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

Objective: The objective of the study is to identify predictors of utilization of a type 2 diabetes (T2D) management App over time for insulin users (IUs) and noninsulin users (NIUs). Research Design and Methods: We followed over 16 weeks a national sample of unselected T2D adults who independently elected to download and pair a CONTOUR DIABETES App with their CONTOUR NEXT ONE glucose meter. App use and frequency of glucose testing were recorded. Baseline surveys recorded participant demographic, disease status, distress, medication taking, and views of technology to predict utilization. Results: Mean age was 51.6 years (108 IUs; 353 NIUs), 48% were female, time with diabetes was 6.9 years, and self-reported HbA1c was 8.1% (36.3 mmol/mol). Mean duration of App use was 85.4 days and 40% stopped using the App before 16 weeks. Continuous users were older and reported higher distress, better medication taking, and more positive attitudes toward technology (all P < .01). IUs tested more frequently than NIUs, but frequency and intensity of testing decreased markedly for both groups over time. More predictors of App use frequency and testing occurred for NIUs than IUs: older age, higher HbA1c, lower distress, more medication taking (all P < .05). Conclusions: App use and testing decreased markedly over time. Variations in the predictors of frequency of App use suggest that the utilization of mobile technologies requires a tailored approach that addresses the specific needs of individual users, compared with adopting a one-size-fits-all strategy, and that IUs and NIUs may require very different strategies of customization.

Background: With the rapid development of new insulin delivery technology, measuring patient experience has become especially pertinent. The current study reports on item development, psychometric validation, and intended use of the newly developed Diabetes Impact and Device Satisfaction (DIDS) Scale. Method: The DIDS Scale was informed by a comprehensive literature review, and field tested as part of two focus groups. The finalized measure was used at baseline and 6 months post-assessment with a large US cohort. Exploratory factor analyses (EFAs) were conducted to determine and confirm factor structure and item selection. Internal reliability, test–retest reliability, and convergent/divergent validity of the emerged factors were tested with demographics, diabetes-specific information, and diabetes behavioral and satisfaction measures. Results: In all, 778 participants with type 1 diabetes (66% female, mean age 47.13 ± 17.76 years, 74% insulin pump users) completed surveys at both baseline and post-assessment. EFA highlighted two factors—Device Satisfaction (seven items, Cronbach’s α = 0.85-0.90) and Diabetes Impact (four items, Cronbach’s α = 0.71-0.75). DIDS Scale demonstrated good concurrent validity and test–retest reliability. Conclusion: The DIDS Scale is a novel and a brief assessment tool with robust psychometric properties. It is recommended for use across all insulin delivery devices and is considered appropriate for use in longitudinal studies. Future studies are recommended to evaluate the performance of DIDS Scale in diverse populations with diabetes.

Cryoprecipitate (cryo) is a plasma-derived blood product utilized during trauma resuscitation, surgery, and other major bleeding. Although local quality control metrics exist, inherent donor variability, and processing may confer differences in hemostatic effect between sources. The purposes of this study were to quantify procoagulant content in three global sources of cryo and evaluate their functional hemostatic effect. In this Institutional Review Board exempt study, 24 units of group A cryo from three different sources, American Red Cross single donor and pooled donor, Australian Red Cross single donor, Southwestern United States single donor, and Southwest pooled donor, were evaluated. Procoagulant factors were quantified from each source using ELISA and automated clot-based assays. Functional hemostasis was evaluated using rotational Thromboelastometry (ROTEM). Microparticles isolated from cryo units were enumerated and evaluated for cellular origin by flow cytometry, as well as their capacity to support thrombin generation. Southwestern United States single donor units demonstrated highest levels of fibrinogen, fibronectin, factor VIII, and von Willebrand factor in the selected units. In the coagulopathy model, successive doses from all cryo units were significantly correlated to decreasing coagulation time (P = 0.0100), and increasing maximum clot firmness (P = 0.0002) and alpha angle (P = 0.0009). Southwest pooled donor demonstrated significantly shorter coagulation time at all three doses (P = 0.02) than other sources. Microparticles support prothrombinase activity and thrombin generation. In this study of global cryo sources, procoagulant activity and in-vitro clot formation varied by source. This could be explained by variance in production and storage protocols. Further study is warranted to assess functional variance in cryo to optimize and standardize the use of cryo products.

