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Summary Background Management of type 1 diabetes is challenging. We compared outcomes using a commercially available hybrid closed-loop system versus a new investigational system with features potentially useful for adolescents and young adults with type 1 diabetes. Methods In this multinational, randomised, crossover trial (Fuzzy Logic Automated Insulin Regulation [FLAIR]), individuals aged 14–29 years old, with a clinical diagnosis of type 1 diabetes with a duration of at least 1 year, using either an insulin pump or multiple daily insulin injections, and glycated haemoglobin (HbA1c) levels of 7·0–11·0% (53–97 mmol/mol) were recruited from seven academic-based endocrinology practices, four in the USA, and one each in Germany, Israel, and Slovenia. After a run-in period to teach participants how to use the study pump and continuous glucose monitor, participants were randomly assigned (1:1) using a computer-generated sequence, with a permuted block design (block sizes of two and four), stratified by baseline HbA1c and use of a personal MiniMed 670G system (Medtronic) at enrolment, to either use of a MiniMed 670G hybrid closed-loop system (670G) or the investigational advanced hybrid closed-loop system (Medtronic) for the first 12-week period, and then participants were crossed over with no washout period, to the other group for use for another 12 weeks. Masking was not possible due to the nature of the systems used. The coprimary outcomes, measured with continuous glucose monitoring, were proportion of time that glucose levels were above 180 mg/dL (>10·0 mmol/L) during 0600 h to 2359 h (ie, daytime), tested for superiority, and proportion of time that glucose levels were below 54 mg/dL ( Findings Between June 3 and Aug 22, 2019, 113 individuals were enrolled into the trial. Mean age was 19 years (SD 4) and 70 (62%) of 113 participants were female. Mean proportion of time with daytime glucose levels above 180 mg/dL (>10·0 mmol/L) was 42% (SD 13) at baseline, 37% (9) during use of the 670G system, and 34% (9) during use of the advanced hybrid closed-loop system (mean difference [advanced hybrid closed-loop system minus 670G system] −3·00% [95% CI −3·97 to −2·04]; p Interpretation Hyperglycaemia was reduced without increasing hypoglycaemia in adolescents and young adults with type 1 diabetes using the investigational advanced hybrid closed-loop system compared with the commercially available MiniMed 670G system. Testing an advanced hybrid closed-loop system in populations that are underserved due to socioeconomic factors and testing during pregnancy and in individuals with impaired awareness of hypoglycaemia would advance the effective use of this technology Funding National Institute of Diabetes and Digestive and Kidney Diseases.

Background: Barriers to mealtime insulin include complexity, fear of injections, and lifestyle interference. This multicenter, randomized controlled trial evaluated efficacy, safety, and self-reported outcomes in adults with type 2 diabetes, inadequately controlled on basal insulin, initiating and managing mealtime insulin with a wearable patch versus an insulin pen. Methods: Adults with type 2 diabetes (n = 278, age: 59.2 ± 8.9 years), were randomized to patch (n = 139) versus pen (n = 139) for 48 weeks, with crossover at week 44. Baseline insulin was divided 1:1 basal: bolus. Using a pattern-control logbook, subjects adjusted basal and bolus insulin weekly using fasting and premeal glucose targets. Results: Glycated hemoglobin (HbA1c) change (least squares mean ± standard error) from baseline to week 24 (primary endpoint) improved (P

Background:Little data exists regarding the impact of continuous glucose monitoring (CGM) in the primary care management of type 2 diabetes (T2D). We initiated a quality improvement (QI) project in a large healthcare system to determine the effect of professional CGM (pCGM) on glucose management. We evaluated both an MD and RN/Certified Diabetes Care and Education Specialist (CDCES) Care Model.Methods:Participants with T2D for >1 yr., A1C ≥7.0% to Results:Sixty-eight participants average age 61.6 years, average duration of T2D 15 years, mean A1C 8.8%, were identified. Pre to post pCGM lowered A1C from 8.8% ± 1.2% to 8.2% ± 1.3% (n=68, P=0.006). The time in range (TIR) and time in hyperglycemia improved along with more hypoglycemia in the subset of 37 participants who wore a second pCGM. Glycemic improvement was due to lifestyle counseling (68% of participants) and intensification of therapy (65% of participants), rather than addition of medications.Conclusions:Using pCGM in primary care, with an MD or RN/CDCES Care Model, is effective at lowering A1C, increasing TIR and reducing time in hyperglycemia without necessarily requiring additional medications.

