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Related Concept Videos

Hypoglycemia and Glucagon01:15

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Without prolonged fasting, healthy individuals maintain blood glucose levels above 3.5 mM due to a well-adapted neuroendocrine counterregulatory system that effectively prevents acute hypoglycemia, a potentially life-threatening condition. The primary clinical scenarios for hypoglycemia encompass diabetes treatment, inappropriate production of endogenous insulin or insulin-like substances by tumors, and the use of glucose-lowering agents in non-diabetic individuals. Notably, hypoglycemia in the...
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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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Diabetes: Symptoms, Diagnosis, and Complications01:15

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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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Repaglinide (Prandin) and Nateglinide (Starlix), known as glinides, are oral insulin secretagogues that stimulate insulin release from pancreatic β cells by closing the ATP-sensitive potassium channels (KATP channel). Repaglinide controls insulin release from pancreatic β cells by managing potassium efflux. It shares two binding sites with sulfonylureas and also has a unique site, indicating overlapping mechanisms of action. With a rapid onset and a 4-7 hour duration, it effectively...
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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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Diabetes Mellitus: Overview and Type I Subtype01:22

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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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Hypoglycaemia detection and prediction techniques: A systematic review on the latest developments.

Omar Diouri1,2, Monika Cigler3, Martina Vettoretti4

  • 1Department of Endocrinology, Diabetes, Nutrition, Montpellier University Hospital, Montpellier, France.

Diabetes/Metabolism Research and Reviews
|March 25, 2021
PubMed
Summary

New technologies aim to detect and prevent dangerous low blood sugar (hypoglycaemia) in diabetes patients. Innovations include advanced sensors, vital sign monitoring, and AI to improve early detection and management.

Keywords:
algorithmsdevicesdiabetes mellitushypoglycaemiasensors

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Area of Science:

  • Biomedical Engineering
  • Endocrinology
  • Sensor Technology

Background:

  • Effective diabetes management aims to control high blood sugar (hyperglycaemia) while preventing low blood sugar (hypoglycaemia), particularly in insulin-treated individuals.
  • Fear of hypoglycaemia often leads to under-dosing of insulin, hindering optimal hyperglycaemia control.
  • Improved awareness and technological solutions are crucial for minimizing hypoglycaemia occurrence and aiding patients with impaired awareness.

Purpose of the Study:

  • To systematically review current and emerging technologies for detecting hypoglycaemia or hypoglycaemia risk.
  • To identify research gaps in the development and application of these technologies for diabetes management.

Main Methods:

  • Systematic review of literature on technologies for hypoglycaemia detection.
  • Analysis of sensor technologies (nanomaterials, galvanic skin response, breath volatile organic compounds, near-infrared spectroscopy).
  • Evaluation of vital sign monitoring (electrocardiogram, encephalogram) and artificial intelligence (deep learning) applications.

Main Results:

  • Nanomaterials enhance continuous glucose monitoring accuracy at low glucose levels.
  • Multivariable analysis can improve noninvasive galvanic skin response devices.
  • Breath analysis and near-infrared spectroscopy show potential for early hypoglycaemia alarms.
  • Deep learning algorithms offer improved prediction of hypoglycaemia from continuous glucose monitoring data.

Conclusions:

  • Current research focuses on improving both invasive and noninvasive glucose monitoring for early hypoglycaemia risk identification.
  • Technological advancements, including AI and novel sensor materials, are key to better hypoglycaemia detection.
  • Demonstrating patient usability is critical for the clinical implementation of these technologies in daily diabetes care.