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ABSTRACT: Objective: Autoantibodies to glutamate decarboxylase (GAD65Ab) are found in patients with autoimmune neurological disorders and patients with type 1 diabetes. The correct diagnosis of GAD65Ab-associated neurological disorders is often delayed by the variability of symptoms and a lack of diagnostic markers. We hypothesize that the frequency of neurological disorders with high GAD65Ab titers is significantly higher than currently recognized.Methods: We analyzed GAD65Ab titer, inhibition of GAD65 enzyme activity, and pattern of GAD65Ab epitopes in a cohort of type 1 diabetes patients (n=100) and correlated our findings with neurological symptoms and diseases.Results: Forty-three percent (43/100) of the patients had detectable GAD65Ab titers (median=400 U/ml, range: 142-250,000U/ml). The GAD65Ab titers in 10 type 1 diabetes patients exceeded the 90th percentile of the cohort (2,000-250,000 U/ml). Sera of these 10 patients were analyzed for their GAD65Ab epitope specificity and their ability to inhibit GAD65 enzyme activity in vitro. GAD65Ab of five patients inhibited the enzyme activity significantly (by 34-55%). Three of these patients complained of muscle stiffness and pain, which was documented in two of these patients.Conclusions: Based on our findings we suggest that neurological disorders with high GAD65Ab titers are more frequent in type 1 diabetes patients than currently recognized.
Endocrine Practice 03/2013; · 2.49 Impact Factor
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Richard M Bergenstal,
Andrew J Ahmann,
Timothy Bailey,
Roy W Beck,
Joan Bissen,
Bruce Buckingham,
Larry Deeb,
Robert H Dolin,
Satish K Garg,
Robin Goland, [......],
Roger S Mazze,
Beth A Olson,
Christopher Parkin,
Anne Peters,
Margaret A Powers,
Henry Rodriguez,
Phil Southerland,
Ellie S Strock,
William Tamborlane,
David M Wesley
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ABSTRACT: Abstract Underutilization of glucose data and lack of easy and standardized glucose data collection, analysis, visualization, and guided clinical decision making are key contributors to poor glycemic control among individuals with type 1 diabetes. An expert panel of diabetes specialists, facilitated by the International Diabetes Center and sponsored by the Helmsley Charitable Trust, met in 2012 to discuss recommendations for standardization of analysis and presentation of glucose monitoring data, with the initial focus on data derived from CGM systems. The panel members were introduced to a universal software report, the Ambulatory Glucose Profile (AGP), and asked to provide feedback on its content and functionality, both as a research tool and in clinical settings. This paper provides a summary of the topics and issues discussed during the meeting and presents recommendations from the expert panel regarding the need to standardize glucose profile summary metrics and the value of a uniform glucose report to aid clinicians, researchers, and patients.
Diabetes Technology & Therapeutics 02/2013; · 1.93 Impact Factor
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Diabetes Technology & Therapeutics 02/2013; 15 Suppl 1:S3-S12. · 1.93 Impact Factor
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ABSTRACT: OBJECTIVE
Despite substantial evidence of the benefit of frequent self-monitoring of blood glucose (SMBG) in type 1 diabetes, certain insurers limit the number of test strips that they will provide. The large database of the T1D Exchange Clinic Registry provided an opportunity to evaluate the relationship between the number of SMBG measurements per day and HbA(1c) levels across a wide age range of children and adults.RESEARCH DESIGN AND METHODS
The analysis included 20,555 participants in the T1D Exchange clinic registry with type 1 diabetes ≥1 year and not using a continuous glucose monitor (11,641 younger than age 18 years and 8,914 18 years old or older). General linear models were used to assess the association between the number of SMBG measurements and HbA(1c) levels after adjusting for potential confounding variables.RESULTSA higher number of SMBG measurements per day were associated with non-Hispanic white race, insurance coverage, higher household income, and use of an insulin pump for insulin delivery (P < 0.001 for each factor). After adjusting for these factors, a higher number of SMBG measurements per day was strongly associated with a lower HbA(1c) level (adjusted P < 0.001), with the association being present in all age groups and in both insulin pump and injection users.CONCLUSIONS
There is a strong association between higher SMBG frequency and lower HbA(1c) levels. It is important for insurers to consider that reducing restrictions on the number of test strips provided per month may lead to improved glycemic control for some patients with type 1 diabetes.
