic episodes although these analyses were imprecise and warrant lower confidence. There was no difference between males and females., Conclusion: RTCGM in T1DM is associated with a reduction in HbA1c primarily in individuals over 15 years of age. We were unable to identify a statistically significant difference in the time spent in hypoglycaemia or the incidence of hypoglycaemic episodes., (© 2016 John Wiley & Sons Ltd.)

Importance: The majority of individuals with type 1 diabetes do not meet recommended glycemic targets., Objective: To evaluate the effects of continuous glucose monitoring in adults with type 1 diabetes treated with multiple daily insulin injections., Design, Setting, and Participants: Open-label crossover randomized clinical trial conducted in 15 diabetes outpatient clinics in Sweden between February 24, 2014, and June 1, 2016 that included 161 individuals with type 1 diabetes and hemoglobin A1c (HbA1c) of at least 7.5% (58 mmol/mol) treated with multiple daily insulin injections., Interventions: Participants were randomized to receive treatment using a continuous glucose monitoring system or conventional treatment for 26 weeks, separated by a washout period of 17 weeks., Main Outcomes and Measures: Difference in HbA1c between weeks 26 and 69 for the 2 treatments. Adverse events including severe hypoglycemia were also studied., Results: Among 161 randomized participants, mean age was 43.7 years, 45.3% were women, and mean HbA1c was 8.6% (70 mmol/mol). A total of 142 participants had follow-up data in both treatment periods. Mean HbA1c was 7.92% (63 mmol/mol) during continuous glucose monitoring use and 8.35% (68 mmol/mol) during conventional treatment (mean difference, -0.43% [95% CI, -0.57% to -0.29%] or -4.7 [-6.3 to -3.1 mmol/mol]; P < .001). Of 19 secondary end points comprising psychosocial and various glycemic measures, 6 met the hierarchical testing criteria of statistical significance, favoring continuous glucose monitoring compared with conventional treatment. Five patients in the conventional treatment group and 1 patient in the continuous glucose monitoring group had severe hypoglycemia. During washout when patients used conventional therapy, 7 patients had severe hypoglycemia., Conclusions and Relevance: Among patients with inadequately controlled type 1 diabetes treated with multiple daily insulin injections, the use of continuous glucose monitoring compared with conventional treatment for 26 weeks resulted in lower HbA1c. Further research is needed to assess clinical outcomes and longer-term adverse effects., Trial Registration: clinicaltrials.gov Identifier: NCT02092051.