Background: Islet autoimmunity may contribute to beta-cell dysfunction in type 2 diabetes (T2D). Its prevalence and clinical significance have not been rigorously determined. We investigated the prevalence of cellular and humoral islet autoimmunity in T2D and their relation to beta-cell function. Methods: The study was nested in the Glycemia Reduction Approaches in Diabetes – A Comparative Effectiveness (GRADE) study. Participants included 419 T2D patients (age 57·4±10·3 y [mean±SD], body mass index 33·6±6·2 kg/m2, diabetes duration 4·0±3·0 y, HbA1c 7·5±0·5%). We measured humoral (autoantibodies against GAD65, IA2, ZnT8) and cellular (T-cell autoreactivity against islet antigens) autoimmunity, beta-cell function (ratio of incremental area under the curve of C-peptide to that of glucose from 0–120 min of an oral glucose tolerance test [iAUC-CG]), and ratio of C-peptide to glucose from 0–30 min (∆C-peptide(0–30)/∆glucose(0–30)), and glycemic parameters. Findings: Cellular islet autoimmunity was present in 41·3%, humoral islet autoimmunity in 13·5%, and both in 5·3%. iAUC-CG and ∆C-peptide(0–30)/∆glucose(0–30) were lower among T-cell-positives than -negatives using two different adjustments for insulin sensitivity (iAUC-CG: 13·2% [95% CI 0·3, 24·4%] or 11·4% [95% CI 0·4, 21·2%] lower; ∆C-peptide(0–30)/∆glucose(0–30)) 19% [95% CI 3·1, 32·3%] or 17·7% [95% CI 2·6, 30·5%] lower). T-cell-positives had 0·17% higher HbA1c (95% CI 0·07,0·28) and 7·7 mg/dL higher fasting plasma glucose levels (95% CI 0·2,15·3) than T-cell-negatives. Interpretation: Islet autoimmunity is highly prevalent in patients with T2D. T-cell-mediated autoimmunity is associated with diminished beta-cell function and worse glycemic control. Funding Information: This study was funded by the NIH. This ancillary study to the GRADE study was independently funded by grant R01DK104832 (to AB and JPP) from the National Institute of Diabetes and Digestive and Kidney Diseases. The GRADE study is supported by a grant from the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) of the National Institutes of Health under Award Number U01DK098246. The planning of GRADE was supported by a U34 planning grant from the NIDDK (U34-DK-088043). The American Diabetes Association supported the initial planning meeting for the U34 proposal. The National Heart, Lung, and Blood Institute and the Centers for Disease Control and Prevention also provided funding support. The Department of Veterans Affairs provided resources and facilities. Additional support was provided by grant numbers P30 DK017047, P30 DK020541-44, P30 DK020572, P30 DK072476, P30 DK079626, P30 DK092926, U54 GM104940, UL1 TR000439, UL1 TR000445, UL1 TR001108, UL1 TR001409, UL1 TR001449, UL1 TR002243, UL1 TR002345, UL1 TR002378, UL1 TR002489, UL1 TR002489, UL1 TR002529, UL1 TR002535, UL1 TR002537, and UL1 TR002548. Educational materials have been provided by the National Diabetes Education Program. Material support in the form of donated medications and supplies has been provided by Becton, Dickinson an Company, Bristol-Myers Squibb, Merck, NovoNordisk, Roche Diagnostics, and Sanofi. Declaration of Interests: The authors declare no conflicts of interest. Ethics Approval Statement: Nineteen centers obtained local Institutional Review Board approval for the ancillary study and contributed participants.

Aim: Determine how patients review CGM and insulin pump data simultaneously to determine self-treatment adjustments. Methods: Subjects (n=21) verbally reported their interpretation/thoughts while examining an AGP (CGM + Insulin Pump) Report in a cognitive interview. Interviews lasted 45-90 minutes. Results: Subjects overwhelmingly prefer phone/watch interfaces; 75% do not have computers at home. Users report looking at their phones/CGM readings on average 16-60 times a day (1-4 times/hour); with several reporting high frequency of 15-45 times/hour. All subjects prefer colored graphs rather than numerical data on a single page report, with heavy preference to focus on CGM data with only occasional review of insulin pump data. Subjects felt the AGP CGM + Pump Report was “helpful” (86%), yet only 57% felt it was easy to understand due to the basal vs. bolus graphs. When asked to identify glucose data patterns: 95% noted trends, 67% noted hypoglycemia, 95% noted hyperglycemia, and 100% identified “missed” opportunities to treat high daily glucose levels. Bolus insulin graph responses included: bolus dose times of day helpful (100%), average meal bolus helpful (71%), and 73% understood the graph after an explanation, but only 38% could teach back offering specific advice. Subjects felt basal insulin graph made sense (90%). Subject confidence using AGP report data for self-care was high (95%) and would allow independent decision making about their DM care including identifying treatment next steps and determining how insulin dosing affects glucose trends. Seventy percent would feel confident making changes to their care by themselves using this report including adjustment of their pump settings, while 90% felt it would help with basal rate adjustments. Conclusion: CGM metrics and pattern visualization have recently been standardized in an AGP CGM report. Our patient interview reinforces that the same efforts are needed worldwide to standardize CGM and insulin dose (pump and connected pen) reporting. Disclosure D.M. Mullen: Consultant; Self; International Diabetes Center DBA HealthPartners Institute. R.M. Bergenstal: Consultant; Self; Ascensia Diabetes Care, Johnson & Johnson. Other Relationship; Self; Abbott, Dexcom, Inc., Hygieia, Lilly Diabetes, Medtronic, Novo Nordisk A/S, Onduo, Roche Diabetes Care, Sanofi, UnitedHealth Group. M.L. Johnson: Consultant; Self; Jaeb Center for Health Research. Research Support; Self; Abbott, Dexcom, Inc., Insulet Corporation, JDRF, Lilly Diabetes, Medtronic, National Institute of Diabetes and Digestive and Kidney Diseases, Novo Nordisk Inc. Funding National Institute of Diabetes and Digestive and Kidney Diseases (3UC4DK10861101S1)

