Publications by authors named "Alessandra T Ayers"

Article Synopsis
  • The Diabetes Research Hub (DRH) is a new system designed to improve how diabetes data is collected, stored, and analyzed for research purposes.!
  • It utilizes advanced analytics on large datasets to provide better insights into diabetes treatment and management, benefiting patient outcomes.!
  • Researchers gathering continuous glucose and related physiological data can significantly enhance their work by using the DRH's resources and capabilities.!
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This report represents the conclusions of 15 experts in nephrology and endocrinology, based on their knowledge of key studies and evidence in the field, on the role of continuous glucose monitors (CGMs) in patients with diabetes and chronic kidney disease (CKD), including those receiving dialysis. The experts discussed issues related to CGM accuracy, indications, education, clinical outcomes, quality of life, research gaps, and barriers to dissemination. Three main goals of management for patients with CKD and diabetes were identified: (1) greater use of CGMs for better glycemic monitoring and management, (2) further research evaluating the accuracy, feasibility, outcomes, and potential value of CGMs in patients with end-stage kidney disease (ESKD) on hemodialysis, and (3) equitable access to CGM technology for patients with CKD.

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Background: The large language models (LLMs), most notably ChatGPT, released since November 30, 2022, have prompted shifting attention to their use in medicine, particularly for supporting clinical decision-making. However, there is little consensus in the medical community on how LLM performance in clinical contexts should be evaluated.

Methods: We performed a literature review of PubMed to identify publications between December 1, 2022, and April 1, 2024, that discussed assessments of LLM-generated diagnoses or treatment plans.

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Artificial intelligence (AI) is increasingly being used to diagnose complications of diabetes. Artificial intelligence is technology that enables computers and machines to simulate human intelligence and solve complicated problems. In this article, we address current and likely future applications for AI to be applied to diabetes and its complications, including pharmacoadherence to therapy, diagnosis of hypoglycemia, diabetic eye disease, diabetic kidney diseases, diabetic neuropathy, diabetic foot ulcers, and heart failure in diabetes.

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With increasing prevalence of obesity and cardiovascular diseases, there is a growing interest in the use of glucagon-like peptide-1 receptor agonists (GLP-1RAs) as an adjunct therapy in type 1 diabetes (T1D). The GLP-1RAs are currently not approved by the US Food and Drug Administration for the treatment of T1D in the absence of randomized controlled trials documenting efficacy and safety of these agents in this population. The Diabetes Technology Society convened a series of three consensus meetings of clinicians and researchers with expertise in diabetes technology, GLP-1RA therapy, and T1D management.

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As medical devices become more integrated with wireless technologies, the risks of cyberattacks and data breaches increase, making stringent cybersecurity measures essential. The implementation of rigorous cybersecurity standards is essential for enhancing the cybersecurity of devices. This article examines the evolving cyber threats faced by the medical technology industry, the role of IEEE 2621 in providing comprehensive security benchmarks for medical devices, and the need for continuous risk assessments and adherence to regulatory standards to mitigate future cyber risks.

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Article Synopsis
  • An error grid is a tool that helps compare glucose levels measured by devices to see if they are correct and to identify any risks.
  • Experts created a new error grid called the DTS Error Grid that works for both blood glucose monitors (BGMs) and continuous glucose monitors (CGMs), organizing accuracy into five risk zones.
  • The results showed that the DTS Error Grid provides a clearer picture of how accurate these devices are and includes a separate matrix to evaluate how well CGMs track glucose trends over time.
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Introduction: Insulin pump therapy can be adversely affected by interruption of insulin flow, leading to a rise in blood glucose (BG) and subsequently of blood beta-hydroxybutyrate (BHB) ketone levels.

Methods: We performed a PubMed search for English language reports (January 1982 to July 2024) estimating the rate of rise in BG and/or BHB after ≥ 60 minutes of interruption of continuous subcutaneous insulin infusion (CSII) in persons with type 1 diabetes (PwT1D). We also simulated the rise in BG in a virtual population of 100 adults with T1D following suspension of continuous subcutaneous insulin infusion.

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