868-P: Live Coaching Improves Glycemic Control and DSMQ Scale in People with Type 2 Diabetes

Background Telemedicine for people with type 2 diabetes (T2D) has the potential to positively impact self-management behaviors and improve health outcomes. The Onduo Virtual Diabetes Clinic (VDC) is a comprehensive telehealth program for people with T2D that combines mobile app technology, remote personalized lifestyle coaching from certified diabetes educators and health coaches, connected devices including blood glucose meters and continuous glucose monitoring systems, and clinical support from board certified endocrinologists. Objective To describe the VDC care delivery model and present preliminary data on change in glycemic control in program participants with up to 6 months of follow-up. Methods Adults ≥18 years of age with T2D and who were members of sponsoring health plans and employers throughout the US were eligible to participate. Those who elected to enroll downloaded the VDC app to their smartphone, provided demographic and clinical information, completed an onboarding survey, and were mailed a self-management kit that included a connected blood glucose meter, test strips and a home glycosylated hemoglobin (HbA1c) testing kit. Participants interacted with their care team primarily through the VDC app, with occasional phone calls, and by synchronous video consultations with endocrinologists, as clinically appropriate. Change in glycemic control in participants who completed a baseline survey from February 2018 through December 31, 2018, with an initial HbA1c measurement within 30 days of enrollment and a follow-up measurement between 90 and 180 days after baseline was analyzed. Results Participants (n=740) were (mean ± SD): 53.8 ± 8.8 years of age, 62% female, BMI 35.6 ± 8.5, initial HbA1c 7.7% ± 1.8, 31.0% were on insulin and 25.9% were on sulfonylureas at baseline, and 30.0% lived in a rural area. HbA1c decreased significantly by 2.3% ± 1.9, 0.7% ± 1.0 and 0.2% ± 0.8 across the baseline categories of >9.0%, 8.0% to 9.0% and 7.0% to <8.0%, respectively (all P<.001). Within these categories, HbA1c improved in 91.9%, 77.3% and 63.5% of participants. For the group with an initial HbA1c >9.0%, HbA1c decreased from 10.7% ± 1.4 to 8.3% ± 1.5, and when stratified by HbA1c ≥8.0% the mean decrease in HbA1c was 1.5%, from 9.5% ± 1.5 to 8.0% ± 1.3, with 84.5% of participants demonstrating improvement. Participants with an initial HbA1c <7.0% who were meeting treatment targets at baseline, HbA1c 6.3% ± 0.4, continued to maintain this level of glycemic control at follow-up, HbA1c 6.4% ± 0.6 (ns). Conclusions Participation in the VDC was associated with a significant improvement in HbA1c in adults with T2D who were not meeting treatment targets, with the greatest improvement observed in those with an initial HbA1c >9.0%. Importantly, the majority of program participants experienced an improvement in glycemic control. Our findings suggest that the VDC program is an effective approach to support individuals with T2D and their clinicians in diabetes management between office visits.

BackgroundPatients with poorly controlled type 2 diabetes (T2D) experience increased morbidity, increased mortality, and higher cost of care. Self-monitoring of blood glucose (SMBG) is a critical component of diabetes self-management with established diabetes outcome benefits. Technological advancements in blood glucose meters, including cellular-connected devices that automatically upload SMBG data to secure cloud-based databases, allow for improved sharing and monitoring of SMBG data. Real-time monitoring of SMBG data presents opportunities to provide timely support to patients that is responsive to abnormal SMBG recordings. Such diabetes remote monitoring programs can provide patients with poorly controlled T2D additional support needed to improve critical outcomes.ObjectiveTo evaluate 6 months of a diabetes remote monitoring program facilitated by cellular-connected glucose meter, access to a diabetes coach, and support responsive to abnormal blood glucose recordings greater than 400 mg/dL or below 50 mg/dL in adults with poorly controlled T2D.MethodsPatients (N=119) receiving care at a diabetes center of excellence participated in a two-arm, 12-month randomized crossover study. The intervention included a cellular-connected glucose meter and phone-based diabetes coaching provided by Livongo Health. The coach answered questions, assisted in goal setting, and provided support in response to abnormal glucose levels. One group received the intervention for 6 months before returning to usual care (IV/UC). The other group received usual care before enrolling in the intervention (UC/IV) for 6 months. Change in hemoglobin A1c (HbA1c) was the primary outcome, and change in treatment satisfaction was the secondary outcome.ResultsImprovements in mean HbA1c were seen in both groups during the first 6 months (IV/UC −1.1%, SD 1.5 vs UC/IV −0.8%, SD 1.5; P<.001). After crossover, there was no significant change in HbA1c in IV/UC (mean HbA1c change +0.2, SD 1.7, P=.41); however, those in UC/IV showed further improvement (mean HbA1c change −0.4%, SD 1.0, P=.008). A mixed-effects model showed no significant treatment effect (IV vs UC) over 12 months (P=.06). However, participants with higher baseline HbA1c and those in the first time period experienced greater improvements in HbA1c. Both groups reported similar improvements in treatment satisfaction throughout the study.ConclusionsPatients enrolled in the diabetes remote monitoring program intervention experienced improvements in HbA1c and treatment satisfaction similar to usual care at a specialty diabetes center. Future studies on diabetes remote monitoring programs should incorporate scheduled coaching components and involve family members and caregivers.Trial RegistrationClinicalTrials.gov NCT03124043; https://clinicaltrials.gov/ct2/show/NCT03124043