We hypothesized that islet autoimmunity, hitherto considered the pathophysiologic basis of type 1 diabetes (T1D) and latent autoimmune diabetes of adults (LADA), could contribute to ß cell dysfunction in patients with type 2 diabetes (T2D). To evaluate this question, the Glycemia Reduction Approaches in Diabetes: A Comparative Effectiveness (GRADE) Study - Beta Cell Ancillary Study Network measured humoral islet autoimmunity (autoantibodies against 65 kDa glutamic acid decarboxylase (GAD65-Ab), islet autoantigen-2 (IA2-Ab) and zinc transporter-8 (ZnT8-Ab)) in 392 participants (age 57.2 ± 10.1 y; BMI 33.5 ± 6.2 kg/m2; diabetes duration 4.0 ± 3.0 y; HbA1c 7.5 ± 0.5 %; on metformin as the sole glucose-lowering medication), and cellular islet autoimmunity (T cell autoreactivity against a broad range of islet antigens) in 322 of the same participants. 41.4% had evidence of cellular islet autoimmunity and 13.5% had evidence of humoral islet autoimmunity, but only 5.4% had both. T cell autoreactivity to islet antigens, but not autoantibody-positivity, was associated with diminished ß cell function, as assessed by the ratio of incremental area under the curve (iAUC) of C-peptide to iAUC of glucose during 0-120 min of an OGTT (ß = -0.1403; se = 0.0612; p = 0.0219) or ∆C-peptide/∆glucose during 0-30 min of an OGTT (ß = -0.2113; se = 0.0728; p = 0.0037), adjusted for insulin sensitivity. T cell positive participants also had higher fasting plasma glucose (p = 0.045) and HbA1c (p = 0.001) than T cell negative participants. These findings indicate that islet autoimmunity in T2D patients is far more prevalent than previously recognized; T cell mediated islet autoimmunity is associated with diminished ß cell function. Disclosure B. Brooks-Worrell: None. C.S. Hampe: None. E.V. Gonzalez: None. B.M. Palomino: None. S.Z. Zangeneh: None. K. Utzschneider: Other Relationship; Self; Medtronic. S.E. Kahn: Advisory Panel; Self; Boehringer Ingelheim International GmbH, Eli Lilly and Company, Intarcia Therapeutics, Janssen Scientific Affairs, LLC., Merck & Co., Inc., Novo Nordisk A/S, Pfizer Inc. M.E. Larkin: None. M.L. Johnson: Consultant; Self; Jaeb Center for Health Research. Research Support; Self; Abbott, Dexcom, Inc., Insulet Corporation, JDRF, Lilly Diabetes, Medtronic, National Institute of Diabetes and Digestive and Kidney Diseases, Novo Nordisk Inc. K.J. Mather: Research Support; Self; Abbott, Merck & Co., Inc., Novo Nordisk Inc., Sanofi. N. Younes: None. N. Rasouli: Advisory Panel; Self; Boehringer Ingelheim Pharmaceuticals, Inc., Novo Nordisk Inc. Research Support; Self; Allergan plc., Novo Nordisk Inc. C. Desouza: Consultant; Self; AstraZeneca, Bayer AG, Novo Nordisk A/S. R.M. Cohen: Stock/Shareholder; Self; Bristol-Myers Squibb. J.Y. Park: None. H. Florez: None. W. Valencia: None. A. Shojaie: None. J.P. Palmer: None. A. Balasubramanyam: None. Funding National Institutes of Health (R01DK104832, U01DK098246)

The purpose of this study was to evaluate feasibility of initiating continuous glucose monitoring (CGM) through telehealth as a means of expanding access. Adults with type 1 diabetes (N = 27) or type 2 diabetes using insulin (N = 7) and interest in starting CGM selected a CGM system (Dexcom G6 or Abbott FreeStyle Libre), which they received by mail. CGM was initiated with a certified diabetes care and education specialist providing instruction via videoconference or phone. The primary outcome was days per week of CGM use during the last 4 weeks. Hemoglobin A1c (HbA1c) was measured at baseline and 12 weeks. Participant self-reported outcome measures were also evaluated. All 34 participants (mean age, 46 ± 18 years; 53% female, 85% white) were using CGM at 12 weeks, with 94% using CGM at least 6 days per week during weeks 9 to 12. Mean HbA1c decreased from 8.3 ± 1.6 at baseline to 7.2 ± 1.3 at 12 weeks (P

Background: The Glycemia Reduction Approaches in Diabetes: A Comparative Effectiveness (GRADE) study has enrolled a racially and ethnically diverse population with type 2 diabetes, performed extensive phenotyping, and randomly assigned the participants to one of four second-line diabetes medications. The continuous glucose monitoring (CGM) substudy has been added to determine whether there are racial/ethnic differences in the relationship between average glucose (AG) and hemoglobin A1c (HbA1c). CGM will also be used to compare time in target range, glucose variability, and the frequency and duration of hypoglycemia across study groups. Methods: The observational CGM substudy will enroll up to 1800 of the 5047 GRADE study participants from the four treatment groups, including as many as 450 participants from each of 4 racial/ethnic minority groups to be compared: Hispanic White, non-Hispanic White, non-Hispanic African American, and non-Hispanic Other. CGM will be performed for 2 weeks in proximity to a GRADE annual visit, during which an oral glucose tolerance test will be performed and HbA1c and glycated albumin measured. Indicators of interindividual variation in red blood cell turnover, based on specialized erythrocyte measurements, will also be measured to explore the potential causes of interindividual HbA1c variations. Conclusions: The GRADE CGM substudy will provide new insights into whether differences exist in the relationship between HbA1c and AG among different racial/ethnic groups and whether glycemic profiles differ among frequently used diabetes medications and their potential clinical implications. Understanding such differences is important for clinical care and adjustment of diabetes medications in patients of different races or ethnicities.

Use of continuous glucose monitoring (CGM) is recognized as a valuable component of diabetes self-management and is increasingly considered a standard of care for individuals with diabetes who are treated with intensive insulin therapy. As the clinical use of CGM technology expands, consistent and standardized glycemic metrics and glucose profile visualization have become increasingly important. A common set of CGM metrics has been proposed by an international expert panel in 2017, including standard definitions of time in ranges, glucose variability, and adequacy of data collection. We describe the core CGM metrics, as well as the standardized glucose profile format consolidating 2 weeks of CGM measurements, referred to as the ambulatory glucose profile (AGP), which was also recommended by the CGM expert panel. We present an updated AGP report featuring the core CGM metrics and a visualization of glucose patterns that need clinical attention. New tools for use by clinicians and patients to interpret AGP data are reviewed. Strategies based on the authors' experience in implementing CGM technology across the clinical care spectrum are highlighted.

