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Arch Neurol ; 69(1): 89-95, 2012 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-22232348

RESUMO

OBJECTIVE: To better characterize the relationship between cerebral white matter lesion load (CWM-LL) and clinical disability by (1) covering the entire range of the Kurtzke Expanded Disability Status Scale (EDSS), (2) minimizing nonbiological sources of variability, and (3) increasing pathologic specificity by studying CWM lesions that are hypointense on T1-weighted magnetic resonance imaging. DESIGN: Cross-sectional, retrospective study. SETTING: Hospital-based multiple sclerosis (MS) clinic. Patients  A total of 110 patients with untreated MS were recruited and studied from June 1, 1997, through June 30, 2003. MAIN OUTCOME MEASURES: Cube-rooted CWM-LL and EDSS-measured clinical disability scores. RESULTS: We found a large, nonplateauing relationship between cube-rooted CWM-LL and concurrent EDSS scores, more so for T1-hypointense than T2-hyperintense lesions (r = 0.619 vs 0.548). Correlations between the EDSS scores and CWM-LL diminished when, as typically done in clinical trials, only those patients with EDSS scores of 0 to 6.0 were studied (n = 92; r = 0.523 for T1-hypointense lesions and r = 0.457 for T2-hyperintense lesions); more important, a series of boot-strapped correlations suggested that this decrease was not simply due to smaller sample size, and these relationships remained even after correcting for disease duration. CONCLUSION: A large, nonplateauing relationship exists between CWM-LL and EDSS-measured clinical disability when patients with MS are studied to examine the entire range of disability, minimize nonbiological sources of variability, and increase pathologic specificity.


Assuntos
Córtex Cerebral/patologia , Avaliação da Deficiência , Esclerose Múltipla/diagnóstico , Fibras Nervosas Mielinizadas/patologia , Análise de Variância , Estudos Transversais , Feminino , Humanos , Processamento de Imagem Assistida por Computador , Imageamento por Ressonância Magnética , Masculino , Esclerose Múltipla/classificação , Estudos Retrospectivos , Estatísticas não Paramétricas
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