Howard Wolpert

Joslin Diabetes Center, Boston, Massachusetts, United States

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Publications (27)151.65 Total impact

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    ABSTRACT: The objective was to develop an analysis methodology for generating diabetes therapy decision guidance using continuous glucose (CG) data. The novel Likelihood of Low Glucose (LLG) methodology, which exploits the relationship between glucose median, glucose variability, and hypoglycemia risk, is mathematically based and can be implemented in computer software. Using JDRF Continuous Glucose Monitoring Clinical Trial data, CG values for all participants were divided into 4-week periods starting at the first available sensor reading. The safety and sensitivity performance regarding hypoglycemia guidance "stoplights" were compared between the LLG method and one based on 10th percentile (P10) values. Examining 13 932 hypoglycemia guidance outputs, the safety performance of the LLG method ranged from 0.5% to 5.4% incorrect "green" indicators, compared with 0.9% to 6.0% for P10 value of 110 mg/dL. Guidance with lower P10 values yielded higher rates of incorrect indicators, such as 11.7% to 38% at 80 mg/dL. When evaluated only for periods of higher glucose (median above 155 mg/dL), the safety performance of the LLG method was superior to the P10 method. Sensitivity performance of correct "red" indicators of the LLG method had an in sample rate of 88.3% and an out of sample rate of 59.6%, comparable with the P10 method up to about 80 mg/dL. To aid in therapeutic decision making, we developed an algorithm-supported report that graphically highlights low glucose risk and increased variability. When tested with clinical data, the proposed method demonstrated equivalent or superior safety and sensitivity performance.
    Journal of diabetes science and technology 04/2014;
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    ABSTRACT: This qualitative study aimed to explore the experience of transition from pediatric to adult diabetes care reported by posttransition emerging adults with type 1 diabetes (T1D), with a focus on preparation for the actual transfer in care.
    Adolescent Health, Medicine and Therapeutics 01/2014; 5:191-8.
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    Howard A Wolpert
    Diabetes care 12/2013; 36(12):e212. · 7.74 Impact Factor
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    ABSTRACT: PurposeThe purpose of this study was to explore perceptions that emerging adults with type 1 diabetes (T1D) have of their patient-provider relationships across the transition from pediatric to adult care.Methods Twenty-six emerging adults with T1D (mean age 26.2 ± 2.5 years) participated in 5 focus groups stratified by current level of glycemic control (A1C). Coded audio-recorded data were analyzed using thematic analysis and aided by NVivo software.ResultsThree major themes emerged from the analysis: (1) loss and gain in provider relationships across the transition-patients expressed 3 key responses to leaving pediatric providers that differed by A1C levels: sad reluctance and "natural progression" (mean A1C ± SD 7.4% ± 0.6%) and wanting to go (mean A1C ± SD 9.8% ± 1.0%); (2) partners in care versus on one's own-patients valued how adult providers' collaborative conversations promoted their involvement and accountability compared to "parent-centric" interactions with pediatric providers, but they also expressed ambivalence over increased independence in adult care; (3) improving provider approaches to transition-patients recommended that pediatric providers actively promote emerging adults' autonomy while maintaining parental support, communication with adult providers, and follow-up with transitioning patients.Conclusions Findings highlight the importance of enhanced provider awareness of T1D emerging adults' complex feelings about the transition in care. Improved integration of individual- and family-centered approaches to developmentally tailored diabetes care is needed to augment patient and provider relationships.