Diabetes care 02/2013; · 8.09 Impact Factor
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Richard M Bergenstal,
Andrew J Ahmann,
Timothy Bailey,
Roy W Beck,
Joan Bissen,
Bruce Buckingham,
Larry Deeb,
Robert H Dolin,
Satish K Garg,
Robin Goland, [......],
Roger S Mazze,
Beth A Olson,
Christopher Parkin,
Anne Peters,
Margaret A Powers,
Henry Rodriguez,
Phil Southerland,
Ellie S Strock,
William Tamborlane,
David M Wesley
[show abstract]
[hide abstract]
ABSTRACT: Underutilization of glucose data and lack of easy and standardized glucose data collection, analysis, visualization, and guided clinical decision making are key contributors to poor glycemic control among individuals with type 1 diabetes mellitus. An expert panel of diabetes specialists, facilitated by the International Diabetes Center and sponsored by the Helmsley Charitable Trust, met in 2012 to discuss recommendations for standardizing the analysis and presentation of glucose monitoring data, with the initial focus on data derived from continuous glucose monitoring systems. The panel members were introduced to a universal software report, the Ambulatory Glucose Profile, and asked to provide feedback on its content and functionality, both as a research tool and in clinical settings. This article provides a summary of the topics and issues discussed during the meeting and presents recommendations from the expert panel regarding the need to standardize glucose profile summary metrics and the value of a uniform glucose report to aid clinicians, researchers, and patients.
Journal of diabetes science and technology 01/2013; 7(2):562-578.
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ABSTRACT: [Box: see text] CME ACCREDITATION NEEDS ASSESSMENT/PROGRAM OVERVIEW There is a need for greater caution in interpreting glycated hemoglobin (A1C) results, which can be inaccurate in individual patients for a wide variety of reasons beyond the patient's control. In addition, A1C alone may not reflect critical aspects of glycemia. A panel of clinical experts from Europe and North America was convened to reexamine our glucose measuring tools and determine ways in which they can better be applied toward more purposeful processes of glycemic management. Among the main issues addressed were the clinical situations in which A1C should not be used, the role of alternative biomarkers in identifying aspects of glycemic dysregulation not captured by A1C, and the value of using patients' own glucose data to consolidate therapeutic, educational, and behavior-change objectives. TARGET AUDIENCE This activity has been designed to meet the educational needs of physicians and registered nurses involved in the management of patients with diabetes. ACCREDITATION AND CREDIT DESIGNATION Physician Continuing Education This activity has been planned and implemented in accordance with the Essential Areas and policies of the Accreditation Council for Continuing Medical Education through the joint sponsorship of Postgraduate Institute for Medicine, Mary Ann Liebert, Inc., and The Diabetes Education Group. Postgraduate Institute for Medicine is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians. Postgraduate Institute for Medicine designates this journal-based CME activity for a maximum of 1.0 AMA PRA Category 1 Credit(s)™. Physicians should claim only the credit commensurate with the extent of their participation in the activity. Nursing Continuing Education This educational activity for 1 contact hour is provided by Postgraduate Institute for Medicine. Postgraduate Institute for Medicine is accredited as a provider of continuing nursing education by the American Nurses Credentialing Center's Commission on Accreditation. Initial Release Date: October 15, 2012 Expiration Date: October 15, 2013 Estimated Time to Complete Activity: 1 hour Instructions for Receiving Credit There are no fees for participating and receiving CME credit for this activity. During the period October 15, 2012 through October 15, 2013, participants must read the learning objectives and faculty disclosures and study the educational activity. Postgraduate Institute for Medicine supports Green CME by offering your Request for Credit online. If you wish to receive acknowledgment for completing this activity, please complete the posttest and evaluation available online at www.cmeuniversity.com On the navigation menu, click on "Find Post-test/Evaluation by Course" and search by course ID 9068. Upon registering and successfully completing the posttest with a score of 70% or better and the activity evaluation, your certificate will be made available immediately. Processing credit requests online will reduce the amount