Background: Very little data exists regarding the impact of CGM in the primary care management of type 2 diabetes (T2D). We initiated a QI project in a large health care system to determine the effect of pCGM on glucose management. We evaluated a MD model, and an RN/Certified Diabetes Educator (CDE) model. Methods: Patients (pts) with T2D for >1 year, A1C ≥7.0 and Results: Sixty-eight pts average age 61.6 years, average duration of T2D 15 years, mean A1C 8.8%, were identified. Pre to post pCGM lowered A1C from 8.8 ± 1.2% to 8.2 ± 1.3% (n=68, p=0.006). The time in range (TIR) and time in hyperglycemia improved along with slightly more hypoglycemia in the subset of 37 pts who wore a second pCGM (Table). Glycemic improvement was largely due to lifestyle counseling (68% of pts) and intensification of current therapy (65% of pts), and not due to addition of medications. Conclusion: Using pCGM in a primary care setting, with an MD or RN/CDE model, is effective at lowering A1C, increasing TIR and reducing time in hyperglycemia. Disclosure T.W. Martens: Research Support; Self; Abbott Laboratories, Dexcom, Inc., Medtronic, Novo Nordisk Inc. R.M. Bergenstal: Research Support; Self; Abbott, Boehringer Ingelheim Pharmaceuticals, Inc., Dexcom, Inc., Glooko, Inc., Hygieia, JDRF, Johnson & Johnson Medical Devices Companies, Lilly Diabetes, Medtronic MiniMed, Inc., Merck & Co., Inc., National Institute of Diabetes and Digestive and Kidney Diseases, Novo Nordisk Inc., Roche Diabetes Care, Sanofi. Other Relationship; Self; Abbott, Helmsley Charitable Trust, Hygieia, Lilly Diabetes, Novo Nordisk Inc., Onduo LLC, Sanofi, UnitedHealth Group Inc. M.L. Johnson: Research Support; Self; Abbott, Calibra Medical, CeQur Corporation, Dexcom, Inc., Medtronic, National Institute of Diabetes and Digestive and Kidney Diseases, Novo Nordisk Inc., Sanofi. J.L. Davidson: None. G. Simonson: Advisory Panel; Self; Merck & Co., Inc. Research Support; Self; Abbott. Funding Abbott Laboratories

A quarter of patients with type 2 diabetes (T2D) use insulin, yet most remain under treated. The shortcoming of the therapy stems from its dynamic nature which necessitate frequent dosage titration. In reality, current overburdened health-care systems fall short of time to delivering sufficient insulin titrations. The d-Nav® Insulin Guidance Service overcomes this barrier. d-Nav is a handheld device that automatically titrates insulin dosage at least weekly, based on glucose readings that the patient is already scheduled to take with the d-Nav. Additionally, the service includes dedicated support of care specialists. We enrolled 181 sub-optimally controlled T2D patients to a multicenter, 1:1 randomized control trial to assess the effectiveness and safety of the d-Nav service compared to close follow-up of diabetes specialists. Both groups received 7 interactions in the 6-month study. d-Nav group: automatic titrations occurred 1±0.2 times per week (see Figure.); A1c reduction 8.7±0.8% to 7.7±1.0%; 94.6% retention; high-level of satisfaction and comfort; minor hypoglycemia ( Control: A1c reduction 8.5±0.8% to 8.2±0.9% (p Severe hypoglycemia: statistically similar and low. Expansion of supervised automated insulin titrations is feasible as long as it is simple to use by the patient and it does not increase providers’ burden. It may lead to a sizable reduction in complications and costs. Disclosure I. Hodish: Stock/Shareholder; Self; Hygieia. R.M. Bergenstal: Research Support; Self; Johnson & Johnson Services, Inc.. Consultant; Self; Johnson & Johnson Services, Inc.. Research Support; Self; Abbott. Advisory Panel; Self; Abbott. Research Support; Self; Becton, Dickinson and Company. Consultant; Self; Becton, Dickinson and Company. Research Support; Self; Boehringer Ingelheim Pharmaceuticals, Inc., AstraZeneca, Takeda Pharmaceuticals U.S.A., Inc., Dexcom, Inc.. Stock/Shareholder; Self; Merck & Co., Inc.. Research Support; Self; Eli Lilly and Company, Sanofi. Advisory Panel; Self; Sanofi, Roche Pharma. Research Support; Self; Novo Nordisk Inc.. Advisory Panel; Self; Novo Nordisk Inc.. Research Support; Self; Medtronic. Consultant; Self; Medtronic. Research Support; Self; Hygieia. Advisory Panel; Self; Hygieia, Glooko, Inc.. Research Support; Self; JAEB Center For Health Research, JDRF, National Institute of Diabetes and Digestive and Kidney Diseases. M.L. Johnson: Research Support; Self; Calibra Medical, Medtronic, Sanofi, Novo Nordisk Inc., Abbott, POPS! Diabetes Care, National Institute of Diabetes and Digestive and Kidney Diseases, Dexcom, Inc., Hygieia, JDRF. R.A. Passi: Research Support; Self; Novo Nordisk Inc., Bristol-Myers Squibb Company, Hygieia, Amylin Pharmaceuticals, Medtronic, Calibra Medical, JAEB Center For Health Research, Boehringer Ingelheim Pharmaceuticals, Inc., National Institutes of Health, JDRF, Abbott, POPS Diabetes Care, Dexcom, Inc.. A. Bhargava: None. N. Young: None. D.F. Kruger: Research Support; Self; Dexcom, Inc.. Speaker's Bureau; Self; Dexcom, Inc.. Stock/Shareholder; Self; Dexcom, Inc.. Consultant; Self; Novo Nordisk Inc.. Speaker's Bureau; Self; Novo Nordisk Inc.. Research Support; Self; Novo Nordisk Inc.. Speaker's Bureau; Self; Eli Lilly and Company, Boehringer Ingelheim Pharmaceuticals, Inc.. Consultant; Self; Intarcia Therapeutics, Inc., Abbott. Research Support; Self; Sanofi. Consultant; Self; Sanofi. Research Support; Self; JAEB Center For Health Research. Consultant; Self; Janssen Pharmaceuticals, Inc.. Speaker's Bureau; Self; Janssen Pharmaceuticals, Inc.. Consultant; Self; AstraZeneca. Speaker's Bureau; Self; AstraZeneca. Research Support; Self; Hygieia, Lexicon Pharmaceuticals, Inc., National Institute of Diabetes and Digestive and Kidney Diseases. Speaker's Bureau; Self; Valeritas, Inc., Insulet Corporation. Consultant; Self; Insulet Corporation. Research Support; Self; Insulet Corporation. Consultant; Self; Merck & Co., Inc.. A. Hailey: None. E. Unger: Employee; Self; Hygieia. E. Bashan: Employee; Self; Hygieia.