    The Diabetes Educator 11/2013; · 1.92 Impact Factor
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    ABSTRACT: To examine the impact of continuous glucose monitoring on diabetes management and marital relationships of adults with Type 1 diabetes and their spouses. Nine younger (30-49 years) and 11 older (50-70 years) patients with Type 1 diabetes and 14 spouses participated in eight focus groups specific to age and role (patient or spouse). Audio-recorded data were transcribed, coded and analysed using thematic analysis and aided by NVivo software. Qualitative analysis revealed participants perceived continuous glucose monitoring as positively influencing hypoglycaemia management by decreasing spouses' anxiety, vigilance and negative experiences. Participants also described continuous glucose monitoring as promoting collaborative diabetes management and increasing spousal understanding of diabetes, especially when planning and managing pregnancy. Couples' conflicts occurred when (1) patients assumed sole responsibility for continuous glucose monitoring and/or did not respond to night-time glucose alarms and (2) spouses did not understand alarms and felt frustrated and helpless to assist patients. Our findings suggest that continuous glucose monitoring may positively impact collaborative diabetes management and marital relationships of patients with Type 1 diabetes and spouses. However, reluctance to collaborate and lack of understanding may contribute to couples' conflicts around continuous glucose monitoring. Our findings have important implications for clinical care and point to the need for interventions that include spouses in continuous glucose monitoring training to increase their understanding of continuous glucose monitoring, minimize risk for spousal conflict and enhance collaborative diabetes management. Further studies are needed to explore these issues in more detail and depth with larger and more diverse populations. This article is protected by copyright. All rights reserved.
    Diabetic Medicine 07/2013; · 3.24 Impact Factor
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    ABSTRACT: Objective: To examine barriers to health care transition reported by young adults with type 1 diabetes and associations between barriers and prolonged gaps between pediatric and adult diabetes care.Methods: We surveyed young adults with type 1 diabetes, aged 22 to 30 years, about their transition experiences, including barriers to timely establishment of adult diabetes care. We evaluated relationships between barriers and gaps in care with multivariate logistic regression.Results: The response rate was 53% (258 of 484 eligible). Respondents (62% female) were 26.7±2.4 years old and transitioned to adult diabetes care at 19.5±2.9 years. Reported barriers included lack of specific adult provider referral name (47%) or contact information (27%), competing life priorities (43%), difficulty getting an appointment (41%), feeling upset about leaving pediatrics (24%), and insurance problems (10%). In multivariate analysis, barriers most strongly associated with gaps in care >6 months were lack of adult provider name (OR 6.1, 95% CI 3.0, 12.7) or contact information (OR 5.3, 95% CI 2.0, 13.9), competing life priorities (OR 5.2, 95% CI 2.7, 10.3), and insurance problems (OR 3.5, 95% CI 1.2, 10.3). Overall, respondents reporting ≥1 moderate/major barrier (48%) had 4.7-fold greater adjusted odds of a gap >6 months (95% CI 2.8, 8.7).Conclusions: Significant barriers to transition, such as lack of specific adult provider referrals, may be addressed with more robust preparation by pediatric providers and care coordination. Further study is needed to evaluate strategies to improve young adult self-care in the setting of competing life priorities.
    Endocrine Practice 06/2013; · 2.49 Impact Factor
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    ABSTRACT: OBJECTIVE Current guidelines for intensive treatment of type 1diabetes base the mealtime insulin bolus calculation exclusively on carbohydrate counting. There is strong evidence that free fatty acids impair insulin sensitivity. We hypothesized that patients with type 1 diabetes would require more insulin coverage for higher-fat meals than lower-fat meals with identical carbohydrate content.RESEARCH DESIGN AND METHODS We used a crossover design comparing two 18-h periods of closed-loop glucose control after high-fat (HF) dinner compared with low-fat (LF) dinner. Each dinner had identical carbohydrate and protein content, but different fat content (60 vs. 10 g).RESULTSSeven patients with type 1 diabetes (age, 55 ± 12 years; A1C 7.2 ± 0.8%) successfully completed the protocol. HF dinner required more insulin than LF dinner (12.6 ± 1.9 units vs. 9.0 ± 1.3 units; P = 0.01) and, despite the additional insulin, caused more hyperglycemia (area under the curve >120 mg/dL = 16,967 ± 2,778 vs. 8,350 ± 1,907 mg/dL⋅min; P < 0001). Carbohydrate-to-insulin ratio for HF dinner was significantly lower (9 ± 2 vs. 13 ± 3 g/unit; P = 0.01). There were marked interindividual differences in the effect of dietary fat on insulin requirements (percent increase significantly correlated with daily insulin requirement; R(2) = 0.64; P = 0.03).CONCLUSION This evidence that dietary fat increases glucose levels and insulin requirements highlights the limitations of the current carbohydrate-based approach to bolus dose calculation. These findings point to the need for alternative insulin dosing algorithms for higher-fat meals and suggest that dietary fat intake is an important nutritional consideration for glycemic control in individuals with type 1 diabetes.