of paper used by nearly 100,000 sheets per year. DISCLOSURE OF UNLABELED USE/DISCLAIMER This educational activity may contain discussion of published and/or investigational uses of agents that are not indicated by the Food and Drug Administration. Postgraduate Institute for Medicine, Mary Ann Liebert, Inc., The Diabetes Education Group, and Bayer HealthCare, Diabetes Care do not recommend the use of any agent outside of the labeled indications. The opinions expressed in the educational activity are those of the faculty and do not necessarily represent the views of Postgraduate Institute for Medicine, Mary Ann Liebert, Inc., The Diabetes Education Group, and Bayer HealthCare, Diabetes Care. Please refer to the official prescribing information for each product for discussion of approved indications, contraindications, and warnings. Participants have an implied responsibility to use the newly acquired information to enhance patient outcomes and their own professional development. The information presented in this activity is not meant to serve as a guideline for patient management. Any procedures, medications, or other courses of diagnosis or treatment discussed or suggested in this activity should not be used by clinicians without evaluation of their patient's conditions and possible contraindications on dangers in use, review of any applicable manufacturer's product information, and comparison with recommendations of other authorities. DISCLOSURE OF CONFLICTS OF INTEREST Postgraduate Institute for Medicine assesses conflict of interest with its instructors, planners, managers, and other individuals who are in a position to control the content of CME activities. All relevant conflicts of interest that are identified are thoroughly vetted by Postgraduate Institute for Medicine for fair balance, scientific objectivity of studies utilized in this activity, and patient care recommendations. Postgraduate Institute for Medicine is committed to providing its learners with high-quality CME activities and related materials that promote improvements or quality in healthcare and not a specific proprietary business interest of a commercial interest. FACULTY DISCLOSURES Irl B. Hirsch, MD Consulting: Roche Diagnostics, Johnson & Johnson, Abbott Diabetes Care Contracted Research: sanofi-aventis, Halozyme Therapeutics Stephanie A. Amiel, BSc, MD Consulting: Roche Diagnostics, Medtronic, Janssen Pharmaceuticals Ian R. Blumer, MD Consulting: AstraZeneca, Bayer Diabetes Care, Bristol Myers Squibb, Eli Lilly, GlaxoSmithKline, Novo Nordisk, Medtronic, sanofi-aventis Bruce W. Bode, MD Consulting: Bayer HealthCare Pharmaceuticals Steven V. Edelman, MD Consulting: Bayer HealthCare Pharmaceuticals, LifeScan, Abbott Laboratories, DexCom, Roche Diagnostics Jane J. Seley, DNP, MPH, MSN, BC-ADM, CDE Consulting: Abbott Diabetes Care, Bayer HealthCare Pharmaceuticals Carol A. Verderese, BA No relevant financial relationships to disclose Eric S. Kilpatrick, MD Consulting: Bayer HealthCare Pharmaceuticals STAFF DISCLOSURES The following Postgraduate Institute for Medicine planners and managers-Trace Hutchison, PharmD; Samantha Mattiucci, PharmD; Jan Schultz, RN, MSN, CCMEP; Laura Excell, ND, NP, MS, MA, LPC, NCC; and Patricia Staples, MSN, NP-C, CCRN-hereby state that they or their spouse/life partner do not have any financial relationships or relationships to products or devices with any commercial interest related to the content of this activity of any amount during the past 12 months. The staff at Mary Ann Liebert, Inc. and The Diabetes Education Group hereby state that they or their spouse/life partner do not have any financial relationships or relationships to products or devices with any commercial interest related to the content of this activity of any amount during the past 12 months. JOINT SPONSORSHIP STATEMENT This activity is jointly sponsored/co-provided by Postgraduate Institute for Medicine, Mary Ann Liebert, Inc., and the Diabetes Education Group. COMMERCIAL SUPPORT This activity is supported by an unrestricted educational grant from Bayer HealthCare, Diabetes Care. EDUCATIONAL OBJECTIVES After completing this activity, the participant should be better able to: • Recognize the potential limitations of A1C when evaluating individual patients • Identify nonglycemic factors, other than methodical inaccuracies, that can falsely raise or lower A1C levels • Enumerate current methods for measuring short-term variations in blood glucose • Utilize patients' own self-monitoring of blood glucose data as a tool for diabetes education • Provide appropriate care and counsel for patients and their families Media: Online and Print Journal article.
