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Diabetic Nephropathy01:28

Diabetic Nephropathy

Definition Diabetic nephropathy is a chronic kidney complication that results from prolonged hyperglycemia.Prevalence It is the most common cause of chronic kidney disease (CKD) and end-stage renal disease (ESRD) worldwide, affecting up to half of individuals with diabetes.Pathophysiology • Sustained hyperglycemia triggers multiple hemodynamic and metabolic changes in the kidney. • Early in the disease, increased renal blood flow and glomerular hyperfiltration occur due to afferent arteriolar...
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DefinitionDiabetic neuropathy is nerve damage caused by long-standing diabetes mellitus. It results directly from prolonged high blood sugar levels.PathophysiologyThe pathophysiology of diabetic neuropathy involves both metabolic and vascular disturbances triggered by chronic hyperglycemia.Metabolic injury: Elevated glucose levels activate the polyol pathway within nerve cells, leading to the accumulation of sorbitol and fructose. This increases oxidative stress, disrupts normal nerve...

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Muscle Network Connectivity Study in Diabetic Peripheral Neuropathy Patients.

Isabel Junquera-Godoy1, José Luís Martinez-De-Juan1, Gemma González-Lorente1

  • 1Centro de Investigación e Innovación en Bioingeniería (Ci2B), Universitat Politècnica de València (UPV), 46022 Valencia, Spain.

Sensors (Basel, Switzerland)
|August 10, 2024
PubMed
Summary

Surface electromyography (sEMG) analysis reveals altered muscle network connectivity in diabetic peripheral neuropathy (DPN). Transfer entropy (TE) effectively detects these changes, aiding DPN monitoring and rehabilitation strategies.

Keywords:
biomarkerdiabetic peripheral neuropathyelectromyographymuscle interactiontransfer entropy

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Area of Science:

  • Biomedical Engineering
  • Neuroscience
  • Clinical Medicine

Background:

  • Diabetic peripheral neuropathy (DPN) is a common diabetes complication affecting quality of life and gait.
  • Surface electromyography (sEMG) is a cost-effective method for assessing muscle activation and identifying abnormalities.

Purpose of the Study:

  • To evaluate muscle network connectivity using information theory methods in individuals with and without DPN.
  • To assess the efficacy of different information theory metrics in detecting DPN-related alterations.

Main Methods:

  • Employed information theory methods: cross-correlation (CC), normalized mutual information (NMI), conditional Granger causality (CG-Causality), and transfer entropy (TE).
  • Analyzed sEMG data from three groups: controls (CT), low-risk DPN (LW), and moderate/high-risk DPN (MH).

Main Results:

  • Significant alterations in intermuscular coupling mechanisms were observed due to diabetes and DPN.
  • Transfer entropy (TE) demonstrated superior performance in differentiating between groups.
  • Increased information transfer and muscle connectivity were found in the LW group compared to controls, while the MH group showed significantly lower values.

Conclusions:

  • sEMG coupling metrics, particularly TE, can reveal neuromuscular mechanisms associated with DPN.
  • These findings support the potential use of sEMG metrics for monitoring DPN progression and guiding rehabilitation strategies.