Objective: To understand the decisional practices of anesthesia providers in managing intraoperative glucose levels., Design: This is a retrospective cohort study., Setting: Operating rooms in an academic medical center., Patients: Adult patients undergoing surgery., Intervention: Intraoperative blood glucose management based on an institutional protocol., Measurements: Glucose management data was extracted from electronic medical records to determine compliance to institutional glucose management protocol that prescribes hourly glucose measurements and insulin doses to maintain glucose levels between 100 to 140mg/dL. Effect of patient and surgery specific factors on compliance to glucose management protocol was explored., Main Results: In 1903 adult patients compliances to hourly glucose measurements was 72.5% and correct insulin adjustments was 12.4%. Insulin was under-dosed compared to the prescribed value by a mean of 0.85U/h (95% CI 0.76-0.95). Multivariate analysis showed that compliance to hourly glucose measurements decreased with increasing length of the procedure (OR=0.92 per hour, 95% CI 0.89-0.95) but increased with ASA status codes (OR=1.25 per ASA unit, 95% CI=1.06-1.49). Greater compliance to correct insulin adjustment was found in diabetic patients compared with non-diabetic patients (OR=1.31, 95% CI 1.09-1.55). On average, providers administered progressively more insulin with an additional 0.11U/h (95% CI=0.00-0.21] for every additional 10kg/m(2) of BMI and 0.20U/h (95% CI=0.01-0.39) less in diabetic patients than in non-diabetic patients. With the above practice pattern, the mean±SD of glucose level was 158±36mg/dL. Hypoglycemic (<60mg/dL) incident rate was 0.1% (9/8301 measurements) while hyperglycemic (>180mg/dL) incident rate was 28%. Glucose levels were within the target range (100-140mg/dL) only 28% of the time., Conclusions: Low compliance and considerable variability in initiating and following institutional glucose management protocol were observed., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Background: Using the standard venous reference for the evaluation of continuous glucose monitoring (CGM) systems could possibly negatively affect measured CGM accuracy since CGM are generally calibrated with capillary glucose and venous and capillary glucose concentrations differ. We therefore aimed to quantify the effect of using capillary versus venous glucose reference samples on estimated accuracy in capillary calibrated CGM., Methods: We evaluated 41 individuals with type 1 diabetes mellitus (T1DM) using the Dexcom G4 CGM system over 6 days. Patients calibrated their CGM devices with capillary glucose by means of the HemoCue system. During 2 visits, capillary and venous samples were simultaneously measured by HemoCue and compared to concomitantly obtained CGM readings. The mean absolute relative difference (MARD) was calculated using capillary and venous reference samples., Results: Venous glucose values were 0.83 mmol/L (15.0 mg/dl) lower than capillary values over all glycemic ranges, P < .0001. Below 4 mmol/l (72 mg/dl), the difference was 1.25 mmol/l (22.5 mg/dl), P = .0001, at 4-10 mmol/l (72-180 mg/dl), 0.67 mmol/l (12.0 mg/dl), P < .0001 and above 10 mmol/l (180 mg/dl), 0.95 mmol/l (17.1 mg/dl), P < .0001. MARD was 11.7% using capillary values as reference compared to 13.7% using venous samples, P = .037. Below 4 mmol/l (72 mg/dl) MARD was 16.6% and 31.8%, P = .048, at 4-10 mmol/l (72-180 mg/dl) 12.1% and 12.6%, P = .32, above 10 mmol/l (180 mg/dl) 8.7% and 9.2%, P = .82., Conclusion: Using capillary glucose concentrations as reference to evaluate the accuracy of CGM calibrated with capillary samples is associated with a lower MARD than using venous glucose as the reference. Capillary glucose concentrations were significantly higher than venous in all glycemic ranges., (© 2016 Diabetes Technology Society.)

Poor perioperative glycemic management can lead to negative surgical outcome. Improved compliance to glucose control protocol could lead to better glucose management. An Anesthesia Information Management System based decision support system-Smart Anesthesia Manager™ (SAM) was used to generate real-time reminders to the anesthesia providers to closely adhere to our institutional glucose management protocol. Compliance to hourly glucose measurements and correct insulin dose adjustments was compared for the baseline period (12 months) without SAM and the intervention period (12 months) with SAM decision support. Additionally, glucose management parameters were compared for the baseline and intervention periods. A total of 1587 cases during baseline and 1997 cases during intervention met the criteria for glucose management (diabetic patients or non-diabetic patients with glucose level >140 mg/dL). Among the intervention cases anesthesia providers chose to use SAM reminders 48.7 % of the time primarily for patients who had diabetes, higher HbA1C or body mass index, while disabling the system for the remaining cases. Compliance to hourly glucose measurement and correct insulin doses increased significantly during the intervention period when compared with the baseline (from 52.6 to 71.2 % and from 13.5 to 24.4 %, respectively). In spite of improved compliance to institutional protocol, the mean glucose levels and other glycemic management parameters did not show significant improvement with SAM reminders. Real-time electronic reminders improved intraoperative compliance to institutional glucose management protocol though glycemic parameters did not improve even when there was greater compliance to the protocol.

