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Kelly L. Close

Bio: Kelly L. Close is an academic researcher. The author has contributed to research in topics: Diabetes mellitus & MEDLINE. The author has an hindex of 20, co-authored 73 publications receiving 3078 citations.


Papers
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Journal ArticleDOI
TL;DR: This article summarizes the ATTD consensus recommendations for relevant aspects of CGM data utilization and reporting among the various diabetes populations.
Abstract: 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.

1,776 citations

Journal ArticleDOI
TL;DR: Clinical significant hypoglycemia is now defined at blood glucose levels <54 mg/dL, whereas blood sugar levels <70mg/dL should be used as an “alert value” to help individuals avoid more severe hypoglycesmia.
Abstract: The American Diabetes Association’s (ADA) 2017 Standards of Care were published in Diabetes Care on 15 December 2016. Notable changes in the new guidelines include the recommendation of sodiumglucose cotransporter 2 (SGLT-2) inhibitor empagliflozin and glucagon-like peptide 1 (GLP-1) agonist liraglutide for type 2 diabetes (T2D) patients at high risk for cardiovascular morbidity and mortality. Data from the Empagliflozin, Cardiovascular Outcomes, and Mortality in Type 2 Diabetes (EMPA-REG OUTCOME) trial and the Liraglutide Effect and Action in Diabetes: Evaluation of Cardiovascular Outcome Results (LEADER) trial are now included in the section on cardiovascular disease and risk management. In addition, fixed-ratio combinations of a basal insulin and a GLP-1 agonist are included in the algorithm for combination therapy, just weeks after the first of these products, Novo Nordisk’s (Copenhagen, Denmark) Xultophy (insulin degludec/liraglutide) and Sanofi’s (Paris, France) Soliqua (insulin glargine/lixisenatide), were approved by the US Food and Drug Administration (FDA) for prescription in the US. Based on recommendations from the International Hypoglycemia Study Group, the ADA’s 2017 Standards of Care features a new classification for hypoglycemia: clinically significant hypoglycemia is now defined at blood glucose levels <54 mg/dL, whereas blood glucose levels <70 mg/dL should be used as an “alert value” to help individuals avoid more severe hypoglycemia. The ADA’s new guidelines also include a greater emphasis on cost of diabetes drugs, T2D prevention (with a push for more frequent prediabetes screenings), and psychosocial support in diabetes care, especially for adolescents and pediatric patients.

506 citations

Journal ArticleDOI
TL;DR: A compelling case can be made that TIR is strongly associated with the risk of microvascular complications and should be an acceptable end point for clinical trials.
Abstract: OBJECTIVE This study evaluated the association of time in range (TIR) of 70–180 mg/dL (3.9–10 mmol/L) with the development or progression of retinopathy and development of microalbuminuria using the Diabetes Control and Complications (DCCT) data set in order to validate the use of TIR as an outcome measure for clinical trials. RESEARCH DESIGN AND METHODS In the DCCT, blood glucose concentrations were measured at a central laboratory from seven fingerstick samples (seven-point testing: pre- and 90-min postmeals and at bedtime) collected during 1 day every 3 months. Retinopathy progression was assessed every 6 months and urinary microalbuminuria development every 12 months. Proportional hazards models were used to assess the association of TIR and other glycemic metrics, computed from the seven-point fingerstick data, with the rate of development of microvascular complications. RESULTS Mean TIR of seven-point profiles for the 1,440 participants was 41 ± 16%. The hazard rate of development of retinopathy progression was increased by 64% (95% CI 51–78), and development of the microalbuminuria outcome was increased by 40% (95% CI 25–56) for each 10 percentage points lower TIR ( P CONCLUSIONS Based on these results, a compelling case can be made that TIR is strongly associated with the risk of microvascular complications and should be an acceptable end point for clinical trials. Although hemoglobin A 1c remains a valuable outcome metric in clinical trials, TIR and other glycemic metrics—especially when measured with continuous glucose monitoring—add value as outcome measures in many studies.

475 citations

Journal ArticleDOI
TL;DR: The authors work toward a multipart solution to facilitate the retention of such a metric, which includes renaming the eA1C the glucose management indicator (GMI) and generating a new formula for converting CGM-derived mean glucose to GMI based on recent clinical trials using the most accurate CGM systems available.
Abstract: While A1C is well established as an important risk marker for diabetes complications, with the increasing use of continuous glucose monitoring (CGM) to help facilitate safe and effective diabetes management, it is important to understand how CGM metrics, such as mean glucose, and A1C correlate. Estimated A1C (eA1C) is a measure converting the mean glucose from CGM or self-monitored blood glucose readings, using a formula derived from glucose readings from a population of individuals, into an estimate of a simultaneously measured laboratory A1C. Many patients and clinicians find the eA1C to be a helpful educational tool, but others are often confused or even frustrated if the eA1C and laboratory-measured A1C do not agree. In the U.S., the Food and Drug Administration determined that the nomenclature of eA1C needed to change. This led the authors to work toward a multipart solution to facilitate the retention of such a metric, which includes renaming the eA1C the glucose management indicator (GMI) and generating a new formula for converting CGM-derived mean glucose to GMI based on recent clinical trials using the most accurate CGM systems available. The final aspect of ensuring a smooth transition from the old eA1C to the new GMI is providing new CGM analyses and explanations to further understand how to interpret GMI and use it most effectively in clinical practice. This Perspective will address why a new name for eA1C was needed, why GMI was selected as the new name, how GMI is calculated, and how to understand and explain GMI if one chooses to use GMI as a tool in diabetes education or management.