Diabetes Technology & Therapeutics 10/2012; · 1.93 Impact Factor
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ABSTRACT: Administration of exogenous insulin for the treatment of diabetes is often accompanied by the development of insulin antibodies
(IA). These antibodies may affect the patient’s requirement for insulin by acting as an insulin binding reservoir. The improvement
of insulin purification in the 1970s and the development of human recombinant insulin both reduced the incidence of IA and
their binding levels. This study investigates the parameters affecting IA frequency and binding levels in a cohort of type
1 diabetes (T1D) patients. All patients were treated with human recombinant insulin. About half of the patients had received
animal insulin prior to the introduction of human recombinant insulin. We tested the IA frequency and binding level for all
serum samples. IA were further analyzed for their epitope specificity comparing human and porcine insulin binding. We found
that T1D patients who received animal insulin in the past show significantly higher IA binding levels as compared to patients
treated exclusively with human recombinant insulin (IA binding level of 0.9 and 0.25 index, respectively, P=0.005). T1D patients who received animal insulin in the past showed a relative bias towards porcine insulin, as compared
to T1D patients who were treated with human recombinant insulin exclusively (P<0.0001). We conclude that IA binding level and epitope specificity are biased by treatment with animal insulin. This bias
remains for over 20years after animal insulin treatment is terminated.
KeywordsType 1 diabetes-Insulin antibodies-Radio ligand binding assay-Antibody epitopes
Acta Diabetologica 04/2012; 47(2):131-135. · 2.78 Impact Factor
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ABSTRACT: Objective: HbA1c has been accepted as the most fundamental biomarker in diabetes, if not all of medicine, as it clearly predicts risks for diabetes-related complications. What is not generally appreciated is that HbA1c is a crude marker of glycemia with many limitations. It is now accepted that HbA1c does not reflect mean glucose for many people, and even for those it does, any level could represent a wide range of glycemia. We present a review of recent literature on the limitations of HbA1c as a marker of glycemic control.Methods: Literature was reviewed specific to analyses of major trials relating glycemic control to diabetes complications, as expressed through Hba1c as a marker of glycemic control.Results: While we have learned HbA1c is not a perfect biomarker, we also know that in the Diabetes Control and Complications Trial, HbA1c could only explain 11% of the variation in retinopathy risk between the conventional and intensive therapy groups. This important finding suggests that other glycemic and non-glycemic factors may be responsible for the pathogenesis of diabetes-related complications. One candidate is glycemic variability, which needs to be differentiated from postprandial hyperglycemia since hypoglycemia can also result in inflammatory activation. Importantly, although it is clear that in insulin-requiring patients glycemic variability is associated with hypoglycemia, we require a definitive prospective trial to confirm glycemic variability's association with one or more vascular complications.Conclusion: What is abundantly clear is that the HbA1c message, as we know it, is too simplistic. While certain wholesome concepts such as motherhood and apple pie are accepted by all, the HbA1c message may be more complex than originally appreciated, and it may be time to reevaluate our most basic premise in diabetes.
Endocrine Practice 01/2012; · 2.49 Impact Factor
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Irl B Hirsch
Diabetes Technology & Therapeutics 01/2012; 14(1):6-7. · 1.93 Impact Factor
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ABSTRACT: To review recent literature on the limitations of hemoglobin A(1c) (HbA(1c)) as a marker of glycemic control.
English-language literature published between 1985 and 2011 was reviewed specific to analyses of major trials relating glycemic control to complications of diabetes mellitus, as expressed through HbA(1c) as a marker of glycemic control.
HbA(1c) has been accepted as the most fundamental biomarker in diabetes, if not all of medicine, as it clearly predicts risk for diabetes-related complications. What is not generally appreciated is that HbA(1c) is a crude marker of glycemia with many limitations. It is now accepted that HbA(1c) does not reflect mean glucose for many people, and even for those it does, any level could represent a wide range of glycemia. While we have learned HbA(1c) is not a perfect biomarker, we also know that in the Diabetes Control and Complications Trial, HbA(1c) could only explain 11% of the variation in retinopathy risk between the conventional and intensive therapy groups. This important finding suggests that other glycemic and nonglycemic factors may be responsible for the pathogenesis of diabetes-related complications. One candidate is glycemic variability, which must be differentiated from postprandial hyperglycemia since hypoglycemia can also result in inflammatory activation. Importantly, although it is clear that in insulin-requiring patients glycemic variability is associated with hypoglycemia, we require a definitive prospective trial to confirm glycemic variability's association with one or more vascular complications.