This multicenter RCT compared clinical, subject-reported, and safety outcomes in T2D subjects on basal insulin (A1C 7.5-11%) initiating mealtime insulin with a wearable bolus insulin delivery patch (Patch, Calibra Medical) vs. an insulin pen (Pen, NovoLog FlexPen®). The Patch was applied at least every 3 days and delivered subcutaneous bolus insulin in 2-U increments per manual click. T2D adults (N=278, age: 59.2 y, duration: 15 y), were randomized to Patch (n=139) or Pen (n=139). Baseline glargine dose was divided 1:1, basal:bolus. Using a pattern-control logbook, subjects adjusted basal and bolus insulin weekly based on fasting and pre-meal glucose targets. Change in A1C (%) from baseline to Week 24 (primary endpoint) for Patch was noninferior (p There were no significant differences in adverse events, including hypoglycemia (3 severe episodes/group). There were significantly greater improvements in subject-reported outcomes for Patch vs. Pen. In conclusion, bolus insulin delivered by Patch or Pen along with an algorithm-based weekly insulin dose titration significantly improved A1C levels in subjects with T2D, with improved patient experience and a preference for Patch. Disclosure R.M. Bergenstal: Research Support; Self; Johnson & Johnson Services, Inc.. Consultant; Self; Johnson & Johnson Services, Inc.. Research Support; Self; Abbott. Advisory Panel; Self; Abbott. Research Support; Self; Becton, Dickinson and Company. Consultant; Self; Becton, Dickinson and Company. Research Support; Self; Boehringer Ingelheim Pharmaceuticals, Inc., AstraZeneca, Takeda Pharmaceuticals U.S.A., Inc., Dexcom, Inc.. Stock/Shareholder; Self; Merck & Co., Inc.. Research Support; Self; Eli Lilly and Company, Sanofi. Advisory Panel; Self; Sanofi, Roche Pharma. Research Support; Self; Novo Nordisk Inc.. Advisory Panel; Self; Novo Nordisk Inc.. Research Support; Self; Medtronic. Consultant; Self; Medtronic. Research Support; Self; Hygieia. Advisory Panel; Self; Hygieia, Glooko, Inc.. Research Support; Self; JAEB Center For Health Research, JDRF, National Institute of Diabetes and Digestive and Kidney Diseases. M. Peyrot: Consultant; Self; Calibra Medical, Eli Lilly and Company, Novo Nordisk Inc.. Research Support; Spouse/Partner; Eli Lilly and Company, Novo Nordisk Inc. D.M. Dreon: Employee; Self; Calibra Medical. V. Aroda: Consultant; Self; Novo Nordisk Inc.. Research Support; Self; Novo Nordisk Inc., AstraZeneca, Calibra Medical, Eisai Inc., Sanofi. Consultant; Self; Sanofi. Research Support; Self; Theracos, Inc.. Employee; Spouse/Partner; Merck & Co., Inc.. Other Relationship; Self; American Diabetes Association. Consultant; Self; ADOCIA. T.S. Bailey: Research Support; Self; Abbott. Consultant; Self; Abbott. Speaker's Bureau; Self; Abbott. Research Support; Self; Ambra BioScience, Ascensia Diabetes Care, Becton, Dickinson and Company. Consultant; Self; Becton, Dickinson and Company. Research Support; Self; Boehringer Ingelheim Pharmaceuticals, Inc., Calibra Medical. Consultant; Self; Calibra Medical. Research Support; Self; Companion Medical, Dexcom, Inc., Glooko, Inc., GlySens Incorporated, Lexicon Pharmaceuticals, Inc., Eli Lilly and Company. Consultant; Self; Eli Lilly and Company. Speaker's Bureau; Self; Eli Lilly and Company. Research Support; Self; Medtronic MiniMed, Inc.. Consultant; Self; Medtronic MiniMed, Inc.. Speaker's Bureau; Self; Medtronic MiniMed, Inc.. Research Support; Self; Novo Nordisk Inc.. Consultant; Self; Novo Nordisk Inc.. Speaker's Bureau; Self; Novo Nordisk Inc.. Research Support; Self; Sanofi. Consultant; Self; Sanofi. Speaker's Bureau; Self; Sanofi. Research Support; Self; Senseonics. Consultant; Self; Intarcia Therapeutics, Inc.. Research Support; Self; Versartis, Inc., Xeris Pharmaceuticals, Inc., MannKind Corporation. R.L. Brazg: Research Support; Self; Abbott, Calibra Medical, Dexcom, Inc., Eli Lilly and Company, GlucoMe, Novo Nordisk Inc., Medtronic. Speaker's Bureau; Self; Medtronic. Research Support; Self; Sanofi-Aventis, Senseonics, Gan & Lee Pharmaceuticals, Gelesis. J.P. Frias: Research Support; Self; AbbVie Inc., Allergan, Amgen Inc., Boehringer Ingelheim Pharmaceuticals, Inc., Bristol-Myers Squibb Company. Consultant; Self; CeQur Corporation. Research Support; Self; Cirius Therapeutics, AstraZeneca, Calibra Medical, Elcelyx Therapeutics, Inc.. Consultant; Self; Elcelyx Therapeutics, Inc.. Research Support; Self; Eli Lilly and Company, Genentech, Inc., Ionis Pharmaceuticals, Inc., ICON plc., Janssen Pharmaceuticals, Inc.. Consultant; Self; Johnson & Johnson Diabetes Institute, LLC.. Research Support; Self; Lexicon Pharmaceuticals, Inc., Ligand Pharmaceuticals, Inc.. Consultant; Self; Ligand Pharmaceuticals, Inc.. Research Support; Self; Merck & Co., Inc., Novartis Pharmaceuticals Corporation, Novo Nordisk Inc., Pfizer Inc., Sanofi. Consultant; Self; Sanofi. Speaker's Bureau; Self; Sanofi. Research Support; Self; Theracos, Inc. M.L. Johnson: Research Support; Self; Calibra Medical, Medtronic, Sanofi, Novo Nordisk Inc., Abbott, POPS! Diabetes Care, National Institute of Diabetes and Digestive and Kidney Diseases, Dexcom, Inc., Hygieia, JDRF. D.C. Klonoff: Consultant; Self; Ascensia Diabetes Care, Lifecare, Intarcia Therapeutics, Inc., Voluntis USA, Novo Nordisk Inc., Onduo, Trividia Health, Inc., American Diabetes Association, The Endocrine Society, American Association of Diabetes Educators. D.F. Kruger: Research Support; Self; Dexcom, Inc.. Speaker's Bureau; Self; Dexcom, Inc.. Stock/Shareholder; Self; Dexcom, Inc.. Consultant; Self; Novo Nordisk Inc.. Speaker's Bureau; Self; Novo Nordisk Inc.. Research Support; Self; Novo Nordisk Inc.. Speaker's Bureau; Self; Eli Lilly and Company, Boehringer Ingelheim Pharmaceuticals, Inc.. Consultant; Self; Intarcia Therapeutics, Inc., Abbott. Research Support; Self; Sanofi. Consultant; Self; Sanofi. Research Support; Self; JAEB Center For Health Research. Consultant; Self; Janssen Pharmaceuticals, Inc.. Speaker's Bureau; Self; Janssen Pharmaceuticals, Inc.. Consultant; Self; AstraZeneca. Speaker's Bureau; Self; AstraZeneca. Research Support; Self; Hygieia, Lexicon Pharmaceuticals, Inc., National Institute of Diabetes and Digestive and Kidney Diseases. Speaker's Bureau; Self; Valeritas, Inc., Insulet Corporation. Consultant; Self; Insulet Corporation. Research Support; Self; Insulet Corporation. Consultant; Self; Merck & Co., Inc. S. Ramtoola: Other Relationship; Self; Janssen Research & Development. Stock/Shareholder; Self; Novo Nordisk A/S, Johnson & Johnson, Eli Lilly and Company. J. Rosenstock: Advisory Panel; Self; Eli Lilly and Company. Consultant; Self; Eli Lilly and Company. Research Support; Self; Novo Nordisk Inc.. Consultant; Self; Novo Nordisk Inc.. Advisory Panel; Self; Sanofi. Consultant; Self; Sanofi. Advisory Panel; Self; Janssen Pharmaceuticals, Inc.. Consultant; Self; Janssen Pharmaceuticals, Inc.. Advisory Panel; Self; Boehringer Ingelheim Pharmaceuticals, Inc.. Consultant; Self; Boehringer Ingelheim Pharmaceuticals, Inc.. Advisory Panel; Self; Intarcia Therapeutics, Inc.. Consultant; Self; Intarcia Therapeutics, Inc.. Research Support; Self; Merck & Co., Inc., Pfizer Inc., Sanofi, Novo Nordisk Inc., Bristol-Myers Squibb Company, Eli Lilly and Company, Intarcia Therapeutics, Inc., Genentech, Inc. P. Serusclat: Board Member; Self; Novo Nordisk A/S, Medtronic, Abbott. Research Support; Self; Novo Nordisk A/S, Eli Lilly and Company, Sanofi. R.S. Weinstock: Research Support; Self; Medtronic MiniMed, Inc., Mylan, Kowa Pharmaceuticals America, Inc., Diasome Pharmaceuticals, Inc., Calibra Medical, Dexcom, Inc., Ultradian Diagnostics LLC., JAEB Center For Health Research, JDRF, National Institute of Diabetes and Digestive and Kidney Diseases. R.G. Naik: Other Relationship; Self; LifeScan, Inc.. D.M. Shearer: None. V. Zraick: Other Relationship; Self; Calibra Medical. B.L. Levy: Employee; Self; LifeScan, Inc..

