A model incorporating ultrasound to predict the probability of fast disease progression in amyotrophic lateral sclerosis
Document Type
Article
Publication Date
10-1-2021
Abstract
Objective: We aimed to develop a model to predict amyotrophic lateral sclerosis (ALS) disease progression based on clinical and neuromuscular ultrasound (NMUS) parameters. Methods: ALS patients were prospectively recruited. Muscle fasciculation ( 1.22 (p = 0.026). A predictive model (scores 0-5) was built with excellent discrimination (area under curve: 0.915). Using a score of 3, the model demonstrated good sensitivity (81.3%) and specificity (91.0%) in differentiating fast from non-fast progressors. Conclusion: The current model is simple and can predict the probability of fast disease progression. Significance: This model has potential as a surrogate biomarker of ALS disease progression. (c) 2021 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.
Keywords
Amyotrophic lateral sclerosis, Ultrasound, Fasciculation, Nerve cross sectional area, Model
Divisions
fac_med
Funders
Malaysian Ministry of Education Fundamental Research Grant Scheme [FRGS/1/2018/SK K08/UM/01/1],ALS Association [IF008-2019],Sydney Southeast Asia Center [IF012-2019]
Publication Title
Clinical Neurophysiology
Volume
132
Issue
10
Publisher
Elsevier
Publisher Location
ELSEVIER HOUSE, BROOKVALE PLAZA, EAST PARK SHANNON, CO, CLARE, 00000, IRELAND