What is abundantly clear is that the HbA(1c) message, as we know it, is too simplistic. While certain wholesome concepts such as motherhood and apple pie are accepted by all, the HbA(1c) message may be more complex than originally appreciated, and it may be time to reevaluate our most basic premise in diabetes.
Endocrine Practice 01/2012; 18(1):78-84. · 2.49 Impact Factor
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Irl B Hirsch
Diabetes Technology & Therapeutics 08/2011; 13(10):981-2. · 1.93 Impact Factor
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ABSTRACT: To evaluate both the patient factors associated with the initiation of exenatide and the real-world treatment patterns of exenatide use with and without insulin.
Using retrospective electronic medical records from the General Electric Centricity database, we performed analyses of 2 cohorts to separately evaluate factors associated with initiation of exenatide among patients with type 2 diabetes mellitus and differences between those who initiated exenatide with and without concurrent insulin use. Cohort 1 was used to assess predictors of exenatide initiation and included adults with type 2 diabetes who were active in the database when exenatide became available (October 1, 2005). Cohort 2 was used to identify characteristics of patients who initiated exenatide with and without insulin.
Cohort 1 included 190 444 adults, and cohort 2 included 9810 adults. In cohort 1, 7383 patients initiated exenatide therapy; factors associated with exenatide initiation were female sex, younger age, body weight of 102.3 kg or greater, body mass index of 35 kg/m2 or greater, residence in the southern United States, a lower Charlson Comorbidity Index, previous or existing therapy with triple oral antidiabetic drugs, and insulin plus oral antidiabetic drugs. In cohort 2, 2470 exenatide-treated patients initiated exenatide with insulin (25%) (with or without oral antidiabetic drugs). They were more likely to weigh more than 113.6 kg, have a body mass index greater than 40 kg/m2, have a Charlson Comorbidity Index of 2 or greater, and have a baseline hemoglobin A1c level greater than 9%.
Exenatide concomitant with insulin use (with or without oral antidiabetic drugs) was common, and was more likely to be prescribed in patients with morbid obesity, comorbid conditions, and poor glycemic control. Randomized controlled trials are needed to confirm the safe and effective use of this combination.
Endocrine Practice 08/2011; 17(5):707-16. · 2.49 Impact Factor
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JAMA The Journal of the American Medical Association 06/2011; 305(24):2522-2523. · 30.03 Impact Factor
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ABSTRACT: One of the first steps in the management of patients with type 2 diabetes mellitus is setting glycemic goals. Professional organizations advise setting specific hemoglobin A(1c) (HbA(1c)) targets for patients, and individualization of these goals has more recently been emphasized. However, the operational meaning of glycemic goals, and specific methods for individualizing them, have not been well-described. Choosing a specific HbA(1c) target range for a given patient requires taking several factors into consideration, including an assessment of the patient's risk for hyperglycemia-related complications versus the risks of therapy, all in the context of the overall clinical setting. Comorbid conditions, psychological status, capacity for self-care, economic considerations, and family and social support systems also play a key role in the intensity of therapy. The individualization of HbA(1c) targets has gained more traction after recent clinical trials in older patients with established type 2 diabetes mellitus failed to show a benefit from intensive glucose-lowering therapy on cardiovascular disease (CVD) outcomes. The limited available evidence suggests that near-normal glycemic targets should be the standard for younger patients with relatively recent onset of type 2 diabetes mellitus and little or no micro- or macrovascular complications, with the aim of preventing complications over the many years of life. However, somewhat higher targets should be considered for older patients with long-standing type 2 diabetes mellitus and evidence of CVD (or multiple CVD risk factors). This review explores these issues further and proposes a framework for considering an appropriate and safe HbA(1c) target range for each patient.