A 44-week, multinational RCT compared efficacy, safety, and subject preference for bolus insulin initiation using a wearable bolus insulin delivery patch (Patch, Calibra Medical) vs. an insulin pen (Pen, NovoLog FlexPen®) in 278 T2D subjects on basal insulin (0.52 U/kg) (A1C: mean ± SD, 8.7% ± 1.0, BMI: 32.6 kg/m2, duration: 15 y), using insulin titration algorithms incorporated into a patient diary. At randomization, basal insulin dose was divided 1:1, basal:bolus. Subjects used SMBG patterns weekly to adjust insulin doses. The diary also included algorithms for adjusting bolus insulin at each meal if SMBG was above or below target and if meal size was larger or smaller than usual. At 44 weeks there was significant (p In summary, by making weekly insulin adjustments based on simple algorithms embedded in a patient glucose diary, T2D subjects can significantly improve A1C values and 7-point glucose profiles. Disclosure M.L. Johnson: Research Support; Self; Calibra Medical, Medtronic, Sanofi, Novo Nordisk Inc., Abbott, POPS! Diabetes Care, National Institute of Diabetes and Digestive and Kidney Diseases, Dexcom, Inc., Hygieia, JDRF. D.M. Dreon: Employee; Self; Calibra Medical. B.L. Levy: Employee; Self; LifeScan, Inc. R.M. Bergenstal: Research Support; Self; Johnson & Johnson Services, Inc.. Consultant; Self; Johnson & Johnson Services, Inc.. Research Support; Self; Abbott. Advisory Panel; Self; Abbott. Research Support; Self; Becton, Dickinson and Company. Consultant; Self; Becton, Dickinson and Company. Research Support; Self; Boehringer Ingelheim Pharmaceuticals, Inc., AstraZeneca, Takeda Pharmaceuticals U.S.A., Inc., Dexcom, Inc.. Stock/Shareholder; Self; Merck & Co., Inc.. Research Support; Self; Eli Lilly and Company, Sanofi. Advisory Panel; Self; Sanofi, Roche Pharma. Research Support; Self; Novo Nordisk Inc.. Advisory Panel; Self; Novo Nordisk Inc.. Research Support; Self; Medtronic. Consultant; Self; Medtronic. Research Support; Self; Hygieia. Advisory Panel; Self; Hygieia, Glooko, Inc.. Research Support; Self; JAEB Center For Health Research, JDRF, National Institute of Diabetes and Digestive and Kidney Diseases.