Background: The majority of individuals with type 1 diabetes today have glucose levels exceeding guidelines. The primary aim of this study was to evaluate whether continuous glucose monitoring (CGM), using the Dexcom G4 stand-alone system, improves glycemic control in adults with type 1 diabetes treated with multiple daily insulin injections (MDI)., Methods: Individuals with type 1 diabetes and inadequate glycemic control (HbA1c ≥ 7.5% = 58 mmol/mol) treated with MDI were randomized in a cross-over design to the Dexcom G4 versus conventional care for 6 months followed by a 4-month wash-out period. Masked CGM was performed before randomization, during conventional treatment, and during the wash-out period to evaluate effects on hypoglycemia, hyperglycemia, and glycemic variability. Questionnaires were used to evaluate diabetes treatment satisfaction, fear of hypoglycemia, hypoglycemia confidence, diabetes-related distress, overall well-being, and physical activity during the different phases of the trial. The primary endpoint was the difference in HbA1c at the end of each treatment phase., Results: A total of 205 patients were screened, of whom 161 were randomized between February and December 2014. Study completion is anticipated in April 2016., Conclusions: It is expected that the results of this study will establish whether using the Dexcom G4 stand-alone system in individuals with type 1 diabetes treated with MDI improves glycemic control, reduces hypoglycemia, and influences quality-of-life indicators and glycemic variability., Competing Interests: Declaration of Conflicting Interests: ML has received research grants from AstraZeneca, Dexcom, and Novo Nordisk, been a consultant or received honoraria from Medtronic, Eli Lilly, Pfizer, Abbot Scandinavia, Bayer, Novo Nordisk, and Rubin Medical. ML has participated in advisory boards for Novo Nordisk. WP has served as a consultant for Dexcom and Abbott Diabetes Care. IBH has received research grants from Novo Nordisk, and been a consultant for Abbott Diabetes Care, Roche, and Becton Dickinson. TH has received research funds from Adocia, AstraZeneca, BD, Biocon, Boehringer Ingelheim, Dance Pharmaceuticals, Grünenthal, Eli Lilly, Medtronic, Novo Nordisk, Novartis, Sanofi, and Senseonics. TH has participated in advisory panels for Novo Nordisk and received speaker honoraria and travel grants from Eli Lilly, Mylan, and Novo Nordisk. JB has received honoraria for consulting and/or lecture fees from Abbott Diabetes Care, AstraZeneca, Integrity Applications, Eli Lilly, and Sanofi. SD, NGP, and PM have no conflicts of interest to declare., (© 2016 Diabetes Technology Society.)

This document represents the official position of the American Association of Clinical Endocrinologists and American College of Endocrinology. Where there were no randomized controlled trials or specific U.S. FDA labeling for issues in clinical practice, the participating clinical experts utilized their judgment and experience. Every effort was made to achieve consensus among the committee members. Position statements are meant to provide guidance, but they are not to be considered prescriptive for any individual patient and cannot replace the judgment of a clinician.

There is no argument that improving mean levels of glycemic control as judged by assays for glycated hemoglobin (HbA(1c)) reduces the risks of microvascular complications and cardiovascular disease events in patients with type 1 and type 2 diabetes. However, observations in some trials have suggested that targeting HbA(1c) to suggested targets may not always result in improved outcomes for people with long-standing type 2 diabetes. The reasons why the glycemic control strategies that primarily use HbA(1c) in these studies did not have predicted outcomes are not clear. Thus, controversy remains as to whether there are glycemic metrics beyond HbA(1c) that can be defined as effective measures that can be used in addition to HbA(1c) to help in assessing the risk of an individual developing diabetes complications. In this regard, the concept of "glycemic variability" (GV) is one metric that has attracted a lot of attention. GV can be simply defined as the degree to which a patient's blood glucose level fluctuates between high (peaks) and low (nadir) levels. The best and most precise way to assess GV is also one that is still debated. Thus, while there is universal agreement that HbA(1c) is the current gold standard for the primary clinical target, there is no consensus as to whether other proposed glycemic metrics hold promise to provide additional clinical data or whether there should be additional targets beyond HbA(1c). Therefore, given the current controversy, we provide a Point-Counterpoint debate on this issue. In the point narrative below, Dr. Hirsch provides his argument that fluctuations in blood glucose as assessed by GV metrics are deleterious and control of GV should be a primary treatment target. In the following counterpoint narrative, Dr. Bergenstal argues that there are better markers to assess the risk of diabetes than GV and provides his consideration of other concepts., (© 2015 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.)