The aim of the present 24-week multicentre randomized non-inferiority trial was to compare the efficacy and safety of two insulin intensification strategies in uncontrolled type 2 diabetes despite optimized basal insulin therapy. Patients with fasting plasma glucose (FPG) <130 mg/dL and HbA1c 7.0%-10.0% while on insulin glargine were randomized to a basal-prandial group (stepwise addition of insulin glulisine) or a premixed insulin group (insulin aspart/insulin aspart protamine 30/70 starting with 6 IU twice daily). The primary endpoint was the change in HbA1c after 24 weeks (non-inferiority margin 0.4%). At Week 24, the adjusted mean change from baseline HbA1c was -0.94 ± 0.09% and -1.04 ± 0.09% in basal-prandial and premixed insulin groups, respectively, with a mean difference of -0.09% (95% confidence interval [CI] -0.35, 0.16). A lower rate of hypoglycemia with a similar reduction in HbA1c was observed during stabilization of the total daily insulin dose in the premixed insulin group (Weeks 0-12). After stabilization of the total daily insulin dose, the rate of hypoglycemia and the total daily insulin dose were similar in the two groups. The efficacy and safety of the two intensifying regimens were similar after stabilization of the total daily insulin dose when oral agents were maintained. Starting with a lower total daily insulin dose with a gradual change in the treatment regimen was helpful in reducing the rate of hypoglycemia during initial stabilization of the total daily insulin dose.

IntroductionGlycated haemoglobin A1c (HbA1c) is the established standard measurement for assessment of glycaemic control in people with diabetes. Here we report on a meta-analysis of real-world observational studies on the impact of flash continuous glucose monitoring on glycaemic control as measured by HbA1c.MethodsA total of 271 studies were identified in our search, of which 29 contained data reporting changes in HbA1c over periods from 1 to 24 months that could be used in a statistical analysis. Our meta-analysis focuses on observed change in HbA1c at either 2, 3 or 4 months, in adult or paediatric subjects, as well as a longitudinal analysis up to 12 months in adult subjects. These data were drawn from 25 of the studies identified in our initial search. These reported HbA1c data up to 12 months in a total of 1723 participants with type 1 diabetes (T1D) or type 2 diabetes (T2D) using the FreeStyle Libre® flash glucose monitoring system.ResultsOverall mean change in laboratory HbA1c across study subjects at 2–4 months was − 0.55% (95% CI − 0.70, − 0.39). Amongst the 1023 adults, mean change in HbA1c was − 0.56% (95% CI − 0.76, − 0.36); for the 447 children and adolescents, mean change in HbA1c was − 0.54% (95% CI − 0.84, − 0.23). Based on regression analysis, the degree of change in HbA1c correlated with the initial HbA1c of the study population. A longitudinal analysis in adult subjects (n = 1276) shows that HbA1c fell within the first 2 months and changes were sustained up to 12 months. No significant differences were detected between T1D and T2D.ConclusionThe meta-analysis reported here confirms that starting the FreeStyle Libre system as part of diabetes care results in a significant and sustained reduction in HbA1c for adults and children with T1D and for adults with T2D.FundingAbbott Diabetes Care.

Improved long-term outcomes in high-risk patients receiving registered dietitian nutritionist care

Registered Dietitian Nutritionists Are Associated with Improved Long-Term Clinical Outcomes in High-Risk Patients

