The Egyptian Journal of Neurology, Psychiatry and Neurosurgery (Jan 2024)

Early detection of peripheral neuropathy in patients with diabetes mellitus type 2

  • Ahmed W. Fadel,
  • Amin E. Nawar,
  • Loai M. Elahwal,
  • Azza A. Ghali,
  • Osama A. Ragab

DOI
https://doi.org/10.1186/s41983-023-00782-9
Journal volume & issue
Vol. 60, no. 1
pp. 1 – 11

Abstract

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Abstract Background Early diagnosis of diabetic polyneuropathy (DPN) can significantly improve the prognosis and help prevent severe complications. The aim of this work was to study clinical, radiological, laboratory and neurophysiological findings for early detection of peripheral neuropathy in T2DM. Methods A total of 60 diabetic patients were classified according to Toronto Clinical Neuropathy Score (TCNS) into: Group 1: 20 diabetic patients with no evident neuropathy. Group 2: 20 diabetic patients with mild neuropathy. Group 3: 20 diabetic patients with moderate and severe neuropathy. All patients underwent a neurological examination, nerve conduction studies and optical coherence tomography (OCT) to assess retinal nerve fiber layer (RNFL) thickness. Additionally, ELISA technique to measure serum interleukin-6 (IL-6). Results The analysis of gender and age distributions among the groups revealed no significant differences. There were statistically significant differences regarding disease duration, HBA1c, body mass index Systolic and diastolic blood pressure. Group 3 had such significant impairment that resulted in an inability to record the measurements of sural nerves. The study's statistical analysis results for OCT variables, and post hoc comparisons revealed significant differences between all three groups. The results demonstrated significant variations in Serum IL6 levels among the groups, with Group 3 having the highest IL6 levels. In groups 1, 2, and 3 the area under the curve for IL-6 and RNFL showed a good differentiation ability between groups. Conclusion We conclude that the total thickness RNFL and serum IL-6 levels are a potential biomarker in prediction the severity of DPN.

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