Your browser doesn't support javascript.
loading
A web-based tool for personalized prediction of long-term disease course in patients with multiple sclerosis.
Galea, I; Lederer, C; Neuhaus, A; Muraro, P A; Scalfari, A; Koch-Henriksen, N; Heesen, C; Koepke, S; Stellmann, P; Albrecht, H; Winkelmann, A; Weber, F; Bahn, E; Hauser, M; Edan, G; Ebers, G; Daumer, M.
Afiliação
  • Galea I; University of Southampton, Southampton, UK. I.Galea@soton.ac.uk
Eur J Neurol ; 20(7): 1107-9, 2013 Jul.
Article em En | MEDLINE | ID: mdl-23379849
ABSTRACT
BACKGROUND AND

PURPOSE:

The Evidence-Based Decision Support Tool in Multiple Sclerosis (EBDiMS) is the first web-based prognostic calculator in multiple sclerosis (MS) capable of delivering individualized estimates of disease progression. It has recently been extended to provide long-term predictions based on the data from a large natural history cohort.

METHODS:

We compared the predictive accuracy and consistency of EBDiMS with that of 17 neurologists highly specialized in MS.

RESULTS:

We show that whilst the predictive accuracy was similar, neurologists showed a significant intra-rater and inter-rater variability.

CONCLUSIONS:

Because EBDiMS was consistent, it is of superior utility in a specialist setting. Further field testing of EBDiMS in non-specialist settings, and investigation of its usefulness for counselling patients in treatment decisions, is warranted.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Prognóstico / Especialização / Sistemas de Apoio a Decisões Clínicas / Internet / Medicina de Precisão / Esclerose Múltipla / Neurologia Tipo de estudo: Evaluation_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2013 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Prognóstico / Especialização / Sistemas de Apoio a Decisões Clínicas / Internet / Medicina de Precisão / Esclerose Múltipla / Neurologia Tipo de estudo: Evaluation_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2013 Tipo de documento: Article