Diabetes prevalence is increasing globally especially in the Asian subcontinent. It is expected that by the year 2030 there may be close to 400 million people with diabetes. All of the research in the past 25 years has clearly documented the effectiveness of improving glucose control in reducing long-term complications of diabetes, both microvascular and macrovascular. The improvement in glucose control usually requires continuous intensive diabetes management, particularly in insulin-requiring patients, which must include home self-monitoring of blood glucose (SMBG). Despite the convincing evidence, the role of SMBG in diabetes management is still being debated even though its availability in the past 35 years has revolutionised diabetes care, especially at home. The International Diabetes Federation (IDF) recently published guidelines for SMBG use in non-insulin-treated diabetic patients, recommending that SMBG should be used only when patients and/or their clinicians possess the ability, willingness and knowledge to incorporate SMBG and therapy adjustment into their diabetes care plan. The IDF also recommends that structured SMBG be performed with the choice of applying different defined blood glucose testing algorithms to patients' individual diabetes care plans. These defined blood glucose testing algorithms give SMBG a medically meaningful structure to collect high quality glucose information and are called structured SMBG. Former SMBG studies have demonstrated SMBG to be beneficial when patients receive feedback regarding the impact of their behaviours on SMBG results. Other studies which did not link SMBG results to these principal behaviours have shown no SMBG benefit. A new wave of clinical studies performed after the release of the IDF guideline have recently been published and have proved the success of the new application of SMBG. The reasons for this ongoing debate may in part be due to rising healthcare costs globally, lack of convincing data in non-insulin-requiring patients with type 2 diabetes in randomised controlled clinical trials and multiple controversial meta-analyses performed on several studies. Sometimes the decisions are extended to insulin-requiring patients, even those with type 1 diabetes. For example, last year in the state of Washington in the USA, legislators were going to stop reimbursing glucose test strips for children with type 1 diabetes. After much debate with committee members (who were not diabetologists and or endocrinologists) and law makers, not only SMBG but even in some cases continuous glucose monitoring (CGM) is now reimbursed. The issue was simply educating non-understanding but well-meaning people whose main concern is saving money. In the end, no one, even those not familiar with paediatric type 1 diabetes, can disagree about the need for SMBG in this age group. It seems to us that we should instead be spending our time and effort in advancing the field and improving diabetes management for patients through newer technologies like CGM and closed-loop systems. As discussed in the section on CGM (Chapter 2) there is ample data from both non-randomised and randomised clinical trials showing the efficacy in reducing time spent in hypoglycaemia and hyperglycaemia along with improvement in glucose control without introducing any additional medication. We hope that the future will be spent in advancing the care rather than useless meta-analyses or going back in time. It is worthwhile to review existing evidence about SMBG to learn, transfer and apply knowledge about the core requirement for good diabetes management, glucose information. Fendler W, Hogendorf A, Szadkowska A, Młynarski W Department of Pediatrics, Oncology, Hematology and Diabetology, Medical University of Lodz, Poland Pediatr Endocrinol Diabetes Metab 2011; 17 : 57–63 Background: SMBG is one of the major components of diabetes management. Aims: To evaluate the potential for miscoding of a personal glucometer, to define a target population among paediatric patients with diabetes for a non-coding glucometer and to assess the accuracy of the Contour TS non-coding system. Methods: Potential for miscoding during SMBG was evaluated by means of an anonymous questionnaire, with worst and best case scenarios evaluated depending on the response pattern. Testing of the Contour TS system was performed according to the national committee for clinical laboratory standards guidelines. Results: The estimated frequency of individuals prone to non-coding ranged from 68.21% [95% confidence interval (CI) 60.70%–75.72%] to 7.95% (95% CI 3.86%–12.31%) for the worse and best case scenarios, respectively. Factors associated with increased likelihood of non-coding were a smaller number of tests per day, a greater number of individuals involved in testing and self-testing by the patient. The Contour TS device showed intra- and inter-assay accuracy of –95%, a linear association with laboratory measurements (R2 = 0.99, p < 0.0001) and small bias of –1.12% (95% CI –3.27% to 1.02%). Clarke error grid analysis showed 4% of values within the benign error zone (B) with the other measurements yielding an acceptably accurate result (zone A). Conclusions: The Contour TS system showed sufficient accuracy to be safely used in the monitoring of paediatric patients with diabetes. Patients from families with a high throughput of test-strips or multiple individuals involved in SMBG using the same meter are candidates for clinical use of such devices due to an increased risk of calibration errors. Comment: This study further highlights the role of making SMBG simpler and easier so that patients can monitor the glucose more effectively. The current study used the Contour TS system which does not require coding by the patient and thus removes the barrier of mis-coding of SMBG. We personally think that all meters going forward must be non-coding meters. Nerhus K 1 , Rustad P 2 , Sandberg S 1,3 1 Norwegian Centre for Quality Improvement of Primary Care Laboratories, Department of Public Health and Primary Health Care, University of Bergen, Bergen, Norway, 2 Norwegian Clinical Chemistry EQA-Program, Fürst Medical Laboratory, Oslo, Norway, 3 Laboratory of Clinical Biochemistry, Haukeland University Hospital, Bergen, Norway Diabetes Technol Ther 2011; 13: 883–92 Background: Analytical quality of SMBG can be affected by environmental conditions. Aims: To determine the influence of a shift in the ambient temperature immediately before measurement and taking measurements in the lower and upper part of the operating temperature range. Methods: Different SMBG systems (n = 9) available on the Norwegian market were tested with heparinised venous blood (4.8 and 19.0 mmol/l). To test the effect of a shift in ambient temperature, the glucometer and strips were equilibrated for 1 h at 5 °C or 30 °C before the meter and strips were moved to room temperature, and measurements were performed after 0, 5, 10, 15 and 30 min. To test the lower and upper temperature range, measurements were performed at 10 °C and at 39 °C after 1 h for temperature equilibration of the glucometer and strips. All the measurements were compared with measurements performed simultaneously on a meter and strips kept the whole time at room temperature. Results: Six of nine SMBG systems overestimated and/or underestimated results by more than 5% after moving meters and strips from 5 °C or 30 °C to room temperature immediately before the measurements. Two systems underestimated the results at 10 °C. One system overestimated and another underestimated the results by more than 5% at 39 °C. Conclusions: A rapid shift in the ambient temperature affects analytical performance. Therefore patients need to wait at least 15 min for temperature equilibration of affected meters and strips before measuring blood glucose. Comment: This study highlights the importance of ambient temperature on analytical performance of SMBG. The study shows that rapid shift in ambient temperature may affect the accuracy and bias in SMBG measurement and highlights the need for 15 min temperature equilibration. In addition to what has been highlighted in the study, future studies also need to assess the accuracy of existing meters (especially the one using glucose oxidase) at higher altitudes (10,000 feet or higher). It is known that many of these meters do not perform well at high altitudes. McAndrew LM 1,2 , Horowitz CR 3 , Lancaster KJ 4 , Quigley KS 2,5,6 , Pogach LM 1,2 , Mora PA 7 , Leventhal H 8 1 War Related Illness and Injury Study Center and REAP Center for Healthcare Knowledge Management, Department of Veterans Affairs, New Jersey Health Care System, East Orange, NJ, USA, 2 University of Medicine and Dentistry of New Jersey, Newark, NJ, USA, 3 Department of Health Evidence and Policy, Mount Sinai School of Medicine,New York, NY, USA, 4 Department of Nutrition, Food Studies and Public Health, New York University, New York, NY, USA, 5 Department of Veterans Affairs, Edith Nourse Rogers Memorial VA Hospital, Bedford, MA, USA, 6 Department of Psychology, Northeastern University, Boston, MA, USA, 7 Psychology Department, University of Texas at Arlington, Arlington, TX, USA, and 8 Institute for Health, Health Care Policy and Research, Rutgers University, New Brunswick, NJ, USA J Diabetes 2011; 3 : 147–52; Comment in J Diabetes 2011; 3 : 93–4 Background: It is unknown whether SMBG can motivate adherence to dietary recommendations. Aims: To evaluate if patients who used more SMBG would also report lower fat and greater fruit and vegetable consumption. Methods: This was a cross-sectional study of primarily minority individuals living with diabetes in East Harlem, New York (n = 401). Fat intake and fruit and vegetable consumption were measured with the Block Fruit/Vegetable/Fiber and Fat Screeners. Results: Greater frequency of SMBG was associated with lower fat intake [r(s) = –0.15; p < 0.01], but not fruit and vegetable consumption. The effects of SMBG were not moderated by insulin use. A significant interaction was found between frequency of SMBG and changing one's diet in response to SMBG on total fat intake. Conclusions: The frequency of SMBG was associated with lower fat intake. The data suggest that participants who use SMBG to guide their diet do not have to monitor multiple times a day to benefit. Comment: This study further highlights the importance of SMBG in daily lifestyle changes. Subjects with higher frequency of SMBG consumed less fat, in part related to overall education and seeing the impact from making dietary changes on SMBG levels. Kuo CY 1,2 , Hsu CT 3 , Ho CS 3 , Su TE 3 , Wu MH 4 , Wang CJ 2,5 1 Department of Clinical Laboratory, Tai-An Hospital, Taichung, Taiwan, 2 Institute of Biochemistry and Biotechnology, Chung Shan Medical University, Taichung, Taiwan, 3 Department of Core Technical Research, Bionime Corporation, Taichung, Taiwan, 4 Department of Laboratory Medicine, Min-Sheng General Hospital, Taoyuan, Taiwan, 5 Department of Medical Research, Chung Shan Medical University Hospital, Taichung, Taiwan Diabetes Technol Ther 2011; 13 : 596–600 Background: SMBG systems should at least meet the minimal requirement of the World Health Organization's ISO 15197:2003. For tight glycaemic control, a tighter accuracy requirement is needed. Methods: Seven SMBG systems were evaluated for accuracy and precision: Bionime Rightest™ GM550 (Bionime Corp., Dali City, Taiwan), Accu-Chek® Performa (Roche Diagnostics, Indianapolis, IN, USA), OneTouch® Ultra®2 (LifeScan Inc., Milpitas, CA, USA), MediSense® Optium™ Xceed (Abbott Diabetes Care Inc., Alameda, CA, USA), Medisafe (TERUMO Corp., Tokyo, Japan), Fora® TD4227 (Taidac Technology Corp., Wugu Township, Taiwan) and Ascensia Contour® (Bayer HealthCare LLC, Mishawaka, IN, USA). The 107 participants were 23–91 years old. The analytical results of seven SMBG systems were compared with those of plasma analysed with the hexokinase method (Olympus AU640, Olympus America Inc., Center Valley, PA, USA). Results: The imprecision of the seven blood glucose meters ranged from 1.1% to 4.7%. Three of the seven blood glucose meters (42.9%) fulfilled the minimum accuracy criterion of ISO 15197:2003. The mean absolute relative error value for each blood glucose meter was calculated and ranged from 6.5% to 12.0%. Conclusions: More than 40% of evaluated SMBG systems meet the minimal accuracy criterion requirement of ISO 15197:2003. However, considering a tighter criterion for accuracy of ±15%, only the Bionime Rightest GM550 meets this requirement. Manufacturers have to try to improve accuracy and precision and to ensure the good quality of blood glucose meters and test strips. Comment: This study further highlights the need for more accurate SMBG systems. Their data concluded that more than 40% of the evaluated SMBG systems meet the minimum ISO criteria. Since patients use blood glucose information for adjusting their insulin dose and/or treating hypoglycaemia, the accuracy of the glucose meters has to be consistent and improved. Hortensius J 1 , Slingerland RJ 2 , Kleefstra N 1,3,4 , Logtenberg SJ 1 , Groenier KH 5 , Houweling ST 3,6 , Bilo HJ 1,4 1 Diabetes Centre, Isala Clinics, Zwolle, The Netherlands, 2 Department of Clinical Chemistry, Isala Clinics, Zwolle, The Netherlands, 3 Medical Research Group, Langerhans, The Netherlands, 4 Department of Internal Medicine, University Medical Center, Groningen, The Netherlands, 5 Department of General Practice, University of Groningen, Groningen, The Netherlands, and 6 General Practice Sleeuwijk, Sleeuwijk, The Netherlands Diabetes Care 2011; 34 : 556–60 Background: There is no agreement regarding the use of the first or second drop of blood for glucose monitoring. Aims: To investigate whether capillary glucose concentrations, as measured in the first and second drops of blood, differed ≥10% compared with a control glucose concentration in different situations. Methods: Capillary glucose concentrations were measured in two consecutive drops of blood in 123 patients with diabetes in the following circumstances: without washing hands, after exposing the hands to fruit, after washing the fruit-exposed hands, and during application of different amounts of external pressure around the finger. The results were compared with control measurements. Results: Not washing hands led to a difference of ≥10% in glucose concentration in the first and in the second drops of blood in 11% and 4% of the participants, respectively. In fruit exposed fingers, these differences were found in 88% and 11% of the participants, respectively. Different external pressures led to ≥10% differences in glucose concentrations in 5%–13% of the participants. Conclusions: Washing hands with soap and water, drying them, and using the first drop of blood for SMBG is recommended. If washing hands is not possible, it is acceptable to use the second drop of blood after wiping away the first drop. External pressure may lead to unreliable readings. Comment: Over the years we have probably under-emphasised the importance of technique with SMBG. One has to wonder how much iatrogenic hypoglycaemia has occurred due to unintended exposure to glucose on the hands, and how often CGM devices are due to technique with SMBG use. 1,2 , 3 , 4 , 5 , 6 , 7 , 8 , 8 , 8 1 University of CA, USA, 2 Diabetes CA, USA, 3 University of CA, USA, 4 University Health System, USA, 5 America Diabetes USA, 6 Health IN, USA, 7 USA, and 8 Diagnostics, Indianapolis, IN, USA Diabetes Care 2011; 34 : To assess the effectiveness of structured blood glucose testing in controlled patients with type 2 diabetes without insulin Methods: A study patients with type 2 diabetes (n = and glycaemic control from 34 care in the were randomised to an control with care or a structured testing with care and at least use of structured SMBG. patients and were to use a to glucose consecutive The was measured at Results: The analysis = = showed greater in mean in the compared with the = p = analysis = = showed even greater mean in the compared with the p < more patients a at the first compared with patients, of the p < and patients significant < 0.0001) in Conclusions: use of structured SMBG glycaemic control and more changes in patients with type 2 diabetes without Comment: It is with an healthcare using a structured glucose testing can improve glucose control in non-insulin-treated Potential are of this can be in a with the more time in a care to be , 5 , 6 , 1,4 1 Department of and Laboratory Medicine, University of 2 Department of and University of 3 Department of Pediatrics, University of 4 Laboratory 5 Corporation, MA, USA, and 6 Department of Health University of J Diabetes Technol 4 : Aims: To analytical error in and glucose meters by in and Methods: The of and were tested and in with each glucose meter and with a plasma glucose method at glucose was by consecutive analysis (n = at glucose levels. analysis was used to the bias associated with the and in Results: Three meters demonstrated bias that was glucose bias on the and the of bias was on small significant on meters. of and of increased the bias and was by of total analytical the glucose meter devices of total analytical error in glucose measurement ranged from to the Conclusions: The of glucose meters to significant analytical is the analytical Comment: with to for SMBG and the research is it does not that many people the This has impact on as new guidelines for greater of are the impact on SMBG accuracy be particularly by the device should be a 1 , 1 , 2 , 3 1 Health and 2 Health, and 3 of and Department of Internal Medicine, : Aims: To evaluate the of SMBG in patients with type 2 diabetes with in Methods: In a study a of diabetes was used to from a published study of SMBG in patients with type 2 diabetes, with and with no of a time was from the of a healthcare and clinical were at Results: or times daily SMBG was associated with in which led to increased and and of diabetes complications compared with no SMBG in type 2 diabetes patients on costs increased by and in patients SMBG or times daily compared with those not using SMBG. were well at and per year respectively. Conclusions: SMBG is to be by standards in patients on in the Comment: This analysis is on a showing of and The concern of is that this analysis is not a randomised controlled and at best the data are about the efficacy of this population using this analysis is probably on controversial 1,2 , 3 , S 3 , 1 Health Research, University School of Medicine, Indianapolis, IN, USA, 2 Institute for Health Care, Indianapolis, IN, USA, 3 of University School of Medicine, Indianapolis, IN, USA, and 4 Diabetes and Center, University School of Medicine, Indianapolis, IN, USA Diabetes 2011; : To assess the and of a glucose monitoring system for with type 1 diabetes and their Methods: Patients with type 1 diabetes who been for at least 1 year in the used the system for 6 3 to and with the glucose monitoring as well as how use of the system affect quality of and diabetes management. Results: about the a number of significant that affected use of the all that the in monitoring testing was The use of the did not the quality of their of with their their of diabetes, or their glycaemic control within the time of the Conclusions: This that glucose monitoring can be used in an population to and in self-monitoring Comment: for both SMBG and CGM is clearly the future for with type 1 diabetes. The will be to how to best use this to improve in this To the is new to how best to use more studies will be to this P 1 , 2 , ST 3 , 2 , 2 , 4 , Bilo 5 , Bilo HJ 1 Department of Internal Medicine, Hospital, The Netherlands, 2 Department of Clinical Chemistry, Isala Clinics, Zwolle, The Netherlands, 3 Department of Isala Clinics, Zwolle, The Netherlands, 4 Centre for The Netherlands, 5 Department of Internal Medicine, Isala Clinics, Zwolle, The Netherlands, and 6 Department of Internal Medicine, University Medical Centre, Groningen, The Netherlands One 5 : Background: Patients with diabetes part in and thus blood glucose meters are studies bias in blood glucose measurements using different at high To evaluate if glucose are more by the lower pressure at than glucose Methods: measurements at of nine glucose glucose were compared with glucose measurement on a at and with a laboratory glucose blood of different glucose were were at a bias from glucose and from glucose mmol/l). Results: significant difference was between measurements at and for glucose or glucose as a Two glucose did not meet performance criteria. Conclusions: high all tested glucose did not influence of All for two glucose performed within criteria. are glucose concentration at high high one glucose best precision and Comment: testing for SMBG meters may be In glucose test strips should be at high altitudes. not in this it should be that patients do not this into when or 1 , J 2 , 2 , 1 , 3 , 4 , J 3 , 5 , J 6 , 7 , 7 , 8 1 Department of Health University of Health Center, USA, 2 and Health Department of Medical and University of USA, 3 Department of and Health University of USA, 4 Diabetes Care Center, Medical USA, 5 Department of University of USA, 6 Medicine Technology Center USA, 7 Department of Medicine, University of USA, and 8 Health Research USA J Aims: To assess the and of using as part of an existing system for between patients with diabetes and a care Methods: In glucose meter and two to feedback on glycaemic control were Results: glucose meter with and data feedback were the system to an and feedback system for value in the system as an to the and Conclusions: diabetes management systems may one to improve the quality of diabetes Comment: best to in a care for type 2 diabetes is still It is that there will be different of that will for different patient the use of the as a means of that device like the of in diabetes management. the now seems to be how to is a It may be that will be the only for many the of time this population 1 , 2 1 Centre for Policy Research, of Health Health Policy and Research, University of and 2 Institute for Medicine, and Health University Medical Centre 2011; : Background: the of and in Patients with 2 Diabetes a in the risk of in patients with type 2 diabetes who performed SMBG. Aims: To evaluate if these are by a that time Methods: The bias in the study was and demonstrated that it is to the effect of SMBG on Results: In the study, patients were as exposed to SMBG for their whole time if performed SMBG for at least 1 year during the study the time between and the after 1 year of self-monitoring was performed is for patients with SMBG. Patients to at least 1 year to be as exposed to this and were from The total of in the SMBG is at least of at risk After of as the relative risk from to Conclusions: The effect of SMBG on in the study is by time Comment: The study is one of the trials in the of SMBG. Study is probably a major for between the studies. Kleefstra N 1,2 , Hortensius J 1 , Logtenberg SJ 1 , 3 , Groenier K 4 , Houweling ST 2,5 , 6 , 2 , Bilo HJ 1 Diabetes Centre, Isala Clinics, Zwolle, The Netherlands, 2 Medical Research Langerhans, Zwolle, The Netherlands, 3 Department of Clinical Chemistry, Isala Clinics, Zwolle, The Netherlands, 4 Department of General Practice, University of Groningen, Groningen, The Netherlands, 5 General Practice Sleeuwijk, Sleeuwijk, The Netherlands, 6 Department of Internal Medicine, University Medical Center Groningen, Groningen, The Netherlands J : Background: It is not if SMBG glycaemic control in patients with type 2 diabetes. To investigate the effects of SMBG in patients with type 2 diabetes who were in glycaemic Methods: Patients years with an of using one to two blood glucose were in the Patients (n = were to receive SMBG to care or to with care for 1 A glucose value and glucose values were measured The efficacy was quality of and were using the Health the the Diabetes and the Results: in between was (95% CI to p = There were no significant changes between on the type or for the which was lower in the difference (95% CI to Conclusions: type 2 diabetes patients some of their the use of SMBG in these patients is and its use should be Comment: This is another SMBG study in non-insulin-treated type 2 the of not patients what to do with the information is one has to wonder if this at some to have some of the it is to that the in care is to more education and time than is in many of these studies. A 1 , 1 , 1 , S 2 , S 3 , A 1 , A 1 , 1 , 4 , 3 , 3 , 1 1 Department of and School of Medicine, 2 Department of School of Medicine, 3 Department of Biochemistry, School of Medicine, and 4 Department of School of Medicine, Diabetes Technol Ther : Background: glucose meters may not be accurate to Aims: of the accuracy and the capillary and venous of different Xceed (Abbott Diabetes Care, Alameda, CA, USA), Contour TS (Bayer Diabetes Care, (Roche Milpitas, CA, and Inc., in an Methods: The insulin hypoglycaemia test was performed for of mean age was measured from venous blood and capillary before and after of insulin were analysed in the laboratory by the hexokinase In tests for method and precision were also performed by the venous Results: All to hypoglycaemia to some was in error zone and was in the error zone Xceed and Contour TS and were than the other two according to error grid analysis or International for criteria. The in tests were consistent with the clinical The capillary and venous of and were than the other Not all are accurate in blood glucose levels. The patients and the should be of these of the and give more to the hypoglycaemia than the values with the These results that there is a need for the of accuracy standards of at blood glucose levels. Comment: We have the that meters are from especially at levels. patients can state a time when an The are not only for the of hypoglycaemia but also as we forward with CGM about how this about this the with the for use of the meters our clinical with patient error us that accuracy a for glucose meters at levels. has research from Inc., Corporation, Inc., and is a for Diagnostics, Diabetes Care and