Annals of internal medicine 04/2011; 154(8):554-9. · 16.73 Impact Factor
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JAMA The Journal of the American Medical Association 03/2011; 305(11):1132-3. · 30.03 Impact Factor
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ABSTRACT: Drawing on previous web-based diabetes management programs based on the Chronic Care Model, we expanded an intervention to include care management through mobile phones and a game console web browser.
The pilot intervention enrolled eight diabetes patients from the University of Washington in Seattle into a collaborative care program: connecting them to a care provider specializing in diabetes, providing access to their full electronic medical record, allowing wireless glucose uploads and e-mail with providers, and connecting them to the program's web services through a game system. To evaluate the study, we conducted qualitative thematic analysis of semistructured interviews.
Participants expressed frustrations with using the cell phones and the game system in their everyday lives, but liked the wireless system for collaborating with a provider on uploaded glucoses and receiving automatic feedback on their blood sugar trends. A majority of participants also expressed that their participation in the trial increased their health awareness.
Mobile communication technologies showed promise within a web-based collaborative care program for type 2 diabetes. Future intervention design should focus on integrating easy-to-use applications within mobile technologies already familiar to patients and ensure the system allows for sufficient collaboration with a care provider.
Diabetes Technology & Therapeutics 03/2011; 13(5):563-9. · 1.93 Impact Factor
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Irl B Hirsch
Journal of Diabetes 12/2010; 2(4):225-6.
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ABSTRACT: To identify the factors that encourage or discourage internal medicine and pediatric residents regarding specializing in endocrinology with a focus on diabetes.
We conducted an electronic survey of internal medicine and pediatric residents using a $10 participation incentive. A total of 653 residents responded to the survey (estimated response rate of 9.2%)-626 from residency programs that were contacted for our survey and 27 from referrals.
Among internal medicine and pediatric residents surveyed, 39 respondents (6.0%) planned to specialize in endocrinology, and 27 of these (4.1% of total respondents) planned to focus on diabetes. "Intellectual satisfaction," "emotional satisfaction," and "work-life balance" were identified by respondents as the most important factors in their choice of a specialty, with ratings of 5.5, 5.4, and 5.3 on a 6-point Likert scale. Among these factors identified as most important to a medical career, endocrinology with a focus on diabetes scored poorly with regard to intellectual and emotional satisfaction but received high ranking with regard to lifestyle. With regard to other factors, endocrinology was rated negatively on "compensation," "number of procedures," and "patient adherence to prescribed treatment." Exposure to diabetes during training had no major influence on the decision to enter endocrinology.
Endocrinology with a focus on diabetes care is not an attractive specialty for most internal medicine and pediatric residents. Therefore, new strategies to attract residents to the field of diabetes care are needed.
Endocrine Practice 11/2010; 17(2):235-9. · 2.49 Impact Factor
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Lynne T Harris,
James Tufano,
Tung Le,
Courtney Rees,
Ginny A Lewis,
Alison B Evert,
Jan Flowers,
Carol Collins,
James Hoath, Irl B Hirsch,
Harold I Goldberg,
James D Ralston
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ABSTRACT: We assessed the feasibility and acceptability of using mobile phones as part of an existing Web-based system for collaboration between patients with diabetes and a primary care team. In design sessions, we tested mobile wireless glucose meter uploads and two approaches to mobile phone-based feedback on glycemic control. Mobile glucose meter uploads combined with graphical and tabular data feedback were the most desirable system features tested. Participants had a mixture of positive and negative reactions to an automated and tailored messaging feedback system for self-management support. Participants saw value in the mobile system as an adjunct to the Web-based program and traditional office-based care. Mobile diabetes management systems may represent one strategy to improve the quality of diabetes care.
Journal of Biomedical Informatics 10/2010; 43(5 Suppl):S37-40. · 1.79 Impact Factor
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ABSTRACT: Type 1 diabetes poses unique inpatient challenges because of the risks of diabetic ketoacidosis, uncontrolled hyperglycemia, and hypoglycemia. Although newer insulin analogs and insulin pumps provide means for improved glycemic control, they can be daunting for nonexperts. This article focuses on inpatient and perioperative insulin management of stable, nonketotic, nonpregnant adults and children with type 1 diabetes. These principles can also be applied to patients with steroid-induced hyperglycemia.
Endocrinology and metabolism clinics of North America 09/2010; 39(3):595-608. · 3.56 Impact Factor
