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Multiple Sclerosis l: Introduction01:19

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Multiple sclerosis is a chronic autoimmune disease of the central nervous system (CNS) that affects the brain, spinal cord, and optic nerves. It is an inflammatory demyelinating disorder and a leading cause of neurological disability in young adults.EpidemiologyMS commonly begins between 20 and 40 years of age and is twice as common in women. Its exact cause remains unclear, but genetic susceptibility contributes, with higher risk in first-degree relatives and identical twins. A greater...

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The Multiple Sclerosis Performance Test (MSPT): An iPad-Based Disability Assessment Tool
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Prediction of long-term disability in multiple sclerosis.

R Schlaeger1, M D'Souza, C Schindler

  • 1Department of Neurology, University Hospital Basel, Basel, Switzerland.

Multiple Sclerosis (Houndmills, Basingstoke, England)
|August 27, 2011
PubMed
Summary

Neurophysiological measures, specifically combined visual (VEP) and motor evoked potentials (MEP), can predict long-term multiple sclerosis (MS) disability. This finding aids in choosing monitoring methods for MS clinical trials and patient care.

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Published on: November 14, 2016

Area of Science:

  • Neuroscience
  • Neurology
  • Clinical Neurophysiology

Background:

  • The predictive value of neurophysiological measures for the long-term prognosis of multiple sclerosis (MS) remains largely unknown.
  • Understanding long-term disability progression is crucial for managing MS.

Purpose of the Study:

  • To prospectively assess if combined visual evoked potentials (VEPs) and motor evoked potentials (MEPs) can predict disability over a 14-year period in MS patients.
  • To explore the utility of neurophysiological tests in forecasting the long-term course of MS.

Main Methods:

  • 30 patients with relapsing-remitting and secondary progressive MS underwent VEPs, MEPs, and Expanded Disability Status Scale (EDSS) assessments at baseline (T0) and at 6, 12, and 24 months.
  • Cranial MRI scans were performed at baseline. EDSS was reassessed at 14 years (T4).
  • Spearman's rank correlation analyzed associations between evoked potentials (EPs), MRI data, and EDSS. Multivariable linear regression predicted EDSS(T4) using z-transformed EP latencies(T0).

Main Results:

  • A significant correlation was found between EDSS values at 14 years (EDSS(T4)) and the sum of z-transformed EP latencies at baseline (T0) (rho = 0.68, p < 0.0001).
  • No significant correlation was observed between EDSS(T4) and baseline MRI parameters.
  • A predictive model using baseline EP latencies (P100 and CMCT) showed strong correlation with observed EDSS(T4) values (rho = 0.69, p < 0.0001).

Conclusions:

  • Combined evoked potentials (EPs) demonstrate the ability to predict long-term disability in patients with multiple sclerosis.
  • These findings have significant implications for selecting appropriate monitoring strategies in MS clinical trials and guiding clinical practice decisions.