The purpose of this study was to evaluate the effectiveness of directly integrating self-monitoring blood glucose (BG) information with insulin pump therapy on overall glycemic control. In this randomized trial, 34 youth with type 1 diabetes using insulin pump therapy were trained on the use of the Deltec Cozmo Insulin Pump. Seventeen were randomized to use the CoZmonitor Blood Glucose Module, a device that attaches to the back of the pump using FreeStyle technology to perform BG tests which read directly on the pump screen. The remaining 17 (control group) used a FreeStyle Flash meter, a stand-alone BG meter, for their BG testing. At baseline, 3 and 6 months, the subjects filled out a questionnaire, had a hemoglobin A1c (HbA1c) test, and had pumps and meters downloaded. After 3 months of study, there were no changes in mean HbA1c (+/- SD) values for the experimental (8.7 +/- 1.1 to 8.6 +/- 1.1) or the control groups (9.1 +/- 1.4 to 9.2 +/- 1.5). There were also no significant differences in HbA1c values after 6 months. The average number of BG tests per day did not change significantly in either group during the study. After 3 and 6 months, the experimental group rated satisfaction with the use of the CoZmonitor at 4.4 and 3.8 (respectively) on a five-point Likert scale, with 5 being the most satisfied. Although significant changes in HbA1c values or the number of BG tests were not found, use of the BG module had a positive level of satisfaction.

