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Journal of Diabetes Science and Technology

Maria Pia Francescato, Miloš Ajčević, Agostino Accardo
Physical activity is a keystone of a healthy lifestyle as well as of management of patients with type 1 diabetes. The risk of exercise-induced hypoglycemia, however, is a great challenge for these patients. The glycemic response to exercise depends upon several factors concerning the patient him/herself (eg, therapy, glycemic control, training level) and the characteristics of the exercise performed. Only in-depth knowledge of these factors will allow to develop individualized strategies minimizing the risk of hypoglycemia...
February 15, 2019: Journal of Diabetes Science and Technology
Robert North, Christine Pospisil, Ryan J Clukey, Christopher G Parkin
Improving user engagement with continuous glucose monitoring (CGM) is considered a major requirement for achieving optimal treatment efficacy. Human factors testing is needed to ensure that CGM product designs and requisite training simplify the user experience and enhance usability and patient safety. Dexcom, Inc, recently introduced a novel, "one-button" automatic sensor applicator (ASA) for use with the Dexcom G6 (rtCGM) system. The device was developed utilizing all phases of the human factors testing process...
February 14, 2019: Journal of Diabetes Science and Technology
Lilli Priesterroth, Jennifer Grammes, Kimberly Holtz, Anna Reinwarth, Thomas Kubiak
BACKGROUND: Diabetes management apps may have positive effects on diabetes self-management. It remains unclear, however, which app features are particularly effective and encourage sustained app usage. Behavior change techniques (BCTs) and gamification are promising approaches to improve user engagement. However, little is known about the frequency BCTs and gamification techniques (GTs) are actually used. This app review aims to provide an overview of BCTs and GTs in current diabetes management apps...
February 14, 2019: Journal of Diabetes Science and Technology
Guido Freckmann, Manuela Link, Ulrike Kamecke, Cornelia Haug, Bernhard Baumgartner, Raimund Weitgasser
BACKGROUND: To be able to compare continuous glucose monitoring (CGM) systems, they have to be worn in parallel by the same subjects. This study evaluated the performance and usability of three different CGM systems in direct comparison. METHOD: In this open, prospective study at two sites, 54 patients with diabetes wore three CGM systems each (Dexcom G5™ Mobile CGM system [DG5], Guardian™ Connect system [GC], and a Roche CGM system [RCGM]) in parallel for 6 or 7 days in a mixed inpatient and outpatient setting...
February 7, 2019: Journal of Diabetes Science and Technology
Steven Setford, Stuart Phillips, Mike Grady
BACKGROUND: Described is a manufacturer's systematic post-market evaluation of the long-term clinical accuracy of a commercially available blood glucose monitoring (BGM) test strip product. METHODS: Production batches of test strips were routinely and regularly sampled and evaluated in a clinical setting to assess product accuracy. Evaluations were performed on capillary blood samples from a minimum of 100 subjects with diabetes, by clinical staff according to instructions for use...
February 7, 2019: Journal of Diabetes Science and Technology
Johan Jendle, Peter Adolfsson
Divers travel to different countries to explore various diving sites worldwide. In 2005, the Divers Alert Network (DAN) published their guidelines for recreational diving and diabetes mellitus. However, although years have passed, there is still no consensus in the form of international guidelines on diabetes and diving. Large differences are noted with regard to the regulations in different countries. Furthermore, the diabetes technology has evolved rapidly and is not reflected in current international guidelines...
February 2, 2019: Journal of Diabetes Science and Technology
Johannes Pöhlmann, Beth D Mitchell, Sanjay Bajpai, Beatrice Osumili, William J Valentine
BACKGROUND: Severe hypoglycemic events (SHEs) in patients with diabetes are associated with substantial health care costs in the United States (US). Injectable glucagon (IG) is currently available for treatment of severe hypoglycemia but is associated with frequent handling errors. Nasal glucagon (NG) is a novel, easier-to-use treatment that is more often administered successfully. The economic impact of this usability advantage was explored in cost-offset and budget impact analyses for the US setting...
