Linked Life Data

8164816

Source:http://linkedlifedata.com/resource/pubmed/id/8164816

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4
pubmed:dateCreated
1994-5-24
pubmed:abstractText
We performed semiautomated quantitative measurement of brain magnetic resonance imaging (MRI) abnormalities seen at presentation and at 5-year follow-up in 84 patients presenting with an acute clinically isolated syndrome of the optic nerves, brainstem, or spinal cord suggestive of multiple sclerosis (MS). At follow-up, 34 (40%) had developed clinically definite and four (5%) clinically probable MS. Patients who developed MS during follow-up had a higher lesion load at presentation than those who did not. There was a strong correlation of the MRI lesion load at presentation with both the increase in lesion load over the next 5 years and disability at follow-up. Increasing initial lesion load correlated with a decreasing time to development of MS clinically (r = -0.328, p < 0.05). At follow-up, disability and brain lesion load were strongly correlated in patients who had developed MS. These results establish that MRI at presentation with clinically isolated syndromes suggestive of MS is useful in predicting the subsequent clinical course and the development of new MRI lesions. This suggests that quantitative brain MRI will be helpful in selecting patients with early clinical MS for treatment trials and for subsequent monitoring of their response to treatment.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
AIM
pubmed:status
MEDLINE
pubmed:month
Apr
pubmed:issn
0028-3878
pubmed:author
pubmed:issnType
Print
pubmed:volume
44
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
635-41
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
1994
pubmed:articleTitle
Quantitative brain MRI lesion load predicts the course of clinically isolated syndromes suggestive of multiple sclerosis.
pubmed:affiliation
NMR Research Group, Institute of Neurology, London, UK.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't