Introduction: Data on switching from premixed insulin to a basal–bolus regimen in routine clinical practice are sparse. The aim was to evaluate the efficacy and safety of switching from twice-daily premixed insulin to basal glargine plus rapid-acting insulin in a “real-world” clinical practice setting in Belgium and The Netherlands.Methods: This prospective, 6-month, noninterventional, observational study was conducted in 37 centres in Belgium and 19 centres in The Netherlands. Adults (≥ 18 years of age) with type 2 diabetes were eligible if they were not taking oral antihyperglycaemic drugs or only taking metformin. The primary objective was the proportion of patients attaining glycated haemoglobin (HbA1c) < 7% at months 3 and 6. Secondary objectives included changes in HbA1c, weight, body mass index (BMI), insulin doses, hypoglycaemic events, and treatment satisfaction.Results: There were 214 patients from Belgium and The Netherlands enrolled. Mean age was 64.6 years, weight was 89.5 kg, BMI was 31.4 kg/m2, and duration of diabetes was 12.1 years. At month 6, the percentage of patients with HbA1c < 7% increased from 3.3% to 24.9% (p < 0.001). Mean HbA1c at baseline was 8.9%; mean change from baseline was -1.5% (p < 0.001). Glargine and prandial insulin doses increased (p < 0.001, each), while body weight and BMI were unchanged. Hypoglycaemic events did not increase. Overall treatment satisfaction improved significantly (p < 0.001).Conclusions: In a Belgian and Dutch clinical practice setting, patients with type 2 diabetes that is poorly controlled on premixed insulin experienced significant improvements in glycaemic control, without a concomitant increase in hypoglycaemic events or weight, when switched from premixed insulin to basal–bolus glargine plus rapid-acting insulin. As a result, treatment satisfaction significantly improved.