Objective: Accuracy of continuous glucose monitoring (CGM) devices in hypoglycemia has been a widely reported shortcoming of this technology. We report the accuracy in hypoglycemia of a new version of the Dexcom (San Diego, CA) G4 Platinum CGM system (software 505) and present results regarding the optimum setting of CGM hypoglycemic alerts., Materials and Methods: CGM values were compared with YSI analyzer (YSI Life Sciences, Yellow Springs, OH) measurements every 15 min. We reviewed the accuracy of the CGM system in the hypoglycemic range using standard metrics. We analyzed the time required for the CGM system to detect biochemical hypoglycemia (70 mg/dL) compared with the YSI with alert settings at 70 mg/dL and 80 mg/dL. We also analyzed the time between the YSI value crossing 55 mg/dL, defined as the threshold for cognitive impairment due to hypoglycemia, and when the CGM system alerted for hypoglycemia., Results: The mean absolute difference for a glucose level of less than 70 mg/dL was 6 mg/dL. Ninety-six percent of CGM values were within 20 mg/dL of the YSI values between 40 and 80 mg/dL. When the CGM hypoglycemic alert was set at 80 mg/dL, the device provided an alert for biochemical hypoglycemia within 10 min in 95% of instances and at least a 10-min advance warning before the cognitive impairment threshold in 91% of instances in the study., Conclusions: Use of an 80 mg/dL threshold setting for hypoglycemic alerts on the G4 Platinum (software 505) may provide patients with timely warning of hypoglycemia before the onset of cognitive impairment, enabling them to treat themselves for hypoglycemia with fast-acting carbohydrates and prevent neuroglycopenia associated with very low glucose levels.

Background: Continuous glucose monitoring (CGM) is a tool widely used in the treatment of patients with type 1 diabetes. The purpose of the current study was to evaluate whether accuracy and patient treatment satisfaction differ between the Enlite™ (Medtronic MiniMed, Inc., Northridge, CA) and Dexcom(®) (San Diego, CA) G4 PLATINUM CGM sensors., Subjects and Methods: Thirty-eight ambulatory patients with type 1 diabetes used the Dexcom G4 and Enlite sensors simultaneously for a minimum of 4 and maximum of 6 days. Patients measured capillary glucose levels with a HemoCue(®) (Ängelholm, Sweden) system six to 10 times a day. In addition, two inpatient studies were performed between Days 1-3 and 4-6., Results: The mean absolute relative difference (MARD) in blood glucose for the Dexcom G4 was significantly lower (13.9%) than for the Enlite sensor (17.8%) (P<0.0001). The corresponding MARDs for Days 1-3 were 15.0% versus 19.4% (P=0.0027) and 13.6% versus 15.9% (P=0.026) for Days 4-6. For glucose levels in the hypoglycemic range (<4.0 mmol/L), the MARD for the Dexcom G4 was 20.0% compared with 34.7% for the Enlite (P=0.0041). On a visual analog scale (VAS) (0-100), patients rated the Dexcom G4 more favorably than the Enlite in 12 out of the 13 user experience questions. For example, more patients rated their experience with the Dexcom G4 as positive (VAS, 79.7 vs. 46.6; P<0.0001) and preferred to use it in their daily lives (VAS, 79.1 vs. 42.1; P<0.0001)., Conclusions: The Dexcom G4 sensor was associated with greater overall accuracy than the Enlite sensor during initial (Days 1-3) and later (Days 4-6) use and for glucose levels in the hypoglycemic range. Patients reported a significantly more positive experience using the Dexcom G4 than the Enlite.