    Diabetes care 11/2012; · 7.74 Impact Factor
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    ABSTRACT: To examine characteristics of the transition from pediatric to adult care in emerging adults with type 1 diabetes and evaluate associations between transition characteristics and glycemic control. We developed and mailed a survey to evaluate the transition process in emerging adults with type 1 diabetes, aged 22 to 30 years, receiving adult diabetes care at a single center. Current A1C data were obtained from the medical record. The response rate was 53% (258 of 484 eligible). The mean transition age was 19.5 ± 2.9 years, and 34% reported a gap >6 months in establishing adult care. Common reasons for transition included feeling too old (44%), pediatric provider suggestion (41%), and college (33%). Less than half received an adult provider recommendation and <15% reported having a transition preparation visit or receiving written transition materials. The most recent A1C was 8.1 ± 1.3%. Respondents who felt mostly/completely prepared for transition had lower likelihood of a gap >6 months between pediatric and adult care (adjusted odds ratio 0.47 [95% CI 0.25-0.88]). In multivariate analysis, pretransition A1C (β = 0.49, P < 0.0001), current age (β = -0.07, P = 0.03), and education (β = -0.55, P = 0.01) significantly influenced current posttransition A1C. There was no independent association of transition preparation with posttransition A1C (β = -0.17, P = 0.28). Contemporary transition practices may help prevent gaps between pediatric and adult care but do not appear to promote improvements in A1C. More robust preparation strategies and handoffs between pediatric and adult care should be evaluated.
    Diabetes care 06/2012; 35(8):1716-22. · 7.74 Impact Factor
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    Julie Wagner, Howard Tennen, Howard Wolpert
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    ABSTRACT: Continuous glucose monitoring (CGM) systems collect and store glucose data in an ongoing fashion for several days at a time. The main advantage of CGM is that it can help identify fluctuations and trends that would otherwise go unnoticed with other glucose measures. Here, we provide a review of CGM for behavioral researchers. We begin with a brief review of diabetes and glucose measurement and then describe what CGM is and reference the commercial CGM systems currently available. We discuss the challenges involved in using CGM in behavioral research. We then present a broad overview of CGM in behavioral research, including data from ours and others' research programs. Finally, we cover some practical issues to be considered when using CGM, suggest reporting guidelines for the behavioral researcher, and offer suggestions for future research. Only a handful of behavioral researchers are using CGM, although its use is increasing. The main ways that CGM is being used in behavioral research is to investigate basic biobehavioral processes, to assess the effects of behavioral interventions on diabetes control, and to use CGM itself as a behavior modification and teaching tool in diabetes self-management interventions. Continuous glucose monitoring holds promise to help behavioral researchers unravel the complex relationships among glucose and intrapersonal, interpersonal, and contextual factors. However, the uptake of CGM for this purpose is limited, and the possibilities for its use are largely unmet. We encourage behavioral researchers to implement CGM in their protocols and to do so in a way that maximizes its explanatory power.
    Psychosomatic Medicine 05/2012; 74(4):356-65. · 4.09 Impact Factor
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    ABSTRACT: The aim was to formulate practice guidelines for determining settings where patients are most likely to benefit from the use of continuous glucose monitoring (CGM). The Endocrine Society appointed a Task Force of experts, a methodologist, and a medical writer. This evidence-based guideline was developed using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) system to describe both the strength of recommendations and the quality of evidence. One group meeting, several conference calls, and e-mail communications enabled consensus. Committees and members of The Endocrine Society, the Diabetes Technology Society, and the European Society of Endocrinology reviewed and commented on preliminary drafts of these guidelines. The Task Force evaluated three potential uses of CGM: 1) real-time CGM in adult hospital settings; 2) real-time CGM in children and adolescent outpatients; and 3) real-time CGM in adult outpatients. The Task Force used the best available data to develop evidence-based recommendations about where CGM can be beneficial in maintaining target levels of glycemia and limiting the risk of hypoglycemia. Both strength of recommendations and quality of evidence were accounted for in the guidelines.