IntroductionThis 32-week, open-label, randomized, parallel-group, multinational trial aimed to compare the efficacy and safety of stepwise insulin intensification of biphasic insulin aspart 30 (BIAsp 30) relative to stepwise intensification of a basal–bolus regimen in insulin-naïve adults with type 2 diabetes (T2D) who continued pretrial treatment with metformin and sulfonylurea.MethodsAdults with T2D were randomized into one of two treatment arms for 32 weeks: (1) BIAsp 30 once daily (OD), with the possibility of stepwise treatment intensification up to BIAsp 30 three times daily (TID); (2) insulin glargine OD, with the possibility of stepwise treatment intensification with insulin aspart up to TID. The primary endpoint was change from baseline in HbA1c after 32 weeks.ResultsAfter 32 weeks, the estimated mean change in HbA1c from baseline was statistically significantly lower in the BIAsp 30 arm (− 1.18%) versus basal–bolus (− 1.36%) [estimated treatment difference 0.18%; 95% confidence interval (95% CI) 0.01; 0.36; p < 0.05]. The proportion of patients with HbA1c below 7.0% was statistically significantly lower with BIAsp 30 (42.9%) compared with basal–bolus (56.9%) (odds ratio 0.58; 95% CI 0.37; 0.89; p = 0.01). The overall rate of severe or blood glucose (BG)-confirmed hypoglycemic events was numerically lower for BIAsp 30 compared with basal–bolus, and a statistically significantly lower rate in nocturnal severe or BG-confirmed hypoglycemia in the BIAsp 30 arm relative to basal–bolus was observed: estimated rate ratio 0.32 (95% CI 0.13; 0.79), p = 0.0131. The proportion of patients with adverse events was similar in both treatment arms.ConclusionInsulin intensification with BIAsp 30 and basal–bolus showed an improvement in glycemic control; the change in HbA1c was statistically significantly lower for BIAsp 30 compared to basal–bolus. Basal–bolus treatment was accompanied by a numerically, and statistically significantly, higher rate of overall and nocturnal severe or BG-confirmed hypoglycemia, respectively, compared with BIAsp 30.FundingNovo Nordisk A/S.Trial RegistrationClinicalTrials.gov identifier, NCT02453685.