With the current and projected shortage of a cytotechnologist (CT) workforce and the desire to reduce laboratory costs, increased productivity with automated assisted primary screening has become an attractive option for many laboratories. To the best of the authors' knowledge, longitudinal studies examining the effect of increasing workload on the performance of individual CTs have not been performed previously.Using the ThinPrep imaging system (TIS), the performance of 3 CTs with variable levels of experience were evaluated. Their productivity was noted to increase from an average of 87 to 118 slides per day. The analysis included comparisons of error rates, screening rates, and screening times, including a review of 22 fields of view (FOV). Poststudy interviews of the CTs were also performed.Increased workload was found to be proportional to the decreased percentage of cases that underwent full manual review (25.2% to 20.1%; P.001), and decreased actual screening times (7.3 hours/day to 6.7 hours/day, and 5.0 minutes/slide to 3.7 minutes/slide). This resulted in a lower detection of total abnormal findings (10.4% to 8.3%; P.001), atypical squamous cells (6.7% to 4.9%; P.001), and high-grade squamous intraepithelial lesion (0.9 %to 0.7%; P = .37), as well as an increased false-negative fraction rate (3.8% to 7.0%; P = .08).The results of the current study indicate that an increased average CT workload100 slides per day with the TIS appears to have been accomplished mostly through a reduction in the amount of time spent reviewing the 22 FOV and the percentage of cases that underwent full manual review, which resulted in a significantly reduced screening performance.

Background: Despite the availability of effective treatments, many patients with diabetes have suboptimal glycemic control. Objective: This study was designed to determine whether the Advanced Insulin Management (AIM) program could help patients with type 1 diabetes mellitus (DM) reduce their A1C levels to ≤7.5% without weight gain, increased incidence of hypoglycemia, or increased diabetes-related distress. Methods: The AIM program, developed to intensify glycemic control in patients with type 1 DM, consisted of a screening visit and 3 to 6 interactive group sessions, depending on whether the patient elects multiple daily injections (MDIs) or an insulin pump. Patients who wanted to learn additional diabetes management skills were referred by their endocrinologist, and those with competent carbohydrate-counting skills and record-keeping practices were eligible to enroll. A nurse, dietitian, psychologist, and physician provided group instruction and supported individual goal setting. The program included depression screening, regimen adjustments, and problem-solving activities. Outcome measures, including blood glucose, A1C, weight, and diabetes-related distress, were tracked for 12 months. Results: The study included 113 adult patients with type 1 DM (59% female; mean age, 39 years). Twenty patients already had insulin pumps, 46 patients initiated pump therapy during the study, and 47 patients elected MDIs. Mean A1C declined by 0.5% (to 7.3%) after 12 months, without weight gain or increased hypoglycemia. A significant decrease in diabetes-related distress was observed. Conclusion: The AIM program was associated with important improvements in glycemic control in patients with type 1 DM, without weight gain or increased hypoglycemic episodes.