Objective: Despite substantial evidence of the benefit of frequent self-monitoring of blood glucose (SMBG) in type 1 diabetes, certain insurers limit the number of test strips that they will provide. The large database of the T1D Exchange clinic registry provided an opportunity to evaluate the relationship between the number of SMBG measurements per day and HbA1c levels across a wide age range of children and adults., Research Design and Methods: The analysis included 20,555 participants in the T1D Exchange clinic registry with type 1 diabetes ≥1 year and not using a continuous glucose monitor (11,641 younger than age 18 years and 8,914 18 years old or older). General linear models were used to assess the association between the number of SMBG measurements and HbA1c levels after adjusting for potential confounding variables., Results: A higher number of SMBG measurements per day were associated with non-Hispanic white race, insurance coverage, higher household income, and use of an insulin pump for insulin delivery (P < 0.001 for each factor). After adjusting for these factors, a higher number of SMBG measurements per day was strongly associated with a lower HbA1c level (adjusted P < 0.001), with the association being present in all age-groups and in both insulin pump and injection users., Conclusions: There is a strong association between higher SMBG frequency and lower HbA1c levels. It is important for insurers to consider that reducing restrictions on the number of test strips provided per month may lead to improved glycemic control for some patients with type 1 diabetes.

Underutilization of glucose data and lack of easy and standardized glucose data collection, analysis, visualization, and guided clinical decision making are key contributors to poor glycemic control among individuals with type 1 diabetes mellitus. An expert panel of diabetes specialists, facilitated by the International Diabetes Center and sponsored by the Helmsley Charitable Trust, met in 2012 to discuss recommendations for standardizing the analysis and presentation of glucose monitoring data, with the initial focus on data derived from continuous glucose monitoring systems. The panel members were introduced to a universal software report, the Ambulatory Glucose Profile, and asked to provide feedback on its content and functionality, both as a research tool and in clinical settings. This article provides a summary of the topics and issues discussed during the meeting and presents recommendations from the expert panel regarding the need to standardize glucose profile summary metrics and the value of a uniform glucose report to aid clinicians, researchers, and patients., (© 2013 Diabetes Technology Society.)

By the year 2030, the diabetes pandemic will likely affect more than 10% of the world's population. The personal, public health, and economic crises implicit in this trend call for decisive action. Yet, escalating dilemmas thwart full realization of current therapies. First, controversial studies, such as the Action to Control Cardiovascular Risk in Diabetes (ACCORD) Trial, have amplified calls to individualize glycated hemoglobin (A1C) targets in the absence of adequate infrastructures for supporting personalized care. Second, costlier medications and technologies addressing more nuanced aspects of metabolic dysfunction are expanding options for diabetes management amidst growing disparities between "affordable" and "best" care. Third, common clinical quandaries, such as discrepancies between A1C and self-monitoring of blood glucose data, as well as misconceptions about long-term glycemic assessment, compound entrenched cycles of inadequate self-care, delayed intervention, and suboptimal glycemic outcomes. Because individual, clinical, and public policy responses to these conflicting forces are based largely on methodologies for glucose measurement, a panel of clinical experts from Europe and North America was convened to reexamine our glucose measuring tools and determine ways in which they can be better applied toward more purposeful processes of glycemic management. Among the main issues addressed were the need for caution in interpreting A1C for individual patients, the role of alternative biomarkers in identifying aspects of glycemic dysregulation not captured by A1C, and the value of using patients' own glucose data to consolidate therapeutic, educational, and behavior-change objectives.

Analyze the effectiveness of mandated point-of-care (POC) blood glucose (BG) meter quality control (QC) testing. All POC BG QC tests were analyzed to evaluate operator and strip/meter error rates and institutional cost. POC BG QC test failure (17/103,580 over 24 months) was low and no meters failed subsequent linearity testing. Examining individual QC measures shows that operator error occurs frequently and total error rate is related to QC familiarity (>50 QC tests/month, 2.4%; <50 QC tests/month, 3.8%, p < .001). Even among the most competent operators, strip/meter error (1.2 ± 0.3%) accounted for 50% of total error. Compared with manufacturer-recommended QC testing, Joint Commission mandated POC BG QC testing during 2008/2009 incurred excess costs of approximately US$127,000. POC BG meter failure within current guidelines is rare and does not justify the cost of daily QC testing. Frequent QC testing can identify operators needing retraining in POC testing. Strip/meter QC errors are common, are not prevented by current QC testing standards, and may contribute to clinical errors., (© 2012 National Association for Healthcare Quality.)