2014
DOI: 10.1007/s10633-014-9466-6
|View full text |Cite
|
Sign up to set email alerts
|

Diagnostic value of visual evoked potentials for clinical diagnosis of multiple sclerosis

Abstract: MS suspects with a P100 latency longer than mean of MS-free subjects are more likely to develop MS than those with lower values. VEP latency combined with MRI could improve the accuracy of MS prediction.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1

Citation Types

1
15
0
1

Year Published

2016
2016
2021
2021

Publication Types

Select...
4
3
1

Relationship

0
8

Authors

Journals

citations
Cited by 28 publications
(17 citation statements)
references
References 14 publications
1
15
0
1
Order By: Relevance
“…Brain lesions in the magnetic resonance were significantly associated with CDMS development (p = 0.001). Therefore, the previsibility to develop CDMS was higher when the P100 latency delay and the brain lesions of magnetic resonance were concomitantly present [36].…”
Section: Vep In Idiopathic Inflammatory Demyelinating Diseasesmentioning
confidence: 98%
“…Brain lesions in the magnetic resonance were significantly associated with CDMS development (p = 0.001). Therefore, the previsibility to develop CDMS was higher when the P100 latency delay and the brain lesions of magnetic resonance were concomitantly present [36].…”
Section: Vep In Idiopathic Inflammatory Demyelinating Diseasesmentioning
confidence: 98%
“…The most common finding in acute ON is delayed latency of wave P100 together with amplitude reduction (8). With recovery from ON, the amplitude improves but latency usually persistently increases.…”
Section: Evoked Potentials In Multiple Sclerosismentioning
confidence: 99%
“…Visual evoked potentials (VEPs) are electrical potentials that can be measured by electroencephalography (EEG) as the brain's responses to a visual stimulus. VEPs are used in a variety of fields ranging from clinical diagnostics (Chirapapaisan et al, 2015) over basic research (Blake & Logothetis, 2002) to their application in a Brain-Computer Interface (BCI) (Wolpaw et al, 2002).…”
Section: Introductionmentioning
confidence: 99%