Cardiovascular disease (CVD) is a leading cause of death in people with type 2 diabetes (T2D). Recent cardiovascular (CV) outcomes trials have shown CV benefits for several GLP-1 receptor agonists and SGLT2 inhibitors. We aimed to evaluate T2D patients’ awareness, perceptions, and behaviors regarding CVD and cardioprotective T2D drugs. An online survey was completed by 927 T2D patients of diverse socioeconomic backgrounds from an opted-in patient research panel in the U.S. Median respondent age was 64 and median duration of diabetes was 15 years. Half were taking a GLP-1 or SGLT2, a statistically robust sample of patients on these therapies. Questions covered perceptions of CVD disease; awareness of and interest in diabetes drugs that reduce CVD risk; knowledge of their own health metrics; physicians seen and frequency of discussions about CVD; self-assigned ‘grades’ on lifestyle behaviors known to reduce CVD risk. Most patients recognized the link between T2D and CVD: 61% strongly agreed that T2D increases CVD risk. Yet, only 29% think often about their risk of CVD. Awareness of CV benefits from some T2D therapies was also low (34% overall; 42% for those on SGLT2 or GLP-1). Interest in taking an additional cardioprotective diabetes agent aligned with awareness (37% overall; 42% for those on SGLT2 or GLP-1). While almost all knew their HbA1c and blood pressure, over 25% did not know their LDL cholesterol or other lipid levels. In the prior year, 31% of patients had seen a cardiologist and 17% had discussed CVD risk with an endocrinologist. Respondents generally ranked themselves ‘average’ to ‘below average’ on heart-healthy behaviors like exercise, weight, sleep, diet, and stress management. Although a majority of T2D patients are aware of the link between T2D and CVD, most are not actively managing their CV health, and few know that some T2D therapies are cardioprotective. These data suggest a need to better inform T2D patients about their risk for CVD, and steps they can take to reduce that risk. Disclosure K.C. Stoner: Other Relationship; Self; Multiple companies and organizations in the diabetes field (greater than 10). E.N. Fitts: Other Relationship; Self; Various diabetes companies. D. Gopisetty: Other Relationship; Self; Various diabetes companies. A. Carracher: Other Relationship; Self; Other. C.S. Florissi: Other Relationship; Self; dQ&A has several clients (&gt;10) in the diabetes field. M.J. Kurian: Other Relationship; Self; Other Company. J. Kwon: Other Relationship; Self; Various diabetes companies. P. Marathe: Consultant; Self; Close Concerns. P. Rentzepis: Other Relationship; Self; Various Diabetes Companies. J.B. Rost: Other Relationship; Self; dQ&A has several clients (&gt;10) in the diabetes field. K.L. Close: Other Relationship; Self; Various diabetes companies. I.B. Hirsch: Consultant; Self; Abbott, Becton, Dickinson and Company, Big Foot, Roche Diabetes Care. Research Support; Self; Medtronic. M.N. Kosiborod: Consultant; Self; Amgen Inc., AstraZeneca, Bayer AG, Boehringer Ingelheim International GmbH, Eisai Co., Ltd., GlaxoSmithKline plc., Glytec, LLC, Intarcia Therapeutics, Inc., Janssen Pharmaceuticals, Inc., Merck & Co., Inc., Novartis AG, Novo Nordisk A/S, Sanofi. Research Support; Self; AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc. R. Wood: Other Relationship; Self; Multiple companies in the diabetes field (&gt;10 companies). Funding AstraZeneca