January 30, 2019: Journal of Diabetes Science and Technology
Boris Kovatchev
Glycemic variability (GV) a well-established risk factor for hypoglycemia and a suspected risk factor for diabetes complications. GV is also a marker of the instability of a person's metabolic system, expressed as frequent high and low glucose excursions and overall volatile glycemic control. In this review, the author discusses topics related to the assessment, quantification, and optimal control of diabetes, including (1) the notion that optimal control of diabetes, that is, lowering of HbA1c-the commonly accepted gold-standard outcome-can be achieved only if accompanied by simultaneous reduction of GV; (2) assessment and visualization of the two principal dimensions of GV, amplitude and time, which is now possible via continuous glucose monitoring (CGM) and various metrics quantifying GV and the risks associated with hypo- and hyperglycemic excursions; and (3) the evolution of diabetes science and technology beyond quantifying GV and into the realm of GV control via pharmacological agents, for example, GLP-1 receptor agonists and DPP-4 inhibitors, which have pronounced variability-reducing effect, or real-time automated closed-loop systems commonly referred to as the "artificial pancreas...
January 29, 2019: Journal of Diabetes Science and Technology
Ana María Gómez, Angélica Imitola Madero, Diana Cristina Henao Carrillo, Martín Rondón, Oscar Mauricio Muñoz, Maria Alejandra Robledo, Martín Rebolledo, Maira García Jaramillo, Fabian León Vargas, Guillermo Umpierrez
INTRODUCTION: Continuous glucose monitoring (CGM) is a better tool to detect hyper and hypoglycemia than capillary point of care in insulin-treated patients during hospitalization. We evaluated the incidence of hypoglycemia in patients with type 2 diabetes (T2D) treated with basal bolus insulin regimen using CGM and factors associated with hypoglycemia. METHODS: Post hoc analysis of a prospective cohort study. Hypoglycemia was documented in terms of incidence rate and percentage of time <54 mg/dL (3...
January 24, 2019: Journal of Diabetes Science and Technology
David C Klonoff, Fraya King, David Kerr
No abstract text is available yet for this article.
January 24, 2019: Journal of Diabetes Science and Technology
David C Klonoff
Behavioral theory is an important factor for designing digital health tools for diabetes to increase adherence to treatment. Many digital health products have not incorporated this method for achieving behavior change. This oversight might explain the disappointing outcomes of many products in this class. Four theories reported to be capable of enhancing the performance of digital health tools for diabetes include (1) Integrate, Design, Assess, and Share (IDEAS); (2) the Behaviour Change Wheel; (3) the Information-Motivation-Behavioral skills (IMB) model; and (4) gamification...
January 24, 2019: Journal of Diabetes Science and Technology
Nasseh Hashemi, Tim Valk, Kim Houlind, Niels Ejskjaer
BACKGROUND: Optimal glucose control has been shown to be useful in critical care as well as in other settings. Glucose concentrations in patients admitted to critical care are characterized by marked variability and hypoglycemia due to inadequate sensing and treatment technologies. METHODS: The insulin balanced infusion system (IBIS) is a closed-loop system that uses a system controller, two syringe pumps, and capillary glucose sensor intravenously infusing regular insulin and/or dextrose...
January 24, 2019: Journal of Diabetes Science and Technology
Ralph Ziegler, Simone von Sengbusch, Jens Kröger, Oliver Schubert, Petra Werkmeister, Dorothee Deiss, Thorsten Siegmund
Continuous glucose monitoring (CGM) systems use trend arrows to accurately display the anticipated glucose curve for the user. These are used for both "real-time" glucose monitoring and for intermittent scanning glucose monitoring. Trend arrow data are used by people with diabetes to make corrections to their glucose control. It is essential that they are correctly interpreted when adjusting insulin doses and to ensure that appropriate treatment decisions are made. The aim of this article is to provide general treatment guidance for diabetes teams and for people with diabetes using CGM in the context of trend arrows...
January 22, 2019: Journal of Diabetes Science and Technology
Andrew A Bremer, Guillermo Arreaza-Rubín
In an article in Journal of Diabetes Science and Technology, Schliess and coauthors describe the conception and design of the European Automated Glu cose Contro l at H ome for People with Chronic Di sease (CLOSE) initiative for the implementation of artificial pancreas (AP) systems for people with diabetes. The CLOSE consortium aims to develop integrated AP solutions (APplus) tailored to the needs of individuals with type 2 diabetes (T2D) by developing superior risk- and cost-benefit scenarios for AP operation to achieve acceptance by users and caregivers and a high likelihood for reimbursement...
