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Related Concept Videos

Diabetes: Management and Pharmacotherapy01:15

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The therapy for diabetes aims to alleviate hyperglycemia-related symptoms, prevent acute metabolic decompensation, and reduce chronic end-organ complications. Glycemic control is evaluated through short-term (self-monitoring, continuous glucose monitoring) and long-term (A1c, fructosamine) metrics, enabling near real-time tracking of blood glucose levels and reflecting glycemic control over specific time frames.
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Type 2 diabetes, characterized by insulin resistance, arises when the insulin receptors on cells lose responsiveness to insulin, diminishing the cell's capacity to take up glucose, resulting in elevated blood glucose levels. To receive a diagnosis of Type 2 diabetes, a series of blood glucose tests are necessary to assess whether the blood glucose falls within normal parameters. If the result is out of the normal range, a patient may be diagnosed as prediabetic or diabetic, depending on the...
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For most patients, experiencing several weeks of polyuria, polydipsia, fatigue, and significant weight loss may indicate the presence of diabetes. Furthermore, adults displaying the phenotypic appearance of type 2 diabetes (particularly those who are obese and not initially insulin-requiring), may have islet cell autoantibodies, suggesting autoimmune-mediated β cell destruction and a diagnosis of latent autoimmune diabetes of adults (LADA). The categorization of glucose homeostasis is...
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Insulin-replacement therapy usually includes both long-acting insulin (basal) and short-acting insulin (to cater to postprandial needs). In a diverse group of type 1 diabetes patients, the average daily insulin dose is typically 0.5-0.7 units/kg body weight. However, obese patients and pubertal adolescents may need more due to insulin resistance.
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Clinical development focuses on how the drug will interact with the human body and encompasses four key phases of clinical trials, each serving a specific purpose in assessing the safety and effectiveness of new drugs. These phases overlap and build upon one another. Phase I involves a small group of healthy volunteers (typically 20-80 individuals) or, in cases where significant toxicity is expected, patients with the targeted disease, such as cancer or AIDS. The volunteers are tested for...
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Diabetes mellitus is a chronic metabolic disorder characterized by high blood glucose levels due to inadequate insulin production, insulin resistance, or both. The condition affects millions worldwide and can significantly impact their health and quality of life.
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Direct-to-Consumer Testing: Relevance for Diabetes Therapy.

Malte Jacobsen1, Lutz Heinemann2

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Summary

Direct-to-consumer testing (DTCT) for diabetes management is expanding beyond glucose and HbA1c. User training and artificial intelligence integration are key for effective self-monitoring and personalized diabetes therapy.

Keywords:
HbA1cdiabetes technologyglucoselaboratoryself-monitoring

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Area of Science:

  • Diabetology
  • Biomedical Diagnostics
  • Health Informatics

Background:

  • Direct-to-consumer testing (DTCT) for diabetes self-management is not a novel concept.
  • The scope of DTCT is expected to broaden beyond glucose and glycated hemoglobin (HbA1c) measurements.
  • Evaluating the advantages and disadvantages of DTCT is crucial for its adoption.

Purpose of the Study:

  • To explore the evolving landscape of direct-to-consumer testing in diabetes care.
  • To identify key factors influencing the utilization of DTCT by individuals with diabetes.
  • To discuss the potential impact of artificial intelligence on diabetes therapy optimization through DTCT.

Main Methods:

  • Conceptual analysis of current and future trends in diabetes self-testing.
  • Review of arguments for and against the widespread use of DTCT.
  • Consideration of the role of user training and artificial intelligence in DTCT.

Main Results:

  • DTCT offers a growing range of measurable parameters for diabetes management.
  • User training is identified as a critical factor for the effective utilization of DTCT.
  • Artificial intelligence holds potential for enhancing the application of DTCT results in daily diabetes therapy.

Conclusions:

  • The future adoption of DTCT will be primarily driven by individuals with diabetes, not healthcare professionals.
  • The perceived benefits of DTCT by individuals with diabetes will determine its popularity.
  • Integrating AI into DTCT could significantly optimize diabetes treatment strategies.