    The Journal of Clinical Endocrinology and Metabolism 10/2011; 96(10):2968-79. · 6.31 Impact Factor
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    ABSTRACT: To determine the individual persistence of the relationship between mean sensor glucose (MG) concentrations and hemoglobin A(1c) (A1C) from the Juvenile Diabetes Research Foundation Continuous Glucose Monitoring (CGM) Randomized Trial. MG was calculated using CGM data for 3 months before A1C measurements at 3, 6, 9, and 12 months for the CGM group and at 9 and 12 months for the control group. An MG-to-A1C ratio was included in analysis for subjects who averaged ≥4 days/week of CGM use. Spearman correlations of the MG-to-A1C ratio between consecutive visits 3 months apart ranged from 0.70 to 0.79. The correlations for children and youth were slightly smaller than those for adults. No meaningful differences were observed by device type or change in A1C. Individual variations in the rate of hemoglobin glycation are persistent and contribute to the inaccuracy in estimating MGs calculated from A1C levels.
    Diabetes care 06/2011; 34(6):1315-7. · 7.74 Impact Factor
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    ABSTRACT: Identify factors predictive of severe hypoglycemia (SH) and assess the clinical utility of continuous glucose monitoring (CGM) to warn of impending SH. In a multicenter randomized clinical trial, 436 children and adults with type 1 diabetes were randomized to a treatment group that used CGM (N = 224), or a control group that used standard home blood glucose monitoring (N = 212) and completed 12 months of follow-up. After 6 months, the original control group initiated CGM while the treatment group continued use of CGM for 6 months. Baseline risk factors for SH were evaluated over 12 months of follow-up using proportional hazards regression. CGM-derived indices of hypoglycemia were used to predict episodes of SH over a 24-h time horizon. The SH rate was 17.9 per 100 person-years, and a higher rate was associated with the occurrence of SH in the prior 6 months and female sex. SH frequency increased eightfold when 30% of CGM values were ≤ 70 mg/dL on the prior day (4.5 vs. 0.5%; P < 0.001), but the positive predictive value (PPV) was low (<5%). Results were similar for hypoglycemic area under the curve and the low blood glucose index calculated by CGM. SH in the 6 months prior to the study was the strongest predictor of SH during the study. CGM-measured hypoglycemia over a 24-h span is highly associated with SH the following day (P < 0.001), but the PPV is low.
    Diabetes care 03/2011; 34(3):586-90. · 7.74 Impact Factor
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    ABSTRACT: To identify psychosocial factors associated with the use of continuous glucose monitoring by adults with Type 1 diabetes. Twenty adult patients (aged 45 +/- 15 years, diabetes duration 25 +/- 19 years, 50% female) followed at our site in the multi-centre Juvenile Diabetes Research Foundation continuous glucose monitoring trial were divided into three groups: Glycated haemoglobin (HbA(1c)) Responders who demonstrated an improvement in glycaemic control with continuous glucose monitoring (baseline HbA(1c)> or = 7.0%, HbA(1c) reduction greater than or equal to 0.5%), Hypoglycaemia Responders (baseline HbA(1c) < 7.0%) who demonstrated decreased time < 3.9 mmol/l while remaining within target HbA(1c), and HbA(1c) Non-Responders (baseline HbA(1c)> or = 7.0%, HbA(1c) reduction less than 0.5%). Subjects participated in semi-structured interviews focusing on their psychosocial experiences with continuous glucose monitoring. Three major themes were identified that differentiated Responders (including both the HbA(1c) and Hypoglycaemia groups) from Non-Responders: (i) coping with frustrations-Responders used self-controlled rather than emotions-based coping when faced with continuous glucose monitoring frustrations; (ii) use of information-Responders used retrospective pattern analysis, not just minute-by-minute data analysis, in glycaemic management; (iii) 'significant other'/spousal involvement-Responders endorsed interest, encouragement and participation by their loved ones. Both Responders and Non-Responders expressed body image concerns when wearing continuous glucose monitoring devices. This qualitative study points to the importance of coping skills, retrospective review of data, and 'significant other' involvement in the effective use of continuous glucose monitoring. These findings will inform clinical initiatives to improve patient selection and training in the use of this new technology and have served as the basis for development of quantitative surveys to be used in clinical practice.