338 citations


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01 Jan 2014
TL;DR: These standards of care are intended to provide clinicians, patients, researchers, payors, and other interested individuals with the components of diabetes care, treatment goals, and tools to evaluate the quality of care.
Abstract: XI. STRATEGIES FOR IMPROVING DIABETES CARE D iabetes is a chronic illness that requires continuing medical care and patient self-management education to prevent acute complications and to reduce the risk of long-term complications. Diabetes care is complex and requires that many issues, beyond glycemic control, be addressed. A large body of evidence exists that supports a range of interventions to improve diabetes outcomes. These standards of care are intended to provide clinicians, patients, researchers, payors, and other interested individuals with the components of diabetes care, treatment goals, and tools to evaluate the quality of care. While individual preferences, comorbidities, and other patient factors may require modification of goals, targets that are desirable for most patients with diabetes are provided. These standards are not intended to preclude more extensive evaluation and management of the patient by other specialists as needed. For more detailed information, refer to Bode (Ed.): Medical Management of Type 1 Diabetes (1), Burant (Ed): Medical Management of Type 2 Diabetes (2), and Klingensmith (Ed): Intensive Diabetes Management (3). The recommendations included are diagnostic and therapeutic actions that are known or believed to favorably affect health outcomes of patients with diabetes. A grading system (Table 1), developed by the American Diabetes Association (ADA) and modeled after existing methods, was utilized to clarify and codify the evidence that forms the basis for the recommendations. The level of evidence that supports each recommendation is listed after each recommendation using the letters A, B, C, or E.

9,618 citations

Journal ArticleDOI
Bin Zhou1, Yuan Lu2, Kaveh Hajifathalian2, James Bentham1  +494 moreInstitutions (170)
TL;DR: In this article, the authors used a Bayesian hierarchical model to estimate trends in diabetes prevalence, defined as fasting plasma glucose of 7.0 mmol/L or higher, or history of diagnosis with diabetes, or use of insulin or oral hypoglycaemic drugs in 200 countries and territories in 21 regions, by sex and from 1980 to 2014.

2,782 citations

Journal ArticleDOI
TL;DR: This article summarizes the ATTD consensus recommendations for relevant aspects of CGM data utilization and reporting among the various diabetes populations.
Abstract: 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.

1,776 citations

Journal ArticleDOI
TL;DR: Document reviewers: Hind Beheiry (Sudan), Irina Chazova (Russia), Albertino Damasceno (Mozambique), Anna Dominiczak (UK), Stephen Harrap (Australia), Hiroshi Itoh (Japan), Tazeen Jafar (Singapore), Marc Jaffe (USA), Patricio Jaramillo-Lopez (Colombia), Kazuomi Kario (Japan).
Abstract: Document reviewers: Hind Beheiry (Sudan), Irina Chazova (Russia), Albertino Damasceno (Mozambique), Anna Dominiczak (UK), Anastase Dzudie (Cameroon), Stephen Harrap (Australia), Hiroshi Itoh (Japan), Tazeen Jafar (Singapore), Marc Jaffe (USA), Patricio Jaramillo-Lopez (Colombia), Kazuomi Kario (Japan), Giuseppe Mancia (Italy), Ana Mocumbi (Mozambique), Sanjeevi N.Narasingan (India), Elijah Ogola (Kenya), Srinath Reddy (India), Ernesto Schiffrin (Canada), Ann Soenarta (Indonesia), Rhian Touyz (UK), Yudah Turana (Indonesia), Michael Weber (USA), Paul Whelton (USA), Xin Hua Zhang, (Australia), Yuqing Zhang (China).

1,657 citations

Journal ArticleDOI
TL;DR: This chapter discusses the development of personalized medicine and home testing in the developing world, and some of the strategies used to achieve this goal have not yet been developed.
Abstract: Introduction A Why POC Diagnostics? B Time B Patient Responsibility and Compliance B Cost B Diagnostic Targets C Proteins C Metabolites and Other Small Molecules C Nucleic Acids C Human Cells D Microbes/Pathogens D Drugs and Food Safety D Current Context of POC Assays E POC Glucose Assays E Lateral Flow Assays E Limitations of “Traditional” POC Approaches F Enabling Technologies G Printing and Laminating G Microfluidic Technologies and Approaches: “Unit Operations” for POC Devices G Pumping and Valving H Mixing I Separation I Reagent Storage J Sample Preparation K Surface Chemistry and Device Substrates L Physical Adsorption L Bioaffinity Attachment L Covalent Attachment M Substrate Materials M Detection M Electrochemical Detection N Optical Detection N Magnetic Detection N Label-Free Methods O Enabling Multiplexed Assays O Recent Innovation O Lateral Flow Assay Technologies O Proteins P Antibodies P Protein Expression and Purification Q Nucleic Acids Q Aptamers R Infectious Diseases and Food/Water Safety R Blood Chemistry S Coagulation Markers S Whole Cells S Trends, Unmet Needs, Perspectives T Glucose T Global Health and the Developing World T Personalized Medicine and Home Testing U Technology Trends U Multiplexing V Author Information V Biographies V Acknowledgment W References W

983 citations