886-P: Response to Imeglimin for Japanese Patients with Type 2 Diabetes—Response Distribution Analysis of Individual Participant in Randomized Placebo-Controlled Trials

Dulaglutide, a glucagon-like peptide-1 (GLP-1) receptor agonist, has been approved for improving glycemic control and reducing the risk of cardiovascular (CV) adverse events. A previous result in healthy Chinese male subjects demonstrated the pharmacokinetic (PK) similarity of LY05008 and the licensed product dulaglutide, with comparable safety and immunogenicity profiles. A well-controlled phase 3 study with an adequate sample size was subsequently conducted for safety and efficacy evaluation. In a multicenter, randomized, open-label, active comparator phase 3 study, Chinese adults diagnosed with type 2 diabetes mellitus (T2DM) were randomly assigned 1:1 to receive a subcutaneous injection of 1.5 mg LY05008 or dulaglutide once weekly for 24 weeks. The primary endpoint was the mean change in HbA1c from baseline to Week 24. The secondary endpoints included the mean change in HbA1c from baseline to Week 12; the proportion of patients who had achieved HbA1c ≤ 6.5% at Weeks 12 and 24; and the mean change in body weight, fasting plasma glucose (FPG) level, and 2-h postprandial plasma glucose (PPG) level from baseline to Weeks 12 and 24. Safety, PK, and immunogenicity profiles were also included for data analysis. A total of 440 patients were randomized to receive LY05008 (n = 222) or dulaglutide (n = 218). The mean changes in HbA1c from baseline to Week 24 in the LY05008 group and dulaglutide group were -1.44% and -1.41%, respectively, with a least square mean difference (LSMD) and 95% confidence interval (CI) of 0.06% (-0.08, 0.19) (p > 0.05). Efficacy equivalence could be demonstrated since the 95% CI between the reference drug and a biosimilar fell entirely within the range of (-0.4%, 0.4%). The mean changes in HbA1c from baseline to Week 12 in the LY05008 group and dulaglutide group were -1.47% and -1.39% (p > 0.05), respectively. At Week 12, 40.1% of patients who received LY05008 and 42.2% of those who received dulaglutide had a decrease in the HbA1c level to 6.5% or less, and 60.4% and 60.6% of patients in the LY05008 group and the dulaglutide group had a decrease in the HbA1C level < 7%, respectively. At Week 24, 41.0% and 43.6% of patients achieved an HbA1c ≤ 6.5%. 55.9% and 66.5% of patients in the LY05008 group and the dulaglutide group achieved the HbA1c goal of < 7%, respectively. The mean changes in body weight from baseline to Weeks 12 and 24 in the LY05008 group and dulaglutide group were -2.01 and -1.71 kg (p > 0.05) and -2.68 and -2.42 kg (p > 0.05), respectively. The mean changes in FPG level from baseline to Weeks 12 and 24 in the LY05008 group and dulaglutide group were -2.578 and -2.681 mmol/L (p > 0.05) and -2.222 and -2.690 mmol/L, respectively. In the LY05008 group and the dulaglutide group, the mean changes in 2-h PPG levels from baseline to Weeks 12 and 24 were -4.364 and -4.800 mmol/L(p > 0.05) and-3.502 and -4.217 mmol/L (p > 0.05), respectively. The common treatment emergent adverse events (TEAEs) in the LY05008 and dulaglutide groups were decreased appetite, diarrhea, upper respiratory tract infection, hyperuricemia, nausea, urinary tract infection, and vomiting. Most TEAEs were mild to moderate in severity. No significant differences were observed between the groups in terms of TEAEs. Hypoglycemic events were noted in 0.9% of patients who had received LY05008 and in 3.7% of those who had received dulaglutide. Serious adverse events were reported in 4.1% of patients in the LY05008 group and in 3.7% of patients in the dulaglutide group. The PK parameter Ctrough and immunogenicity profiles were similar across the two treatment groups. The primary endpoint was met in this study through the demonstration of equivalent efficacy in HbA1c reduction in Chinese adults with T2DM between LY05008 and dulaglutide. Overall, the biosimilar product LY05008 showed comparable safety, PK, and immunogenicity profiles against the reference drug dulaglutide. ClinicalTrials.gov identifier: CTR20221721.

BackgroundDiabetes is a global epidemic affecting approximately 30 million people in the United States. The World Health Organization recommends using technology and telecommunications to improve health care delivery and disease management. The Livongo for Diabetes Program offers a remote monitoring technology with Certified Diabetes Educator outreach.ObjectiveThe purpose of this study was to examine health outcomes measured by changes in HbA1c, in time in target blood glucose range, and in depression symptoms for patients enrolled in a remote digital diabetes management program in a Diabetes Center of Excellence setting.MethodsThe impact of the Livongo for Diabetes program on hemoglobin A1c (HbA1c), blood glucose ranges, and depression screening survey results (Patient Health Questionnaire-2 [PHQ-2]) were assessed over 12 months in a prospective cohort recruited from the University of South Florida Health Diabetes Home for Healthy Living. Any patient ≥18 years old with a diagnosis of diabetes was approached for voluntary inclusion into the program. The analysis was a pre-post design for those members enrolled in the study. Data was collected at outpatient clinic visits and remotely through the Livongo glucose meter.ResultsA total of 86 adults were enrolled into the Livongo for Diabetes program, with 49% (42/86) female, an average age of 50 (SD 15) years, 56% (48/86) with type 2 diabetes mellitus, and 69% (59/86) with insulin use. The mean HbA1c drop amongst the group was 0.66% (P=.17), with all participants showing a decline in HbA1c at 12 months. A 17% decrease of blood glucose checks <70 mg/dL occurred concurrently. Participants with type 2 diabetes not using insulin had blood glucose values within target range (70-180 mg/dL) 89% of the time. Participants with type 2 diabetes using insulin were in target range 68% of the time, and type 1 diabetes 58% of the time. Average PHQ-2 scores decreased by 0.56 points during the study period.ConclusionsParticipants provided with a cellular-enabled blood glucose meter with real-time feedback and access to coaching from a certified diabetes educator in an outpatient clinical setting experienced improved mean glucose values and fewer episodes of hypoglycemia relative to the start of the program.

(Analytical) Accuracy of Blood Glucose Meters and Patients: How Do They Come Together?

The primary objectives of this study were to evaluate the change in glycated haemoglobin (HbA1c) and its association to clinical activities. The secondary objective was to elucidate moderators of the relationship between pharmacist-involved collaborative care (PCC) and change in HbA1c. This study was a retrospective cohort study conducted in a tertiary hospital over 12 months. Individuals with Type 2 diabetes, aged ≥21 years with established cardiovascular diseases were included while individuals with incomplete care documentation or missing data related to cardiovascular diseases were excluded. Individuals under the care of PCC were matched 1:1 based on baseline HbA1c with an eligible person who received care from the cardiologists (CC). Changes in mean HbA1c were analysed using linear mixed model. Linear regression was used to determine clinical activities that associated with improvement in HbA1c. Moderation analyses were conducted using the MacArthur framework. A total of 420 participants (PCC:210, CC:210) were analysed. The mean age of the participants was 65.6 ± 11.1 years, with the majority being male and Chinese. The mean HbA1c among participants in the PCC group decreased significantly after 6 months (PCC: -0.4% versus CC: -0.1%, P = 0.016), with maintenance of improvement at 12 months (PCC: -0.4% versus CC: -0.2%, P < 0.001). Frequencies of lifestyle counselling, reinforcement of visits to healthcare providers, health education, resolution of drug-related problems, emphasis on medication adherence, dose adjustments and advice on self-care techniques were significantly higher in the intervention group (P < 0.001). Improvements in HbA1c were associated with the provision of health education and medication adjustments.