    Diabetic Medicine 09/2010; 27(9):1060-5. · 3.24 Impact Factor
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    Howard A Wolpert
    New England Journal of Medicine 07/2010; 363(4):383-4. · 54.42 Impact Factor
  • Greeshma Shetty, Howard Wolpert
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    ABSTRACT: In recent years continuous subcutaneous insulin infusion pumps have become widely adopted in many parts of the world in the treatment of type 1 diabetes in adults. A comprehensive summary of all aspects of pump therapy is beyond the scope of this article, and in this review we will focus on several practical issues that in our experience are of clinical importance in the care of patients using insulin pumps. These include: benefits and risks of pump therapy, including the use of pumps to limit hypoglycemia; individual patient considerations in choosing between pump therapy and multiple daily injections; common pump-specific etiologies of erratic glucose control, including routine clinical practices that can assist with the detection of these problems; and the use of different pump bolus types for prandial insulin coverage.
    Diabetes Technology &amp Therapeutics 06/2010; 12 Suppl 1:S11-6. · 2.29 Impact Factor
  • William C. Hsu, Howard A. Wolpert
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    ABSTRACT: New diabetes technologies, such as insulin pump therapies and continuous glucose monitors (CGM), have become important tools for helping control hypoglycemia and achieving glycemic targets. There are, of course, advantages and disadvantages to the adoption of these technological tools, and patients require mastery of new skills in order to use these tools successfully. For the patient, use of the new technologies can be overwhelming or extremely helpful, which often depends on one’s level of knowledge about the new tools. Therefore, this chapter provides the basic foundation for educating patients about these new diabetes technologies.
    12/2008: pages 135-141;
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    ABSTRACT: The objective of the study was to evaluate the clinical effectiveness and safety of a device that combines an insulin pump with real-time continuous glucose monitoring (CGM), compared to using an insulin pump with standard blood glucose monitoring systems. This 6-month, randomized, multicenter, treat-to-target study enrolled 146 subjects treated with continuous subcutaneous insulin infusion between the ages of 12 and 72 years with type 1 diabetes and initial A1C levels of >or=7.5%. Subjects were randomized to pump therapy with real-time CGM (sensor group [SG]) or to pump therapy and self-monitoring of blood glucose only (control group [CG]). Clinical effectiveness and safety were evaluated. A1C levels decreased (P<0.001) from baseline (8.44+/-0.70%) in both groups (SG, -0.71+/-0.71%; CG, -0.56+/-0.072%); however, between-group differences did not achieve significance. SG subjects showed no change in mean hypoglycemia area under the curve (AUC), whereas CG subjects showed an increase (P=0.001) in hypoglycemia AUC during the blinded periods of the study. The between-group difference in hypoglycemia AUC was significant (P<0.0002). Greater than 60% sensor utilization was associated with A1C reduction (P=0.0456). Fourteen severe hypoglycemic events occurred (11 in the SG group and three in the CG group, P=0.04). A1C reduction was no different between the two groups. Subjects in the CG group had increased hypoglycemia AUC and number of events during blinded CGM use; however, there was no increase in hypoglycemia AUC or number of events in the SG group. Subjects with greater sensor utilization showed a greater improvement in A1C levels.