January 19, 2019: Journal of Diabetes Science and Technology
Shizuki Sai, Mitsunori Urata, Iwao Ogawa
BACKGROUND: When a patient with diabetes measures blood glucose levels using a simple blood glucose meter, an error message or abnormal value may be displayed because of interfering substances, potentially leading to unnecessary medical treatment. METHODS: Here, we tested 10 self-monitoring of blood glucose (SMBG) and point-of-care testing (POCT) devices to investigate under what conditions they fail to measure blood glucose levels or display abnormal values instead...
January 19, 2019: Journal of Diabetes Science and Technology
Lutz Vogt, Andreas Thomas, Gert Fritzsche, Peter Heinke, Klaus-Dieter Kohnert, Eckhard Salzsieder
BACKGROUND: The decisive factor in successful intensive insulin therapy is the ability to deliver need-based-adjusted nutrition-independent insulin dosages at the closest possible approximation to the physiological insulin level. Because this basal insulin requirement is strongly influenced by the patient's lifestyle, its subtlety is of great importance. This challenge is very different between patients with type 1 diabetes and those with insulin-dependent type 2 diabetes. Furthermore, it is more difficult to finetune a basal insulin dosage with intensified conventional insulin therapy (ICT), due to delayed insulin delivery, compared to insulin pump therapy, which provides continuous delivery of small doses of exclusively short-acting insulin...
January 19, 2019: Journal of Diabetes Science and Technology
Nicole Hobbs, Iman Hajizadeh, Mudassir Rashid, Kamuran Turksoy, Marc Breton, Ali Cinar
BACKGROUND: Physical activity presents a significant challenge for glycemic control in individuals with type 1 diabetes. As accurate glycemic predictions are key to successful automated decision-making systems (eg, artificial pancreas, AP), the inclusion of additional physiological variables in the estimation of the metabolic state may improve the glucose prediction accuracy during exercise. METHODS: Predictor-based subspace identification is applied to a dynamic glucose prediction model including heart rate measurements along with variables representing the carbohydrate consumption and insulin boluses...
January 18, 2019: Journal of Diabetes Science and Technology
Kristin L Schneider, Ryan T Crews, Vasanth Subramanian, Elizabeth Moxley, Sungsoon Hwang, Frank E DiLiberto, Laura Aylward, Jermaine Bean, Sai Yalla
BACKGROUND: Among adults with diabetes, 19-34% will develop a diabetic foot ulcer (DFU), which increases amputation risk and health care costs, and worsens quality of life. Regular physical activity, when increased gradually, may help prevent DFUs. In this mixed-methods study, we examined the feasibility of a low-intensity, technology-based behavioral intervention to increase activity in adults at risk for DFUs. METHOD: Participants at risk for a DFU (n = 12; 66% female; mean age = 59...
January 18, 2019: Journal of Diabetes Science and Technology
Ravi Reddy, Navid Resalat, Leah M Wilson, Jessica R Castle, Joseph El Youssef, Peter G Jacobs
BACKGROUND: Fear of exercise related hypoglycemia is a major reason why people with type 1 diabetes (T1D) do not exercise. There is no validated prediction algorithm that can predict hypoglycemia at the start of aerobic exercise. METHODS: We have developed and evaluated two separate algorithms to predict hypoglycemia at the start of exercise. Model 1 is a decision tree and model 2 is a random forest model. Both models were trained using a meta-data set based on 154 observations of in-clinic aerobic exercise in 43 adults with T1D from 3 different studies that included participants using sensor augmented pump therapy, automated insulin delivery therapy, and automated insulin and glucagon therapy...
January 17, 2019: Journal of Diabetes Science and Technology
Tamara Oukes, Helga Blauw, Arianne C van Bon, J Hans DeVries, Ariane M von Raesfeld
BACKGROUND: Psychosocial factors that may affect acceptance of artificial pancreas (AP) systems have been investigated in small sample sizes of highly motivated, self-selected persons with type 1 diabetes (T1DM) with a focus on product characteristics. We aimed to develop a valid survey to investigate the association of technology readiness and social influence with AP acceptance in a larger sample, including both self-selected and invited respondents with T1DM. METHODS: An online survey was developed based on established questionnaires...
January 15, 2019: Journal of Diabetes Science and Technology
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