OBJECTIVE—To determine whether clinically significant differences exist in fasting blood glucose (BG) at the forearm, palm, and thigh relative to the fingertip; to assess the impact of prandial status by comparing BG between alternative sites and the fingertip at several time intervals after carbohydrate intake; to assess the effects of moderate brief exercise on site-to-site differences in BG; to evaluate the impact of site preparation by local rubbing on alternative-site testing (AST) equivalence; and to determine levels of perceived pain and satisfaction associated with AST. RESEARCH DESIGN AND METHODS—Fasting BG was measured using the One Touch Ultra (LifeScan, Milpitas, CA) at the fingertip, palm, thigh, and each forearm (with local rubbing) in 86 patients with type 2 diabetes. A 40-g carbohydrate meal was consumed and BG was again measured from each site at 60, 90, and 120 min postmeal, with an additional forearm test at 90 min without local rubbing. Patients then exercised for 15 min with repeat BG at each site. Differences in BG between sites were assessed using repeated-measures ANOVA and regression analyses. RESULTS—Significant differences in BG at alternative sites were found 60 min postmeal (P = 0.0003) and postexercise (P = 0.037). Specifically, clinically significant differences (expressed as percent difference from the fingertip) at 60 min include −8.8 ± 10.8% at the forearm and −13.7 ± 10.7% at the thigh, and postexercise +19.1 ± 19.1% at the forearm and +15.6 ± 22.6% at the thigh. However, no significant differences were observed between sites in either the fasting state or at 90 and 120 min postmeal. The dynamic results suggest a time lag in equilibration of forearm and thigh BG during periods of rapid glucose change. Palm and fingertip BG test results were similar at all time points. CONCLUSIONS—AST results are consistent with fingertip BG results in both the fasting state and 2 h postmeal; no benefit from site preparation by local rubbing was noted. However, testing at sites other than the hand cannot be recommended 1 h postmeal or immediately after exercise. AST is equivalent and appropriate for use at testing times commonly used in clinical practice.

Of the “four C’s,”cut has historically been the most complex to understand and assess. This article presents a three-dimensional mathematical model to study the interaction of light with a fully faceted, colorless, symmetrical roundbrilliant-cut diamond. With this model, one can analyze how various appearance factors (brilliance, fire, and scintillation) depend on proportions. The model generates images and a numerical measurement of the optical efficiency of the round brilliant—called weighted light return (WLR)—which approximates overall brilliance. This article examines how WLR values change with variations in cut proportions, in particular crown angle, pavilion angle, and table size. The results of this study suggest that there are many combinations of proportions with equal or higher WLR than “Ideal” cuts. In addition, they do not support analyzing cut by examining each proportion parameter independently. However, because brilliance is just one aspect of the appearance of a faceted diamond, ongoing research will investigate the added effects of fire and scintillation.

GEMS & GEMOLOGY Winter 1997 any factors influence the color appearance of colorless to faint yellow diamonds. Typically, such diamonds are quality graded for the absence of color according to the D-to-Z scale developed by the Gemological Institute of America in the 1940s (Shipley and Liddicoat, 1941). By color appearance, however, we mean the overall look of a polished diamond’s color that results from a combination of factors such as bodycolor, shape, size, cutting proportions, and the position and lighting in which it is viewed. When exposed to invisible ultraviolet (UV) radiation, some diamonds emit visible light, which is termed fluorescence (figure 1). This UV fluorescence arises from submicroscopic structures in diamonds. Various colors of fluorescence in diamond are known, but blue is by far the most common. The response of a diamond to the concentrated radiation of an ultraviolet lamp is mentioned as an identifying characteristic (rather than a grading factor) on quality-grading reports issued by most gem-testing laboratories. Other light sources—such as sunlight or fluorescent tubes—also contain varying amounts of UV radiation. Although there have been instances where the color and strength of the fluorescence seen in diamonds observed in these other light sources are also believed to influence color appearance, in recent years the fluorescence noted on grading reports has been singled out by many in the diamond trade and applied across the board as a marker for pricing distinctions. Generally, these distinctions are applied in the direction of lower offering prices for colorless and near-colorless diamonds that exhibit fluorescence to a UV lamp (Manny Gordon, pers. comm., 1997). Other trade members contend that the overall color appearance of a diamond typically is not adversely affected by this property (William Goldberg, pers. comm., 1997); many even say that blue fluorescence enhances color appearance. A CONTRIBUTION TO UNDERSTANDING THE EFFECT OF BLUE FLUORESCENCE ON THE APPEARANCE OF DIAMONDS

In New Jersey and throughout the country, the new Municipal Stormwater Regulation Program will require significant changes in the way stormwater infrastructure is managed. Digital mapping can offer a variety of solutions to make this process easier. A digital map allows the user to manage multiple sheets in a single electronic file, and to retrieve the necessary mapping information in a matter of seconds. By taking digital maps to the next level with Geographic Information System (GIS) technology, it is also possible to add other critical data right to the map itself. Whereas a digital map will allow the user to view the location of a stormwater drainage pipe in relation to its surroundings, GIS technology will allow the user to view tables of information about the same stormwater drainage pipe with a simple click of the mouse. Entire infrastructure systems, as well as Stormwater Management Plans and Stormwater Pollution Prevention Plans can be mapped, and a wide variety of related data can be organized and managed with GIS. The zoning and land use aspects associated with good stormwater management and water quality improvement practices can also be tracked with GIS. For example, by performing a build-out analysis, it is possible to study the impact of future growth and development on a municipality or region. By analyzing the “what-if” factors of additional impervious surfaces, potable water needs, and even pollution from additional automobiles now, it will be possible to utilize Smart Growth and related initiatives to prevent environmental damage before it occurs, rather than trying to deal with its impact later on. GIS can also assist with the public education initiatives needed to make these changes seem both positive and possible.

Tetrahedrites of composition (Cu, Ag)10(Cu2, Fe, Zn)2(Sb, As)4S13 or Cu12Sb14/3S13 have 208 valence electrons per unit cell and are expected to be semiconductors. The bands are full in these cases, whereas compositions towards the classical formula Cu12Sb4S13 (204 valence electrons per unit cell) have only partially filled bands and are therefore expected to be metallic. These predictions are supported by new optical absorption spectra of tetrahedrites with 205 and 208 valence electrons per unit cell. The gap between valence and conduction bands of the semiconductor is about 1.7 (±0.2) eV. A further prediction based on a nearly-free electron model is that 208 valence electrons per unit cell represent a compositional limit for tetrahedrites, and that the stability increases as compositions approach this limit. Existing data indicate an exponential increase in the number of occurrences as the limit is approached.