    Diabetes Technology &amp Therapeutics 11/2008; 10(5):377-83. · 2.29 Impact Factor
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    ABSTRACT: BACKGROUND: The value of continuous glucose monitoring in the management of type 1 diabetes mellitus has not been determined. METHODS: In a multicenter clinical trial, we randomly assigned 322 adults and children who were already receiving intensive therapy for type 1 diabetes to a group with continuous glucose monitoring or to a control group performing home monitoring with a blood glucose meter. All the patients were stratified into three groups according to age and had a glycated hemoglobin level of 7.0 to 10.0%. The primary outcome was the change in the glycated hemoglobin level at 26 weeks. RESULTS: The changes in glycated hemoglobin levels in the two study groups varied markedly according to age group (P=0.003), with a significant difference among patients 25 years of age or older that favored the continuous-monitoring group (mean difference in change, -0.53%; 95% confidence interval [CI], -0.71 to -0.35; P<0.001). The between-group difference was not significant among those who were 15 to 24 years of age (mean difference, 0.08; 95% CI, -0.17 to 0.33; P=0.52) or among those who were 8 to 14 years of age (mean difference, -0.13; 95% CI, -0.38 to 0.11; P=0.29). Secondary glycated hemoglobin outcomes were better in the continuous-monitoring group than in the control group among the oldest and youngest patients but not among those who were 15 to 24 years of age. The use of continuous glucose monitoring averaged 6.0 or more days per week for 83% of patients 25 years of age or older, 30% of those 15 to 24 years of age, and 50% of those 8 to 14 years of age. The rate of severe hypoglycemia was low and did not differ between the two study groups; however, the trial was not powered to detect such a difference. CONCLUSIONS: Continuous glucose monitoring can be associated with improved glycemic control in adults with type 1 diabetes. Further work is needed to identify barriers to effectiveness of continuous monitoring in children and adolescents. (ClinicalTrials.gov number, NCT00406133.)
    The New England journal of medicine. 10/2008; 359(14):1464-1476.
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    ABSTRACT: Continuous glucose monitoring (CGM) is an evolving technology poised to redefine current concepts of glycemic control and optimal diabetes management. To date, there are few randomized studies examining how to most effectively use this new tool. Therefore, a group of eight diabetes specialists heard presentations on continuous glucose sensor technology and then discussed their experience with CGM in order to identify fundamental considerations, objectives, and methods for applying this technology in clinical practice. The group concluded that routine use of CGM, with real-time data showing the rate and direction of glucose change, could revolutionize current approaches to evaluating and managing glycemia. The need for such progress is indicated by the growing prevalence of inadequately treated hyperglycemia. Coordinating financial and educational resources and developing clear protocols for using glucose sensor technology are urgent priorities in promoting wide adoption of CGM by patients and health care providers. Finally, researchers, manufacturers, payers, and advocacy groups must join forces on the policy level to create an environment conducive to managing continuous data, measuring outcomes, and formalizing best practices.
    Diabetes Technology &amp Therapeutics 09/2008; 10(4):232-44; quiz 245-6. · 2.29 Impact Factor
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    Howard Wolpert
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    ABSTRACT: Real-time continuous glucose monitoring (RT-CGM) devices provide detailed information on glucose patterns and trends, and alarms that alert the patient to both hyper- and hypoglycemia. This technology can dramatically improve the day-to-day management of patients with diabetes and promises to be a major advance in diabetes care. The safe and effective use of RT-CGM in diabetes management rests on an understanding of several physiological as well as technological issues. This article outlines the key issues that should be addressed in the training curriculum for patients starting on RT-CGM: (1) physiologic lag between interstitial and blood glucose levels and the implications for device calibration, and interpretation and use of data in diabetes management; (2) practical considerations with the use of sensor alarms and caveats in the setting of alarm thresholds; and (3) potential risk for hypoglycemia related to excessive postprandial bolusing by RT-CGM users, and the practical implications for patient training.
    Journal of diabetes science and technology 03/2008; 2(2):307-10.

Publication Stats

570 Citations
151.65 Total Impact Points

Institutions

  • 2008–2014
    • Joslin Diabetes Center
      Boston, Massachusetts, United States
    • University of Washington Seattle
      • Department of Medicine
      Seattle, WA, United States
  • 2005–2013
    • Harvard University
      Cambridge, Massachusetts, United States
    • University of New Mexico
      Albuquerque, New Mexico, United States
  • 2012
    • UConn Health Center
      Farmington, Connecticut, United States
  • 2011
    • Mills-Peninsula Health Services
      Burlingame, California, United States
    • Stanford University
      • Division of Pediatric Endocrinology
      Stanford, CA, United States
  • 2007
    • Harvard Medical School
      Boston, Massachusetts, United States
  • 2004
    • Baylor College of Medicine
      • Children's Nutrition Research Center
      Houston, TX, United States